ALBERT

Description: In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

Description: The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its nine along-track view angles, four visible/near-infrared spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space. The more than 10-year (and counting) MISR data record provides unprecedented opportunities for characterizing long-term trends in aerosol, cloud, and surface properties, and includes 3-D textural information conventionally thought to be accessible only to active sensors.

Description: Autonomous onboard processing of data allows rapid response to detections of dynamic, changing processes. Software that can detect volcanic eruptions from thermal emission has been used to retask the Earth Observing 1 spacecraft to obtain additional data of the eruption. Rapid transmission of these data to the ground, and the automatic processing of the data to generated images, estimates of eruption parameters and maps of thermal structure, has allowed these products to be delivered rapidly to volcanologists to aid them in assessing eruption risk and hazard. Such applications will enhance science return from future Earth-orbiting spacecraft and also from spacecraft exploring the Solar System, or beyond, which hope to image dynamic processes. Especially in the latter case, long communication times between the spacecraft and Earth exclude a rapid response to what may be a transient process - only using onboard autonomy can the spacecraft react quickly to such an event.

Description: The advent of the Landsat Data Continuity Mission (LDCM), currently with a launch readiness date of December, 2012, will see evolutionary changes in the Landsat data products available from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The USGS initiated a revolution in 2009 when EROS began distributing Landsat data products at no cost to requestors in contrast to the past practice of charging the cost of fulfilling a request; that is, charging $600 per Landsat scene. To implement this drastic change, EROS terminated data processing options for requestors and began to produce all data products using a consistent processing recipe. EROS plans to continue this practice for the LDCM and will required new algorithms to process data from the LDCM sensors. All previous Landsat satellites flew multispectral scanners to collect image data of the global land surface. Additionally, Landsats 4, 5, and 7 flew sensors that acquired imagery for both reflective spectral bands and a single thermal band. In contrast, the LDCM will carry two pushbroom sensors; the Operational Land Imager (OLI) for reflective spectral bands and the Thermal InfraRed Sensor (TIRS) for two thermal bands. EROS is developing the ground data processing system that will both calibrate and correct the data from the thousands of detectors employed by the pushbroom sensors and that will also combine the data from the two sensors to create a single data product with registered data for all of the OLI and TIRS bands.

Description: Lake Victoria, the second largest fresh water lake in the Eastern part of Africa is a vital natural resource for the economic well being and prosperity of over 30 million people located in riparian regions of Uganda, Kenya and Tanzania. It covers a large area of about 68,870 km2 and produces a GDP of about US $30 billion per year. The region is also very much prone to natural disasters such as severe floods during heavy precipitation periods in the Eastern part of Africa. In addition to floods, the precipitation also produces large infestations of mosquito larvae due to the standing water in many areas. This further causes multiple vector borne diseases such as Malaria, Rift Valley Fever and more. These problems are of serious concern and require active and aggressive surveillance and management to minimize the loss of human and animal lives and property damage. Satellite imagery and observations along with the in situ measurements provide a great tool to analyze and study this area and inform the policy makers to make calculated policy decisions which are more beneficial to the environment. Recently, NASA and USAID have joined forces with the Regional Center for Mapping of Resources for Development (RCMRD) located in Nairobi, Kenya to utilize multiple NASA sensors such as TRMM, SRTM and MODIS to develop flood potential maps for the Lake Victoria Basin. The idea is to generate a flood forecasts and "nowcasts" that can be sent to the disaster management organizations of Uganda, Kenya, and Tanzania. Post flood event satellite imagery is becoming a common tool to assess the areas inundated by flooding. However, this work is unique undertaking by utilizing land imaging and atmospheric satellites to build credible flood potential maps. At same time, we are also studying the potential occurrence and spread of Rift Valley Fever disease based on the short term climate records and precipitation data. These activities require multi-nation coordination and agreements and multiple operational agencies within each respective country. It also requires credible in situ data such as precipitation, river flow rates and lake levels to further validate the global and regional Hood models and algorithms. This also requires a considerable amount of training and capacity building for the RCMRD experts who will help us validate the model results and eventually transition it for operational use. In a final analysis, Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid Hood mapping and distribution, and e) validation of Hood forecasting and detection products.

Description: Around the Gulf of Mexico, high-input crops in several regions make a significant contribution to nutrient loading of small to medium estuaries and to the near-shore Gulf. Some crops cultivated near the coast include sorghum in Texas, rice in Texas and Louisiana, sugarcane in Florida and Louisiana, citrus orchards in Florida, pecan orchards in Mississippi and Alabama, and heavy sod and ornamental production around Mobile and Tampa Bay. In addition to crops, management of timberlands in proximity to the coasts also plays a role in nutrient loading. In the summer of 2008, a feasibility project is planned to explore the use of NASA data to enhance the spatial and temporal resolution of near-coast nutrient source information available to the coastal community. The purpose of this project is to demonstrate the viability of nutrient source information products applicable to small to medium watersheds surrounding the Gulf of Mexico. Conceptually, these products are intended to complement estuarine nutrient monitoring.

Description: Our objective is to provide NASA remote sensing products that provide inundation and salinity information on an ecosystem level to support habitat switching models. Project born out of need by the Coastal Restoration Monitoring System (CRMS), joint effort by Louisiana Department of Natural Resources and the U.S. Geological Survey, for information on persistence of flooding by storm surge and other flood waters. The results of the this work support the habitat-switching modules in the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) model, which provides scientific evaluation for restoration management. CLEAR is a collaborative effort between the Louisiana Board of Regents, the Louisiana Department of Natural Resources (LDNR), the U.S. Geological Survey (USGS), and the U.S. Army Corps of Engineers (USACE). Anticipated results will use: a) Resolution enhanced time series data combining spatial resolution of Landsat with temporal resolution of MODIS for inundation estimates. b) Potential salinity products from radar and multispectral modeling. c) Combined inundation and salinity inputs to habitat switching module to produce habitat switching maps (shown at left)

Description: The presentation provides a summary of VSWIR data collected at 19-day intervals for most areas. TIR data was collected both day and night on a 5-day cycle (more frequently at higher latitudes), the TIR swath is four times as wide as VSWIR, and the 5-day orbit repeat is approximate. Topics include nested swath geometry for reference point design and coverage simulations for sample FLUXNET tower sites. Other points examined include variation in latitude for revisit frequency, overpass times, and TIR overlap geometry and timing between VSWIR data collections.

Description: The Aleutian Islands of Alaska are home to a number of major volcanoes which periodically present a significant hazard to aviation. During summer of 2008, the Okmok and Kasatochi volcanoes experienced moderate eruptive events. These were followed a dramatic, major eruption of Mount Redoubt in late March 2009. The Redoubt case is extensively covered in this paper. Volcanic ash and SO2 from each of these eruptions dispersed throughout the atmosphere. This created the potential for major problems for air traffic near the ash dispersions and at significant distances downwind. The NASA Applied Sciences Weather Program implements a wide variety of research projects to develop volcanic ash detection, characterization and tracking applications for NASA Earth Observing System and NOAA GOES and POES satellites. Chemistry applications using NASA AURA satellite Ozone Monitoring System (OMI) retrievals produced SO2 measurements to trace the dispersion of volcanic aerosol. This work was complimented by advanced multi-channel imager applications for the discrimination and height assignment of volcanic ash using NASA MODIS and NOAA GOES and POES imager data. Instruments similar to MODIS and OMI are scheduled for operational deployment on NPOESS. In addition, the NASA Calipso satellite provided highly accurate measurements of aerosol height and dispersion for the calibration and validation of these algorithms and for corroborative research studies. All of this work shortens the lead time for transition to operations and ensures that research satellite data and applications are operationally relevant and utilized quickly after the deployment of operational satellite systems. Introduction

Description: This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.

