{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:41:57Z","timestamp":1776300117378,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"National Natural Science Foundation","award":["U1809208"],"award-info":[{"award-number":["U1809208"]}]},{"name":"National Natural Science Foundation","award":["31901310"],"award-info":[{"award-number":["31901310"]}]},{"name":"State Key Laboratory of Subtropical Silviculture","award":["ZY20180201"],"award-info":[{"award-number":["ZY20180201"]}]},{"name":"Zhejiang Provincial Collaborative Innovation Center for Bamboo Resources and High-Efficiency Utilization","award":["S2017011"],"award-info":[{"award-number":["S2017011"]}]},{"name":"the Key Research and Development Program of Zhejiang Province","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Future land use and cover change (LUCC) simulations play an important role in providing fundamental data to reveal the carbon cycle response of forest ecosystems to LUCC. Subtropical forests have great potential for carbon sequestration, yet their future dynamics under natural and human influences are unclear. Zhejiang Province in China is an important distribution area for subtropical forests. For forest management, it is of great significance to explore the future dynamic changes of subtropical forests in Zhejiang. As a popular LUCC spatial simulation model, the cellular automata (CA) model coupled with machine learning and LUCC quantitative demand models such as system dynamics (SD) can achieve effective LUCC simulation. Therefore, we first integrated a back propagation neural network (BPNN), a CA, and a SD model as a BPNN_CA_SD (BCS) coupled model for future LUCC simulation and then designed a slow development scenario (SD_Scenario), a harmonious development scenario (HD_Scenario), a baseline development scenario (BD_Scenario), and a fast development scenario (FD_Scenario), combining climate change and human disturbance. Thirdly, we obtained future land-use patterns in Zhejiang Province from 2014 to 2084 under multiple scenarios, and finally, we analyzed the temporal and spatial changes of land use and discussed the subtropical forest dynamics of the future. The results showed the following: (1) The overall accuracy was approximately 0.8, the kappa coefficient was 0.75, and the figure of merit (FOM) value was over 28% when using the BCS model to predict LUCC, indicating that the model could predict the consistent change of LUCC accurately. (2) The future evolution of the LUCC under different scenarios varied, with the growth of bamboo forests and the decline of coniferous forests in the FD_Scenario being prominent among the forest dynamics changes. Compared with 2014, the bamboo forest in 2084 will increase by 37%, while the coniferous forest will decrease by 25%. (3) Comparing the area and spatial change of the subtropical forests, the SD_Scenario was found to be beneficial for the forest ecology. These results can provide an important decision-making reference for land-use planning and sustainable forest development in Zhejiang Province.<\/jats:p>","DOI":"10.3390\/rs14071698","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T21:34:29Z","timestamp":1648762469000},"page":"1698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Simulating Future LUCC by Coupling Climate Change and Human Effects Based on Multi-Phase Remote Sensing Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7443-6515","authenticated-orcid":false,"given":"Zihao","family":"Huang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuejian","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaqiang","family":"Du","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangjie","family":"Mao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Han","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiliang","family":"Fan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanxin","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Luo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S1002-0160(09)60277-0","article-title":"Land use and soil organic carbon in China\u2019s village landscapes","volume":"20","author":"Jiao","year":"2010","journal-title":"Pedosphere"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1088\/1748-9326\/9\/1\/014010","article-title":"National contributions to observed global warming","volume":"9","author":"Matthews","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/S1002-0160(06)60020-9","article-title":"Soil organic carbon content and distribution in a small landscape of Dongguan, South China","volume":"16","author":"Su","year":"2006","journal-title":"Pedosphere"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-16953-8","article-title":"Contribution of land use to the interannual variability of the land carbon cycle","volume":"11","author":"Yue","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3741","DOI":"10.1111\/gcb.14768","article-title":"Largely underestimated carbon emission from land use and land cover change in the conterminous United States","volume":"25","author":"Yu","year":"2019","journal-title":"Glob. Chang. Biol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6859","DOI":"10.1175\/JCLI-D-12-00623.1","article-title":"Effect of anthropogenic land-use and land-cover changes on climate and land carbon storage in CMIP5 projections for the twenty-first century","volume":"26","author":"Brovkin","year":"2013","journal-title":"J. Clim."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3092","DOI":"10.1002\/ldr.3969","article-title":"Analysis and prediction of land cover changes using the land change modeler (LCM) in a semiarid river basin, Iran","volume":"32","author":"Sadoddin","year":"2021","journal-title":"Land. Degrad. Dev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.agsy.2011.12.002","article-title":"A system dynamics approach to land use changes in agro-pastoral systems on the desert margins of Sahel","volume":"107","author":"Rasmussen","year":"2012","journal-title":"Agric. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecolmodel.2017.02.005","article-title":"A new temporal\u2013spatial dynamics method of simulating land-use change","volume":"350","author":"Liu","year":"2017","journal-title":"Ecol. Model."