Land | Invitation to Read Papers and Hot Topic Special Issues Related to Machine Learning and Land System Science

We are delighted to share some papers on machine learning and land system science research that were published in our journal Land (ISSN: 2073-445X) from 2023 to 2025. In addition, some Special Issues related to this topic are currently open for submission.

The following is a list of articles and Special Issues that we believe will interest you:

1. “Enabling Regenerative Agriculture Using Remote Sensing and Machine Learning”
by Michael Gbenga Ogungbuyi, Juan P. Guerschman, Andrew M. Fischer, Richard Azu Crabbe, Caroline Mohammed, Peter Scarth, Phil Tickle, Jason Whitehead and Matthew Tom Harrison
Land 2023, 12(6), 1142; https://doi.org/10.3390/land12061142
Available online: https://www.mdpi.com/2073-445X/12/6/1142

2. “Enhancing Wind Erosion Assessment of Metal Structures on Dry and Degraded Lands through Machine Learning”
by Marta Terrados-Cristos, Francisco Ortega-Fernández, Marina Díaz-Piloñeta, Vicente Rodríguez Montequín and José Valeriano Álvarez Cabal
Land 2023, 12(8), 1503; https://doi.org/10.3390/land12081503
Available online: https://www.mdpi.com/2073-445X/12/8/1503

3. “Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study”
by Artur Łopatka, Grzegorz Siebielec, Radosław Kaczyński and Tomasz Stuczyński
Land 2023, 12(8), 1587; https://doi.org/10.3390/land12081587
Available online: https://www.mdpi.com/2073-445X/12/8/1587

4. “A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers”
by Joe Yazbeck and John B. Rundle
Land 2023, 12(11), 1977; https://doi.org/10.3390/land12111977
Available online: https://www.mdpi.com/2073-445X/12/11/1977

5. “Mapping Soil Organic Carbon Stock and Uncertainties in an Alpine Valley (Northern Italy) Using Machine Learning Models”
by Sara Agaba, Chiara Ferré, Marco Musetti and Roberto Comolli
Land 2024, 13(1), 78; https://doi.org/10.3390/land13010078
Available online: https://www.mdpi.com/2073-445X/13/1/78

6. “Evaluating Machine Learning-Based Approaches in Land Subsidence Susceptibility Mapping”
by Elham Hosseinzadeh, Sara Anamaghi, Massoud Behboudian and Zahra Kalantari
Land 2024, 13(3), 322; https://doi.org/10.3390/land13030322
Available online: https://www.mdpi.com/2073-445X/13/3/322

7. “Determining the Climatic Drivers for Wine Production in the Côa Region (Portugal) Using a Machine Learning Approach”
by Helder Fraga, Teresa R. Freitas, Marco Moriondo, Daniel Molitor and João A. Santos
Land 2024, 13(6), 749; https://doi.org/10.3390/land13060749
Available online: https://www.mdpi.com/2073-445X/13/6/749

8. “Machine Learning for Criteria Weighting in GIS-Based Multi-Criteria Evaluation: A Case Study of Urban Suitability Analysis”
by Lan Qing Zhao, Alysha van Duynhoven and Suzana Dragićević
Land 2024, 13(8), 1288; https://doi.org/10.3390/land13081288
Available online: https://www.mdpi.com/2073-445X/13/8/1288

9. “Machine Learning Models for the Spatial Prediction of Gully Erosion Susceptibility in the Piraí Drainage Basin, Paraíba Do Sul Middle Valley, Southeast Brazil”
by Jorge da Paixão Marques Filho, Antônio José Teixeira Guerra, Carla Bernadete Madureira Cruz, Maria do Carmo Oliveira Jorge and Colin A. Booth
Land 2024, 13(10), 1665; https://doi.org/10.3390/land13101665
Available online: https://www.mdpi.com/2073-445X/13/10/1665

10. “Estimating Rainfall Erosivity in North Korea Using Automated Machine Learning: Insights into Regional Soil Erosion Risks”
by Jeongho Han and Seoro Lee
Land 2024, 13(12), 2038; https://doi.org/10.3390/land13122038
Available online: https://www.mdpi.com/2073-445X/13/12/2038

11. “Machine Learning-Based Prediction of Ecosystem-Scale CO₂ Flux Measurements”
by Jeffrey Uyekawa, John Leland, Darby Bergl, Yujie Liu, Andrew D. Richardson and Benjamin Lucas
Land 2025, 14(1), 124; https://doi.org/10.3390/land14010124
Available online: https://www.mdpi.com/2073-445X/14/1/124

12. “Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las Vegas”
by Jingyi Liu, Yuxuan Cai and Xiwei Shen
Land 2025, 14(5), 957; https://doi.org/10.3390/land14050957
Available online: https://www.mdpi.com/2073-445X/14/5/957

13. “Detection of Agricultural Terraces Platforms Using Machine Learning from Orthophotos and LiDAR-Based Digital Terrain Model: A Case Study in Roya Valley of Southeast France”
by Michael Vincent Tubog, Karine Emsellem and Stephane Bouissou
Land 2025, 14(5), 962; https://doi.org/10.3390/land14050962
Available online: https://www.mdpi.com/2073-445X/14/5/962

14. “A Machine Learning Approach to Generate High-Resolution Maps of Irrigated Olive Groves”
by Rosa Gutiérrez-Cabrera, Ana M. Tarquis and Javier Borondo
Land 2025, 14(5), 1001; https://doi.org/10.3390/land14051001
Available online: https://www.mdpi.com/2073-445X/14/5/1001

15. “Monitoring Post-Fire Deciduous Shrub Cover Using Machine Learning and Multiscale Remote Sensing”
by Hannah Trommer and Timothy Assal
Land 2025, 14(8), 1603; https://doi.org/10.3390/land14081603
Available online: https://www.mdpi.com/2073-445X/14/8/1603

Special Issues:
“Feature Papers for Land Innovations—Data and Machine Learning: 3rd Edition”
Guest Editor: Chuanrong Zhang
Submission deadline: 31 December 2025

“AI-Enabled Decision Support Systems for Sustainable Agricultural Land Use”
Guest Editors: Jaume Segura-Garcia, Miguel García-Pineda, Sergi Maicas and Yiyun Chen
Submission deadline: 28 February 2026

“Data-Driven Geospatial Methods for Land Use and Land Cover Change Monitoring”
Guest Editors: Sabah Sabaghy and Deepak Gautam
Submission deadline: 31 May 2026