Notebook: How to resample Copernicus Global Land Service vegetation-related products (i.e. NDVI, FAPAR...) from 333m resolution to 1km using R-based packages and functions
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Updated
Aug 22, 2020 - HTML
Notebook: How to resample Copernicus Global Land Service vegetation-related products (i.e. NDVI, FAPAR...) from 333m resolution to 1km using R-based packages and functions
Detecting vegetation anomalies from CGLS products (e.g. NDVI)
A series of jupyter notebook pipelines for processing lidar point clouds (LAS files) and deriving vegetation structure metrics.
This repository contains a study how we can examine the vegetation cover of a region with the help of satellite data. The notebook in this repository aims to familiarise with the concept of satellite imagery data and how it can be analyzed to investigate real-world environmental and humanitarian challenges.
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