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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Radar and Lidar Radar DEM

Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

remote sensing↗
NASA NTRS1993

Techniques and applications of SAR interferometry for ERS-1

The ERS-1 Synthetic Aperture Radar (SAR) demonstrated that it is possible to measure high resolution topography over large areas using interferometry with repeat orbit data sets. Given that the ERS-1 orbit is known with high precision, an automatic system for generation of interferograms is presented. Least squares estimation using ground control points provides an accurate method for determining the precise interferometric baseline. The system parameters which affect the accuracy of the Digital Elevation Models (DEM's) are errors in the interferometric baseline, decorrelation caused by baseline separation, thermal noise, and surface change. An adaptive filter based on the local interferometric coherence was developed to improve phase unwrapping of the interferogram. Final accuracies of the DEM's generated for single scene pairs in Alaska (U.S.) and Bonn (Germany) are on the order of 5 to 10 m.

Werner, Charles L.↗
NASA NTRS2000

Tropospheric Delay Signal in SAR Interferogram and its Correction for Precise Surface Change Detection

Synthetic Aperture Radar (SAR) interferometry has become an important tool for measuring the surface deformation and mapping topography. The largest error source of the SAR interferometry measurements is differential atmospheric delay of water vapor. It reflects detailed distribution of water vapor in troposphere at data acquisition. We found phase difference associated with atmospheric waves and severe local atmospheric phenomena in interferograms. To distinguish phase difference associated with surface deformation from tropospheric effect, we need several SAR interferograms including the time period of the deformation. Averaging the interferograms is an effective way to reduce the tropospheric delay from horizontal inhomogeneity of the water vapor distribution. Apart from the tropospheric delay of the horizontal water vapor inhomogeneity, we often find the differential phase correlated to the topography (elevation) in interferograms, which might cause error in interpretation of surface deformation. This phase is due to the differential tropospheric delay caused by the topography and vertical change of water vapor between two images in different atmospheric condition. Theoretical calculation shows that the phase difference can be approximated by linear expression of the elevation. We applied a simple and effective correction method that the error is removed by subtracting the DEM (Digital Elevation Model) multiplied a coefficient.

Fujiwara, Satoshi↗
NASA NTRS1995

Accurate estimation of sigma(exp 0) using AIRSAR data

During recent years signature analysis, classification, and modeling of Synthetic Aperture Radar (SAR) data as well as estimation of geophysical parameters from SAR data have received a great deal of interest. An important requirement for the quantitative use of SAR data is the accurate estimation of the backscattering coefficient sigma(exp 0). In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived from sensor position and Digital Elevation Model (DEM) data must always be considered. Especially in the airborne case, the antenna gain pattern can be an additional source of radiometric error, because the radar look angle is not known precisely as a result of the the aircraft motions and the local surface topography. Consequently, radiometric distortions due to the antenna gain pattern must also be corrected for each resolution cell, by taking into account aircraft displacements (position and attitude) and position of the backscatter element, defined by the DEM data. In this paper, a method to derive an accurate estimation of the backscattering coefficient using NASA/JPL AIRSAR data is presented. The results are evaluated in terms of geometric accuracy, radiometric variations of sigma(exp 0), and precision of the estimated forest biomass.

Holecz, Francesco↗
NASA NTRS1999

An Airborne Scanning Laser Altimetry Survey of Long Valley, California

Between 28 September and 7 October 1995, we conducted an airborne laser altimetry experiment over the Long Valley caldera, California, in which each of two scanning laser altimeters (dubbed SLICER and RASCAL) were flown in a NASA T-39 jet aircraft. Operating concurrently were a Global Positioning System (GPS) guidance system and dual frequency receivers for precise navigation and post-flight calculation or the airplane trajectory relative to a ground station, and an inertial navigation system (INS) for attitude determination. Reduction of raw laser ranges requires merging the differential kinematic GPS aircraft trajectory and the INS data with the laser data, and determination of the atmospheric delay. Data geolocation consists of obtaining the centre location and the mean elevation within each footprint in a geodetic coordinate system. The elevation of Crowley Lake is recovered to an accuracy of approximately 3 cm or better from 3 km above ground level and crossover analysis indicates that the elevation estimates are consistent from pass to pass. We test our geolocation procedures by comparing laser-derived elevations with those determined in situ for recognizable ground features. A comparison of laser and GPS-derived positions shows that the horizontal accuracy is better than the diameter of the footprint and vertical accuracy is within the error inherent in the range measurement. A comparison of SLICER elevation data with digital elevation models (DEMs) of the region shows that the DEM data provides surface topography to within stated accuracy limits. Although research continues to utilize the full potential of laser altimetry data, our results constitute a successful demonstration that the technique may be used to perform geodetic monitoring of surface topographic changes.

