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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.01628 |
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| _version_ | 1866918134034726912 |
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| author | Moula, Md. Moktader Shonom, Israt Jahan Islam, Azharul Hossain, Mohammad Mosharraf |
| author_facet | Moula, Md. Moktader Shonom, Israt Jahan Islam, Azharul Hossain, Mohammad Mosharraf |
| contents | Monitoring vegetation dynamics is crucial for addressing global environmental challenges like degradation and deforestation, but traditional remote sensing methods are often complex and resource-intensive. To overcome these barriers, we developed an interactive, cloud-based application on the Google Earth Engine (GEE) platform for few clicks on-demand global vegetation analysis without complex technical knowledge. The application automates the calculation of vegetated areas using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 and Landsat imagery. It utilizes a median composite of images over a selected period to create a single, robust, cloud-free image, minimizing atmospheric noise and other artifacts. It offers a flexible, global multi-scale analytical platform, allowing users to define regions of interest based on administrative boundaries, protected areas, or custom-drawn polygons. The user-friendly interface enables the selection of specific time periods and NDVI thresholds to quantify vegetation cover in real time, eliminating the need for manual and time intensive data handling and processing. A validation of the platform was conducted for two protected areas in Bangladesh which demonstrated high accuracy, with area estimates showing over 97% agreement with published reference data. By simplifying access to powerful geospatial analytics to general people, this tool provides a scalable and practical solution for researchers, land managers, policymakers, and any interested person to monitor vegetation trends, support conservation efforts, to inform decision making in spatial context where policy maker need to use insights in few clicks and inform environmental policy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01628 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Interactive Google Earth Engine Application for Global Multi-Scale Vegetation Analysis Using NDVI Thresholding Moula, Md. Moktader Shonom, Israt Jahan Islam, Azharul Hossain, Mohammad Mosharraf Human-Computer Interaction Monitoring vegetation dynamics is crucial for addressing global environmental challenges like degradation and deforestation, but traditional remote sensing methods are often complex and resource-intensive. To overcome these barriers, we developed an interactive, cloud-based application on the Google Earth Engine (GEE) platform for few clicks on-demand global vegetation analysis without complex technical knowledge. The application automates the calculation of vegetated areas using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 and Landsat imagery. It utilizes a median composite of images over a selected period to create a single, robust, cloud-free image, minimizing atmospheric noise and other artifacts. It offers a flexible, global multi-scale analytical platform, allowing users to define regions of interest based on administrative boundaries, protected areas, or custom-drawn polygons. The user-friendly interface enables the selection of specific time periods and NDVI thresholds to quantify vegetation cover in real time, eliminating the need for manual and time intensive data handling and processing. A validation of the platform was conducted for two protected areas in Bangladesh which demonstrated high accuracy, with area estimates showing over 97% agreement with published reference data. By simplifying access to powerful geospatial analytics to general people, this tool provides a scalable and practical solution for researchers, land managers, policymakers, and any interested person to monitor vegetation trends, support conservation efforts, to inform decision making in spatial context where policy maker need to use insights in few clicks and inform environmental policy. |
| title | An Interactive Google Earth Engine Application for Global Multi-Scale Vegetation Analysis Using NDVI Thresholding |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.01628 |