Algorithms for Quantitative Pedology

Using CNN-LSTM deep learning model for digital soil mapping. This is the code for paper "Zhang et al. A CNN-LSTM model for soil organic carbon content prediction with long time series of MODIS-based phenological variables"

S4SS: Statistics for Soil Survey

Soil Organic Carbon mapping Cookbook

Download raster data from the Soil and Landscape Grid of Australia - http://www.clw.csiro.au/aclep/soilandlandscapegrid/

An R implementation of the DSMART algorithm

Annual mapping of soil organic carbon stock in Brazil 1985-present. Training field soil data

Workspace for projects and active development.

Digital Soil Mapping Focus Teams

Using CNN-LSTM deep learning model for digital soil mapping. This is the code for paper "Zhang et al. A CNN-LSTM model for soil organic carbon content prediction with long time series of MODIS-based phenological variables"

Examples and utilities for performing Digital Soil Mapping (DSM) with python

This repository contains files for automated soil sampling selection using the K-Means algorithm in R. The repository is intended for researchers and practitioners interested in automated soil sampling selection using the K-Means algorithm.

Spatial modelling via QGIS-R integration

Disaggregation of Conventional Soil Maps, PhD thesis

Tier 4 maps of soil pH at 25m resolution for the Netherlands

This repository contains the code of the sampling method proposed in the paper "Zhang et al. An adaptive uncertainty-guided sampling method for geospatial prediction and its application in digital soil mapping" published in IJGIS.

Presentation at the annual conference of the German Soil Science Society on September 4, 2023

Solving for y: digital soil mapping using statistical models and improved models of land surface

Presentation at the KIDA workshop on September 27, 2023

Citizen-based mapping of paleosol/hydropedologic sequences using machine learning. The outputs contributed to the creation and management of a conservation area in Cerro Seco, southern Bogotá.