Description: Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan.

Description: The objective of the first phase of this project was to determine the feasibility of applying satellite altimetry data to monitor sea level rise and inundation within coastal Louisiana. Global sea level is rising, and coastal Louisiana is subsiding. Therefore, there is a need to monitor these trends over time for coastal restoration and hazard mitigation efforts. TOPEX/POSEIDON and Jason-data are used for global sea level estimates and have also been demonstrated successfully in water level studies of lakes, river basins, and floodplains throughout the world. To employ TOPEX/POSEIDON and Jason-1 data in coastal regions, the numerous steps involved in processing the data over non-open ocean areas must be assessed. This project outlined the appropriate methodology for processing non-open ocean data, including retracking and atmospheric corrections. It also inventoried the many factors in coastal land loss including subsidence, sea level rise, coastal geomorphology, and salinity levels, among others, through a review of remote sensing and field methods. In addition, the project analyzed the socioeconomic factors within the Coastal Zone as compared to the rest of Louisiana. While sensor data uncertainty must be addressed, it was determined that it is feasible to apply radar altimetry data from TOPEX/POSEIDON and Jason 1 to see trends in change within Coastal Louisiana since

Description: This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

Description: This poster presents an overview of the Global Precipitation Measurement (GPM) constellation of satellites which are designed to measure the Earth's precipitation. It includes the schedule of launches for the various satellites in the constellation, and the coverage of the constellation, It also reviews the mission capabilities, and the mission science objectives.

Description: This slide presentation reviews the coverage areas for the two instruments that are scheduled to be on board the HyspIRI mission, (i.e.,visible to short wave infrared (VSWIR) and a multispectral thermal infrared (TIR) imager.)

Description: Problem: Information gaps exist regarding health status and location of cypress forests in coastal Louisiana (LA). Such information is needed to aid coastal forest conservation and restoration programs. Approach to Issue Mitigation: Use NASA data to revise cypress forest cover type maps. Landsat and ASTER data. Use NASA data to identify and track cypress forest change. Landsat, ASTER, and MODIS data. Work with partners and end-users to transfer useful products and technology.

Description: NASA provides a wide variety of Earth-observing satellite data products to a diverse community. These data are annotated with quality information in a variety of ways, with the result that many users struggle to understand how to properly account for quality when dealing with satellite data. To address this issue, a Data Quality Screening Service (DQSS) is being implemented for a number of datasets. The DQSS will enable users to obtain data files in which low-quality pixels have been filtered out, based either on quality criteria recommended by the science team or on the user s particular quality criteria. The objective is to increase proper utilization of this critical quality data in science data analysis of satellite data products.

Description: The need for realtime data to aid in disaster management and monitoring has been clearly demonstrated for the past several years, e.g., during the tsunami in Indonesia in 2004, the hurricane Katrina in 2005, fires, etc. Users want (and often require) the means to get earth observation data for operational regional use as soon as they are generated by satellites. This is especially true for events that can cause loss of human life and/or property. To meet this need, NASA's Earth Observing System (EOS) satellites, Terra and Aqua, provide realtime data useful to disaster management teams. This paper describes the satellites, their Direct Broadcast (DB) capabilities, the data uses, what it takes to deploy a DB ground station, and the future of the DB.

Description: Scientists from the Image Science and Analysis Laboratory (ISAL) at NASA's Johnson Space Center (JSC) work with astronauts onboard the International Space Station (ISS) who take images of Earth. Astronaut photographs, sometimes referred to as Crew Earth Observations, are taken using hand-held digital cameras onboard the ISS. These digital images allow scientists to study our Earth from the unique perspective of space. Astronauts have taken images of Earth since the 1960s. There is a database of over 900,000 astronaut photographs available at http://eol.jsc.nasa.gov . Images are requested by ISAL scientists at JSC and astronauts in space personally frame and acquire them from the Destiny Laboratory or other windows in the ISS. By having astronauts take images, they can specifically frame them according to a given request and need. For example, they can choose to use different lenses to vary the amount of area (field of view) an image will cover. Images can be taken at different times of the day which allows different lighting conditions to bring out or highlight certain features. The viewing angle at which an image is acquired can also be varied to show the same area from different perspectives. Pointing the camera straight down gives you a nadir shot. Pointing the camera at an angle to get a view across an area would be considered an oblique shot. Being able to change these variables makes astronaut photographs a unique and useful data set. Astronaut photographs are taken from the ISS from altitudes of 300 - 400 km (~185 to 250 miles). One of the current cameras being used, the Nikon D3X digital camera, can take images using a 50, 100, 250, 400 or 800mm lens. These different lenses allow for a wider or narrower field of view. The higher the focal length (800mm for example) the narrower the field of view (less area will be covered). Higher focal lengths also show greater detail of the area on the surface being imaged. Scientists from the Image Science and Analysis Laboratory (ISAL) at NASA s Johnson Space Center (JSC) work with astronauts onboard the International Space Station (ISS) who take images of Earth. Astronaut photographs, sometimes referred to as Crew Earth Observations, are taken using hand-held digital cameras onboard the ISS. These digital images allow scientists to study our Earth from the unique perspective of space. Astronauts have taken images of Earth since the 1960s. There is a database of over 900,000 astronaut photographs available at http://eol.jsc.nasa.gov . Images are requested by ISAL scientists at JSC and astronauts in space personally frame and acquire them from the Destiny Laboratory or other windows in the ISS. By having astronauts take images, they can specifically frame them according to a given request and need. For example, they can choose to use different lenses to vary the amount of area (field of view) an image will cover. Images can be taken at different times of the day which allows different lighting conditions to bring out or highlight certain features. The viewing angle at which an image is acquired can also be varied to show the same area from different perspectives. Pointing the camera straight down gives you a nadir shot. Pointing the camera at an angle to get a view across an area would be considered an oblique shot. Being able to change these variables makes astronaut photographs a unique and useful data set. Astronaut photographs are taken from the ISS from altitudes of 300 - 400 km (approx.185 to 250 miles). One of the current cameras being used, the Nikon D3X digital camera, can take images using a 50, 100, 250, 400 or 800mm lens. These different lenses allow for a wider or narrower field of view. The higher the focal length (800mm for example) the narrower the field of view (less area will be covered). Higher focal lengths also show greater detail of the area on the surface being imaged. There are four major systems or spheres of Earth. They are: Atmosphere, Biosphere, Hydrosphe, and Litho/Geosphere.

Description: Heat and moisture exchange between ocean surface and atmosphere plays an integral role in short-term, regional NWP. Current SST products lack both spatial and temporal resolution to accurately capture small-scale features that affect heat and moisture flux. NASA satellite is used to produce high spatial and temporal resolution SST analysis using an OI technique.

