In-depth verification of Sentinel-1 and TerraSAR-X geolocation accuracy using the Australian Corner Reflector Array

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques—also called imaging geodesy—can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improve�ment of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy

Characterizing slope instability kinematics by integrating multi-sensor satellite remote sensing observations

Over the past few decades, the occurrence and intensity of geological hazards, such as landslides, have substantially risen due to various factors, including global climate change, seismic events, rapid urbanization and other anthropogenic activities. Landslide disasters pose a significant risk in both urban and rural areas, resulting in fatalities, infrastructure damages, and economic losses. Nevertheless, conventional ground-based monitoring techniques are often costly, time-consuming, and require considerable resources. Moreover, some landslide incidents occur in remote or hazardous locations, making ground-based observation and field investigation challenging or even impossible. Fortunately, the advancements in spaceborne remote sensing technology have led to the availability of large-scale and high-quality imagery, which can be utilized for various landslide-related applications, including identification, monitoring, analysis, and prediction. This efficient and cost-effective technology allows for remote monitoring and assessment of landslide risks and can significantly contribute to disaster management and mitigation efforts. Consequently, spaceborne remote sensing techniques have become vital for geohazard management in many countries, benefiting society by providing reliable downstream services. However, substantial effort is required to ensure that such benefits are provided. For establishing long-term data archives and reliable analyses, it is essential to maintain consistent and continued use of multi-sensor spaceborne remote sensing techniques. This will enable a more thorough understanding of the physical mechanisms responsible for slope instabilities, leading to better decision-making and development of effective mitigation strategies. Ultimately, this can reduce the impact of landslide hazards on the general public. The present dissertation contributes to this effort from the following perspectives: 1. To obtain a comprehensive understanding of spaceborne remote sensing techniques for landslide monitoring, we integrated multi-sensor methods to monitor the entire life cycle of landslide dynamics. We aimed to comprehend the landslide evolution under complex cascading events by utilizing various spaceborne remote sensing techniques, e.g., the precursory deformation before catastrophic failure, co-failure procedures, and post-failure evolution of slope instability. 2. To address the discrepancies between spaceborne optical and radar imagery, we present a methodology that models four-dimensional (4D) post-failure landslide kinematics using a decaying mathematical model. This approach enables us to represent the stress relaxation for the landslide body dynamics after failure. By employing this methodology, we can overcome the weaknesses of the individual sensor in spaceborne optical and radar imaging. 3. We assessed the effectiveness of a newly designed small dihedral corner reflector for landslide monitoring. The reflector is compatible with both ascending and descending satellite orbits, while it is also suitable for applications with both high-resolution and medium-resolution satellite imagery. Furthermore, although its echoes are not as strong as those of conventional reflectors, the cost of the newly designed reflectors is reduced, with more manageable installation and maintenance. To overcome this limitation, we propose a specific selection strategy based on a probability model to identify the reflectors in satellite images

Remote Sensing of Savannas and Woodlands

Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome

Monitoring wetlands and water bodies in semi-arid Sub-Saharan regions

Surface water in wetlands is a critical resource in semi-arid West-African regions that are frequently exposed to droughts. Wetlands are of utmost importance for the population as well as the environment, and are subject to rapidly changing seasonal fluctuations. Dynamics of wetlands in the study area are still poorly understood, and the potential of remote sensing-derived information as a large-scale, multi-temporal, comparable and independent measurement source is not exploited. This work shows successful wetland monitoring with remote sensing in savannah and Sahel regions in Burkina Faso, focusing on the main study site Lac Bam (Lake Bam). Long-term optical time series from MODIS with medium spatial resolution (MR), and short-term synthetic aperture radar (SAR) time series from TerraSAR-X and RADARSAT-2 with high spatial resolution (HR) successfully demonstrate the classification and dynamic monitoring of relevant wetland features, e.g. open water, flooded vegetation and irrigated cultivation. Methodological highlights are time series analysis, e.g. spatio-temporal dynamics or multitemporal-classification, as well as polarimetric SAR (polSAR) processing, i.e. the Kennaugh elements, enabling physical interpretation of SAR scattering mechanisms for dual-polarized data. A multi-sensor and multi-frequency SAR data combination provides added value, and reveals that dual-co-pol SAR data is most recommended for monitoring wetlands of this type. The interpretation of environmental or man-made processes such as water areas spreading out further but retreating or evaporating faster, co-occurrence of droughts with surface water and vegetation anomalies, expansion of irrigated agriculture or new dam building, can be detected with MR optical and HR SAR time series. To capture long-term impacts of water extraction, sedimentation and climate change on wetlands, remote sensing solutions are available, and would have great potential to contribute to water management in Africa

Remote Sensing of the Aquatic Environments

The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Sustainable Agriculture and Advances of Remote Sensing (Volume 1)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others