Scholarlink

In this project, we created a cloud-based pipeline that performs annual Sentinel-2 NDVI map comparison for the detection of vegetation loss zones. By exporting 10-m composites using Google Earth Engine and performing pixel-wise analysis on Google Colab, we computed year-on-year NDVI and flagged pixels where NDVI dropped by more than 0.10. For a region covering the Trivandrum district-specified ROI: lat/lon bounding box used in our scripts-this pipeline estimated the cumulative loss to be  5,079.5 hectares between 2019 and 2025. Containerizing the visualization in Streamlit and creating summary reports in Looker Studio is done for stakeholder review. The code, analysis parameters, and step-by-step notebook commands have also been included in the supplementary material to make the results reproducible.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Cloud-Enabled NDVI Change Detection for Deforestation Monitoring Using Sentinel-2

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • S. Adwaith,
  • RT Afam Salam,
  • Arundhathi Jayakumar,
  • Kavya P Nair,
  • Divya Udayan J,
  • Anila Johnson

摘要

In this project, we created a cloud-based pipeline that performs annual Sentinel-2 NDVI map comparison for the detection of vegetation loss zones. By exporting 10-m composites using Google Earth Engine and performing pixel-wise analysis on Google Colab, we computed year-on-year NDVI and flagged pixels where NDVI dropped by more than 0.10. For a region covering the Trivandrum district-specified ROI: lat/lon bounding box used in our scripts-this pipeline estimated the cumulative loss to be  5,079.5 hectares between 2019 and 2025. Containerizing the visualization in Streamlit and creating summary reports in Looker Studio is done for stakeholder review. The code, analysis parameters, and step-by-step notebook commands have also been included in the supplementary material to make the results reproducible.