Green-Cover-Analysis

Analysis of geo mapped photographs and satellite imagery to estimate green cover over time across the globe.
A web app has also been developed using Django REST Framework and React for the same.

Link to the deployed ipynb notebooks: https://gcnotebooks.herokuapp.com/

Web App:

Link to the deployed web app: https://green-cover.netlify.app/
Link to frontend repo: https://github.com/VirajPatidar/green-cover-frontend
Link to backend repo: https://github.com/VirajPatidar/green-cover-backend

Tech Stack:

Vision Analytics, Machine Learning, Datasets and Satellite Imagery:

• Google Earth Engine Datasets
• Google Earth Engine Python API
• Geemap

Features:

• Rendering dynamic maps to analyse green cover and generate timelapses representing change in green cover.
• Time series chart/graph representing change in green cover over the years for the state of Maharashtra.
• Predicting type of landcover in the state of Maharashtra by performing supervised classification using existing datasets.
• Analysis of air quality on basis of various parameters for the state of Maharashtra.

Features along with datasets used:

TASK / FEATURE	DATASET
Estimating Green Cover using Vegetation Indexes (Global)	USGS Landsat 8 Level 2, Collection 2, Tier 1
Timelapse for Normalized Difference Vegetation Index (NDVI) (Global)	USGS Landsat 8 Level 2, Collection 2, Tier 1 USGS Landsat 5 Level 2, Collection 2, Tier 1
Time series graphical analysis representing Vegetation Indexes (NDVI & EVI) of Maharashtra	MOD13Q1.006 MODIS Terra Vegetation Indices 16-Day Global 250m
Landcover Analysis of Maharashtra	USGS Landsat 8 Level 2, Collection 2, Tier 1 MCD12Q1.006 MODIS Land Cover Type Yearly Global 500m
Analysing Air Quality of Maharashtra	Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde