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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1↗
NASA NTRS1993

Estimation of Soil Moisture and Biomass Changes Using SAR Data During EFEDA-Spain Experiment

During the 1991 MAC-EUROPE campaign, the Castilla La-Mancha region of Spain was surveyed by the Multi-frequency (P-,L-, C-band) polarimetric AIRSAR of Jet Propulsion Laboratory. The experiment was devised to demonstrate the role of SAR imagery in detecting and estimating surface parameters such as soil moisture and canopy water content.

Soil MoistureBiomass Changes Spain↗
NASA NTRS2004

Modified polar format algorithm for processing spaceborne SAR data

This paper describes a modified polar format algorithm for SAR image-formation processing. the algorithm focuses raw data assuming a spherical reference surface (ground surface), and, unlike standard polar format algorithms, it assumes spherical rather than planar signal wavefronts.

polar format processing↗
NASA NTRS2004

Software Processes SAR Motion-Measurement Data

Motion Measurement Processor (MMP) is one of three computer programs that are used together in the operation of a terrain-mapping dual-frequency interferometric synthetic-aperture-radar (SAR) system. The other two programs - Jurassicprok and Calibration Processor - are described in the two immediately preceding articles. MMP acquires all the motion and attitude data collected by onboard instrumentation systems, including radar, laser and camera metrology, inertial navigation systems, and Global Positioning System (GPS) receivers. MMP combines all this information and processes it into all the trajectory information needed to run Jurassicprok, which performs the interferometric processing and mapping functions. MMP includes several Kalman filters for combining and smoothing aircraft motion and attitude data, and least-squares inversion and filtering software tools for solving for interferometric baseline lengths. MMP synchronizes the motion and radar data. It combines the various measurement data into a unified, seven-dimensional reference system and puts out the resulting filtered trajectory and attitude data along with instructions for use of the data by Jurassicprok, as well as the command files used to operate Jurassicprok.

Freedman, Adam↗
NASA NTRS2012

Integrated Analysis of Interferometric SAR, Satellite Altimetry and Hydraulic Modeling to Quantify Louisiana Wetland Dynamics

Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.

Lee, Hyongki↗
NASA NTRS2012

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

subsurface sensing↗
NASA NTRS2012

Impact of Ionospheric Scintillation on Spaceborne SAR Observations Studied Using GNSS

A survey of artifacts seen in JAXA's Phase Array type L-band synthetic aperture radar (PALSAR) data over South America during a low solar activity year is reported in this paper. A significant impact on the radar data is revealed: about 14% of the surveyed PALSAR images (totally 2779) are affected by the artifacts during a month and the artifacts occur on 74.2% of the surveyed days. The characteristics of the artifacts have led to a consideration that the artifacts are the effects of ionospheric scintillation. This raises not only a concern about scintillation effects on radar but also a question about active scintillation conditions during a low solar activity year. To assess and verify the scintillation conditions, GPS data collected from the constellation of FORMOSAT-3/COSMIC satellites and three ground-based GPS networks are processed and analyzed. The GPS data provides a global context and regional dense converge, respectively, of ionospheric irregularity and scintillation measurements. It is concluded tat even during a low solar activity year, L-band scintillation at low latitudes can occur frequently and affect L-band SAR significantly.

remote sensing↗
NASA NTRS2017

Leveraging the Usage of GPUs in SAR Processing for the NISAR Mission

The NASA ISRO Synthetic Aperture Radar (NISAR) mission will redefine the future of earth science in terms of both the quality as well as the quantity of data that will be downlinked daily. The current software architecture used to process this data is the InSAR Scientific Computing Environment (ISCE), a powerful and modular platform that applies a combination of novel and legacy processing modules to many sources of SAR data. Until recently, this architecture could process most images in a reasonable amount of time; however in the case of the NISAR mission (where the daily influx as well as the size of the images themselves are significantly larger) the current architecture can take hours to process even a single image. This paper explores new efforts to use a Graphics Processing Unit (GPU) to accelerate one of the processing modules to achieve unprecedented runtimes with no loss in precision, potentially setting a new standard in radar processing in the world of “Big Data”.

Cohen, Joshua↗
NASA NTRS2017

NISAR L-SAR Digital Electronics Subsystem - A Multichannel Distributed Processing System with Synchronous Timing Control for Digital Beam Forming and Multiple Echo Tracking

The NASA-ISRO Synthetic Aperture Radar (NISAR) L-band SAR instrument employs multiple digital channels to optimize resolution while keeping a large swath on a single pass. High-speed digitization with fine synchronization and digital beam forming are necessary in order to facilitate this new technique called SweepSAR. An architecture employing multiple FPGA based digital signal processors has been conceived to facilitate digital calibration on an individual channel basis as well as digital signal processing to optimize the receive signal. On-board processing and data compression has been implemented to reduce the volume of data in order to satisfy the operational requirements of near global coverage for the desired science targets. A novel command and timing architecture was developed to manage this complex system while providing detailed control of individual channel receive window timing required for digital beam forming. The NISAR L-band Digital Electronics Subsystem is the combination of the hardware, firmware and software components architected and implemented to operate this radar and return the desired quantity and quality of data for the science community.

Chuang, Chung-Lun↗
NASA NTRS1993

Alaska SAR Facility Mass Storage, Current System

This paper examines the mass storage systems that are currently in place at the Alaska SAR facility (ASF). The architecture of the facility will be presented including specifications of the mass storage media that are currently used and the performances that we have realized from the various media. The distribution formats and media will also to be discussed. Because the facility is expected to survice future sensors, the new requriements and possible solutions to these requriements will also be discussed.

