The TOPSAR interferometric radar topographic mapping instrument

The NASA DC-8 AIRSAR instrument was augmented with a pair of C-band antennas displaced across track to form an interferometer sensitive to topographic variations of the Earth's surface. The antennas were developed by the Italian consortium Co.Ri.S.T.A., under contract to the Italian Space Agency (ASI), while the AIRSAR instrument and modifications to it supporting TOPSAR were sponsored by NASA. A new data processor was developed at JPL for producing the topographic maps, and a second processor was developed at Co.Ri.S.T.A. All the results presented below were processed at JPL. During the 1991 DC-8 flight campaign, data were acquired over several sites in the United States and Europe, and topographic maps were produced from several of these flight lines. Analysis of the results indicate that statistical errors are in the 2-3 m range for flat terrain and in the 4-5 m range for mountainous areas

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop

The Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996, was divided into two smaller workshops:(1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, and The Airborne Synthetic Aperture Radar (AIRSAR) workshop. This current paper, Volume 2 of the Summaries of the Sixth Annual JPL Airborne Earth Science Workshop, presents the summaries for The Airborne Synthetic Aperture Radar (AIRSAR) workshop

Current and future use of TOPSAR digital topographic data for volcanological research

In several investigations of volcanoes, high quality digital elevation models (DEM's) are required to study either the geometry of the volcano or to investigate temporal changes in relief due to eruptions. Examples include the analysis of volume changes of a volcanic dome, the prediction of flow paths for pyroclastic flows, and the quantitative investigation of the geometry of valleys carved by volcanic mudflows. Additionally, to provide input data for models of lava flow emplacement, accurate measurements are needed of the thickness of lava flows as a function of distance from the vent and local slope. Visualization of volcano morphology is also aided by the ability to view a DEM from oblique perspectives. Until recently, the generation of these DEM's has required either high resolution stereo air photographs or extensive field surveying using the Global Positioning System (GPS) and other field techniques. Through the use of data collected by the NASA/JPL TOPSAR system, it is now possible to remotely measure the topography of volcanoes using airborne radar interferometry. TOPSAR data can be collected day or night under any weather conditions, thereby avoiding the problems associated with the derivation of DEM's from air photographs that may often contain clouds. Here we describe some of our initial work on volcanoes using TOPSAR data for Mt. Hekla (Iceland) and Vesuvius (Italy). We also outline various TOPSAR topographic studies of volcanoes in the Galapagos and Hawaii that will be conducted in the near future, describe how TOPSAR complements the volcanology investigations to be conducted with orbital radars (SIR-C/X-SAR, JERS-1 and ERS-1), and place these studies into the broader context of NASA's Global Change Program

Detecting Small-Scale Topographic Changes and Relict Geomorphic Features on Barrier Islands Using SAR

The shapes and elevations of barrier islands may change dramatically over a short period of time during a storm. Coastal scientists and engineers, however, are currently unable to measure these changes occurring over an entire barrier island at once. This three-year project, which is funded by NASA and jointly conducted by the Bureau of Economic Geology and the Center for Space Research at The University of Texas at Austin, is designed to overcome this problem by developing the use of interferometry from airborne synthetic aperture radar (AIRSAR) to measure coastal topography and to detect storm-induced changes in topography. Surrogate measures of topography observed in multiband, fully polarimetric AIRSAR (This type of data are now referred to as POLSAR data.) are also being investigated. Digital elevation models (DEM) of Galveston Island and Bolivar Peninsula, Texas obtained with Topographic SAR (TOPSAR) are compared with measurements by Global Positioning System (GPS) ground surveys and electronic total station surveys. In addition to topographic mapping, this project is evaluating the use of POLSAR to detect old features such as storm scarps, storm channels, former tidal inlets, and beach ridges that have been obscured by vegetation, erosion, deposition, and artificial filling. We have also expanded the work from the original proposal to include the mapping of coastal wetland vegetation and depositional environments. Methods developed during this project will provide coastal geologists with an unprecedented tool for monitoring and understanding barrier island systems. This understanding will improve overall coastal management policies and will help reduce the effects of natural and man-induced coastal hazards. This report summarizes our accomplishments during the second year of the study. Also included is a discussion of our planned activities for year 3 and a revised budget

Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 3: AIRSAR Workshop

This publication is the third containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in Volume 1; (2) The Airborne synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in this volume; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2

