Prediction in Terrestrial and Aquatic Ecosystems Using Sentinel-2, Landsat 8, and MODIS Data: An Integrated Approach through Google Earth Engine

Year 2025, Volume: 12 Issue: 3, 251 - 262, 29.09.2025

Nehir Uyar

Abstract

This study focuses on predicting drought conditions in terrestrial and aquatic ecosystems by leveraging data from Sentinel-2, Landsat 8, and MODIS satellites. Using the Google Earth Engine (GEE) platform, the study integrates these diverse satellite datasets to assess plant indices and drought indicators. The research covers the period from 2017 to 2023 and employs the Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) derived from Sentinel-2 data to evaluate drought conditions. NDVI values are processed to calculate annual averages and VCI, while Landsat 8 and MODIS data are utilized to monitor larger areas and conduct long-term assessments. The data processing involves calculating the minimum and maximum NDVI values for VCI computation, which is then classified into various drought severity levels. Results are visualized through color maps and histograms, illustrating the spatial distribution of drought conditions. Additionally, a graph depicting annual average NDVI and VCI values highlights changes and trends over the study period. The findings indicate that combining Sentinel-2, Landsat 8, and MODIS data provides a robust method for drought prediction. The integration of these datasets within the Google Earth Engine framework demonstrates effective data processing and visualization capabilities. The study concludes that this comprehensive approach is valuable for monitoring and managing drought conditions in both terrestrial and aquatic ecosystems, offering insights into vegetation cover changes and drought trends.

Keywords

Normalized Difference Vegetation Index 1 , Vegetation Condition Index 2 , Google Earth Engine 3 , ecosystems 4

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