Mass↗
NASA NTRS2018

Impact of Gaps in the NASA-ISRO SAR Mission Swath

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission will carry L-band and S-band SAR instruments, each with a 240 km swath width. The L-band instrument has the capability to map the entire Earth’s land and ice covered surfaces from both ascending and descending orbit positions, continuously in an exact 12 day repeating cycle, given temporally dense (better than 6-day on average) sampling of Earth over the life of the mission. To achieve this swath coverage without loss of resolution or polarimetric capability, NISAR uses a reflector-feed based antenna system with scan-on-receive (“SweepSAR”) capability. One of the characteristics of SweepSAR is that the pulse repetition interval of the radar is shorter than the echo receive window for the 240 km swath. Therefore, transmit events occur during the receive window and the receivers must be blanked periodically, creating gaps in the coverage. For fixed pulse rate operations, these gaps are persistent strips of blanked ranges. NISAR is being designed to allow variation of the pulse rate in order to spread out these gaps throughout the synthetic aperture, but processing these variably-acquired data is more challenging and can lead to compromises in image quality. At the highest level NISAR places requirements on science measurements rather than image quality, so there is often a debate among science and engineering team members as to whether to operate with fixed pulse rates – leading to range strips consistently blank from cycle to cycle but with optimal image quality – or to vary the pulse rate, fill in the gaps, and live with degraded image quality. NISAR’s performance team has shown that science requirements can be met with the gaps. However, scientists are eager for maximum and coverage within a swath. A companion paper (Villano et al.) describes image quality for NISAR using a variable PRF approach, but does not go further to science requirements. This paper explores the issues when gaps are present in the swath due to fixed PRF operations.

Veeramachaneni, Chandini↗
NASA NTRS2020

Detecting differential ground displacements of civil structures in fast-subsiding metropolises with interferometric SAR and band-pass filtering

Ground displacements due to changes in soil conditions represent a threat to the stability of civil structures in many urban areas, worldwide. In fast-subsiding areas, regional subsidence (wavelength ~ 1,000’s m) can be dominantly high and, consequently, mask other signals at local scales (wavelength ~ 10–100’s m). Still, engineering and construction applications require a comprehensive knowledge of local-scale signals, which can threaten the stability of buildings and infrastructure. Here we present a new technique based on band-pass filters for uncovering local-scale signals hidden by regional subsidence as detected by interferometric SAR measurements. We apply our technique to a velocity field calculated from 21 high-resolution COSMO-SkyMed scenes acquired over Mexico City and obtain components of long (> 478 m), intermediate (42–478 m) and short (< 42 m) spatial wavelengths. Our results reveal that long-wavelength velocities exceed − 400 mm/year, whereas intermediate- and short-wavelength velocities are in the order of ± 15 mm/year. We show that intermediate-wavelength velocities are useful for retrieving signals such as uplift along elevated viaducts of Metro lines 4 and B, as well as differential displacements in Pantitlán station’s pedestrian overpass system and across sharp geotechnical boundaries in the piedmont of Sierra de Santa Catarina—where surface faulting occurs.

Darío Solano-Rojas↗
NASA NTRS2020

Residual Motion Estimation for Multi-Squint Airborne SAR

Airborne SAR data are often challenging to analyze due tothe limited accuracy of the platform motion measurements.In interferometric scenarios, even small residual motion er-rors cause undesirable artifacts in the interferometric phaseand geometric registration of image pairs. Various calibrationtechniques have been developed, often exploiting spectral di-versity in some way. The UAVSAR L-band system has imple-mented a new operating mode where multiple images are ac-quired simultaneously at different azimuth squint angles, pro-viding enhanced opportunities for motion calibration. Thispaper describes this imaging mode and the residual motioncalibration technique developed for these special data sets.

Hawkins, Brian↗
NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗
NASA NTRS2021

Potential of Full-polarimetric P- and L-band Sar Data in Characterizing Post-fire Recovery of Arctic Tundra

We used the airborne full polarimetric L-band and P-band SAR (PolSAR) data collected from recent NASA ABoVE Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign to understand the sensitivity of longwave radar backscatter intensity and phase to post-fire recovery process of Arctic tundra. The 2007 Anaktuvuk River fire was used as a case study. At 10-year post-fire, we observed a strong increase (>~4 dB) in both the P- and L-band radar backscatter in the severely burned areas, in contrast to limited backscatter differences (VV, VH) between burned and unburned areas at C-band. The polarimetric target decomposition analysis indicated a general trend towards more random surface scattering, and strong increases of the double-bounce and volumetric scattering power at both P- and L-band in the burned areas. Large differences were also observed in the Pauli phase angle and the dominant-scattering-type Touzi phase angle between the burned and unburned areas. The above changes are likely caused by increasing surface roughness and microtopography due to thermokarst development and ice degradation, and increasing subsurface scattering due to an overall drier and deeper active layer in the burned areas

Miller, Charles E.↗
NASA NTRS2021

Science Status of the NASA-ISRO SAR Mission

The NASA-ISRO SAR (NISAR) Mission is entering its second phase of integration and test, preparing for a launch in January 2023. The mission will exploit synthetic aperture radar to map Earth’s surface every 12 days, persistently on ascending and descending portions of the orbit, over all land and ice-covered surfaces. The mission’s primary objectives will be to study Earth land and ice deformation, and ecosystems, in areas of common interest to the US and Indian science communities. This single observatory solution with an L-band (24 cm wavelength) and S-band (10 cm wavelength) radar has a swath of over 240 km at fine resolution, and will operate primarily in a dual-polarimetric mode in an exact repeat orbit. The science teams at NASA and ISRO are working jointly to finalize the joint science plan, calibration and validation plan, and science products, and operational procedures.

Kumar, Raj↗