Development of an open-access interactive tool for multi-index agricultural and environmental analysis using Landsat and Sentinel-2 on Google Earth Engine
Abstract
Accurate and timely monitoring of vegetation health, soil conditions, surface water dynamics, and agricultural drought is essential for sustainable land management and food security. However, access to satellite based analytical tools remains constrained by technical barriers, including programming requirements, platform account dependencies, and fragmented analytical capabilities across specialized applications. This study presents an open access interactive tool developed on the Google Earth Engine (GEE) cloud computing platform, enabling users to extract and analyze more than forty spectral indices from Landsat 8/9 and Sentinel 2 imagery without programming expertise or a personal GEE account. The tool integrates vegetation, water, soil, chlorophyll sensitive Red Edge, and thermal drought indices, including the Vegetation Health Index (VHI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) derived from Landsat thermal infrared bands, within a unified browser based interface that provides interactive raster maps, time series profiles, statistical histograms, and GeoTIFF and CSV export options. Cloud and shadow contamination are addressed using QA PIXEL masking for Landsat and the Cloud Score + algorithm for Sentinel 2, while optional Path/Row and MGRS tile filtering ensures temporal consistency in time series analyses by restricting input imagery to a single scene footprint. The tool's performance was demonstrated through four case studies: multi temporal vegetation expansion monitoring in the Toshka Canal region, Egypt (2020 to 2025); crop growth and land cover discrimination in an agricultural area west of Wuhan, China; flood extent mapping following the February 2023 earthquake in northwestern Syria; and an eleven year (2015 to 2025) agricultural drought assessment in the Al Ghab Plain, Syria, using integrated VHI and Land Surface Temperature records. Results confirm the tool's reliability and flexibility across diverse environmental and geographic contexts. Compared with existing platforms, including GEE PICX, Sentinel Hub, and NASA AppEEARS, the tool is distinguished by its integration of thermal drought monitoring, Red Edge chlorophyll indices, interactive time series analytics, and unrestricted open access without subscription requirements.
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BibTeX
@article{ayek2026development,
title = {{Development of an open-access interactive tool for multi-index agricultural and environmental analysis using Landsat and Sentinel-2 on Google Earth Engine}},
author = {Almustafa Abd Elkader Ayek and Norah Alshahrani and Mena Elassal and Mohannad Ali Loho and Adeb Qaid},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-73524-5},
url = {https://www.nature.com/articles/s41598-026-73524-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Development of an open-access interactive tool for multi-index agricultural and environmental analysis using Landsat and Sentinel-2 on Google Earth Engine
AU - Almustafa Abd Elkader Ayek
AU - Norah Alshahrani
AU - Mena Elassal
AU - Mohannad Ali Loho
AU - Adeb Qaid
PY - 2026
DA - 2026/10/08
JO - Scientific Reports
DO - 10.1038/s41598-026-73524-5
UR - https://www.nature.com/articles/s41598-026-73524-5
AB - Accurate and timely monitoring of vegetation health, soil conditions, surface water dynamics, and agricultural drought is essential for sustainable land management and food security. However, access to satellite based analytical tools remains constrained by technical barriers, including programming requirements, platform account dependencies, and fragmented analytical capabilities across specialized applications. This study presents an open access interactive tool developed on the Google Earth Engine (GEE) cloud computing platform, enabling users to extract and analyze more than forty spectral indices from Landsat 8/9 and Sentinel 2 imagery without programming expertise or a personal GEE account. The tool integrates vegetation, water, soil, chlorophyll sensitive Red Edge, and thermal drought indices, including the Vegetation Health Index (VHI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) derived from Landsat thermal infrared bands, within a unified browser based interface that provides interactive raster maps, time series profiles, statistical histograms, and GeoTIFF and CSV export options. Cloud and shadow contamination are addressed using QA PIXEL masking for Landsat and the Cloud Score + algorithm for Sentinel 2, while optional Path/Row and MGRS tile filtering ensures temporal consistency in time series analyses by restricting input imagery to a single scene footprint. The tool's performance was demonstrated through four case studies: multi temporal vegetation expansion monitoring in the Toshka Canal region, Egypt (2020 to 2025); crop growth and land cover discrimination in an agricultural area west of Wuhan, China; flood extent mapping following the February 2023 earthquake in northwestern Syria; and an eleven year (2015 to 2025) agricultural drought assessment in the Al Ghab Plain, Syria, using integrated VHI and Land Surface Temperature records. Results confirm the tool's reliability and flexibility across diverse environmental and geographic contexts. Compared with existing platforms, including GEE PICX, Sentinel Hub, and NASA AppEEARS, the tool is distinguished by its integration of thermal drought monitoring, Red Edge chlorophyll indices, interactive time series analytics, and unrestricted open access without subscription requirements.
SN - 2045-2322
ER -