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"

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"

R scripts for predicting soil organic carbon using soil spectral library from visible, near-infrared and shortwave-infrared (VNIR) and middle-infrared (MIR) using LASSO and PLS regression methods and the target-oriented cross-validation strategy.

Code associated with the dataPaper

Fully Connected Neural Network algorithm for LUCAS-2015

This repository contains data and code for the manuscript: Spatial access and resource limitations control carbon mineralization in soils. Kaizad F. Patel et al. doi: 10.1016/j.soilbio.2021.108427

How can we get an accurate estimate of carbon stocks across a landscape with minimal ground truth data?

"Personalizing Sustainable Agriculture with Causal Machine Learning". Best Proposal Paper of "Tackling Climate Change with Machine Learning" Workshop, NeurIPS'22.