{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T08:29:20Z","timestamp":1773736160154,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T00:00:00Z","timestamp":1720742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Kurdistan","award":["3.4-1230353-IRN-GF-E"],"award-info":[{"award-number":["3.4-1230353-IRN-GF-E"]}]},{"name":"University of Tubingen","award":["3.4-1230353-IRN-GF-E"],"award-info":[{"award-number":["3.4-1230353-IRN-GF-E"]}]},{"name":"Alexander von Humboldt Foundation","award":["3.4-1230353-IRN-GF-E"],"award-info":[{"award-number":["3.4-1230353-IRN-GF-E"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land suitability assessment, as an important process in modern agriculture, involves the evaluation of numerous aspects such as soil properties, climate, relief, hydrology and socio-economic aspects. The aim of this study was to evaluate the suitability of soils for wheat cultivation in the Gavshan region, Iran, as the country is facing the task of becoming self-sufficient in wheat. Various methods were used to evaluate the land, such as multi-criteria decision-making (MCDM), which is proving to be important for land use planning. MCDM and machine learning (ML) are useful for decision-making processes because they use complicated spatial data and methods that are widely available. Using a geomorphological map, seventy soil profiles were selected and described, and ten soil properties and wheat yields were determined. Three MCDM approaches, including the technique of preference ordering by similarity to the ideal solution (TOPSIS), gray relational analysis (GRA), and simple additive weighting (SAW), were used and evaluated. The criteria weights were extracted using Shannon\u2019s entropy method. Random forest (RF) model and auxiliary variables (remote sensing data, terrain data, and geomorphological maps) were used to represent the land suitability values. Spatial autocorrelation analysis as a statistical method was applied to analyze the spatial variability of the spatial data. Slope, CEC (cation exchange capacity), and OC (organic carbon) were the most important factors for wheat cultivation. The spatial autocorrelation between the key criteria (slope, CEC, and OC) and wheat yield confirmed these results. These results also showed a significant correlation between the land suitability values of TOPSIS, GRA, and SAW and wheat yield (0.74, 0.72, and 0.57, respectively). The spatial distribution of land suitability values showed that the areas classified as good according to TOPSIS and GRA were larger than those classified as moderate and weak according to the SAW approach. These results were also confirmed by the autocorrelation of the MCDM techniques with wheat yield. In addition, the RF model showed its effectiveness in processing complex spatial data and improved the accuracy of land suitability assessment. In this study, by integrating advanced MCDM techniques and ML, an applicable land evaluation approach for wheat cultivation was proposed, which can improve the accuracy of land suitability and be useful for considering sustainability principles in land management.<\/jats:p>","DOI":"10.3390\/rs16142566","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T14:04:35Z","timestamp":1720793075000},"page":"2566","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8616-6084","authenticated-orcid":false,"given":"Kamal","family":"Nabiollahi","sequence":"first","affiliation":[{"name":"Department of Soil Science and Engineering, College of Agriculture, University of Kurdistan, Sanandaj 6617715175, Iran"},{"name":"Chair of Soil Science and Geomorphology, University of T\u00fcbingen, 72074 T\u00fcbingen, Germany"}]},{"given":"Ndiye","family":"M. Kebonye","sequence":"additional","affiliation":[{"name":"Chair of Soil Science and Geomorphology, University of T\u00fcbingen, 72074 T\u00fcbingen, Germany"},{"name":"DFG Cluster of Excellence \u201cMachine Learning: New Perspectives for Science\u201d, University of T\u00fcbingen, AI Research Building, Maria-von-Linden-Str. 6, 72076 T\u00fcbingen, Germany"}]},{"given":"Fereshteh","family":"Molani","sequence":"additional","affiliation":[{"name":"Department of Soil Science and Engineering, College of Agriculture, University of Kurdistan, Sanandaj 6617715175, Iran"}]},{"given":"Mohammad Hossein","family":"Tahari-Mehrjardi","sequence":"additional","affiliation":[{"name":"Faculty of Management, University of Tehran, Tehran 141556311, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4620-6624","authenticated-orcid":false,"given":"Ruhollah","family":"Taghizadeh-Mehrjardi","sequence":"additional","affiliation":[{"name":"Faculty of Agriculture and Natural Resources, Ardakan University, Ardakan 77871-31587, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2833-032X","authenticated-orcid":false,"given":"Hadi","family":"Shokati","sequence":"additional","affiliation":[{"name":"Chair of Soil Science and Geomorphology, University of T\u00fcbingen, 72074 T\u00fcbingen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4875-2602","authenticated-orcid":false,"given":"Thomas","family":"Scholten","sequence":"additional","affiliation":[{"name":"Chair of Soil Science and Geomorphology, University of T\u00fcbingen, 72074 T\u00fcbingen, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100002","DOI":"10.1016\/j.soisec.2020.100002","article-title":"The Science of Soil Security and Food Security","volume":"1","author":"Pozza","year":"2020","journal-title":"Soil Secur."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.gfs.2014.08.004","article-title":"Food Wedges: Framing the Global Food Demand and Supply Challenge towards 2050","volume":"3","author":"Keating","year":"2014","journal-title":"Glob. 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