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Chesapeake Bay SAV Data collection via http://www.vims.edu/ research team. More than a spatial, and tabular data repository, the older .arc files have been converted to shapefiles, all have been converted to geojson. Future intentions include visualizing sav annual maps over time (70s-current), real-time analysis and monitoring, as well as some …
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.
Source code for the publications on "a non-linear Granger-causality framework to investigate climate–vegetation dynamics", by Papagiannopoulou et al., GMD & ERL 2017
Clustering vegetative areas in ISRO Resourcesat-1,2 satellite images to extract crop cycle parameters. For a cool Landsat-8 visualization project, click on the link below.
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