Evaluation of the prediction effectiveness for geochemical mapping using machine learning methods: A case study from northern Guangdong Province in China

Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables

Tomislav Hengl, Madlene Nussbaum, Marvin N. Wright et al. · PeerJ · 2018 · 1.1K citations · Full text

Computing, Geography, Geoinformatics +17

A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

Kennedy Were, Dieu Tien Bui, Øystein B. Dick et al. · Ecological Indicators · 2015 · 813 citations

Agriculture, Earth Sciences, Soil Sciences +15

Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information

Matthew J. Cracknell, Anya M. Reading · Computers & Geosciences · 2013 · 652 citations · Full text

Computing, Earth Sciences, Geoinformatics +14

Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China

Junliang Fan, Wenjun Yue, Lifeng Wu et al. · Agricultural and Forest Meteorology · 2018 · 547 citations

Natural Sciences, Earth Sciences, Hydrology +16

Health risk assessment of heavy metal(loid)s in park soils of the largest megacity in China by using Monte Carlo simulation coupled with Positive matrix factorization model

Jingling Huang, Yuying Wu, Jiaxun Sun et al. · Journal of Hazardous Materials · 2021 · 524 citations

Natural Sciences, Environmental Sciences, Soil Sciences +17