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.ecolmodel.2013.02.027","article-title":"Combining system dynamics and hybrid particle swarm optimization for land use allocation","volume":"257","author":"Liu","year":"2013","journal-title":"Ecol. Model."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.landurbplan.2012.02.006","article-title":"A coupled model for simulating spatio-temporal dynamics of land-use change: A case study in Changqing, Jinan, China","volume":"106","author":"Zheng","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.ecocom.2010.02.001","article-title":"Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang, China","volume":"7","author":"Luo","year":"2010","journal-title":"Ecol. Complex."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101581","DOI":"10.1016\/j.scs.2019.101581","article-title":"Spatiotemporal dynamic simulation of land-use and landscape-pattern in the Pearl River Delta, China","volume":"49","author":"Jiao","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"108176","DOI":"10.1016\/j.ecolind.2021.108176","article-title":"Scenario simulation of ecological risk based on land use\/cover change\u2014A case study of the Jinghe county, China","volume":"131","author":"Zhang","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"146716","DOI":"10.1016\/j.scitotenv.2021.146716","article-title":"Future land-use changes and its impacts on terrestrial ecosystem services: A review","volume":"781","author":"Gomes","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"101622","DOI":"10.1016\/j.compenvurbsys.2021.101622","article-title":"An efficient dynamic route optimization for urban flooding evacuation based on Cellular Automata","volume":"87","author":"He","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"104081","DOI":"10.1016\/j.landurbplan.2021.104081","article-title":"Modelling transitions in sealed surface cover fraction with Quantitative State Cellular Automata","volume":"211","author":"Priem","year":"2021","journal-title":"Landsc. Urban Plan."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Aguejdad, R. (2021). The Influence of the Calibration Interval on Simulating Non-Stationary Urban Growth Dynamic Using CA-Markov Model. Remote Sens., 13.","DOI":"10.3390\/rs13030468"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, K., Feng, M., Biswas, A., Su, H., Niu, Y., and Cao, J. (2020). Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China. Sensors, 20.","DOI":"10.3390\/s20102757"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1080\/10106049.2013.776641","article-title":"Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques","volume":"28","author":"Sharma","year":"2013","journal-title":"Geocarto. Int."},{"key":"ref_21","first-page":"265","article-title":"Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion","volume":"21","author":"Helbich","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Mallick, J., AlQadhi, S., Talukdar, S., Pradhan, B., Bindajam, A.A., Islam, A.R.M.T., and Dajam, A.S. (2021). A Novel Technique for Modeling Ecosystem Health Condition: A Case Study in Saudi Arabia. Remote Sens., 13.","DOI":"10.3390\/rs13132632"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.envsoft.2018.10.006","article-title":"A novel algorithm for calculating transition potential in cellular automata models of land-use\/cover change","volume":"112","author":"Roodposhti","year":"2019","journal-title":"Environ. Model. Software"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Chen, Z., Huang, M., Zhu, D., and Altan, O. (2021). Integrating Remote Sensing and a Markov-FLUS Model to Simulate Future Land Use Changes in Hokkaido, Japan. Remote Sens., 13.","DOI":"10.3390\/rs13132621"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Marondedze, A.K., and Sch\u00fctt, B. (2021). Predicting the Impact of Future Land Use and Climate Change on Potential Soil Erosion Risk in an Urban District of the Harare Metropolitan Province, Zimbabwe. Remote Sens., 13.","DOI":"10.3390\/rs13214360"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.landurbplan.2017.09.019","article-title":"A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects","volume":"168","author":"Liu","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_27","first-page":"1","article-title":"Parallelizing backpropagation neural network using MapReduce and cascading model","volume":"2016","author":"Liu","year":"2016","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1126\/science.1130168","article-title":"Old-growth forests can accumulate carbon in soils","volume":"314","author":"Zhou","year":"2006","journal-title":"Science"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1016\/j.atmosenv.2010.12.041","article-title":"An old-growth subtropical Asian evergreen forest as a large carbon sink","volume":"45","author":"Tan","year":"2011","journal-title":"Atmos. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4015","DOI":"10.1073\/pnas.1700304115","article-title":"Climate change, human impacts, and carbon sequestration in China","volume":"115","author":"Fang","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Liu, F.-h., Xu, C.-Y., Yang, X.-x., and Ye, X.-c. (2020). Controls of climate and land-use change on terrestrial net primary productivity variation in a subtropical humid basin. Remote Sens., 12.","DOI":"10.3390\/rs12213525"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.foreco.2016.03.048","article-title":"Effects of land use change on the composition of soil microbial communities in a managed subtropical forest","volume":"373","author":"Guo","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2709","DOI":"10.1038\/s41467-018-05132-5","article-title":"Limits to growth of forest biomass carbon sink under climate change","volume":"9","author":"Zhu","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1108","DOI":"10.1016\/j.scib.2018.07.015","article-title":"Future biomass carbon sequestration capacity of Chinese forests","volume":"63","author":"Yao","year":"2018","journal-title":"Sci. Bull."