biodivMapR VS MODIStsp

Compare biodivMapR vs MODIStsp and see what are their differences.

biodivMapR

biodivMapR: an R package for α- and β-diversity mapping using remotely-sensed images (by jbferet)
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biodivMapR MODIStsp
2 1
35 152
- 0.7%
6.7 3.9
7 days ago 7 months ago
R R
GNU General Public License v3.0 only GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

biodivMapR

Posts with mentions or reviews of biodivMapR. We have used some of these posts to build our list of alternatives and similar projects.

MODIStsp

Posts with mentions or reviews of MODIStsp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-07.

What are some alternatives?

When comparing biodivMapR and MODIStsp you can also consider the following projects:

awesome-spectral-indices - A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

sentinel2-cloud-detector - Sentinel Hub Cloud Detector for Sentinel-2 images in Python

healthyR.ts - A time-series companion package to healthyR

whiteboxR - WhiteboxTools R Frontend

stplanr - Sustainable transport planning with R

continuous-reforestation - Make continuous reforestation part of your daily workflow :deciduous_tree:

targets - Function-oriented Make-like declarative workflows for R

gn_mobile_occtax - Application mobile pour la saisie dans le module Occtax de GeoNature

eoreader - Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.