Hofton, M. A.↗
NASA NTRS1999

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

Freedman, Adam↗
NASA NTRS1987

Stereocorrelation of Landsat TM images

A digital elevation model (DEM) developed from Landsat TM images of a rugged terrain area in north Georgia by automated stereocorrelation techniques yielded an rms error (z), RMSE(z), value of + or - 42 m. Based on the B/H ratio of 0.18 for the Landsat data, this Z-error corresponds to a planimetric correlation accuracy of about + or - 0.3 pixels, confirming that precise correlation can be achieved with operational satellite data. Contours at a 100-m interval interpolated from the DEM show a deviation of + or - 33 m from reference contours obtained from existing 1:24,000-scale maps. The 28.5-m pixel resolution and the weak B/H ratio impose limitations on the accuracy that can be achieved with Landsat TM data. However, it is anticipated that RMSE(z) values of + or - 10 m or less can be achieved with SPOT-1 panchromatic stereo images of 10-m resolution recorded at B/H ratios of 0.5 to 1.0. DEMs generated by stereocorrelation techniques can be used to create orthoimages, perspective views, and topographic map products.

Ehlers, Manfred↗
NASA NTRS1994

Accurate Estimation of Backscattering Coefficient Using Airsar Data

In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived form sensor position and Digital Elevation Model (DEM) data must always be considered.

Synthetic Aperture Rada Backscatter↗
NASA NTRS1997

Interferometric SAR for observation of glacier motion and firn penetration

A digital elevation model (DEM) for a swath in west Greenland above Jakobshavn Isbrae derived from a number ERS-1 interferograms combined so as to reduce phase errors and other problems is presented. The DEM shows a wealth of kilometer-scale, dynamically supported topography, which arises from ice sheet flow over the rough bed. A correlation is shown between topography and interferometric phase due solely to ice sheet motion, which clearly shows the translations of scatterers in the surface up and downslope in the topography. Finally, the low correlation in interferograms of ice sheet dry snow zones motivates investigation on the depth-locus of backscattering. A scattering model is presented, including realistic firn grain size distributions and layering, which shows that layering helps to localize backscattering from dry firn to shallower depths than would otherwise be expected.

Winebrenner, Dale P.↗
NASA NTRS2001

Imaging Radar in the Mojave Desert-Death Valley Region

The Mojave Desert-Death Valley region has had a long history as a test bed for remote sensing techniques. Along with visible-near infrared and thermal IR sensors, imaging radars have flown and orbited over the area since the 1970's, yielding new insights into the geologic applications of these technologies. More recently, radar interferometry has been used to derive digital topographic maps of the area, supplementing the USGS 7.5' digital quadrangles currently available for nearly the entire area. As for their shorter-wavelength brethren, imaging radars were tested early in their civilian history in the Mojave Desert-Death Valley region because it contains a variety of surface types in a small area without the confounding effects of vegetation. The earliest imaging radars to be flown over the region included military tests of short-wavelength (3 cm) X-band sensors. Later, the Jet Propulsion Laboratory began its development of imaging radars with an airborne sensor, followed by the Seasat orbital radar in 1978. These systems were L-band (25 cm). Following Seasat, JPL embarked upon a series of Space Shuttle Imaging Radars: SIRA (1981), SIR-B (1984), and SIR-C (1994). The most recent in the series was the most capable radar sensor flown in space and acquired large numbers of data swaths in a variety of test areas around the world. The Mojave Desert-Death Valley region was one of those test areas, and was covered very well with 3 wavelengths, multiple polarizations, and at multiple angles. At the same time, the JPL aircraft radar program continued improving and collecting data over the Mojave Desert Death Valley region. Now called AIRSAR, the system includes 3 bands (P-band, 67 cm; L-band, 25 cm; C-band, 5 cm). Each band can collect all possible polarizations in a mode called polarimetry. In addition, AIRSAR can be operated in the TOPSAR mode wherein 2 antennas collect data interferometrically, yielding a digital elevation model (DEM). Both L-band and C-band can be operated in this way, with horizontal resolution of about 5 m and vertical errors less than 2 m. The findings and developments of these earlier investigations are discussed.

