ALBERT

Description: This document is concentrates on a couple of the missions where the Spacelab hardware was used to do Earth science. The Atmospheric Laboratory for Applications and Science (ATLAS) series of missions and the Lidar in-Space Technology Experiment (LITE) mission, the ATLAS being a series of three Shuttle missions that were very much Spacelab missions, are described. A little bit about the history, what the missions were, some of the instruments that were on them, and results are given.

Description: The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Description: Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.

Description: The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Description: The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre-and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric and 5% spatial has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).

Description: Collaborative effort is underway to map boreal forests worldwide using L-band, single polarization Synthetic Aperture Radar (SAR) imagery from the Japanese Earth Resources (JERS-1) satellite. Final products of the North American Boreal Forest Mapping Project will include two continental scale radar mosaics and supplementary multitemporal mosaics for Alaska, central Canada, and eastern Canada. For selected sites, we are also producing local scale (100 km x 100 km) and regional scale maps (1000 km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web. Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR Facility.

Description: Global Positioning System (GPS) signals reflected from the ocean surface have potential use for various remote sensing purposes. Some possibilities arc measurements of surface roughness characteristics from which ware height, wind speed, and direction could be determined. For this paper, GPS-reflected signal measurements collected at aircraft altitudes of 2 km to 5 km with a delay-Doppler mapping GPS receiver arc used to explore the possibility of determining wind speed. To interpret the GPS data, a theoretical model has been developed that describes the power of the reflected GPS signals for different time delays and Doppler frequencies as a function of geometrical and environmental parameters. The results indicate a good agreement between the measured and the modeled normalized signal power waveforms during changing surface wind conditions. The estimated wind speed using surface- reflected GPS data, obtained by comparing actual and modeled waveforms, shows good agreement (within 2 m/s) with data obtained from a nearby buoy and independent wind speed measurements derived from the TOPEX/Poseidon altimetric satellite.

Description: A collection of issues is discussed that are potential pitfalls, if handled incorrectly, for earth-orbiting lidar remote sensing instruments. These issues arise due to the long target ranges, high lidar-to-target relative velocities, low signal levels, use of laser scanners, and other unique aspects of using lasers in earth orbit. Consequences of misunderstanding these topics range from minor inconvenience to improper calibration to total failure. We will focus on wind measurement using coherent detection Doppler lidar, but many of the potential pitfalls apply also to noncoherent lidar wind measurement, and to measurement of parameters other than wind.

Description: In order to evaluate side-lobe contamination from the near-nadir region for Ku-Band radars, a statistical characterization of global near-nadir backscatter is constructed. This characterization is performed for a variety of surface types using data from TRMM, Seasat, and Topex. An assessment of the relative calibration accuracy of these sensors is also presented.

Description: In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.