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.compenvurbsys.2009.06.001","article-title":"Complexity and performance of urban expansion models","volume":"34","author":"Poelmans","year":"2010","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1080\/15481603.2019.1603187","article-title":"Incorporation of spatial heterogeneity-weighted neighborhood into cellular automata for dynamic urban growth simulation","volume":"56","author":"Feng","year":"2019","journal-title":"GISci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10584-011-0148-z","article-title":"The representative concentration pathways: An overview","volume":"109","author":"Edmonds","year":"2011","journal-title":"Clim. Chang."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.techfore.2014.12.002","article-title":"IPCC fifth assessment synthesis report: \u201cClimate change 2014: Longer report\u201d: Critical analysis","volume":"92","author":"Jefferson","year":"2015","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"107936","DOI":"10.1016\/j.ecolind.2021.107936","article-title":"Coupled SSPs-RCPs scenarios to project the future dynamic variations of water-soil-carbon-biodiversity services in Central Asia","volume":"129","author":"Li","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.isprsjprs.2010.10.002","article-title":"Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey","volume":"66","author":"Dubovyk","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zheng, J., Mao, F., Du, H., Li, X., Zhou, G., Dong, L., Zhang, M., Han, N., Liu, T., and Xing, L. (2019). Spatiotemporal simulation of net ecosystem productivity and its response to climate change in subtropical forests. Forests, 10.","DOI":"10.3390\/f10080708"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1002\/ldr.3509","article-title":"Mapping spatiotemporal decisions for sustainable productivity of bamboo forest land","volume":"31","author":"Li","year":"2020","journal-title":"Land. Degrad. Dev."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Li, Y., Han, N., Li, X., Du, H., Mao, F., Cui, L., Liu, T., and Xing, L. (2018). Spatiotemporal estimation of bamboo forest aboveground carbon storage based on Landsat data in Zhejiang, China. Remote Sensing, 10.","DOI":"10.3390\/rs10060898"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zhang, M., Du, H., Mao, F., Zhou, G., Li, X., Dong, L., Zheng, J., Zhu, D.e., Liu, H., and Huang, Z. (2020). Spatiotemporal evolution of urban expansion using Landsat time series data and assessment of its influences on forests. ISPRS Int. J. Geoinf., 9.","DOI":"10.3390\/ijgi9020064"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"109265","DOI":"10.1016\/j.jenvman.2019.109265","article-title":"Spatiotemporal evolution and impacts of climate change on bamboo distribution in China","volume":"248","author":"Li","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_46","first-page":"547","article-title":"Simulating Multiple Land Use Scenarios in China during 2010\u20132050 Based on System Dynamic Model","volume":"37","author":"Tian","year":"2017","journal-title":"Trop. Geogr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s10584-011-0152-3","article-title":"RCP2.6: Exploring the possibility to keep global mean temperature increase below 2\u00b0C","volume":"109","author":"Vuuren","year":"2011","journal-title":"Clim. Chang."},{"key":"ref_48","first-page":"791","article-title":"Multi-model climate change projections for India under representative concentration pathways","volume":"103","author":"Chaturvedi","year":"2012","journal-title":"Curr. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s10584-011-0149-y","article-title":"RCP 8.5\u2014A scenario of comparatively high greenhouse gas emissions","volume":"109","author":"Riahi","year":"2011","journal-title":"Clim. Chang."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1007\/s00376-013-2209-x","article-title":"Near future (2016\u201340) summer precipitation changes over China as projected by a regional climate model (RCM) under the RCP8.5 emissions scenario: Comparison between RCM downscaling and the driving GCM","volume":"30","author":"Zou","year":"2013","journal-title":"Adv. Atmos. Sci."},{"key":"ref_51","first-page":"568","article-title":"Integrating the system dynamic and cellular automata models to predict land use and land cover change","volume":"52","author":"Xu","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"101569","DOI":"10.1016\/j.compenvurbsys.2020.101569","article-title":"Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China","volume":"85","author":"Liang","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"105826","DOI":"10.1016\/j.landusepol.2021.105826","article-title":"Simulation of land-use pattern evolution in hilly mountainous areas of North China: A case study in Jincheng","volume":"112","author":"Xu","year":"2022","journal-title":"Land Use Policy"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s00168-007-0138-2","article-title":"Comparing the input, output, and validation maps for several models of land change","volume":"42","author":"Pontius","year":"2008","journal-title":"Ann. Regional Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1007\/s10980-019-00809-8","article-title":"Future forest dynamics under climate change, land use change, and harvest in subtropical forests in Southern China","volume":"34","author":"Wu","year":"2019","journal-title":"Landsc. Ecol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"074025","DOI":"10.1088\/1748-9326\/ac0b66","article-title":"Accounting for internal migration in spatial population projections\u2014A gravity-based modeling approach using the Shared Socioeconomic Pathways","volume":"16","author":"Reimann","year":"2021","journal-title":"Environ. Res. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1698\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:47:54Z","timestamp":1760136474000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,31]]},"references-count":56,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071698"],"URL":"https:\/\/doi.org\/10.3390\/rs14071698","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,31]]}}}