{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T09:50:43Z","timestamp":1723801843425},"reference-count":86,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,15]],"date-time":"2024-02-15T00:00:00Z","timestamp":1707955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFB3903503"],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Project of Chongqing Science and Technology Bureau","award":["cstc2021jcyj-msxmX0384"]},{"name":"Opening Funds from Chongqing Jinfo Mountain Karst Ecosystem National Research and Observation Station","award":["JFS2023B01"]},{"name":"National Natural Science Foundation of China","award":["41501575","U2244216","42171338","42371333","72221002"]},{"name":"Sichuan Science and Technology Program","award":["2023NSFSC1916"]},{"name":"Special Fund for Youth Team of the Southwest University","award":["SWU-XJLJ202305","XJPY202307"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Soil organic carbon (SOC) is generally thought to act as a carbon sink; however, in areas with high spatial heterogeneity, using a single model to estimate the SOC of the whole study area will greatly reduce the simulation accuracy. The earth surface unit division is important to consider in building different models. Here, we divided the research area into different habitat patches using partitioning around a medoids clustering (PAM) algorithm; then, we built an SOC simulation model using machine learning algorithms. The results showed that three habitat patches were created. The simulation accuracy for Habitat Patch 1 (R2 = 0.55; RMSE = 2.89) and Habitat Patch 3 (R2 = 0.47; RMSE = 3.94) using the XGBoost model was higher than that for the whole study area (R2 = 0.44; RMSE = 4.35); although the R2 increased by 25% and 6.8%, the RMSE decreased by 33.6% and 9.4%, and the field sample points significantly declined by 70% and 74%. The R2 of Habitat Patch 2 using the RF model increased by 17.1%, and the RMSE also decreased by 10.5%; however, the sample points significantly declined by 58%. Therefore, using different models for corresponding patches will significantly increase the SOC simulation accuracy over using one model for the whole study area. This will provide scientific guidance for SOC or soil property monitoring with low field survey costs and high simulation accuracy.<\/jats:p>","DOI":"10.3390\/rs16040688","type":"journal-article","created":{"date-parts":[[2024,2,15]],"date-time":"2024-02-15T10:55:59Z","timestamp":1707994559000},"page":"688","source":"Crossref","is-referenced-by-count":2,"title":["Significant Improvement in Soil Organic Carbon Estimation Using Data-Driven Machine Learning Based on Habitat Patches"],"prefix":"10.3390","volume":"16","author":[{"given":"Wenping","family":"Yu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, The Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"},{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China"}]},{"given":"Ting","family":"Wang","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"ORCID":"http:\/\/orcid.org\/0009-0005-4218-5319","authenticated-orcid":false,"given":"Jieyun","family":"Xiao","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"given":"Yao","family":"Peng","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]},{"given":"Haoran","family":"Li","sequence":"additional","affiliation":[{"name":"The Six Topographic Survey Team of Ministry of Natural Resources, Chengdu 610500, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9263-7599","authenticated-orcid":false,"given":"Yuechen","family":"Li","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1111\/j.1365-2486.2008.01745.x","article-title":"Quantitative aspects of heterogeneity in soil organic matter dynamics in a cool-temperate Japanese beech forest: A radiocarbon-based approach","volume":"15","author":"Koarashi","year":"2009","journal-title":"Glob. 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