THE CONTRIBUTION OF RADAR REMOTE SENSING VIA SENTINEL-1 DATA AND PHOTO-INTERPRETATION BY GOOGLE EARTH IMAGES FOR WETLAND MAPPING

Wetlands are considered as sensitive ecosystems exposed and threatened by climate change and the urbanization of natural environments. In the purpose of managing these sensitive areas and conservatizing their biodiversity, remote sensing is an efficient way to track environmental variables over large areas as wetlands. However, when it comes to the study of hydrologic dynamics, high temporal and spatial resolutions are essential. Since the access to optical satellite imagery is restrictive because of the large cloud cover that masks the ground, radar sensors that are working in the microwave field, are particularly suited to the characterization of hydrological dynamics due to the sensitivity of their measurements in the presence of water, regardless of the vegetation in place. Recently, radar remote sensing has experienced a real revolution with the launch of the Sentinel-1A satellite in 2014, followed by its twin Sentinel-1B two years later by the European Space Agency as part of the Copernicus program. These sensors acquire C-band data (λ = 5.6 cm) with a temporal resolution of 12 days by satellite and their distribution is open and free. This article aims to assess the potential of Sentinel A1 SAR data for wetland mapping in the city of Benslimane (Central Morocco). The first part is explaining the methodology for mapping water surfaces. We identified a confusion of the C-band radar response of water surfaces and that of certain bare soils. We then showed that the VH polarization is the most suitable for the mapping of water surfaces, comparing four methods of detecting areas in water. It. The second part is discussing the use of unsupervised methods without a priori data demonstrating that the methods taking into account the spatial neighborhood give better results. Temporal filtering has been developed and has made it possible to improve detection and to overcome confusion between bare soil and permanent water surfaces. Water surfaces larger than 0.5 ha are at 80% detected. Classification was performed using the SVM (Support Vector Machine) algorithm. This latter information was then implemented into the thematic map derived from SPOT-4 images to obtain the final weltands map.

Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

Rice is one of the main agricultural crops and plays an important role in food security. Therefore, it is essential to propose a method for monitoring the distribution of rice yield. Radar remote sensing data sources provide a sustainable solution for rice monitoring challenges in the countries located in the tropical monsoon region like Vietnam. The SAR (Synthetic Aperture Radar) remote sensing data from the Sentinel-1 satellite provided by the European Space Agency (ESA) is free of charge, has a large coverage and high spatial-temporal resolution. In this paper, rice growing areas in the An Giang province of Vietnam Mekong Delta were analyzed, which demonstrates the potential applications of multi-temporal data and proposes a method to estimate rice yield for agricultural management. The analysis results showed that in 2018 the Winter-Spring rice crop has the highest yield, and the Autumn-Winter crop has the lowest yield. Accurate and timely estimation of rice yield and production can provide important information in terms of spatial distribution and seasonal yield for government and decision-makers in policy making related to import and export.

Sentinel-1 and RADARSAT Constellation Mission InSAR Assessment of Slope Movements in the Southern Interior of British Columbia, Canada

Landslides are the most common natural hazard in British Columbia. The province has recorded the largest number of historical landslide fatalities in Canada, and damage to infrastructure comes at a great cost. In order to understand the potential impacts of landslides, radar remote sensing has become a cost-effective method for detecting downslope movements. This study investigates downslope movements in the Southern Interior of British Columbia, Canada, with Sentinel-1 and RADARSAT Constellation Mission (RCM) interferometric synthetic aperture radar (InSAR) data. The 2-dimensional time-series analysis with Sentinel-1 ascending and descending InSAR pairs from October 2017 to June 2021 observed distinct earthflow movements of up to ~15 cm/year in the east–west direction. The Grinder Creek, Red Mountain, Yalakom River, and Retaskit Creek earthflows previously documented are still active, with east–west movements of ~30 cm over the past four years. New RCM data acquired from June 2020 to September 2020 with a 4-day revisit capability were compared to 12-day Sentinel-1 InSAR pairs. The 4-day RCM InSAR pairs at higher spatial resolution showed better performance by detecting relatively small-sized slope movements within a few hundred meters, which were not clearly observed by Sentinel-1. The temporal variabilities observed from the RCM InSAR showed great potential for observing detailed slope movements within a narrower time window.

Review of Collision Avoidance and Path Planning Methods for Ships Utilizing Radar Remote Sensing

The paper presents a comparative analysis of recent collision avoidance and real-time path planning algorithms for ships. Compared methods utilize radar remote sensing for target ships detection. Different recently introduced approaches are briefly described and compared. An emphasis is put on input data reception using a radar as a remote sensing device applied in order to detect moving obstacles such as encountered ships. The most promising methods are highlighted and their advantages and limitations are discussed. Concluding remarks include proposals of further research directions in the development of collision avoidance methods utilizing radar remote sensing.

Kerch Strait and Its Technogenic Pollution: Possibilities of Optical and Radar Remote Sensing

The possibilities of using satellite imagery of modern remote sensing satellites, both optical and radar, to study anthropogenic pollution and the state of the marine environment of the Kerch Strait are discussed. It is shown that satellite data and images allow one to quickly obtain practically complete information about a particular phenomenon and emergency situation in the strait.

Yield estimation of the 2020 Beirut explosion using open access waveform and remote sensing data

We report on a multi-technique analysis using publicly available data for investigating the huge, accidental explosion that struck the city of Beirut, Lebanon, on August 4, 2020. Its devastating shock wave led to thousands of injured with more than two hundred fatalities and caused immense damage to buildings and infrastructure. Our combined analysis of seismological, hydroacoustic, infrasonic and radar remote sensing data allows us to characterize the source as well as to estimate the explosive yield. The latter is determined within 0.13 to 2 kt TNT (kilotons of trinitrotoluene). This range is plausible given the reported 2.75 kt of ammonium nitrate as explosive source. As there are strict limitations for an on-site analysis of this catastrophic explosion, our presented approach based on data from open accessible global station networks and satellite missions is of high scientific and social relevance that furthermore is transferable to other explosions.