Detecting Land Cover Changes Using Multi-Temporal Radar Imagery: A Case Study of Taiwan^s Western Coastal Region
Ting-Yu Lai 1*, Kuo-Hsin Tseng 1,2

1 Department of Civil Engineering, National Central University
2 Center for Space and Remote Sensing Research, National Central University

Abstract

Satellite remote sensing data have been widely used to identify surface coverage- however, traditional optical images are limited in monitoring long-term surface changes due to cloud cover and atmospheric moisture interference. In contrast, Synthetic Aperture Radar (SAR) is less affected by atmospheric conditions and sunshine, and is more sensitive to surface texture changes, which can complement optical satellite imagery by providing long-term and stable observation of surface changes. Therefore, in this study, the C-band Sentinel-1 GRD images from 2016 to 2024 and the X-band TerraSAR-X data from 2021 to 2025 were collected in the western coastal area of Taiwan to observe the temporal changes of features and water bodies. The study is divided into two parts: land and coastal areas. Firstly, all the images are using SNAP software for a standardized preprocessing workflow, and then the land section involves stacking multi-temporal data and composing false-color images using selected polarization bands from specific periods to observe changes in urban infrastructure and agricultural activities. For the coastal area, three to five low-tide images are selected every year based on the tide level data, and the average backscatter intensity values are calculated. These annual averages are assigned to different channels of pseudo-color images. The results reveal erosion and sedimentation hotspots along the west coastline of Taiwan. By integrating multi-temporal radar data, this study provides a foundational basis for future applications such as land classification, change detection, and spatial planning.

Keywords: Synthetic Aperture Radar (SAR), Sentinel-1, TerraSAR-X, Change Detection

Topic: Topic A: General Remote Sensing