This repository contains a pipeline blending Python and R features, first to: download, preprocess, and compute Sentinel-1 SAR vegetation indices (all in Python); following for image sampling in R.

All the code in this branch will be python based, upon jupyter notebook. You will be able to find all codes for Google Earth Engine(GEE) on this repository. You will be able to link code with each post blog on readme file for each folders. Content from the Blog https://kaflekrishna.com.np will be uploaded here. https://google-earth-engine.com/

Render GeoJSON polygons over aerial imagery and analyse pixels covered by vegetation; used to calculate green spaces in residential gardens

VICAL is a open-source implementation to calculate 23 VIs map (VIs commonly used in agricultural applications) and time series of any agricultural area

A repository to showcase environmental projects implemented with Google Earth Engine platform, Javascript and machine learning algorithms.

Calculation of the vegetation indices (VIs) in order to estimate the crop health of the under-study field.

This repo includes the a detailed comparison of different vegetation indices (like NDVI, EVI, SAVI, NDWI) between landsat 8 and new landsat 9 satellite.

Generating high-resolution (10-m) vegetation greenness fraction with Sentinel-2 imagery and machine learning

Set of Jupyter notebooks and geospatial data developed by the MAPSPADES project to study desertification in the Algerian steppe using EO data.

AppGro: Flutter realtime GGA and GA image calculator application made in flutter

codes for GRSL paper: Time-Resolved Sentinel-3 Vegetation Indices via Inter-Sensor 3D Convolutional Regression Networks

A step-by-step guide to vegetation classification and calculation of unvegetated - vegetated ratio of salt marshes with public aerial imagery

Visualizing Vegetation Indices using python.

Quarto source code for my master's thesis "Remote Sensing of Foliar Nitrogen in Californian Almonds" (2023)