Radar systems for the water resources mission, volume 1

The state of the art determination was made for radar measurement of: soil moisture, snow, standing and flowing water, lake and river ice, determination of required spacecraft radar parameters, study of synthetic-aperture radar systems to meet these parametric requirements, and study of techniques for on-board processing of the radar data. Significant new concepts developed include the following: scanning synthetic-aperture radar to achieve wide-swath coverage; single-sideband radar; and comb-filter range-sequential, range-offset SAR processing. The state of the art in radar measurement of water resources parameters is outlined. The feasibility for immediate development of a spacecraft water resources SAR was established. Numerous candidates for the on-board processor were examined

The 1993-1994 Surge Of Bering Glacier, Alaska Observed With Satellite Synthetic Aperture Radar

Thesis (M.S.) University of Alaska Fairbanks, 1996Sequential synthetic aperture radar (SAR) images acquired by the First European Remote Sensing Satellite (ERS-1) were employed for observation of the 1993-'94 surge of Bering Glacier, Alaska. Evidence of accelerated motion became visible in late April 1993. Subsequently the surge front propagated down-glacier at a mean velocity of 90 m/day between 19 May and 25 August, reaching most of the 34 km perimeter of the terminus by shortly after 25 August. The calving terminus then advanced rapidly into proglacial Vitus Lake at a maximum rate, during 9 August to 18 October, of 19 m/day in its central area. The propagating surge front consisted of a distributed region of undulations and bulges on the glacier surface having heights, estimated from SAR data, of 40 to 110 m and widths varying from 0.7 to 1.5 km. The measurements were made using terrain-corrected, geocoded and coregistered images. <p

Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

Upgrade of foss date plug-in: Implementation of a new radargrammetric DSM generation capability

Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome "La Sapienza", and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery

Synthetic Aperture Radar: Rapid Detection of Target Motion in Matlab

Synthetic Aperture Radar (SAR) has come into widespread use in several civilian and military applications. The focus of this paper is the military application of imaging point targets captured by an airborne SAR platform. Using the traditional SAR method of determining target motion by analyzing the difference between subsequent images takes a relatively large amount of processing resources. Using methods in this thesis, target motion can be estimated before even a single image is obtained, reducing the amount of time and power used by a significantly large amount. This thesis builds on work done by Brain Zaharri and David So. Brain Zaharri successfully created a SAR simulation that accurately models the airborne SAR system capturing data of a target space using the Range Doppler Algorithm (RDA). David So extended this work by adding functionality to determine target velocity in the range and azimuth directions by processing the intermittent data created by the several steps of Brian Zaharri’s simulation. This thesis shows further extensions of processing the intermittent data using unique methods. The methods in this thesis successfully demonstrate the ability to quickly and accurately estimate target position, velocity, and acceleration without the need for using multiple SAR images. Target motion in the range direction is detected without using any part of the RDA, while the azimuth direction cuts out several steps, including the range compression phase and the range cell migration correction. Removing these unneeded processing steps dramatically decreases target motion data acquisition time. Both Brian Zaharri’s and David So’s work, along with this thesis, are part of the Cal Poly SAR Automatic Target Recognition (ATR) group of projects, which is sponsored by Raytheon Space & Airborne Systems Division. Because U.S. military SAR data remains classified, the Cal Poly SAR ATR projects addresses the need to educate researchers on the processing of SAR data

Moving Target Azimuth Velocity Estimation for the MASA Mode Based on Sequential SAR Images

A novel azimuth velocity estimation method is proposed based on the multiple azimuth squint angles (MASA) imaging mode, acquiring sequential synthetic aperture radar images with different squint angles and time lags. The MASA mode acquisition geometry is given first, and the effect of target motion on azimuth offset and slant range offset is discussed in detail. Then, the azimuth velocity estimation accuracy is analyzed, considering the errors caused by registration, defocusing, and range velocity. Moreover, the interaction between target azimuth velocity and range velocity is studied for a better understanding of the azimuth velocity estimation error caused by the range velocity. With the proposed error compensation step, the new method can achieve a very high accuracy in azimuth velocity estimation, as verified by experimental results based on both simulated data and the TerraSAR-X data

The Effects of Signal and Image Compression of SAR Data on Change Detection Algorithms

With massive amounts of SAR imagery and data being collected, the need for effective compression techniques is growing. One of the most popular applications for remote sensing is change detection, which compares two geo-registered images for changes in the scene. While lossless compression is needed for signal compression, the same is not often required for image compression. In almost every case the compression ratios are much higher in lossy compression making them more appealing when bandwidth and storage becomes an issue. This research analyzes different types of compression techniques that are adapted for SAR imagery, and tests these techniques with three different change detection algorithms. Many algorithms exist that allow large compression ratios, however, the usefulness of the data is always the final concern. It is necessary to identify compression methods that will not degrade the performance of change detection analysis

Geodetic Imaging of Volcanic Deformation with Time Series Radar Interferometry

Volcanic hazards threaten millions of people in their vicinity worldwide. To mitigate the volcanic risk, we need to know which volcanoes are actively deforming and how much have they deformed. Ideally, ascending magma leads to surface uplift through elastic response, which can be precisely measured using the technique of interferometric synthetic aperture radar (InSAR) and inferred through geophysical inverse model, such as the point pressure source. In practice, the (de)pressurization process could have complex geometry in space and change nonlinearly in time, posing challenging for the deformation mapping and risk assessment afterwards. Here, I first develop algorithms to correct for phase unwrapping error in InSAR stack processing and merge them with other state-of-art algorithms to form a generic routine workflow, implement as the Miami INsar Time-series software in PYthon (MintPy). Then I demonstrate the power of this software by applying to the Kyushu Island in SW Japan using all available L-band SAR data from 1992 to 2019 and detect five out of eight actively deforming volcanoes in addition to subsidence due to anthropogenic activities. Next, I combine the radar imaging with geodetic modeling to study the shallow hydrothermal and magmatic systems in Kirishima volcanic complex during the recent unrest since 2008, covering the 2008-2010, 2011, 2017 and 2018 eruption at Shinmoe-dake and the 2018 eruption in Iwo-yama

From imagery to ecology: Leveraging time series of all available Landsat observations to map and monitor ecosystem state and dynamics

https://zslpublications.onlinelibrary.wiley.com/doi/full/10.1002/rse2.24Published versio

Science plan for the Alaska SAR facility program. Phase 1: Data from the first European sensing satellite, ERS-1

Science objectives, opportunities and requirements are discussed for the utilization of data from the Synthetic Aperture Radar (SAR) on the European First Remote Sensing Satellite, to be flown by the European Space Agency in the early 1990s. The principal applications of the imaging data are in studies of geophysical processes taking place within the direct-reception area of the Alaska SAR Facility in Fairbanks, Alaska, essentially the area within 2000 km of the receiver. The primary research that will be supported by these data include studies of the oceanography and sea ice phenomena of Alaskan and adjacent polar waters and the geology, glaciology, hydrology, and ecology of the region. These studies focus on the area within the reception mask of ASF, and numerous connections are made to global processes and thus to the observation and understanding of global change. Processes within the station reception area both affect and are affected by global phenomena, in some cases quite critically. Requirements for data processing and archiving systems, prelaunch research, and image processing for geophysical product generation are discussed