Description: This paper presents a ground system architecture to service future NASA decadal missions and in particular, the high rate science data downlinks, by evolving EDOS current infrastructure and upgrading high rate network lines. The paper will also cover EDOS participation to date in formulation and operations concepts for the respective missions to understand the particular mission needs and derived requirements such as data volumes, downlink rates, data encoding, and data latencies. Future decadal requirements such as onboard data recorder management and file protocols drive the need to emulate these requirements within the ground system. The EDOS open system modular architecture is scalable to accommodate additional missions using the current sites antennas and future sites as well and meet the data security requirements and fulfill mission's objectives

Description: AIRS was launched on EOS Aqua on May 4, 2002 together with ASMU-A and HSB to form a next generation polar orbiting infrared and microwave atmosphere sounding system (Pagano et al 2003). The theoretical approach used to analyze AIRS/AMSU/HSB data in the presence of clouds in the AIRS Science Team Version 3 at-launch algorithm, and that used in the Version 4 post-launch algorithm, have been published previously. Significant theoretical and practical improvements have been made in the analysis of AIRS/AMSU data since the Version 4 algorithm. Most of these have already been incorporated in the AIRS Science Team Version 5 algorithm (Susskind et al 2010), now being used operationally at the Goddard DISC. The AIRS Version 5 retrieval algorithm contains three significant improvements over Version 4. Improved physics in Version 5 allowed for use of AIRS clear column radiances (R(sub i)) in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations were used primarily in the generation of clear column radiances (R(sub i)) for all channels. This new approach allowed for the generation of accurate Quality Controlled values of R(sub i) and T(p) under more stressing cloud conditions. Secondly, Version 5 contained a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 contained for the first time an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS Only sounding methodology was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Susskind et al 2010 shows that Version 5 AIRS Only sounding are only slightly degraded from the AIRS/AMSU soundings, even at large fractional cloud cover.

Description: The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.

Description: The amount of evapotranspiration (ET) to the atmosphere can account for 60% or more of the water loss in many semi-arid locations, and can critically affect local economies tied to agriculture, recreation, hydroelectric power, ecosystems, and numerous other water-related areas. NASA supports many activities using satellite and Earth science data to more accurately and cost effectively estimate ET. NASA ET related work includes the research, development and application of techniques. The free and open access of NASA satellite data and products now permits a much wider application of ET mapping. Typically the NASA supported approaches ranges from large regional and continental ET mapping using MODIS (also with AIRS and CERES), GRACE (gravimetric water balance), geostationary (e.g., GOES and Meteosat for near continental sca|e), land surface modeling (i.e, Land Data Assimilation Systems) to fine scale mapping such as provided bvLandsatdata(〈100 m). Usually satellite or airborne thermal imagery are used as input to an ET estimated surface energy balance based approach. There are currently several of these ET approaches under development and implementation including 'METRIC', 'SEBS', 'ALEXI/DisALEXI', etc.. One exception is an approach using GRACE satellite data that estimates the terrestrial water storage using gravimetric data over large areas and estimates ET indirectly. Also land surface modeling within the context of data assimilation and integration schemes provides the capability to integrate in situ, ancillary and satellite together to provide a spatially and synoptic estimates of ET also for use to provide for short-term ET predictions. We will summarize NASA related activities contributing to the improved estimation of ET for water management and agriculture with an emphasis on the Western U3.. This summary includes a description of ET projects in the Middle Rio Grande, Yakima, North Platte and other selected basins in the western US. We will also discuss plans to further address ET applications through working with the USDA and the Group on Earth Observations (GEO) to extend and evaluate western U.S. ET mapping to other parts of the U.S. and internationally.

Description: Health providers/researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. The field of geospatial health remains in its infancy, and this program will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential. NASA will discuss some of their Public Health Projects and also providing the audience with information on opportunities for future collaborations with NASA for future research.

Description: The past decade has seen a rapid increase in availability and usage of near real-time data from satellite sensors. Applications have demonstrated the utility of timely data in a number of areas ranging from numerical weather prediction and forecasting, to monitoring of natural hazards, disaster relief, agriculture and homeland security. As applications mature, the need to transition from prototypes to operational capabilities presents an opportunity to improve current near real-time systems and inform future capabilities. This paper presents NASA s effort to implement a near real-time capability for land and atmosphere data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments on the Terra, Aqua, and Aura satellites. Index Terms- Real time systems, Satellite applications

Description: This poster presentation reviews the use of Google Earth to assist in three dimensional online visualization of NASA Earth science and geospatial data. The NASA A-Train satellite constellation is a succession of seven sun-synchronous orbit satellites: (1) OCO-2 (Orbiting Carbon Observatory) (will launch in Feb. 2013), (2) GCOM-W1 (Global Change Observation Mission), (3) Aqua, (4) CloudSat, (5) CALIPSO (Cloud-Aerosol Lidar & Infrared Pathfinder Satellite Observations), (6) Glory, (7) Aura. The A-Train makes possible synergy of information from multiple resources, so more information about earth condition is obtained from the combined observations than would be possible from the sum of the observations taken independently

Description: This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

Description: Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2008. While the PM2.5 concentration is highest in the winter, the aerosol optical depth measured from MODIS is highest in the summer. A seasonal comparison shows that PM2.5 in the winter can exceed summer PM2.5 by 55%, while summer AOD exceeds winter AOD by 43%. Higher temperatures wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not surface particulate matter monitors. Measurements of the boundary layer height from lidar instruments are necessary to incorporate satellite measurements with air quality measurements.

Description: This paper assesses the resilience of Alaska s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Description: A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.

Description: This software has been designed to detect water bodies that are out in the open on cross-country terrain at mid- to far-range (approximately 20 100 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). Non-traversable water bodies, such as large puddles, ponds, and lakes, are indirectly detected by detecting reflections of the sky below the horizon in color imagery. The appearance of water bodies in color imagery largely depends on the ratio of light reflected off the water surface to the light coming out of the water body. When a water body is far away, the angle of incidence is large, and the light reflected off the water surface dominates. We have exploited this behavior to detect water bodies out in the open at mid- to far-range. When a water body is detected at far range, a UGV s path planner can begin to look for alternate routes to the goal position sooner, rather than later. As a result, detecting water hazards at far range generally reduces the time required to reach a goal position during autonomous navigation. This software implements a new water detector based on sky reflections that geometrically locates the exact pixel in the sky that is reflecting on a candidate water pixel on the ground, and predicts if the ground pixel is water based on color similarity and local terrain features

Description: The western half of the United States is made up of a number of diverse ecosystems ranging from arid desert to coastal wetlands and rugged forests. Every summer for the past 7 years students ranging from high school to graduate level gather at NASA Ames Research Center (ARC) as part of the DEVELOP Internship Program. Under the guidance of Jay Skiles [Ames Research Center (ARC) - Ames DEVELOP Manager] and Cindy Schmidt [ARC/San Jose State University Ames DEVELOP Coordinator] they work as a team on projects exploring topics including: invasive species, carbon flux, wetland restoration, air quality monitoring, storm visualizations, and forest fires. The study areas for these projects have been in Washington, Utah, Oregon, Nevada, Hawaii, Alaska and California. Interns combine data from NASA and partner satellites with models and in situ measurements to complete prototype projects demonstrating how NASA data and resources can help communities tackle their Earth Science related problems.

Description: A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by coordinating monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main goal of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE (See diagram below). Soil moisture is currently a primary data gap at WAOB.

