{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T02:51:32Z","timestamp":1771037492755,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T00:00:00Z","timestamp":1626393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011190","name":"Kunming Institute of Botany, Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["QYZDY-SSW-SMC014"],"award-info":[{"award-number":["QYZDY-SSW-SMC014"]}],"id":[{"id":"10.13039\/501100011190","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Most natural rubber trees (Hevea brasiliensis) are grown on plantations, making rubber an important industrial crop. Rubber plantations are also an important source of household income for over 20 million people. The accurate mapping of rubber plantations is important for both local governments and the global market. Remote sensing has been a widely used approach for mapping rubber plantations, typically using optical remote sensing data obtained at the regional scale. Improving the efficiency and accuracy of rubber plantation maps has become a research hotspot in rubber-related literature. To improve the classification efficiency, researchers have combined the phenology, geography, and texture of rubber trees with spectral information. Among these, there are three main classifiers: maximum likelihood, QUEST decision tree, and random forest methods. However, until now, no comparative studies have been conducted for the above three classifiers. Therefore, in this study, we evaluated the mapping accuracy based on these three classifiers, using four kinds of data input: Landsat spectral information, phenology\u2013Landsat spectral information, topography\u2013Landsat spectral information, and phenology\u2013topography\u2013Landsat spectral information. We found that the random forest method had the highest mapping accuracy when compared with the maximum likelihood and QUEST decision tree methods. We also found that adding either phenology or topography could improve the mapping accuracy for rubber plantations. When either phenology or topography were added as parameters within the random forest method, the kappa coefficient increased by 5.5% and 6.2%, respectively, compared to the kappa coefficient for the baseline Landsat spectral band data input. The highest accuracy was obtained from the addition of both phenology\u2013topography\u2013Landsat spectral bands to the random forest method, achieving a kappa coefficient of 97%. We therefore mapped rubber plantations in Xishuangbanna using the random forest method, with the addition of phenology and topography information from 1990\u20132020. Our results demonstrated the usefulness of integrating phenology and topography for mapping rubber plantations. The machine learning approach showed great potential for accurate regional mapping, particularly by incorporating plant habitat and ecological information. We found that during 1990\u20132020, the total area of rubber plantations had expanded to over three times their former area, while natural forests had lost 17.2% of their former area.<\/jats:p>","DOI":"10.3390\/rs13142793","type":"journal-article","created":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T10:52:58Z","timestamp":1626432778000},"page":"2793","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Integrating Phenological and Geographical Information with Artificial Intelligence Algorithm to Map Rubber Plantations in Xishuangbanna"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7605-4185","authenticated-orcid":false,"given":"Jianbo","family":"Yang","sequence":"first","affiliation":[{"name":"Centre for Mountain Futures (CMF), Kunming Institute of Botany, Kunming 650201, China"},{"name":"Key Laboratory for Economic Plants and Biotechnology, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2485-2254","authenticated-orcid":false,"given":"Jianchu","family":"Xu","sequence":"additional","affiliation":[{"name":"Centre for Mountain Futures (CMF), Kunming Institute of Botany, Kunming 650201, China"},{"name":"Key Laboratory for Economic Plants and Biotechnology, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China"},{"name":"East and Central Asia Regional Office, World Agroforestry (ICRAF), Kunming 650201, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5957-2482","authenticated-orcid":false,"given":"De-Li","family":"Zhai","sequence":"additional","affiliation":[{"name":"Centre for Mountain Futures (CMF), Kunming Institute of Botany, Kunming 650201, China"},{"name":"Key Laboratory for Economic Plants and Biotechnology, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.apgeog.2011.06.018","article-title":"Mapping rubber tree growth in mainland Southeast Asia using time-series MODIS 250 m NDVI and statistical data","volume":"32","author":"Li","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_2","unstructured":"Bowers, J.E. (1990). Natural Rubber-Producing Plants for the United States, National Agricultural Library."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1111\/conl.12170","article-title":"Increasing Demand for Natural Rubber Necessitates a Robust Sustainability Initiative to Mitigate Impacts on Tropical Biodiversity","volume":"8","author":"Dolman","year":"2015","journal-title":"Conserv. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Warren-Thomas, E.M., Edwards, D.P., Bebber, D.P., Chhang, P., Diment, A.N., Evans, T.D., Lambrick, F.H., Maxwell, J.F., Nut, M., and O\u2019Kelly, H.J. (2018). Protecting tropical forests from the rapid expansion of rubber using carbon payments. Nat. Commun., 9.","DOI":"10.1038\/s41467-018-03287-9"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1016\/j.indcrop.2012.09.005","article-title":"Breeding Hevea brasiliensis for yield, growth and SALB resistance for high disease environments","volume":"44","author":"Rivano","year":"2013","journal-title":"Ind. Crop. Prod."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chen, H., Yi, Z.F., Schmidt-Vogt, D., Ahrends, A., Becksch\u00e4fer, P., Kleinn, C., Ranjitkar, S., and Xu, J. (2016). Pushing the Limits: The Pattern and Dynamics of Rubber Monoculture Expansion in Xishuangbanna, SW China. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0150062"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1016\/j.ecolind.2013.03.016","article-title":"Developing indicators of economic value and biodiversity loss for rubber plantations in Xishuangbanna, southwest China: A case study from Menglun township","volume":"36","author":"Yi","year":"2013","journal-title":"Ecol. Indic."