Using Spectral Indices (NDVI–NDWI) to Monitor Land Cover Changes in the Marshes of Al-Chibayish East Al-Hammar, for the Period 1992–2024

Abstract

      Remote sensing data are among the primary sources widely used for detecting changes in land cover. In this study, selected modern techniques were applied to detect changes using the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), along with the post-classification comparison method to distinguish two main land cover categories: vegetation and water bodies, in order to assess change detection in the study area.

Two Landsat satellite images were used—one from the Thematic Mapper (TM) sensor and another from the Operational Land Imager (OLI) sensor—captured in 1992 and 2024, respectively, for the purpose of calculating the NDVI and NDWI spectral indices. The main objective of this study is to monitor the nature of land cover changes in the marshes of the study area. The spectral signatures of the studied land cover classes were more distinct in the NDVI and NDWI imagery than in the original images, with class clusters being well isolated. Consequently, the modern techniques used proved to be both effective and reliable.