Description: The Indo-Gangetic Plain (IGP) of the northern Indian subcontinent produces anthropogenic pollution from urban, industrial and rural combustion sources nearly continuously and is affected by convection-induced winds driving desert and alluvial dust into the atmosphere during the premonsoon period. Within the IGP, the NASA Aerosol Robotic Network (AERONET) project initiated the TIGERZ measurement campaign in May 2008 with an intensive operational period from May 1 to June 23, 2008. Mesoscale spatial variability of aerosol optical depth (AOD, tau) measurements at 500mn was assessed at sites around Kanpur, India, with averages ranging from 0.31 to 0.89 for spatial variability study (SVS) deployments. Sites located downwind from the city of Kanpur indicated slightly higher average aerosol optical depth (delta Tau(sub 500)=0.03-0.09). In addition, SVS AOD area-averages were compared to the long-tenn Kanpur AERONET site data: Four SVS area-averages were within +/- 1 cr of the climatological mean of the Kanpur site, while one SVS was within 2sigma below climatology. For a SVS case using AERONET inversions, the 440-870mn Angstrom exponent of approximately 0.38, the 440-870mn absorption Angstrom exponent (AAE) of 1.15-1.53, and the sphericity parameter near zero suggested the occurrence of large, strongly absorbing, non-spherical aerosols over Kanpur (e.g., mixed black carbon and dust) as well as stronger absorption downwind of Kanpur. Furthermore, the 3km and lOkm Terra and Aqua MODIS C005 aerosol retrieval algorithms at tau(sub 550) were compared to the TIGERZ data set. Although MODIS retrievals at higher quality levels were comparable to the MODIS retrieval uncertainty, the total number of MODIS matchups (N) were reduced with subsequent quality levels (N=25, QA〉=0; N=9,QA〉=l; N=6, QA〉=2; N=1, QA=3) over Kanpur during the premonsoon primarily due to the semi-bright surface, complex aerosol mixture and cloud-contaminated pixels. The TIGERZ 2008 data set provided a unique opportunity to measure the spatial and temporal variations of aerosol loading in the IGP. The strong aerosol absorption derived from ground-based sun/sky radiometer measurements suggested the presence of a predominately black carbon and dust mixture during the pre-monsoon period. Consistent with the elevated heat-pump hypothesis, these absorbing aerosols found across Kanpur and the greater IGP region during the pre-monsoon period likely induced regional atmospheric warming, which lead to a more rapid advance of the southwest Asian monsoon and above normal precipitation over northern India in June 2008.

Description: Aerosols are generated in the atmosphere through anthropogenic and natural mechanisms. These sources have signatures in the aerosol optical and microphysical properties that can be used to identify the aerosol type/mixture. Spectral aerosol absorption information (absorption Angstrom exponent; AAE) used in conjunction with the particle size parameterization (extinction Angstrom exponent; EAE) can only identify the dominant absorbing aerosol type in the sample volume (e.g., black carbon vs. iron oxides in dust). This AAE/EAE relationship can be expanded to also identify non-absorbing aerosol types/mixtures by applying an absorption weighting. This new relationship provides improved aerosol type distinction when the magnitude of absorption is not equal (e.g, black carbon vs. sulfates). The Aerosol Robotic Network (AERONET) data provide spectral aerosol optical depth and single scattering albedo - key parameters used to determine EAE and AAE. The proposed aerosol type/mixture relationship is demonstrated using the long-term data archive acquired at AERONET sites within various source regions. The preliminary analysis has found that dust, sulfate, organic carbon, and black carbon aerosol types/mixtures can be determined from this AAE/EAE relationship when applying the absorption weighting for each available wavelength (Le., 440, 675, 870nm). Large, non-spherical dust particles absorb in the shorter wavelengths and the application of 440nm wavelength absorption weighting produced the best particle type definition. Sulfate particles scatter light efficiently and organic carbon particles are small near the source and aggregate over time to form larger less absorbing particles. Both sulfates and organic carbon showed generally better definition using the 870nm wavelength absorption weighting. Black carbon generation results from varying combustion rates from a number of sources including industrial processes and biomass burning. Cases with primarily black carbon showed improved definition in the 870nm wavelength absorption weighting due to the increased absorption in the near-infrared wavelengths, while the 440nm wavelength provided better definition when black carbon mixed with dust. Utilization of this particle type scheme provides necessary information for remote sensing applications, which needs a priori knowledge of aerosol type to model the retrieved properties especially over semi-bright surfaces. In fact, this analysis reveals that the aerosol types occurred in mixtures with varying magnitudes of absorption and requires the use of more than one assumed aerosol mixture model. Furthermore, this technique will provide the aerosol transport model community a data set for validating aerosol type.

Description: Land cover change driven by human activity is profoundly affecting Earth's natural systems with impacts ranging from a loss of biological diversity to changes in regional and global climate. This change has been so pervasive and progressed so rapidly, compared to natural processes, scientists refer to it as "the great transformation". Urbanization or the 'gray wave' of land transformation is being increasingly recognized as an important process in global climate change. A hallmark of our success as a species, large urban conglomerates do in fact alter the land surface so profoundly that both local climate and the basic ecology of the landscape are affected in ways that have consequences to human health and economic well-being. Fortunately we have incredible new tools for planning and developing urban places that are both enjoyable and sustainable. A suite of Earth observing satellites is making it possible to study the interactions between urbanization, biological processes, and weather and climate. Using these Earth Observatories we are learning how urban heat islands form and potentially ameliorate them, how urbanization can affect rainfall, pollution, and surface water recharge at the local level and climate and food security globally.

Description: The science value of satellite altimeter observations has grown dramatically over time as enabling models and technologies have increased the value of data acquired on both past and present missions. With the prospect of an observational time series extending into several decades from TOPEX/Poseidon through Jason-1 and the Ocean Surface Topography Mission (OSTM), and further in time with a future set of operational altimeters, researchers are pushing the bounds of current technology and modeling capability in order to monitor global sea level rate at an accuracy of a few tenths of a mm/yr. The measurement of mean sea-level change from satellite altimetry requires an extreme stability of the altimeter measurement system since the signal being measured is at the level of a few mm/yr. This means that the orbit and reference frame within which the altimeter measurements are situated, and the associated altimeter corrections, must be stable and accurate enough to permit a robust MSL estimate. Foremost, orbit quality and consistency are critical to satellite altimeter measurement accuracy. The orbit defines the altimeter reference frame, and orbit error directly affects the altimeter measurement. Orbit error remains a major component in the error budget of all past and present altimeter missions. For example, inconsistencies in the International Terrestrial Reference Frame (ITRF) used to produce the precision orbits at different times cause systematic inconsistencies to appear in the multimission time-frame between TOPEX and Jason-1, and can affect the intermission calibration of these data. In an effort to adhere to cross mission consistency, we have generated the full time series of orbits for TOPEX/Poseidon (TP), Jason-1, and OSTM based on recent improvements in the satellite force models, reference systems, and modeling strategies. The recent release of the entire revised Jason-1 Geophysical Data Records, and recalibration of the microwave radiometer correction also require the further re-examination of inter-mission consistency issues. Here we present an assessment of these recent improvements to the accuracy of the 17 -year sea surface height time series, and evaluate the subsequent impact on global and regional mean sea level estimates.