Farr, Tom G.↗
NASA NTRS2011

Evaluation of the Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010) Using ICESat Geodetic Control

Supported by NASA's Earth Surface and Interior (ESI) Program, we are producing a global set of Ground Control Points (GCPs) derived from the Ice, Cloud and land Elevation Satellite (ICESat) altimetry data. From February of 2003, to October of 2009, ICESat obtained nearly global measurements of land topography (+/- 86deg latitudes) with unprecedented accuracy, sampling the Earth's surface at discrete approx.50 m diameter laser footprints spaced 170 m along the altimetry profiles. We apply stringent editing to select the highest quality elevations, and use these GCPs to characterize and quantify spatially varying elevation biases in Digital Elevation Models (DEMs). In this paper, we present an evaluation of the soon to be released Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). Elevation biases and error statistics have been analyzed as a function of land cover and relief. The GMTED2010 products are a large improvement over previous sources of elevation data at comparable resolutions. RMSEs for all products and terrain conditions are below 7 m and typically are about 4 m. The GMTED2010 products are biased upward with respect to the ICESat GCPs on average by approximately 3 m.

Carabajal, Claudia C.↗
NASA NTRS2000

The Shuttle Radar Topography Mission: A Global DEM

Digital topographic data are critical for a variety of civilian, commercial, and military applications. Scientists use Digital Elevation Models (DEM) to map drainage patterns and ecosystems, and to monitor land surface changes over time. The mountain-building effects of tectonics and the climatic effects of erosion can also be modeled with DEW The data's military applications include mission planning and rehearsal, modeling and simulation. Commercial applications include determining locations for cellular phone towers, enhanced ground proximity warning systems for aircraft, and improved maps for backpackers. The Shuttle Radar Topography Mission (SRTM) (Fig. 1), is a cooperative project between NASA and the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense. The mission is designed to use a single-pass radar interferometer to produce a digital elevation model of the Earth's land surface between about 60 degrees north and south latitude. The DEM will have 30 m pixel spacing and about 15 m vertical errors.

Farr, Tom G.↗
NASA NTRS1996

(abstract) The Shuttle Radar Topography Mapper

The Shuttle Radar Topography Mapper (SRTM), is a cooperative project between NASA and the Defense Mapping Agency of the U.S. Department of Defense. The mission is designed to use a single-pass radar interferometer to produce a digital elevation model of the Earth's land surface between about 60 degrees north and south latitude. The DEM will have 30 m horizontal resolution and about 10 m vertical errors.

Shuttle Radar Topography Mapper interferometry glo↗
NASA NTRS1996

An Automated Mapping Processor Using C-Band Interferometric SAR Data

We present the description of a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric SAR processing producing a Digital Elevation Model (DEMs) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a GIS system which allows for both hard copy map products and for digital applications.

Rodriguez, E.↗
NASA NTRS1996

An Automated Mapping Processor using C-Band Interferometric SAR Data

We describe a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric synthetic aperture radar (SAR) processing producing a digital elevation model (DEM) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a geographical information system (GIS) which allows for both hard copy map products and digital applications.

Rodriguez, E.↗
NASA NTRS2019

Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery

Knowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.

Yao Li↗
NASA NTRS1993

Topographic mapping using radar interferometry - Processing techniques

In the summer of 1991 the NASA DC-8 airborne synthetic aperture radar (SAR) system acquired data with the radar configured in a C-band across-track interferometer mode. The data were processed to generate rectified topographic maps. A new processing scheme was developed featuring motion compensation, absolute phase retrieval, and three-dimensional 1ocation. The new processor has been tested using data which were acquired with extreme aircraft motion so that performance could be evaluated under adverse conditions. The topographic maps generated by the radar were compared to Digital Elevation Models (DEM's) derived using conventional optical stereo techniques. In one region we measured rms elevation deviations which were less than the specified DEM accuracy, and in the region covered by the more accurate DEM we found errors varying from 2.2 m rms in relatively flat terrain up to 5.0 m in mountainous areas. The rms difference between radar and DEM elevations over the 6.5 km by 22 km area covered by the more accurate DEM was 3.6 m.

Madsen, Soren N.↗