Estimating Vegetation and Surface Topographic Parameters From Multibaseline Radar
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Drawing from recently submitted work, this paper first gives a heuristic description of the sensitivity of interferometric synthetic aperture radar (INSAR) to vertical vegetation distribution and under laying surface topography. A parameter estimation scenario is then described in which the INSAR cross correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of INSAR observations for single baseline, single frequency, single incidence-angle, single polarization INSAR. Using ancillary ground truth data to compensate for the under determination of the parameters, forest depths are estimated from the INSAR data. A recently analyzed multi-baseline data set is also discussed and the potential for stand alone INSAR parameter estimation is assessed. The potential of combining the information content of INSAR with that of infrared/optical remote sensing data is briefly discussed.
This paper first gives a heuristic description of the sensitivity of Interferometric Synthetic Aperture Radar to vertical vegetation distributions and underlying surface topography. A parameter estimation scenario is then described in which the Interferometric Synthetic Aperture Radar cross-correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous-layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of Interferometric Synthetic Aperture Radar observations for single-baseline, single-frequency, single-incidence-angle, single-polarization Interferometric Synthetic Aperture Radar. Using ancillary ground-truth data to compensate for the underdetermination of the parameters, forest depths are estimated from the INSAR data. A recently-analyzed multibaseline data set is also discussed and the potential for stand-alone Interferometric Synthetic Aperture Radar parameter estimation is assessed. The potential of combining the information content of Interferometric Synthetic Aperture Radar with that of infrared/optical remote sensing data is briefly discussed.
The temporal changes that are recorded by ERTS were evaluated for an area around Bathurst Inlet in the North West Territories. The seasons represented by the images included: early winter, spring, early summer, summer, and fall. Numerous surface characteristics (vegetation, drainage patterns, surface texture, lineament systems and topographic relief, etc.) were used to relate the change in observable features with the different seasons. It was found that the time of year when an observation is made has a strong control over the amount and type of information that can be derived by an experienced interpreter. It was concluded that a detailed study of temporal changes is an important part of any ERTS interpretation for geology.
A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.
Advanced knowledge in atmospheric CO2 is critical in reducing large uncertainties in predictions of the Earth' future climate. Thus, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) from space was recommended by the U.S. National Research Council to NASA. As part of the preparation for the ASCENDS mission, NASA Langley Research Center (LaRC) and Exelis, Inc. have been collaborating in development and demonstration of the Intensity-Modulated Continuous-Wave (IM-CW) lidar approach for measuring atmospheric CO2 column from space. Airborne laser absorption lidars such as the Multi-Functional Fiber Laser Lidar (MFLL) and ASCENDS CarbonHawk Experiment Simulator (ACES) operating in the 1.57 micron CO2 absorption band have been developed and tested to obtain precise atmospheric CO2 column measurements using integrated path differential absorption technique and to evaluate the potential of the space ASCENDS mission. This presentation reports the results of our lidar atmospheric CO2 column measurements from 2014 summer flight campaign. Analysis shows that for the 27 Aug OCO-2 under flight over northern California forest regions, significant variations of CO2 column approximately 2 ppm) in the lower troposphere have been observed, which may be a challenge for space measurements owing to complicated topographic condition, heterogeneity of surface reflection and difference in vegetation evapotranspiration. Compared to the observed 2011 summer CO2 drawdown (about 8 ppm) over mid-west, 2014 summer drawdown in the same region measured was much weak (approximately 3 ppm). The observed drawdown difference could be the results of the changes in both meteorological states and the phases of growing seasons. Individual lidar CO2 column measurements of 0.1-s integration were within 1-2 ppm of the CO2 estimates obtained from on-board in-situ sensors. For weak surface reflection conditions such as ocean surfaces, the 1- s integrated signal-to-noise ratio (SNR) of lidar measurements at 11 km altitude reached 376, which was equivalent to a 10-s CO2 error 0.33 ppm. For the entire processed 2014 summer flight campaign data, the mean differences between lidar remote sensed and in-situ estimated CO2 values were about -0.013 ppm. These results indicate that current laser absorption lidar approach could meet space measurement requirements for CO2 science goals.