Description: The upcoming Ozone Mapper and Profiler Suite (OMPS), which will be launched on the NPOESS Preparatory Project (NPP) platform in early 2011, will continue monitoring the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth's limb radiance (which is due to the scattering of solar photons by air molecules, aerosol and Earth surface) in the ultra-violet (UV), visible and near infrared, from 285 to 1000 nm. The LP simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each covering a vertical tangent height range of 100 km and each horizontally spaced by 250 km in the cross-track direction. Measurements are made every 19 seconds along the orbit track, which corresponds to a distance of about 150km. Several data analysis tools are presently being constructed and tested to retrieve ozone and aerosol vertical distribution from limb radiance measurements. The primary NASA algorithm is based on earlier algorithms developed for the SOLSE/LORE and SAGE III limb scatter missions. All the existing retrieval algorithms rely on a spherical symmetry assumption for the atmosphere structure. While this assumption is reasonable in most of the stratosphere, it is no longer valid in regions of prime scientific interest, such as polar vortex and UTLS regions. The paper will describe a two-dimensional retrieval algorithm whereby the ozone distribution is simultaneously retrieved vertically and horizontally for a whole orbit. The retrieval code relies on (1) a forward 2D Radiative Transfer code (to model limb radiances within a non-uniform atmosphere and evaluate 2D analytical partial derivatives) and (2) an optimal estimator inversion routine. The algorithm uses the typically sparse nature of the kernel matrices as well as fast matrix inversion techniques to allow for fast inversion of limb data with efficient memory management (as was done for MIPAS data processing). While the method has so far only been developed in the context of Single Scatter, the paper will show how the CPU intensive Multiple Scatter modeling can be implemented using parallel CPU processing. Initial results will be presented in terms of retrieved ozone profiles and code performance.

Description: Advanced satellite sensors are tasked with improving global measurements of the Earth s atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Achieving such measurement improvements requires instrument system advancements. This presentation focuses on the impact of spectral resolution and coverage changes on remote sensing system information content, with a specific emphasis on thermodynamic state and trace species variables obtainable from advanced atmospheric sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) systems on the MetOp and NPP/NPOESS series of satellites. Key words: remote sensing, advanced sounders, information content, IASI, CrIS

Description: The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Description: In this study, a model for backscattering at L-band from a corn canopy is proposed. The canopy consists of a quasi-periodic distribution of stalks and a random distribution of leaves. The Distorted Born Approximation (DBA) is employed to calculate the single scattered return from the corn field. The new feature of the method is that the coherence of the stalks in the row direction is incorporated in the model in a systematic fashion. Since the wavelength is on the order of the distance between corn stalks in a row, grating lobe behavior is observed at certain azimuth angles of incidence. The results are compared with experimental values measured in Huntsville, Alabama in 1998. The mean field and the effective dielectric constant of the canopy are obtained by using the Foldy approximation. The stalks are placed in the effective medium in a two dimensional lattice to simulate the row structure of a corn field. In order to mimic a real corn field, a quasi-periodic stalk distribution is assumed where the stalks are given small random perturbations about their lattice locations. Corn leaves are also embedded in the effective medium and the backscattered field from the stalks and the leaves is computed. The backscattering coefficient is calculated and averaged over successive stalk position perturbations. It is assumed that soil erosion has smoothed the soil sufficiently so that it can be assumed flat. Corn field backscatter data was collected from cornfields during the Huntsville 98 experimental campaign held at Alabama A&M University Research Station, Huntsville, Alabama in 1998 using the NASA/GW truck mounted radar. Extensive ground truth data was collected. This included soil moisture measurements and corn plant architectural data to be used in the model. In particular, the distances between the stalks in a single row have been measured. The L-band radar backscatter data was collected for both H and V polarizations and for look angles of 15o and 45o over a two week period under varying soil moisture conditions. These measured backscattering values will be compared with the model backscattering values and a discussion of the results will be presented.

Description: In this paper, three approximate physical microwave radiometry models have been used to calculate brightness temperatures from a forest canopy at L-band. These models are (1) tau-omega model (zero order scattering approximation to radiative transfer equations), (2) successive order of scattering model up to first order (first order scattering approximation to the radiative transfer equations), and (3) Peak technique utilizing the active solution obtained from the Distorted Born Approximation (DBA). These models are physically-based and treat vegetation as a layer of discrete scatterers over a rough surface. Vegetation components within the canopy are represented by canonical shapes such as dielectric discs and cylinders. The tau-omega model is based on a zero-order solution to the radiative transfer (RT) equations. The model ignores scattering except for the effect of the scatterers in the attenuation of the emission through the vegetation. Application of the tau-omega model to data acquired during airborne and ground-based campaigns over the years has solidified scientific understanding of microwave interactions with different landscapes. In particular, shrubland, grasslands, agricultural crops, and light to moderate vegetation have been investigated. Its applicability to areas with a significant tree fraction is unknown. The first order scattering model is based on an iterative solution of the RT equation up to the first order. The first order solution is obtained by substituting the zeroth-order solution into the scattering source term and then solving the resulting radiative transfer equations. This formulation adds a new scattering term to the tau-omega model. It represents emission by particles in the layer and emission by the ground that is scattered once by particles in the layer. The resulting model represents an improvement over the standard zero-order solution (the tau-omega model) since it accounts for the scattered vegetation and ground radiation that can have a pronounced effect on the observed brightness temperature. The third model is based on the Peake formulation in conjunction with the DBA. The procedure for calculation of forest emission is accomplished by first calculating the bistatic scattering cross section for each type of scatterer, then by using the DBA to calculate specular albedo of the ground and the diffused albedo of the layer. Once the albedos are determined, Peake s principle relating active and passive problems can be used to determine the effective emissivity of the forest layer.

Description: The Soil Moisture Active and Passive (SMAP) mission is a NASA earth science mission aiming at improving our understanding of the dynamics of the cycles of energy, water, and carbon at global scales. The mission features two complementary sensors on the same low-Earth orbiting platform: an L-band synthetic aperture radar (SAR) operating at 1.26 GHz and an L-band radiometer operating at 1.41 GHz. Together these instruments will provide global mapping of soil moisture and freeze/thaw states in 2-3 days, with a tentative launch date in 2014. The work reported in this study focuses primarily on the development of the SMAP radiometer-only soil moisture data product. For passive soil moisture retrieval at satellite footprint scales, one way to improve retrieval accuracy is to correct for the microwave emission from open water bodies prior to retrieval. The accuracy of this correction will depend on not only the locations of these water bodies, but also the geolocation accuracy of the instrument. As perfect knowledge is never attainable in practice, it is important to assess the impacts of these uncertainties on the SMAP radiometer observations and hence the passive soil moisture retrieval accuracy. In this presentation, we present the results of our preliminary assessment on the impacts of these uncertainties. Our study consists of two parts: (1) a sensitivity analysis on the SMAP radiometer observations due to uncertainties in water-body classification, and (2) realistic global simulations that take into account of additional uncertainties (e.g., geolocation and ancillary data) and SMAP-specific instrument characteristics (e.g., orbit sampling and antenna pattern). The results will provide valuable prelaunch guidance to the SMAP team in identifying different error sources and their relative impacts on the passive soil moisture data product.

Description: Lake Thonotosassa is a highly eutrophied lake located in an area with rapidly growing population in the Tampa Bay watershed, Florida. The Florida Administrative Code has designated its use for "recreation, propagation and maintenance of a healthy, well-balanced population of fish and wildlife." Although this lake has been the subject of efforts to improve water quality since 1970, overall water quality has remained below the acceptable state standards, and has a high concentration of nutrients. This condition is of great concern to public health since it has favored episodic blooms of Cyanobacteria. Some Cyanobacterial species release toxins that can reach humans through drinking water, fish consumption, and direct contact with contaminated water. The lake has been historically popular for fishing and water sports, and its overflow water drains into the Hillsborough River, the main supply of municipal water for the City of Tampa, this explains why it has being constantly monitored in situ for water quality by the Environmental Protection Commission of Hillsborough County (EPC). Advances in remote sensing technology, however, open the possibility of facilitating similar types of monitoring in this and similar lakes, further contributing to the implementation of surveillance systems that would benefit not just public health, but also tourism and ecosystems. Although traditional application of this technology to water quality has been focused on much larger coastal water bodies like bays and estuaries, this study evaluates the feasibility of its application on a 46.6 km2 freshwater lake. Using surface reflectance products from Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra, this study evaluates associations between remotely sensed data and in situ data from the EPC. The parameters analyzed are the surface water quality standards used by the State of Florida and general indicators of trophic status.

