Scale Effects on Terrain Attribute Calculation and Their Use as Environmental Covariates for Digital Soil Mapping
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Updated
Nov 15, 2018 - HTML
Scale Effects on Terrain Attribute Calculation and Their Use as Environmental Covariates for Digital Soil Mapping
Solving for y: digital soil mapping using statistical models and improved models of land surface
Spatial modelling via QGIS-R integration
Workspace for projects and active development.
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.
Disaggregation of Conventional Soil Maps, PhD thesis
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 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.
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.
Presentation at the KIDA workshop on September 27, 2023
Presentation at the annual conference of the German Soil Science Society on September 4, 2023
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
Tier 4 maps of soil pH at 25m resolution for the Netherlands
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
Algorithms for Quantitative Pedology
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