Land Cover Classification using Sentinel-1 Radar Mission Interferometry

Synthetic Aperture Radar (SAR) has been widely used for many years in the field of remote sensing. SAR has valuable contribution due to its ability to provide complementary information to optical systems, penetration of radar waves through volumetric targets and high-resolution. SAR has the ability to operate during day and night. It provides operational services under all weather conditions. SAR imagery has many applications including land cover changes, environmental monitoring, climate change and military surveillance. This work focuses on land cover classification with SAR interferometry (InSAR) technique using Sentinel-1 space radar image pair. Sentinel-1 data were collected over the southern part of Estonia. Two SLC SAR images were acquired from both Sentinel-1A and Sentinel-1B with six days temporal difference. In this study, interferometric coherence and backscattering intensity processing chains have been set up and applied to Sentinel-1 SAR image pair. The Sentinel Application Platform (SNAP) has been used for processing of single pair for Sentinel-1 mission. The SNAP is an European Space Agency (ESA) software. The Sentinel-1 image pair processing has been done using Sentinel-1 Toolbox (S1TBX) which is a part of SNAP. Corine Land Cover (CLC) 2012 database has been used as a reference data with 20 m resolution. The CLC2012 contains land use/cover information for most of the European countries. A single optical image from Sentinel-2A was additionally used for feature extraction. An overall accuracy of 68% to 73% was achieved when performing classification into five classes (Urban, Field, Forest, Peat-land, Water) using supervised classification with k-nearest neighbour (kNN) algorithm. The accuracy assessment was done by using confusion matrices

A Study of Landfast Ice with Sentinel-1 Repeat-Pass Interferometry over the Baltic Sea

Mapping of fast ice displacement and investigating sea ice rheological behavior is a major open topic in coastal ice engineering and sea ice modeling. This study presents first results on Sentinel-1 repeat-pass space borne synthetic aperture radar interferometry (InSAR) in the Gulf of Bothnia over the fast ice areas. An InSAR pair acquired in February 2015 with a temporal baseline of 12 days has been studied here in detail. According to our results, the surface of landfast ice in the study area was stable enough to preserve coherence over the 12-day baseline, while previous InSAR studies over the fast ice used much shorter temporal baselines. The advantage of longer temporal baseline is in separating the fast ice from drift ice and detecting long term trends in deformation maps. The interferogram showed displacement of fast ice on the order of 40 cm in the study area. Parts of the displacements were attributed to forces caused by sea level tilt, currents, and thermal expansion, but the main factor of the displacement seemed to be due to compression of the drift ice driven by southwest winds with high speed. Further interferometric phase and the coherence measurements over the fast ice are needed in the future for understanding sea ice mechanism and establishing sustainability of the presented InSAR approach for monitoring dynamics of the landfast ice with Sentinel-1 data.Peer reviewe

Implementazione dei software Snap e StaMPS per l'elaborazione di immagini SAR con tecnica interferometrica

L’Earth Observation (EO), osservazione della Terra, è una disciplina che negli ultimi 30 anni è stata notevolmente sviluppata ed innovata, per poter soddisfare le sempre crescenti necessità dell’uomo di controllare il nostro pianeta, studiarne i cambiamenti e monitorarne l’evoluzione. Uno dei principali strumenti di remote-sensing in questi anni sempre più utilizzato è il SAR, il Radar ad Apertura Sintetica, soggetto principale del presente studio. Il SAR è uno strumento attivo, che non dipende da altre fonti di energia elettromagnetica, in grado di individuare gli oggetti e stimarne la distanza, con una precisione millimetrica. Sfruttando le microonde il SAR non è ostacolato dalle nubi e può quindi operare durante tutte le condizioni meteorologiche, di giorno e di notte. Le acquisizioni SAR si presentano come immagini, in cui all’interno di ogni pixel sono contenute informazioni legate alla fase del segnale ricevuto e all’ampiezza della risposta energetica generata dal bersaglio colpito al suolo. Scopo del presente studio è stato individuare, analizzare e iniziare a padroneggiare i diversi software necessari ad individuare i Persistent Scatterers, PS: pixel che durante le diverse acquisizioni mantengono una risposta stabile e possono essere per questo utilizzati come riferimento per valutare l’evoluzione dinamica della superficie terrestre. Per il nostro studio è stato scelto di analizzare i software free Snap e StaMPS, effettuando una descrizione esaustiva delle singole operazioni da svolgere, dei parametri necessari e dei prodotti intermedi per individuare i PS. Infine, per apprezzare le notevoli potenzialità del SAR, sono state svolte due elaborazioni di più di 200 acquisizioni effettuate tra il 2016 e il 2021, dai satelliti Sentinel-1, dell’area della provincia di Bologna, utilizzando Snap e StaMPS, per valutare l’evoluzione del suolo in questa importante area della nostra penisola