Description: Respiratory diseases such as asthma can be triggered by environmental conditions that can be monitored using Earth observing data and environmental forecast models. Frequent dust storms in the southwestern United States, the annual cycle of juniper pollen events in the spring, and increased aerosol and ozone concentrations in summer, are health concerns shared by the community at large. Being able to forecast the occurrence of these events would help the health care community prepare for increased visits to emergency rooms, as well as allow public health officials to issue alerts to affected persons. This information also is important to epidemiologists for analyzing long-term trends and impacts of these events on the health and well-being of the community. Earth observing data collected by remote sensing platforms are important for improving the performance of models that can forecast these events, and in turn, improve products and information for decision-making by public health authorities. This presentation will discuss the benefits of using remote sensing data for forecasting environmental events that can adversely affect individuals with respiratory ailments. The presentations will include a brief discussion on relevant Earth observing data, the forecast models used, and societal benefits of the resulting products and information. Several NASA-funded projects will be highlighted as examples

Description: We describe observations of Earth conducted using the High Resolution Instrument (HRI) - a 0.3 m f/35 telescope - on the Deep Impact (DI) spacecraft during its recent flybys. Earth was observed on five occasions: 2008-Mar-18 18:18 UT, 2008-May-28 20:05 UT, 2008-Jun-4 16:57 UT, 2009-Mar-27 16:19 and 2009-Oct-4 09:37 UT. Each set of observations was conducted over a full 24-hour rotation of Earth and a total of thirteen NIR spectra were taken on two-hour intervals during each observing period. Photometry in the 450, SSO, 650 and 8S0 nm filters was taken every fifteen minutes and every hour for the 350, 750 and 950 nm filters. The spacecraft was located over the equator for the three sets of observations in 2008, while the 2009- Mar and 2009-Oct were taken over the north and south Polar Regions, respectively. Observations of calibrator stars Canopus and Achernar were conducted on multiple occasions through all filters. The observations detected a strong specular glint not necessarily associated with a body of water. We describe spectroscopic characterization of the glint and evidence for the possibility of detection of reflection from high cirrus clouds. We describe implications for observations of extrasolar planets.

Description: A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Description: The first joint meeting between NASA, KNMI and FMI scientists was held on 13 & 14 June, 2000, almost exactly 10 years ago. NASA had recently selected 14 US scientists to work on instrument calibration, science algorithms, and validation activities related to the Ozone Monitoring Instrument (OMI) that we being built by collaboration between the Netherlands and Finland for flight on NASA's EOS Aura satellite. The progress on this project had been remarkable for a space based instrument. Only two years before this meeting my colleague Ernest Hilsenrath and I had visited Netherlands at the invitation of Fokker Space to persuade KNMI management to collaborate with NASA on this mission. And only 4 years after the first science meeting was held OMI was lunched on the Aura spacecraft. Next month will be the 6 th anniversary of this launch and very successful operation of OMI. All this was possible because of the leadership from Dr. Hennie Kelder and KNMI management who in 1998 saw the opportunity for Netherlands in the mission and stepped up to the challenge by creating a young and talented team of scientists at KNMI under the leadership of Dr. Pieterenel Levelt. This vision has now put Netherlands as the leading country in the world in monitoring air quality from space. Recent selection of TROPOMI by ESA attests to the success of this vision. I will present some selected highlights of our very successful collaboration on this project over the past 10 years.

Description: In data sparse regions, remotely-sensed observations can be used to improve analyses and lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles in clear and cloudy regions with accuracy which approaches that of radiosondes. The purpose of this paper is to describe an approach to assimilate AIRS thermodynamic profile data into a regional configuration of the Advanced Research WRF (ARW) model using WRF-Var. Quality indicators are used to select only the highest quality temperature and moisture profiles for assimilation in clear and partly cloudy regions, and uncontaminated portions of retrievals above clouds in overcast regions. Separate error characteristics for land and water profiles are also used in the assimilation process. Assimilation results indicate that AIRS profiles produce an analysis closer to in situ observations than the background field. Forecasts from a 37-day case study period in the winter of 2007 show that AIRS profile data can lead to improvements in 6-h cumulative precipitation forecasts resulting from improved thermodynamic fields. Additionally, in a convective heavy rainfall event from February 2007, assimilation of AIRS profiles produces a more unstable boundary layer resulting in enhanced updrafts in the model. These updrafts produce a squall line and precipitation totals that more closely reflect ground-based observations than a no AIRS control forecast. The location of available high-quality AIRS profiles ahead of approaching storm systems is found to be of paramount importance to the amount of impact the observations will have on the resulting forecasts.

Description: The Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission (ARCADE) is a balloon-borne instrument to measure the frequency spectrum of the cosmic microwave background and diffuse Galactic foregrounds at centimeter wavelengths. ARCADE greatly reduces measurement uncertainties compared to previous balloon-borne or ground-based instrument using a double-nulled design that features fully cryogenic optics with no windows between the atmosphere and the 2.7 K instrument. A four-hour flight in 2006 achieved sensitivity comparable to the COBE/FIRAS satellite measurement while providing new insights for emission ranging from spinning dust in the interstellar medium to an unexpectedly bright extragalactic radio background. I will discuss scientific results from the ARCADE program and implications of the ARCADE cold optics for millimeter and sub-mm astronomy.

Description: The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Description: Accurate global measurement of carbon dioxide column with the aim of discovering and quantifying unknown sources and sinks has been a high priority for the last decade. In order to uncover the "missing sink" that is responsible for the large discrepancies in the budget the critical precision for a measurement from space needs to be on the order of 1 ppm. To better understand the CO2 budget and to evaluate its impact on global warming the National Research Council (NRC) in its recent decadal survey report (NACP) to NASA recommended a laser based total CO2 mapping mission in the near future. That's the goal of Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission - to significantly enhance the understanding of the role of CO2 in the global carbon cycle. Our current goal is to develop an ultra precise, inexpensive new lidar system for column measurements of CO2 changes in the lower atmosphere that uses a Fabry-Perot interferometer based system as the detector portion of the instrument and replaces the narrow band laser commonly used in lidars with a high power broadband source. This approach reduces the number of individual lasers used in the system and considerably reduces the risk of failure. It also tremendously reduces the requirement for wavelength stability in the source putting this responsibility instead on the Fabry- Perot subsystem.

Description: The Landsat Data Continuity Mission (LDCM), a joint NASA and USGS mission, is scheduled for launch in December, 2012. The LDCM instrument payload will consist of the Operational Land Imager (OLI), provided by Ball Aerospace and Technology Corporation (BATC} under contract to NASA and the Thermal Infrared Sensor (TIRS), provided by NASA's Goddard Space Flight Center (GSFC). This paper outlines the design of the TIRS instrument and gives an example of its application to monitoring water consumption by measuring evapotranspiration.