Inland flooding from tropical cyclones can be a significant factor in storm-related deaths in the United States and other countries. Information collected during NASA tropical cyclone field studies suggest surface water and flooding induced by tropical cyclone precipitation can be detected and therefore monitored using passive microwave airborne radiometers. In particular, the 10.7 GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) flown on the NASA ER-2 has demonstrated high resolution detection of anomalous surface water and flooding in numerous situations. This presentation will highlight the analysis of three cases utilizing primarily satellite and airborne radiometer data. Radiometer data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during landfalling Hurricane Georges in both the Dominican Republic and Louisiana. A third case is landfalling Tropical Storm Gert in Eastern Mexico during the Tropical Cloud Systems and Processes (TCSP) experiment in 2005. AMPR data are compared to topographic data and vegetation indices to evaluate the significance of the surface water signature visible in the 10.7 GHz information. The results of this study suggest the benefit of an aircraft 10 GHz radiometer to provide real-time observations of surface water conditions as part of a multi-sensor flood monitoring network.
The NASA/JPL TOPSAR instrument recently was extended from a single wavelength C-band dual aperture synthetic aperture radar (SAR) interferometer to include a second wavelength at the L-band. Adding the second wavelength invites comparison of wavelength-diverse effects in topographic mapping of surfaces, with the principal goal of understanding the penetration of the radar signals in vegetation canopies, and determining the inferred topographic height. A first analysis of these data was conducted at two sites. Elkhorn Slough near Monterey, California presented flat, vegetation free terrain required for calibrating the radar interferometer parameters. A second site stretching from San Jose to Santa Cruz, California, which is heavily vegetated, provided the first test case for wavelength diverse penetration studies. Preliminary results show that: (a) the interferometer calibration determined at Elkhorn Slough is extenable to Laurel Quad and gives confidence in the C- and L-band height measurements; (b) Clear differences were observed between the C- and L-band heights associated with vegetation, with the C-band derived topographic heights generally higher than those from L-band. The noise level in the L-band interferometer is presently the limiting factor in penetration studies.
The NASA/JPL TOPSAR instrument recently was extended from a single- wavelength C-band (5.6 cm-lambda) dual aperture synthetic aperture radar interferometer to include a second wavelength at L-band (24 cm). Adding the second wavelength invites comparison of wavelength-diverse effects in topographic mapping of surfaces, with the principal goal of understanding the penetration of the radar signals in vegetation canopies, and determining the inferred topographic height. A first analysis of these data was conducted at two sites. Elkhorn Slough near Monterey, California presented flat, vegetation free terrain required for calibrating the radar interferometric parameters. A second site stretching from San Jose to Santa Cruz, CA, which is heavily vegetated, provided the first test case for wavelength diverse penetration studies. Preliminary results show that: (a) the interferometer calibration determined at Elkhorn Slough is extendable to Laurel Quad and gives confidence in the C- and L-band height measurements; and (b) Clear differences are observed between the C- and L-band heights associated with vegetation, with C-band-derived topographic heights generally higher than those from L-band. The noise level in the L-band interferometer is presently the limiting factor in penetration studies.
Teh NASA/JPL TOPSAR instrument recently was extended from a single wavelength C-band dual aperture synthetic aperture radar interferometer to include a second wavelength at L-band. Adding the second wavelength invites comparison of wavelength diverse effects in topographic mapping of surfaces, with the principal goal of understanding the penetration of the radar signals in vegetation canopies, and determining the inferred topographic height.
A lidar instrument on a spacecraft was first used to measure planetary surface height and topography on the Apollo 15 mission to the Moon in 1971, The lidar was based around a flashlamp-pumped ruby laser, and the Apollo 15-17 missions used them to make a few thousand measurements of lunar surface height from orbit. With the advent of diode pumped lasers in the late 1980s, the lifetime, efficiency, resolution and mass of lasers and space lidar all improved dramatically. These advances were utilized in NASA space missions to map the shape and surface topography of Mars with > 600 million measurements, demonstrate initial space measurements of the Earth's topography, and measured the detailed shape of asteroid. NASA's ICESat mission in Earth orbit just completed its polar ice measurement mission with almost 2 billion measurements of the Earth's surface and atmosphere, and demonstrated measurements to Antarctica and Greenland with a height resolution of a few em. Space missions presently in cruise phase and in operation include those to Mercury and a topographic mapping mission of the Moon. Orbital lidar also have been used in experiments to demonstrate laser ranging over planetary distances, including laser pulse transmission from Earth to Mars orbit. Based on the demonstrated value of the measurements, lidar is now the preferred measurement approach for many new scientific space missions. Some missions planned by NASA include a planetary mission to measure the shape and dynamics of Europa, and several Earth orbiting missions to continue monitoring ice sheet heights, measure vegetation heights, assess atmospheric CO2 concentrations, and to map the Earth surface topographic heights with 5 m spatial resolution. This presentation will give an overview of history, ongoing work, and plans for using space lidar for measurements of the surfaces of the Earth and planets.
