ALBERT

Description: The Scientific Data Purchase (SDP) project acquires science data from commercial sources. It is a demonstration project to test a new way of doing business, tap new sources of data, support Earth science research, and support the commercial remote sensing industry. Phase I of the project reviews simulated/prototypical data sets from 10 companies. Phase II of the project is a 3 year purchase/distribution of select data from 5 companies. The status of several SDP projects is reviewed in this viewgraph presentation, as is the SDP process of tasking, verification, validation, and data archiving. The presentation also lists SDP results for turnaround time, metrics, customers, data use, science research, applications research, and user feedback.

Description: Major changes in salinity (approx.14 ppt.) and temperature (approx.40C) were continuously registered by two prototype NASA DRIFTERs, surface moored floaters, that NASA's Applied Science and Technology Project Office (ASTPO) has developed. The DRIFTER floating sensor module is equipped with an Arduino open-source electronics prototyping platform and programming language (http://www.arduino.cc), a GPS (Global Positioning System) module with antenna, a cell phone SIM (Subscriber Identity Module) card and a cellular antenna which is used to transmit data, and a probe to measure temperature and conductivity (from which salinity can be derived). The DRIFTER is powered by a solar cell panel and all the electronic components are mounted and sealed in [ waterproof encasement. Position and measurement data are transmitted via short message service (SMS) messaging to a Twitter site (DRIFTER 002@NASADRIFTER_002 and DRIFTER 004@NASADRIFTER_004), which provides a live feed. These data are the imported into a Google spreadsheet where conductivity is converted to salinity, and graphed in real-time. The spreadsheet data will be imported into a webpage maintained by ASTPO, where it will be displayed available for dO\\1lload.

Description: Many areas in coastal Louisiana are below sea level and protected from flooding by a system of natural and man-made levees. Flooding is common when the levees are overtopped by storm surge or rising rivers. Many levees in this region are further stressed by erosion and subsidence. The floodwaters can become constricted by levees and trapped, causing prolonged inundation. Vegetative communities in coastal regions, from fresh swamp forest to saline marsh, can be negatively affected by inundation and changes in salinity. As saltwater persists, it can have a toxic effect upon marsh vegetation causing die off and conversion to open water types, destroying valuable species habitats. The length of time the water persists and the average annual salinity are important variables in modeling habitat switching (cover type change). Marsh type habitat switching affects fish, shellfish, and wildlife inhabitants, and can affect the regional ecosystem and economy. There are numerous restoration and revitalization projects underway in the coastal region, and their effects on the entire ecosystem need to be understood. For these reasons, monitoring persistent saltwater intrusion and inundation is important. For this study, persistent flooding in Louisiana coastal marshes was mapped using MODIS (Moderate Resolution Imaging Spectroradiometer) time series of a Normalized Difference Water Index (NDWI). The time series data were derived for 2000 through 2009, including flooding due to Hurricane Rita in 2005 and Hurricane Ike in 2008. Using the NDWI, duration and extent of flooding can be inferred. The Time Series Product Tool (TSPT), developed at NASA SSC, is a suite of software developed in MATLAB(R) that enables improved-quality time series images to be computed using advanced temporal processing techniques. This software has been used to compute time series for monitoring temporal changes in environmental phenomena, (e.g. NDVI times series from MODIS), and was modified and used to compute the NDWI indices and also the Normalized Difference Soil Index (NDSI). Coastwide Reference Monitoring System (CRMS) water levels from various hydrologic monitoring stations and aerial photography were used to optimize thresholds for MODIS-derived time series of NDWI and to validate resulting flood maps. In most of the profiles produced for post-hurricane assessment, the increase in the NDWI index (from storm surge) is accompanied by a decrease in the vegetation index (NDVI) and then a period of declining water. The NDSI index represents non-green or dead vegetation and increases after the hurricane s destruction of the marsh vegetation. Behavior of these indices over time is indicative of which areas remain flooded, which areas recover to their former levels of vegetative vigor, and which areas are stressed or in transition. Tracking these indices over time shows the recovery rate of vegetation and the relative behavior to inundation persistence. The results from this study demonstrated that identification of persistent marsh flooding, utilizing the tools developed in this study, provided an approximate 70-80 percent accuracy rate when compared to the actual days flooded at the CRMS stations.