Description: We determine the aerosol extinction-to-backscatter (Sa) ratios of dust using airborne in-situ measurements of microphysical properties, and CALIPSO observations during the NASA African Monsoon Multidisciplinary Analyses (NAMMA). The NAMMA field experiment was conducted from Sal, Cape Verde during Aug-Sept 2006. Using CALIPSO measurements of the attenuated backscatter of lofted Saharan dust layers, we apply the transmittance technique to estimate dust Sa ratios at 532 nm and a 2-color method to determine the corresponding 1064 nm Sa. Using this method, we found dust Sa ratios of 39.8 plus or minus 1.4 sr and 51.8 plus or minus 3.6 sr at 532 nm and 1064 nm, respectively. Secondly, Sa ratios at both wavelengths is independently calculated using size distributions measured aboard the NASA DC-8 and estimates of Saharan dust complex refractive indices applied in a T-Matrix scheme. We found Sa ratios of 39.1 plus or minus 3.5 sr and 50.0 plus or minus 4 sr at 532 nm and 1064 nm, respectively, using the T-Matrix calculations applied to measured size spectra. Finally, in situ measurements of the total scattering (550 nm) and absorption coefficients (532 nm) are used to generate an extinction profile that is used to constrain the CALIPSO 532 nm extinction profile.

Description: This slide presentation highlights how satellite observation systems are assets for studying the environment in relation to public health. It includes information on current and future satellite observation systems, NASA's public health and safety research, surveillance projects, and NASA's public health partners.

Description: NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Description: Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

Description: After briefly reviewing America's Energy Policy laid out by the Obama Administration, we outline how a Global Carbon Observing System designed to monitor Carbon from space can provide the necessary data and tools to equip decision makers with the knowledge necessary to formulate effective energy use and practices policy. To stabilize greenhouse gas emissions in the atmosphere in a manner that it does not interfere with the Earth's climate system (which is one of the goals of United Nations Framework for Convention on Climate Change) requires vastly improved prediction of the atmospheric carbon dioxide (CO2) concentrations. This in torn requires a robust understanding of the carbon exchange mechanisms between atmosphere, land, and oceans and a clear understanding of the sources and sinks (i.e. uptake and storage) of CO2. We discuss how the Carbon Observing System from space aids in better understanding of the connection between the carbon cycle and climate change and provides more accurate predictions of atmospheric CO2 concentration. It also enables implementation of greenhouse gas (GHG) mitigation policies such as cap and trade programs, international climate treaties, as well as formulation of effective energy use policies.

Description: A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.

Description: The Operational Land Imager (OLI) on the Landsat Data Continuity Mission (LDCM) has a comprehensive radiometric characterization and calibration program beginning with the instrument design, and extending through integration and test, on-orbit operations and science data processing. Key instrument design features for radiometric calibration include dual solar diffusers and multi-lamped on-board calibrators. The radiometric calibration transfer procedure from NIST standards has multiple checks on the radiometric scale throughout the process and uses a heliostat as part of the transfer to orbit of the radiometric calibration. On-orbit lunar imaging will be used to track the instruments stability and side slither maneuvers will be used in addition to the solar diffuser to flat field across the thousands of detectors per band. A Calibration Validation Team is continuously involved in the process from design to operations. This team uses an Image Assessment System (IAS), part of the ground system to characterize and calibrate the on-orbit data.

Description: Barrier Islands are the first line of defense against tropical storms and hurricanes for coastal areas. Historically, tropical cyclonic events have had a great impact on the transgression of barrier islands, especially the Chandeleur Island chain off the eastern coast of Louisiana. These islands are of great importance, aiding in the protection of southeastern Louisiana from major storms, providing habitat for nesting and migratory bird species, and are part of the second oldest wildlife refuge in the country. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both federal and state agencies. Since then, multiple storm events have steadily diminished the integrity of the islands. Hurricane Katrina in 2005 thwarted all previous restoration efforts, with Hurricane Gustav in 2008 exacerbating island erosion and vegetation loss. Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 2-4 Multispectral Scanner (MSS), and Landsat 5 Thematic Mapper (TM) will be utilized to detect land loss, island transgression, and vegetation change from 1979 to 2009. This study looks to create a more synoptic view of the transgression of the Chandeleur Islands and correlate weather and sea surface phenomena with erosion trends over the past 30 years, so that partnering organizations such as the Pontchartrain Institute for Environmental Sciences (PIES) can better monitor and address the continual change of the island chain.

Description: Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.

Description: This slide presentation reviews the use of remote sensing to monitor the relationships between the urban development and water quality in Tampa Bay and the tributaries. It examines the changes in land cover/land use (LU/LC) and the affects that this change has on the water quality of Tampa Bay, Lake Thonotosassa and the tributaries, and that shows the ways that these changes can be estimated with remote sensing.

Description: Fully utilize current and near-term airborne and spaceborne assets and capabilities. NASA spaceborne instruments are for research but can be applied to natural disaster response as appropriate. NASA airborne instruments can be targeted specifically for disaster response. Could impact research programs. Better flow of information improves disaster response. Catalog capability, product, applicable disaster, points of contact. Ownership needs to come from the highest level of NASA - unpredictable and irregular nature of disasters requires contingency funding for disaster response. Build-in transfer of applicable natural disaster research capabilities to operational functionality at other agencies (e.g., USFS, NOAA, FEMA...) at the outset, whenever possible. For the Decadal Survey Missions, opportunities exist to identify needs and requirements early in the mission design process. Need to understand additional needs and commitments for meeting the needs of the disaster community. Opportunity to maximize disaster response and mitigation from the Decadal Survey Missions. Additional needs or capabilities may require agency contributions.

Description: Goal 1: Enhance Applications Research Advance the use of NASA Earth science in policy making, resource management and planning, and disaster response. Key Actions: Identify priority needs, conduct applied research to generate innovative applications, and support projects that demonstrate uses of NASA Earth science. Goal 2: Increase Collaboration Establish a flexible program structure to meet diverse partner needs and applications objectives. Key Actions: Pursue partnerships to leverage resources and risks and extend the program s reach and impact. Goal 3:Accelerate Applications Ensure that NASA s flight missions plan for and support applications goals in conjunction with their science goals, starting with mission planning and extending through the mission life cycle. Key Actions: Enable identification of applications early in satellite mission lifecycle and facilitate effective ways to integrate end-user needs into satellite mission planning

Description: SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.

Description: CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

Description: After launch we discovered that the CALIOP daytime measurements were subject to thermally induced beamdrift,and this caused the calibration to vary by as much as 30% during the course of a single daytime orbit segment. Using an algorithm developed by Powell et al.(2010), empirically derived correction factors are now computed in near realtime as a function of orbit elapsed time, and these are used to compensate for the beam wandering effects.

Description: The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASA s Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson and Ruf.

Description: The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.

Description: This presentation discusses an effort to use select MODIS phenological products for forest disturbance monitoring at the regional and CONUS scales. Forests occur on ~1/3 of the U.S. land base and include regionally prevalent forest disturbances that can threaten forest sustainability. Regional and CONUS forest disturbance monitoring is needed for a national forest threat early warning system being developed by the USDA Forest Service with help from NASA, ORNL, and USGS. MODIS NDVI phenology products are being used to develop forest disturbance monitoring capabilities of this EWS.

Description: No abstract available

Description: No abstract available

Description: Field experiment data sets that include coincident remote sensing measurements and in situ sampling will be valuable in the development and validation of the soil moisture algorithms of the NASA's future SMAP (Soil Moisture Active and Passive) mission. This paper presents an overview of the field experiment data collected from SGP99, SMEX02, CLASIC and SMAPVEX08 campaigns. Common in these campaigns were observations of the airborne PALS (Passive and Active L- and S-band) instrument, which was developed to acquire radar and radiometer measurements at low frequencies. The combined set of the PALS measurements and ground truth obtained from all these campaigns was under study. The investigation shows that the data set contains a range of soil moisture values collected under a limited number of conditions. The quality of both PALS and ground truth data meets the needs of the SMAP algorithm development and validation. The data set has already made significant impact on the science behind SMAP mission. The areas where complementing of the data would be most beneficial are also discussed.