MONITORING THE 2018 ERUPTION OF KĪLAUEA VOLCANO USING VARIOUS REMOTE SENSING TECHNIQUES

Monitoring the regions that are prone to natural hazards is essential in disaster management to provide early warnings. Airborne and space-borne remote sensing techniques are cost-effective in accomplishing this task. Interferometric Synthetic Aperture Radar (InSAR) is an advanced remote sensing technique used to detect and measure the changes in the Earth’s topography over time. Spaceborne InSAR is a precise (~mm accuracy) way to measure the land surface altitudinal changes. Persistent Scatterer Interferometry (PSI) is a powerful method of differential SAR interferometry that processes the InSAR data by automatically selecting the persistent scatterers in the region. In this thesis, I developed a new algorithm to estimate the areal coverage and volume of newly erupted lava by integrating the space-borne InSAR, thermal infrared, Light Detection and Ranging (LiDAR), and Normalized Difference Vegetation Index (NDVI) techniques. I applied this algorithm to the eruption of the East Rift Zone (ERZ) of the Kīlauea volcano that took place between May and August 2018 as a case study, and estimated the areal coverage and volume of lava erupted. I compared the results of InSAR to those derived from airborne LiDAR. I found that although air-borne LiDAR provides data with higher resolution and accuracy, InSAR is almost as good as LiDAR in monitoring deformed areas and has larger spatial and temporal coverage. I also performed the PSI analysis using the Stanford Method for Persistent Scatterers (StaMPS) algorithm, and determined the Line-of-Sight (LOS) deformations prior, during, and after the 2018 eruption of the Kīlauea volcano. Results from the PSI processing show regional subsidence on the Big Island, indicating the deflation of the southern and western part of the Big Island during the eruption at the East Rift Zone. Keywords: Kilauea

Exploration du contenu en information de l'interférométrie RSO lié à la neige

The objective of this research is to explore the information content of repeat-pass cross-track Interferometric SAR (InSAR) with regard to snow, in particular Snow Water Equivalent (SWE) and snow depth. The study is an outgrowth of earlier snow cover modeling and radar interferometry experiments at Schefferville, Quebec, Canada and elsewhere which has shown that for reasons of loss of coherence repeat-pass InSAR is not useful for the purpose of snow cover mapping, even when used in differential InSAR mode. Repeat-pass cross-track InSAR would overcome this problem. As at radar wavelengths dry snow is transparent, the main reflection is at the snow/ground interface. The high refractive index of ice creates a phase delay which is linearly related to the water equivalent of the snow pack. When wet, the snow surface is the main reflector, and this enables measurement of snow depth. Algorithms are elaborated accordingly. Field experiments were conducted at two sites and employ two different types of digital elevation models (DEM) produced by means of cross track InSAR. One was from the Shuttle Radar Topography Mission digital elevation model (SRTM DEM), flown in February 2000. It was compared to the photogrammetrically produced Canadian Digital Elevation Model (CDEM) to examine snow-related effects at a site near Schefferville, where snow conditions are well known from half a century of snow and permafrost research. The second type of DEM was produced by means of airborne cross track InSAR (TOPSAR). Several missions were flown for this purpose in both summer and winter conditions during NASA's Cold Land Processes Experiment (CLPX) in Colorado, USA. Differences between these DEM's were compared to snow conditions that were well documented during the CLPX field campaigns. The results are not straightforward. As a result of automated correction routines employed in both SRTM and AIRSAR DEM extraction, the snow cover signal is contaminated. Fitting InSAR DEM's to known topography distorts the snow information, just as the snow cover distorts the topographic information. The analysis is therefore mostly qualitative, focusing on particular terrain situations. At Schefferville, where the SRTM was adjusted to known lake levels, the expected dry-snow signal is seen near such lakes. Mine pits and waste dumps not included in the CDEM are depicted and there is also a strong signal related to the spatial variations in SWE produced by wind redistribution of snow near lakes and on the alpine tundra. In Colorado, cross-sections across ploughed roads support the hypothesis that in dry snow the SWE is measurable by differential InSAR. They also support the hypothesis that snow depth may be measured when the snow cover is wet. Difference maps were also extracted for a 1 km2 Intensive Study Area (ISA) for which intensive ground truth was available. Initial comparison between estimated and observed snow properties yielded low correlations which improved after stratification of the data set.In conclusion, the study shows that snow-related signals are measurable. For operational applications satellite-borne cross-track InSAR would be necessary. The processing needs to be snow-specific with appropriate filtering routines to account for influences by terrain factors other than snow