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An R package for automatic download and preprocessing of MODIS Land Products Time-Series.
lang: R
stars: 156
last activity:
A remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
lang: Python
stars: 311
last activity:
A Python package that provides a simple way to use nighttime lights data from NASA's Black Marble project that provides a product suite of daily, monthly and yearly global nighttime lights.
lang: Jupyter Notebook
stars: 44
last activity:
Provides an overview of methods we can use to study agricultural development decisions and generate forecasts of decision outcomes.
lang: HTML
stars: 24
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Data Analysis and Visualization in Python for Ecologists.
lang: Jupyter Notebook
stars: 168
last activity:
These tools help you to assess if a financial portfolio aligns with climate goals.
lang: R
stars: 12
last activity:
A family of tools for quantifying the values of natural capital in clear, credible, and practical ways.
lang: Python
stars: 193
last activity:
An R binding package for calling Google Earth Engine API from within R.
lang: R
stars: 733
last activity:
Download and process satellite imagery in Python using Sentinel Hub services.
lang: Python
stars: 854
last activity:
Clay is a foundational model of Earth using a vision transformer architecture adapted to understand geospatial and temporal relations on Earth Observation data.
lang: Python
stars: 452
last activity:
Help us build the most accessible and accurate climate tech resource on the planet.
lang: Jupyter Notebook
stars: 80
last activity:
Search, download or stream NASA Earth science data with just a few lines of code.
lang: Python
stars: 493
last activity:
A community learning resource for Python-based computing in the geosciences.
lang: Jupyter Notebook
stars: 66
last activity:
Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.
lang: Python
stars: 231
last activity:
A collection of Python utilities for retrieving atmospheric and oceanic data from remote sources, focusing on being able to retrieve data from Unidata data technologies.
lang: Python
stars: 232
last activity: