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The Shuttle Radar Topography Mission (SRTM) flown on the Space Shuttle Endeavor on Flight STS-99 will produce digital elevation data of the Earth's land mass between 60 degrees north latitude and 54 degrees south latitude.
This paper provides an overview of the Shuttle Radar Topography Mission (SRTM), with emphasis on flight system implementation and mission operations from systems engineering perspective. Successfully flown in February, 2000, the SRTM's primary payload consists of several subsystems to form the first spaceborne dual-frequency (C-band and X-band) fixed baseline interferometric synthetic aperture radar (InSAR) system, with the mission objective to acquire data sets over 80% of Earth's landmass for height reconstruction. The paper provides system architecture, unique design features, engineering budgets, design verification, in-flight checkout and data acquisition of the SRTM payload, in particular for the C-band system. Mission operation and post-mission data processing activities are also presented. The complexity of the SRTM as a system, the ambitious mission objective, the demanding requirements and the high interdependency between multi-disciplined subsystems posed many challenges. The engineering experience and the insight thus gained have important implications for future spaceborne interferometric SAR mission design and implementation.
This paper provides an overview of the Shuttle Radar Topography Mission (SRTM), with emphasis on flight system implementation and mission operations from systems engineering perspective.
The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and SRTM data is well suited for vegetation 3-D mapping on a continental scale.
A report discusses Ka-band (35-GHz) radar for mapping the surface topography of glaciers and ice sheets at high spatial resolution and high vertical accuracy, independent of cloud cover, with a swath-width of 70 km. The system is a single- pass, single-platform interferometric synthetic aperture radar (InSAR) with an 8-mm wavelength, which minimizes snow penetration while remaining relatively impervious to atmospheric attenuation. As exhibited by the lower frequency SRTM (Shuttle Radar Topography Mission) AirSAR and GeoSAR systems, an InSAR measures topography using two antennas separated by a baseline in the cross-track direction, to view the same region on the ground. The interferometric combination of data received allows the system to resolve the pathlength difference from the illuminated area to the antennas to a fraction of a wavelength. From the interferometric phase, the height of the target area can be estimated. This means an InSAR system is capable of providing not only the position of each image point in along-track and slant range as with a traditional SAR but also the height of that point through interferometry. Although the evolution of InSAR to a millimeter-wave center frequency maximizes the interferometric accuracy from a given baseline length, the high frequency also creates a fundamental problem of swath coverage versus signal-to-noise ratio. While the length of SAR antennas is typically fixed by mass and stowage or deployment constraints, the width is constrained by the desired illuminated swath width. As the across-track beam width which sets the swath size is proportional to the wavelength, a fixed swath size equates to a smaller antenna as the frequency is increased. This loss of antenna size reduces the two-way antenna gain to the second power, drastically reducing the signal-to-noise ratio of the SAR system. This fundamental constraint of high-frequency SAR systems is addressed by applying digital beam-forming (DBF) techniques to synthesize multiple simultaneous receive beams in elevation while maintaining a broad transmit illumination. Through this technique, a high antenna gain on receive is preserved, thereby reducing the required transmit power and thus enabling high-frequency SARs and high-precision InSAR from a single spacecraft.
The primary objective of the STS-99 mission was to complete high resolution mapping of large sections of the Earth's surface using the Shuttle Radar Topography Mission (SRTM), a specially modified radar system. This videotape shows technicians in clean room suits working on the SRTM in the Multi-Payload Processing Facility (MPPF).
World Wind allows users to zoom from satellite altitude down to any place on Earth, leveraging high-resolution LandSat imagery and SRTM (Shuttle Radar Topography Mission) elevation data to experience Earth in visually rich 3D. In addition to Earth, World Wind can also visualize other planets, and there are already comprehensive data sets for Mars and the Earth's moon, which are as easily accessible as those of Earth. There have been more than 20 million downloads to date, and the software is being used heavily by the Department of Defense due to the code s ability to be extended and the evolution of the code courtesy of NASA and the user community. Primary features include the dynamic access to public domain imagery and its ease of use. All one needs to control World Wind is a two-button mouse. Additional guides and features can be accessed through a simplified menu. A JAVA version will be available soon. Navigation is automated with single clicks of a mouse, or by typing in any location to automatically zoom in to see it. The World Wind install package contains the necessary requirements such as the .NET runtime and managed DirectX library. World Wind can display combinations of data from a variety of sources, including Blue Marble, LandSat 7, SRTM, NASA Scientific Visualization Studio, GLOBE, and much more. A thorough list of features, the user manual, a key chart, and screen shots are available at http://worldwind.arc.nasa.gov.
Live footage of the STS-99 crew members shows Commander Kevin R. Kregel, Pilot Dominic L. Pudwill Gorie, Mission Specialists Janet L. Kavandi, Janice E. Voss, Mamoru Mohri, and Gerhard P.J. Thiele going through various training exercises. These exercises include Post Landing Egress, SRTM (Shuttle Radar Topography Mission) Deploy and Mapping Activities, HDTV (High Definition Television) Camera Training, and Ascent Simulation. Footage also includes the six-member crew participating in a photo session.
Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.
Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.
A radar interferometric topography mapper designed to acquire digital elevation maps of the Earth's surface from the Space Shuttle is described and its performance estimated.
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The Shuttle Radar Topography Mission (SRTM), carrying a single-pass interferometric synthetic aperture radar(SAR) instrument, collected a global elevation data set, which has been widely used in scientific, military and commercial communities. In the new proposed NASA SRTM reprocessing task, the SRTM elevation data is going to be processed at higher spatial resolution and with improved height accuracy. Upon completion, the improved SRTM product will be freely available. This paper describes the calibration approaches for reduction of elevation ripple effects and height accuracy improvements.
The Shuttle Radar Topographic Mission will map 80% of the Earth land mass topography with one arc-sec (30 meter) posting using a 60 meter baseline radar interferometer.
A database for Earth is now being created as the result of the Shuttle Radar Topography Mission (SRTM) during a 11 day Shuttle Endeavour flight in February.
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