Description: Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Description: This presentation discusses a NASA Stennis Space Center project in which NASA-supported satellite and aerial data is being used to aid state and federal agencies in restoring the Mississippi barrier islands. Led by the Applied Science and Technology Project Office (ASTPO), this project will produce geospatial information products from multiple NASA-supported data sources, including Landsat, ASTER, and MODIS satellite data as well as ATLAS multispectral, CAMS multispectral, AVIRIS hyperspectral, EAARL, and other aerial data. Project objectives include the development and testing of a regional sediment transport model and the monitoring of barrier island restoration efforts through remote sensing. Barrier islands provide invaluable benefits to the State of Mississippi, including buffering the mainland from storm surge impacts, providing habitats for valuable wildlife and fisheries habitat, offering accessible recreational opportunities, and preserving natural environments for educating the public about coastal ecosystems and cultural resources. Unfortunately, these highly valued natural areas are prone to damage from hurricanes. For example, Hurricane Camille in 1969 split Ship Island into East and West Ship Island. Hurricane Georges in 1998 caused additional land loss for the two Ship Islands. More recently, Hurricanes Ivan, Katrina, Rita, Gustav, and Ike impacted the Mississippi barrier islands. In particular, Hurricane Katrina caused major damage to island vegetation and landforms, killing island forest overstories, overwashing entire islands, and causing widespread erosion. In response, multiple state and federal agencies are working to restore damaged components of these barrier islands. Much of this work is being implemented through federally funded Coastal Impact Assessment and Mississippi Coastal Improvement programs. One restoration component involves the reestablishment of the island footprints to that in 1969. Our project will employ NASA remote sensing data and products to support these federally funded efforts on multiple fronts. Landsat and ASTER data is being analyzed to assess changes in barrier island land cover over the last 35 years. ASTER, SRTM, and EAARL terrain products and other NASA airborne imagery are being applied in assessing changes in barrier island geomorphology and geospatial extent. MODIS data is being examined as a tool for sediment transport modeling by supplying geospatial data that quantifies in-water sediment concentrations. MODIS satellite data is being assessed for monitoring changes in the spatial extent of individual barrier islands. Results thus far indicate that NASA data products are useful in assessing barrier island conditions and changes. This value is enhanced with additional historical geospatial data, commercial high resolution satellite data, other non-NASA aerial imagery, and field survey data. The project s products are relevant to the Gulf of Mexico Alliance priority issues, including coastal habitat conservation, restoration and coastal community resilience. Such products will be available to state and federal agencies involved with coastal restoration. Potential end-users of these products include the National Park Service, U.S. Geological Survey, U.S. Army Corps of Engineers, Environmental Protection Agency, Mississippi Department of Environmental Quality, and Mississippi Department of Marine Resources.

Description: This candidate solution proposes to use the night-imaging capabilities of the HSTC from SAC-C and of the HSC from SAC-D/Aquarius to detect bioluminescent events associated with HABs (harmful algal blooms). Once detected, this information could be fed to the NOAA CSCOR (Center for Sponsored Coastal Ocean Research) Harmful Algal Bloom Event Response Program, which acts quickly to fund the mobilization of research teams and to engage local agencies in a response. The HSC/HSTC data can serve as input to the HABSOS decision support system to provide information on location, extent, and duration of HAB events. Society will benefit from improved protection of the health of humans beings, aquatic ecosystems, and coastal economies. This work supports coastal management, public health, and homeland security applications.

Description: The 28-foot storm surge from Hurricane Katrina pushed inland along bays and rivers for a distance of 12 miles in some areas, contributing to the damage or destruction of about half of the fleet of boats in coastal Mississippi. Most of those boats had sought refuge in back bays and along rivers. Some boats were spared damage because the owners chose their mooring site well. Gulf mariners need a spatial analysis tool that provides guidance on the safest places to anchor their boats during future hurricanes. This product would support NOAA s mission to minimize the effects of coastal hazards through awareness, education, and mitigation strategies and could be incorporated in the Coastal Risk Atlas decision support tool.

Description: In an effort to more full explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as a focal point in this analysis.

Description: NASA's Scientific Data Purchase (SDP) project is currently a $70 million operation managed by the Earth Science Applications Directorate at Stennis Space Center. The SDP project was developed in 1997 to purchase scientific data from commercial sources for distribution to NASA Earth science researchers. Our current data holdings include 8TB of remote sensing imagery consisting of 18 products from 4 companies. Our anticipated data volume is 60 TB by 2004, and we will be receiving new data products from several additional companies. Our current system capacity is 24 TB, expandable to 89 TB. Operations include tasking of new data collections, archive ordering, shipment verification, data validation, distribution, metrics, finances, customer feedback, and technical support. The program has been included in the Stennis Space Center Commercial Remote Sensing ISO 9001 registration since its inception. Our operational system includes automatic quality control checks on data received (with MatLab analysis); internally developed, custom Web-based interfaces that tie into commercial-off-the-shelf software; and an integrated relational database that links and tracks all data through operations. We've distributed nearly 1500 datasets, and almost 18,000 data files have been downloaded from our public web site; on a 10-point scale, our customer satisfaction index is 8.32 at a 23% response level. More information about the SDP is available on our Web site.