Land Consumption Classification Using Sentinel 1 Data: A Systematic Review

Abstract

The development of remote sensing technology has redefined the approaches to the Earth’s surface monitoring. The Copernicus Programme promoted by the European Space Agency (ESA) and the European Union (EU), through the launch of the Synthetic Aperture Radar (SAR) Sentinel-1 and the multispectral Sentinel-2 satellites, has provided a valuable contribution to monitoring the Earth’s surface. There are several review articles on the land use/land cover (LULC) matter using Sentinel images, but it lacks a methodical and extensive review in the specific field of land consumption monitoring, concerning the application of SAR images, in particular Sentinel-1 images. In this paper, we explored the potential of Sentinel-1 images to estimate land consumption using mathematical modeling, focusing on innovative approaches. Therefore, this research was structured into three principal steps: (1) searching for appropriate studies, (2) collecting information required from each paper, and (3) discussing and comparing the accuracy of the existing methods to evaluate land consumption and their applied conditions using Sentinel-1 Images. Current research has demonstrated that Sentinel-1 data has the potential for land consumption monitoring around the world, as shown by most of the studies reviewed: the most promising approaches are presented and analyzed.

Remote Sensing for Lithology Mapping in Vegetation-Covered Regions: Methods, Challenges, and Opportunities

“…Sentinel-1 is a SAR satellite developed by the European Space Agency (ESA) and forms part of a two-satellite Earth observation system [46]. It consists of two satellites named S1A and S1B launched on 3 April 2014 and 25 April 2016, respectively [44].…”

“…While the X-band (8~12 GHz) might not be commonly used for direct lithology identification in remote sensing applications, it can still contribute to lithology identification efforts by providing valuable information through high-precision topographic data. Sentinel-1 [46], polarimetric SAR (Pol-SAR) [47], and Phased Array type L-band SAR (PALSAR) [45,48] are highly favored for lithological mapping. However, studies have shown that radar data generally has lower spatial resolution compared to optical images, and the acquisition and processing of radar data can be complex [45].…”

YOLOV4_CSPBi: Enhanced Land Target Detection Model

“…Optical distant sensing images are not only unique from images in common natural scenes but also have huge differences between various targets in their own sample images. This phenomenon of huge differences in appearance and shape makes it difficult to preset the anchor frame of the network, resulting in the result that the target is missed [20][21][22].…”