Description: The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 um spectral region with spectral resolution of better than 1200. The AIRS was designed to measure temperature and water vapor profiles and cloud properties for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers and have shown considerable forecast improvement. Scientists have also demonstrated accurate retrievals of minor gases from AIRS including Carbon Monoxide, Methane, and Ozone. The excellent sensitivity and stability of the AIRS instrument has recently allowed the AIRS team to successfully retrieve Carbon Dioxide (CO2) concentrations in the mid-troposphere (8-10 km) with a horizontal resolution of 100 km and accuracy of 1-2 ppm. The AIRS retrieves over 15,000 measurements per day and can achieve full global coverage in 30 days. The AIRS CO2 accuracy has been validated against a variety of aircraft measurements in the mid-troposphere and upward looking interferometers. Findings from the AIRS data include higher than expected variability in the mid-troposphere, the presence of a belt of CO2 in the southern hemisphere, and numerous observations of atmospheric circulation including the effects of El Nino/La Nina on the CO2 concentrations in the mid-troposphere. The full mid-tropospheric AIRS CO2 data set is now available at the NASA GES/DISC for almost eight years since AIRS has been operational.

Description: HyspIRI is evaluating a X-band Direct Broadcast (DB) capability that would enable data to be delivered to ground stations virtually as it is acquired. However the HyspIRI VSWIR and TIR instruments will produce 1 Gbps data while the DB capability is 15 M bps for an approximate 60x oversubscription. In order to address this data volume mismatch a DB concept has been developed that determines which data to downlink based on both: 1. the type of surface the spacecraft is overflying and 2. onboard processing of the data to detect events. For example when the spacecraft is overflying polar regions it might downlink a snow/ice product. Additionally the onboard software will search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected, thereby reducing data volume.

Description: Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of variance suggesting that the algorithm is reliable and robust, except in the tropics where some systematic differences are observed. Finally, comparisons with ground data suggest that the algorithm is performing well, but that end of season metrics associated with vegetation senescence and dormancy have higher uncertainties than start of season metrics.

Description: The NASA Global Hawk Project is supporting Earth Science research customers. These customers include: US Government agencies, civilian organizations, and universities. The combination of the Global Hawk's range, endurance, altitude, payload power, payload volume and payload weight capabilities separates the Global Hawk platform from all other platforms available to the science community. This presentation includes an overview of the concept of operations and an overview of the first two science campaigns. In addition the future science plans, using the NASA Global Hawk System, will be presented.

Description: Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P 〈 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P 〈 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Description: Lyme disease (LD) accounts for most vector-borne disease reports in the U.S., and although its existence in Alabama remains controversial, other tick-borne illnesses (TBI) such as Southern Tick-Associated Rash Illness (STARI) pose a health concern in the state. Phase One of the Marshall Space Flight Center-UAB DEVELOP study of TBI identified the presence of the chain of infection for LD (Ixodes scapularis ticks carrying Borrelia burgdorferi bacteria) and STARI (Amblyomma americanum ticks and an as-yet-unconfirmed agent) in Alabama. Both LD and STARI are associated with the development of erythema migrans rashes around an infected tick bite, and while treatable with oral antibiotics, a review of educational resources available to state residents revealed low levels of prevention information. To improve prevention, recognition, and treatment of TBI in Alabama, Phase Two builds a health communication campaign based on vector habitat mapping and risk perception assessment. NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery identified likely tick habitats using remotely sensed measurements of vegetation vigor (Normalized Difference Vegetation Index) and soil moisture. Likely tick habitats, identified as those containing both high vegetation density and soil moisture, included Oak Mountain State Park, Bankhead National Forest, and Talladega National Forest. To target a high-risk group -- outdoor recreation program participants at Alabama universities -- the study developed a behavior survey instrument based on existing studies of LD risk factors and theoretical constructs from the Social Ecological Model and Health Belief Model. The survey instrument was amended to include geographic variables in the assessment of TBI knowledge, attitudes, and prevention behaviors, and the vector habitat model will be expanded to incorporate additional environmental variables and in situ data. Remotely sensed environmental data combined with risk perception assessments inform an ongoing outreach campaign consisting of stakeholder meetings and educational seminars.

Description: This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Description: The water cycle research community has generated many regional to global scale products using data from individual NASA missions or sensors (e.g., TRMM, AMSR-E); multiple ground- and space-based data sources (e.g., Global Precipitation Climatology Project [GPCP] products); and sophisticated data assimilation systems (e.g., Land Data Assimilation Systems [LDAS]). However, it is often difficult to access, explore, merge, analyze, and inter-compare these data in a coherent manner due to issues of data resolution, format, and structure. These difficulties were substantiated at the recent Collaborative Energy and Water Cycle Information Services (CEWIS) Workshop, where members of the NASA Energy and Water cycle Study (NEWS) community gave presentations, provided feedback, and developed scenarios which illustrated the difficulties and techniques for bringing together heterogeneous datasets. This presentation reports on the findings of the workshop, thus defining the problems and challenges of multi-dataset research. In addition, the CEWIS prototype shown at the workshop will be presented to illustrate new technologies that can mitigate data access roadblocks encountered in multi-dataset research, including: (1) Quick and easy search and access of selected NEWS data sets. (2) Multi-parameter data subsetting, manipulation, analysis, and display tools. (3) Access to input and derived water cycle data (data lineage). It is hoped that this presentation will encourage community discussion and feedback on heterogeneous data analysis scenarios, issues, and remedies.

Description: Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. Generating global fields of these variables, however, is still a challenge. The goal of a land data assimilation system (LDAS)is to ingest satellite-and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast.

Description: The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been two folds: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. Because the goal of Overview of Year Of Tropical Convection (YOTC) involves examining a scientifically complex, multi-scale "process", rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 - April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO, and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO).

Description: This slide presentation reviews some of the issues in quality of remote sensing data. Data "quality" is used in several different contexts in remote sensing data, with quite different meanings. At the pixel level, quality typically refers to a quality control process exercised by the processing algorithm, not an explicit declaration of accuracy or precision. File level quality is usually a statistical summary of the pixel-level quality but is of doubtful use for scenes covering large areal extents. Quality at the dataset or product level, on the other hand, usually refers to how accurately the dataset is believed to represent the physical quantities it purports to measure. This assessment often bears but an indirect relationship at best to pixel level quality. In addition to ambiguity at different levels of granularity, ambiguity is endemic within levels. Pixel-level quality terms vary widely, as do recommendations for use of these flags. At the dataset/product level, quality for low-resolution gridded products is often extrapolated from validation campaigns using high spatial resolution swath data, a suspect practice at best. Making use of quality at all levels is complicated by the dependence on application needs. We will present examples of the various meanings of quality in remote sensing data and possible ways forward toward a more unified and usable quality framework.

Description: This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornadoes, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Description: This slide presentation reviews the use of MODIS and QuikSCAT data to measure the surface and sub-surface melting on the Greenland Ice Sheet. The project demonstrated the consistence of this technique for measuring the ice melt on the Greenland Ice Sheet. The blending of the two instruments data allows for determination of surface vs subsurface melting. Also, the use of albedo maps can provide information about the intensity of the melting.