undpindia / dicra
Data in Climate Resilient Agriculture (DiCRA) is a collaborative digital public good which provides open access to key geospatial datasets pertinent to climate resilient agriculture. These datasets are curated and validated through collaborative efforts of hundreds of data scientists and citizen scientists across the world.
☆25Updated last month
Alternatives and similar repositories for dicra:
Users that are interested in dicra are comparing it to the libraries listed below
- Links and slides from the OpenGeoHub summer school 2022☆47Updated 2 years ago
- contents for 2019 raster tutorial☆19Updated 3 years ago
- Presentations for the OpenGeoHub Summer School 2019: https://opengeohub.org/summer_school_2019☆20Updated 11 months ago
- ☆29Updated this week
- Scripts and notebooks for scalable geospatial data science☆22Updated last year
- Open source book: Spatial sampling with R☆75Updated last year
- GeoPAT 2 - a suite of modules dedicated to analysis of large datasets in their entirety using spatial and/or temporal patterns☆45Updated 5 months ago
- earth engine conversion for jupyter notebook use☆16Updated 7 years ago
- Rmarkdown tutorial on how to generate spatial sampling and how to use resampling methods for ML☆13Updated last year
- Raster time series visualization☆21Updated last year
- Package designed to detect and quantify water quality and cyanobacterial harmful algal bloom (CHABs) from remotely sensed imagery☆43Updated 9 months ago
- Scraping, parsing, and analyzing every public Earth Engine repository☆19Updated 2 years ago
- Ressources for the session on machine learning and remote sensing at the OpenGeoHub Summer school in Wageningen 2020☆15Updated 4 years ago
- Tools for Downloading, Customizing, and Processing Time Series of Satellite Images from Landsat, MODIS, and Sentinel☆51Updated last year
- A python implementation and a QGIS plugin for Land Use Mix indices and other related calculations.☆22Updated 10 months ago
- Material for the course on machine-learning based environmental monitoring at geostat 2018☆37Updated 6 years ago
- Complete-coverage gridded predictions of soil properties (percent organic carbon, total nitrogen, bulk density, pH, and percent sand and …☆35Updated 7 years ago
- This repo contains all the code I used to create maps for the #30DayMapChallenge in 2020 and 2021.☆9Updated 3 years ago
- R package for harmonic modelling of time-series data☆29Updated 4 years ago
- 🌎🌏🌏 Google Earth Engine with R : : Cheatsheet 🚀☆17Updated 2 years ago
- the GWR route maps for physical and human geography☆12Updated 3 years ago
- Instructor: Xiaojiang Li☆15Updated last year
- Spatial feature processing of satellite imagery☆31Updated 6 years ago
- Various blending functions for Google Earth Engine☆35Updated 2 years ago
- Search, composite, and download 'Google Earth Engine' imagery with the 'Python' module 'geedim'☆47Updated last year
- Ressources for the session on machine learning and remote sensing at the OpenGeoHub Summer school in Münster 2019☆27Updated 5 years ago
- Predictive soil mapping aiming at making complete consistent soil type maps of the world☆20Updated last year
- Links and slides from the OpenGeoHub summer school 2023☆47Updated last year