A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.
The continued growth of Southwestern cities depends on reliable water export from Rocky Mountain headwaters, which provide ~85% of Colorado River Basin (CRB) streamflow. Despite being more sensitive to warming temperatures, alpine systems are simplified in the regional-scale models currently in use to plan for future water supply. We used an integrated hydrologic model that couples groundwater and surface water with snow and vegetation processes to examine the effect of topographic simplifications as a result of grid coarsening in a representative CRB headwater basin. High-resolution (100 m) simulations predicted headwater streamflow losses of 16% by 2050 while coarse-resolution (1 km) simulations predict only 12%, suggesting that regional-scale models (coarser than 1 km) likely overestimate future Colorado River Basin water supplies.
Over the last several decades, warming in the Arctic has outpaced the already impressive increases in global mean temperatures. The impact of these increases in temperature has been observed in a multitude of ecological changes in North American tundra including changes in vegetative cover, depth of active layer, and surface water extent. The low topographic relief and continuous permafrost create an ideal environment for the formation of small water bodies - a definitive feature of tundra surface. In this study, water bodies in Nunavut territory in northern Canada were mapped using a long-term record of remotely sensed observations at 30 meters spatial resolution from the Landsat suite of instruments. The temporal trajectories of water extent between 1985 and 2015 were assessed. Over 675,000 water bodies have been identified over the 31-year study period with over 168,000 showing a significant (probability is less than 0.05) trend in surface area. Approximately 55 percent of water bodies with a significant trend were increasing in size while the remaining 45 percent were decreasing in size. The overall net trend for water bodies with a significant trend is 0.009 hectares per year per water body.
The data package contains model input files and executables for the East River, Colorado (750 km2) located in the headwaters of the Upper Colorado River Basin. The code applied is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution to represent topographic complexity and a daily timestep accounts for energy and water partitioning between the snowpack, vegetation, soil zone and bedrock. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model accounts for nine stratigraphic units and extends 400 m below land surface. Using this modeling framework we explore historical water budgets (water year 1987-2022) and the influence of seasonal warming and associated mechanisms driving groundwater declines and streamflow loss. A Readme_062424.txt file provides instructions on how to download all files. Input and output files are provided for the historical simulation representative of water years 1987 to 2022 (i.e. baseline) and the all-year +4C warming scenario. Instructions are provided to run the seasonal warming scenarios with warming applied only to the autumn, winter, spring or summer months. Modeled output used in figures for Carroll et al., 2024 are also provided with metadata describing where these data were obtained. This dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Updated on 06-24-2024: The dataset was updated to include model outputs (updated base.zip and 4C.zip files), figure source files (Figure_Source_Files.zip), an updated Readme file (Readme_062424.txt), climate input files (climate_input_files.zip), and the adoption of ESS-DIVE File Level Metadata and CSV reporting formats (inclusion of flmd.csv and dd.csv files).
Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near- Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skillful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.
We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.
A series of NASA airborne lidars have been used in support of satellite laser altimetry missions. These airbornelaser altimeters have been deployed for satellite instrument development, for spaceborne data validation, and to bridge the data gap between satellite missions. We used data from ground-based Global Positioning System (GPS) surveys of an 11 km long track near Summit Station, Greenland, to assess the surface elevation bias and measurement precision of three airborne laser altimeters including the Airborne Topographic Mapper (ATM), the Land, Vegetation, and Ice Sensor (LVIS), and the Multiple Altimeter Beam Experimental Lidar (MABEL). Ground-based GPS data from the monthly ground-based traverses, which commenced in 2006, allowed for the assessment of nine airborne lidar surveys associated with ATM and LVIS between 2007 and 2016. Surface elevation biases for these altimeters over the flat, ice-sheet interior are less than 0.12 m, while assessments of measurement precision are 0.09 m or better. Ground-based GPS positions determined both with and without differential post-processing techniques provided internally consistent solutions. Results from the analyses of ground-based and airborne data provide validation strategy guidance for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) elevation and elevation-change data products.