Investigating rapid deforestation and carbon dioxide release in Bangladesh using geospatial information from remote sensing data

Rapid deforestation over the last few years due to the massive influx of refugees from neighboring Myanmar has been reported and is seen as a precursor to environmental disaster, raising the need for more effective monitoring of forest areas. The availability of data from several space-borne synthetic aperture radar (SAR) missions allow enhanced monitoring of forest areas. The objective of this study was to map deforestation in two selected areas located in northeast and southeast Bangladesh using Sentinel-1 imageries and determine the applicability of SAR in forest monitoring in Bangladesh. Towards these purpose satellite imageries from 2017 and 2018 collected by Sentinel-1A and Sentinel-1 Band SAR data in dual-polarization mode were used. In the northeastern area of interest, temporary deforestation was detected, which had occurred in low lying areas due to prolonged flooding. The second area of interest, in the southeast, revealed man-made deforestation in high land areas on an immense scale due to the influx and settlement of seven hundred thousand refugees. The results of the two sub-studies demonstrate the applicability and need of SAR data to effectively monitor deforestation in Bangladesh especially as it allows isolating natural and anthropogenic deforestation

Pre-Flight SAOCOM-1A SAR Performance Assessment by Outdoor Campaign

In the present paper, we describe the design, execution, and the results of an outdoor experimental campaign involving the Engineering Model of the first of the two Argentinean L-band Synthetic Aperture Radars (SARs) of the Satelite Argentino de Observacion con Microondas (SAOCOM) mission, SAOCOM-1A. The experiment's main objectives were to test the end-to-end SAR operation and to assess the instrument amplitude and phase stability as well as the far-field antenna pattern, through the illumination of a moving target placed several kilometers away from the SAR. The campaign was carried out in Bariloche, Argentina, during June 2016. The experiment was successful, demonstrating an end-to-end readiness of the SAOCOM-SAR functionality in realistic conditions. The results showed an excellent SAR signal quality in terms of amplitude and phase stability

Identificação de áreas inundáveis na porção sul de Roraima com auxílio de imagens de radar

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-graduação, 2018.As áreas úmidas são de extrema importância para o equilíbrio da vida na Terra, compreender o seu comportamento é crucial para a preservação destes ecossistemas. Muitas dessas áreas, como as inseridas em domínio amazônico, são de difícil acesso para um estudo em campo. As técnicas de Sensoriamento Remoto têm evoluído muito, aliadas aos avanços da inteligência artificial, contribuindo para o desenvolvimento de estudos em locais de difícil acesso, possibilitando bons resultados de acordo com o tipo de dado utilizado. O presente estudo utilizou a técnica de aprendizado de máquina Random Forest, e limiar de retroespalhamento em imagens SAR do satélite Sentinel 1, da Agência Espacial Europeia, para identificar áreas úmidas no sul do estado de Roraima ao longo do ano de 2017. O trabalho identificou o comportamento típico de áreas inundáveis nas margens dos rios e feições adjacentes ao principal rio do estado (rio Branco). O pico de cheia foi encontrado no mês de Julho, cobrindo mais de 72.000 hectares da área de estudo (11,9% da área total da cena), e o de seca no mês de Dezembro, cobrindo mais de 37.000 hectares (6,1% da área total da cena).Wetlands are of extreme importance for the balance of life on Earth, understanding their behavior is crucial to the preservation of these ecosystems. Many of these areas, such as those in the Amazonian domain, are difficult to access for field study. The techniques of Remote Sensing have evolved a lot, combined with the advances of artificial intelligence, contributing to the development of studies in places of difficult access, allowing good results according to the type of data used. The present study used the Random Forest machine learning technique and backscatter threshold in SAR images of the Sentinel 1 satellite of the European Space Agency to identify wetlands in the south of the state of Roraima throughout 2017. The work identified the typical behavior of flooded areas on the banks of the rivers and features adjacent to the main river of the state (Rio Branco). The flood peak was found in July, covering more than 72,000 hectares of the study area (11.9% of the total area of the scene), and the dry season in December, covering more than 37,000 hectares (6.1 % of the total area of the scene)

Traceable Radiometric Calibration of Synthetic Aperture Radars

Synthetic aperture radar (SAR) systems allow to quantitatively measure the radar backscatter of an imaged terrain region. In order to achieve comparability between measurement results, traceable radiometric calibration is indispensable. The central claim of the work is that nowadays, however, radiometric SAR measurements are not traceably calibrated. In order to resolve this problem, five contributions are made: (a) The new measurement quantity “equivalent radar cross section” (ERCS) is defined. (b) A numerical approach for linking the known quantity “radar cross section” (RCS) with the novel ERCS is introduced. (c) The effect of the chosen apodization functions on radiometric measurements is analytically investigated. (d) The novel three-transponder method is developed which allows accurate RCS calibrations of SAR transponders. (e) The method of hierarchical Bayesian data analysis is introduced to the field of radiometric SAR calibration. The achieved traceability for radiometric SAR measurements allows more accurate radiometric measurement results especially for modern, high-resolution SAR systems. Furthermore, data exchange and cooperation is facilitated

Independent Verification of the Sentinel-1A System Calibration

In the frame of the GMES program, the main objective of the Sentinel-1 mission is to ensure the continuity of SAR data ac- quisitions in C-band for global earth monitoring. Sentinel-1A is the first of two C-band satellites launched in April 2014. In addition to the commissioning of Sentienl-1A executed by ESA, an independent verification of the system calibration has been executed. For this purpose, the complete calibration chain was developed and established by DLR, starting with a calibration concept, a detailed in-orbit calibration plan, the SW-tools for analyzing and evaluating all the measurements up to the calibration targets serving as accurate reference. Based on an efficient calibration strategy, this paper describes the different activities performed by DLR and presents the results obtained during the commissioning phase of Sentinel- 1A