scholarly journals Anthropogenic and Environmental Strain on Beach Environments Retrieved and Monitored by Spaceborne Synthetic Aperture Radar

2021 ◽  
Author(s):  
Valeria Di Biase ◽  
Ramon F. Hanssen
Keyword(s):  
Synthetic Aperture Radar ◽  
Satellite Remote Sensing ◽  
Continuous Monitoring ◽  
Remote Sensing Data ◽  
Weather Conditions ◽  
Synthetic Aperture ◽  
Environmental Strain ◽  
Protection Strategies ◽  
The Relationship ◽  
Aperture Radar

Environmental effects and climate change are lately representing an increasing strain of the coastal areas which topography strongly depends on these conditions. However, the processes by which weather and environmental phenomena influence the highly variable beach morphology are still unknown. A continuous monitoring of the beach environment is necessary to implement protection strategies. This paper presents the results of an innovative study performed on a coastal area using satellite remote sensing data with the aim of understanding how environmental phenomena affect beaches. Two-years of synthetic aperture radar (SAR) Sentinel-1 images are used over a test area in Noordwijk, the Netherlands. At the same time as the SAR acquisitions, information on tidal and weather conditions are collected and integrated from nearby meteorological stations. Dedicated codes are implemented in order to understand the relationship between the SAR amplitude and the considered phenomena: wind, precipitation, tidal conditions. Surface roughness is taken into account. The results indicate a strong correlation between the amplitude and the wind. No particular correlation or trend could be noticed in the relation with the precipitation. The analysis of the amplitude also shows a decreasing trend moving from the dry area of the beach towards the sea and the correlation coefficient between the amplitude and the tide level gets negative with the increase of the water content.

scholarly journals GOLD MINERAL PROSPECTING USING PHASED ARRAY TYPE L-BAND SYNTHETIC APERTURE RADAR (PALSAR) SATELLITE REMOTE SENSING DATA, CENTRAL GOLD BELT, MALAYSIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 409-412 ◽  
Author(s):  
Amin Beiranvand Pour ◽  
Mazlan Hashim
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Peninsular Malaysia ◽  
Suture Zone ◽  
Synthetic Aperture ◽  
Sensing Data ◽  
Tropical Environments ◽  
Aperture Radar

The Bentong-Raub Suture Zone (BRSZ) of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR) data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.

scholarly journals GOLD MINERAL PROSPECTING USING PHASED ARRAY TYPE L-BAND SYNTHETIC APERTURE RADAR (PALSAR) SATELLITE REMOTE SENSING DATA, CENTRAL GOLD BELT, MALAYSIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 409-412 ◽  
Author(s):  
Amin Beiranvand Pour ◽  
Mazlan Hashim
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Peninsular Malaysia ◽  
Suture Zone ◽  
Synthetic Aperture ◽  
Sensing Data ◽  
Tropical Environments ◽  
Aperture Radar

The Bentong-Raub Suture Zone (BRSZ) of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR) data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.

Economic Feasibility Study for Pavement Monitoring Using Synthetic Aperture Radar-Based Satellite Remote Sensing: Cost–Benefit Analysis

2017 ◽  
Vol 2645 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Mingxin Li ◽  
Ardeshir Faghri ◽  
Abdulkadir Ozden ◽  
Yixiang Yue
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Satellite Remote Sensing ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Economic Feasibility ◽  
Synthetic Aperture ◽  
Benefit Analysis ◽  
Pavement Monitoring ◽  
Aperture Radar

