Version 1.0: 04/15/2021
This project used an open-source software R to perform different kriging methods, including Simple Kriging, Ordinary Kriging, and Random Forest Regression Kriging, to develop digital soil maps of the Gopalganj district in Bangladesh, which is well-known for peat soil. Several environmental variables contributed to the spatial distribution of soil organic carbon (SOC). Using Landsat imagery and Random Forest algorithm, the authors identified the best prediction method of carbon sequestration in paddy soil.
This repository contains all documentation, R files, geospatial, and non-geospatial data used for developing digital maps of SOC at Gopalganj district in Bangladesh. There are a series of R markdown files that contain the steps in the analysis.
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out" Copyright (C) 2020 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit)
Packages: CRAN(Comprehensive R Archive Network) Program language: Default, Restore Workspace: Default, Save Workspace: Default, Always Save History: Default, Enable Code Indexing: Yes, Use Spaces For Tab: Yes, Encoding: UTF-8,
The project can be reached at: jf1760@msstate.edu