Open Intelligence for Every Farm - Monitor crop health with satellite imagery, detect anomalies early, and make data-driven decisions.

We are team AgriBotics, this repo contains the codes for building an autonomous agriculture drone with 2 phases, mapping drone to map and mark the selected areas for pesticide spraying based on pigmentation level and agricultural drone to spray the pesticide

Complemento para o QGIS focado na extração e análise de séries temporais de índices de vegetação (NDVI) integrando dados da plataforma Satveg

Geospatial machine learning pipeline to detect and quantify urban expansion in Surat (India) using multi-temporal Landsat imagery. Implements NDVI/NDBI-based weak supervision, Random Forest classification, confidence-filtered change detection, and directional growth analysis.

Data analysis and object detection to assess Hurricane Maria's impact using NDVI analysis and YOLO modeling for disaster relief planning.

Contains cleaned data and analysis scripts for a multi‐site woodland restoration study, focusing on key indicators—microbial biomass carbon (µg/g), PLFA community, total organic carbon (TOC) and soil pH. It provides summary statistics, ANOVA tests and visualisation workflows to compare soil health and microbial dynamics across restoration ages.

Streamlit dashboard for crop mapping validation using survey points and NDVI

Monitor vegetation change and detect potential deforestation using Sentinel-2 imagery and NDVI difference over a ~300,000 km² sub-region in the Brazilian Amazon (southern Rondônia / northern Mato Grosso).

NDVI-based vegetation change analysis in Tangerang Selatan, Indonesia, using Sentinel-2 data and Google Earth Engine (2019–2025). This project maps green space dynamics and identifies areas with significant vegetation increase or decrease.