Recent developments in satellite remote sensing and the availability of high-resolution synthetic aperture radar (SAR) products have created an opportunity for the use of SAR-based monitoring for pavement and infrastructure management. No previous studies have performed a detailed cost–benefit analysis to analyze the economic feasibility of pavement monitoring through the use of SAR-based satellite remote sensing. The aim of this study was to fill this knowledge gap by proposing a comprehensive methodology to estimate the most important benefits and expenses associated with the use of data obtained from satellites by SAR and interferometric SAR for advanced monitoring of the infrastructure and to gain a better understanding of the strategies used to identify their effects. A general cost–benefit analysis framework that could serve as a pavement management tool for assessment of pavement deformations and deformation velocities with millimeter accuracy was developed. The results of a case study performed in the state of Delaware to demonstrate how the proposed approaches can be used to assess the impacts of SAR-based monitoring projects are also presented.

scholarly journals Artificial Neural Network Modeling of High Arctic Phytomass Using Synthetic Aperture Radar and Multispectral Data

2021 ◽  
Author(s):  
Adam Collingwood ◽  
Paul Treitz ◽  
Francois Charbonneau ◽  
David M. Atkinson
Keyword(s):  
Synthetic Aperture Radar ◽  
High Arctic ◽  
Synthetic Aperture ◽  
The Arctic ◽  
Optical Data ◽  
Neural Network Modeling ◽  
Artificial Neural ◽  
Sar Data ◽  
The Relationship ◽  
Aperture Radar

Vegetation in the Arctic is often sparse, spatially heterogeneous, and difficult to model. Synthetic Aperture Radar (SAR) has shown some promise in above-ground phytomass estimation at sub-arctic latitudes, but the utility of this type of data is not known in the context of the unique environments of the Canadian High Arctic. In this paper, Artificial Neural Networks (ANNs) were created to model the relationship between variables derived from high resolution multi-incidence angle RADARSAT-2 SAR data and optically-derived (GeoEye-1) Soil Adjusted Vegetation Index (SAVI) values. The modeled SAVI values (i.e., from SAR variables) were then used to create maps of above-ground phytomass across the study area. SAVI model results for individual ecological classes of polar semi-desert, mesic heath, wet sedge, and felsenmeer were reasonable, with r2 values of 0.43, 0.43, 0.30, and 0.59, respectively. When the outputs of these models were combined to analyze the relationship between the model output and SAVI as a group, the r2 value was 0.60, with an 8% normalized root mean square error (% of the total range of phytomass values), a positive indicator of a relationship. The above-ground phytomass model also resulted in a very strong relationship (r2 = 0.87) between SAR-modeled and field-measured phytomass. A positive relationship was also found between optically derived SAVI values and field measured phytomass (r2 = 0.79). These relationships demonstrate the utility of SAR data, compared to using optical data alone, for modeling above-ground phytomass in a high arctic environment possessing relatively low levels of vegetation.

scholarly journals Strategies for landslide detection using open-access synthetic aperture radar backscatter change in Google Earth Engine

2021 ◽  
Author(s):  
Alexander L. Handwerger ◽  
Shannan Y. Jones ◽  
Pukar Amatya ◽  
Hannah R. Kerner ◽  
Dalia B. Kirschbaum ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Situational Awareness ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Disaster Mitigation ◽  
Synthetic Aperture ◽  
Landslide Event ◽  
Combining Data ◽  
Google Earth Engine ◽  
Aperture Radar

Abstract. Rapid detection of landslides is critical for emergency response, disaster mitigation, and improving our understanding of landslide dynamics. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days of a triggering event, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a SAR backscatter change detection approach that uses multi-temporal stacks of freely available data from the Copernicus Sentinel-1 satellites to detect areas with high landslide density using the cloud-based Google Earth Engine (GEE). Importantly, our approach does not require downloading a large volume of data to a local system or specialized processing software. We provide strategies, including a landslide density heatmap approach, that can aid in rapid response and landslide detection. We test our GEE-based approach on multiple recent rainfall- and earthquake-triggered landslide events. Our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries, and applying topographic masks to remove flat areas unlikely to experience landslides. Importantly, our GEE approach allows the broader hazards and landslide community to utilize and advance these state-of-the-art remote sensing data for improved situational awareness of landslide hazards.

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