Monitoring and Analyzing Desertification in Haditha District Using Spectral Indices (NDVI, BSI, and DRI) and Machine Learning Techniques within the Google Earth Engine Platform

Authors

  • Asst. Lecturer Natiq Hashim Tofan Ministry of Education General Directorate of Education in Wasit
  • Prof. Dr. Ali Majeed Yasseen Dhi Qar University / College of Arts Department of Geography

DOI:

https://doi.org/10.58564/ma.v16iمؤتمر%20قسم%20الجغرافية.2648

Keywords:

Keywords : Desertification – Spectral Indices – Vegetation Cover – Bare Soil – Drought – Haditha District – Remote Sensing – Geographic Information Systems – Google Earth Engine.

Abstract

   Desertification is considered one of the most prominent environmental challenges affecting arid and semi-arid regions, due to its direct impact on the degradation of agricultural lands, the reduction of vegetation productivity, and the threat to food security. Haditha District is among the areas affected by this phenomenon as a result of climatic changes and anthropogenic pressures. This study aims to monitor and analyze desertification in Haditha District using remote sensing techniques and Geographic Information Systems (GIS), through the application of spectral indices including the Normalized Difference Vegetation Index (NDVI), the Bare Soil Index (BSI), and the Drought Response Index (DRI), within the Google Earth Engine platform. The study relied on Sentinel-2 Surface Reflectance imagery, which provides high spatial and spectral resolution suitable for assessing environmental changes. The years 2020 and 2025 were selected, with a focus on March and September to represent seasonal variations between periods of peak vegetation growth and environmental stress. Preprocessing included cloud filtering and the creation of monthly composite images, followed by the derivation of spectral indices and analysis of their spatial and temporal distribution across the study area. Machine learning techniques were also employed within Google Earth Engine to improve the accuracy of desertification classification and to determine the levels of land degradation. The results revealed clear variations in spectral index values, where decreases in NDVI coincided with increases in BSI and DRI in areas most exposed to desertification, reflecting vegetation deterioration and increasing drought conditions. The outputs of this study provide valuable support for decision-makers by offering updated spatial maps that can assist in developing effective strategies to mitigate desertification and enhance food security in Haditha District.

Published

2026-06-27