},{"key":"ref_8","first-page":"1","article-title":"Observation-based implementation of ecophysiological processes for a rubber plant functional type in the community land model (CLM4.5-rubber_v1)","volume":"2018","author":"Ali","year":"2018","journal-title":"Geosci. Model Dev. Discuss."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1016\/j.rse.2007.07.004","article-title":"Landsat continuity: Issues and opportunities for land cover monitoring","volume":"112","author":"Wulder","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2014.02.001","article-title":"Landsat-8: Science and product vision for terrestrial global change research","volume":"145","author":"Roy","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-Resolution Global Maps of 21st-Century Forest Cover Change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.rse.2013.03.014","article-title":"Mapping deciduous rubber plantations through integration of PALSAR and multi-temporal Landsat imagery","volume":"134","author":"Dong","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Azizan, F.A., Kiloes, A.M., Astuti, I.S., and Abdul Aziz, A. (2021). Application of Optical Remote Sensing in Rubber Plantations: A Systematic Review. Remote Sens., 13.","DOI":"10.3390\/rs13030429"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1048","DOI":"10.3390\/rs70101048","article-title":"Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images","volume":"7","author":"Kou","year":"2015","journal-title":"Remote Sens."},{"key":"ref_15","first-page":"1769","article-title":"Rubber Plantations in Xishuangbanna: Remote Sensing Identification and Digital Mapping","volume":"34","author":"Liu","year":"2012","journal-title":"Resour. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.isprsjprs.2012.07.004","article-title":"Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery","volume":"74","author":"Dong","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2795","DOI":"10.3390\/rs5062795","article-title":"Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China) Using Multi-Spectral Phenological Metrics from MODIS Time Series","volume":"5","author":"Senf","year":"2013","journal-title":"Remote Sens."},{"key":"ref_18","first-page":"117","article-title":"Mapping tropical forests and deciduous rubber plantations in Hainan Island, China by integrating PALSAR 25-m and multi-temporal Landsat images","volume":"50","author":"Chen","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1080\/2150704X.2014.996678","article-title":"Mapping rubber tree plantations using a Landsat-based phenological algorithm in Xishuangbanna, southwest China","volume":"6","author":"Li","year":"2015","journal-title":"Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhai, D., Dong, J., Cadisch, G., Wang, M., Kou, W., Xu, J., Xiao, X., and Abbas, S. (2018). Comparison of Pixel- and Object-Based Approaches in Phenology-Based Rubber Plantation Mapping in Fragmented Landscapes. Remote Sens., 10.","DOI":"10.3390\/rs10010044"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Xiao, C., Li, P., Feng, Z., Lin, Y., You, Z., and Yang, Y. (2019). Mapping rubber plantations in Xishuangbanna, southwest China based on the re-normalization of two Landsat-based vegetation-moisture indices and meteorological data. Geocarto Int., 1\u201315.","DOI":"10.1080\/10106049.2019.1687592"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.asr.2019.09.022","article-title":"Is the phenology-based algorithm for mapping deciduous rubber plantations applicable in an emerging region of northern Laos?","volume":"65","author":"Xiao","year":"2020","journal-title":"Adv. Space Res."},{"key":"ref_23","first-page":"30","article-title":"Monitoring annual dynamics of mature rubber plantations in Xishuangbanna during 1987-2018 using Landsat time series data: A multiple normalization approach","volume":"77","author":"Xiao","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1007\/s11442-013-1060-4","article-title":"Rubber plantation and its relationship with topographical factors in the border region of China, Laos and Myanmar","volume":"23","author":"Liu","year":"2013","journal-title":"J. Geogr. Sci."},{"key":"ref_25","first-page":"163","article-title":"Application of decision tree classification to rubber plantations extraction with remote sensing","volume":"29","author":"Liu","year":"2013","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gao, S., Liu, X., Bo, Y., Shi, Z., and Zhou, H. (2019). Rubber Identification Based on Blended High Spatio-Temporal Resolution Optical Remote Sensing Data: A Case Study in Xishuangbanna. Remote Sens., 11.","DOI":"10.3390\/rs11050496"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1111\/j.1744-7429.2006.00147.x","article-title":"Geological history, flora, and vegetation of Xishuangbanna, southern Yunnan, China","volume":"38","author":"Zhu","year":"2006","journal-title":"Biotropica"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.indcrop.2014.08.001","article-title":"Greater diurnal temperature difference, an overlooked but important climatic driver of rubber yield","volume":"62","author":"Yu","year":"2014","journal-title":"Ind. Crop. Prod."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1111\/j.1744-7429.2006.00146.x","article-title":"Tropical forests of Xishuangbanna, China","volume":"38","author":"Cao","year":"2006","journal-title":"Biotropica"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/0006-3207(94)00118-A","article-title":"Tropical forest vegetation of Xishuangbanna, SW China and its secondary changes, with special reference to some problems in local nature conservation","volume":"73","author":"Zhang","year":"1995","journal-title":"Biol. Conserv."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s00484-017-1448-4","article-title":"Responses of rubber leaf phenology to climatic variations in Southwest China","volume":"63","author":"Zhai","year":"2019","journal-title":"Int. J. Biometeorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1007\/s00484-018-1598-z","article-title":"Evaluation of key meteorological determinants of wintering and flowering patterns of five rubber clones in Xishuangbanna, Yunnan, China","volume":"63","author":"Liyanage","year":"2019","journal-title":"Int. J. Biometeorol."},{"key":"ref_33","unstructured":"Rouse, J.W., Haas, R.W., Schell, J.A., Deering, D.W., and Harlan, J.C. (1974). Monitoring the Vernal Advancement and Retrogradation (Greenwave Effect) of Natural Vegetation, Type III Final Report., Texas A & M University, Remote Sensing Center."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.rse.2003.11.008","article-title":"Satellite-based modeling of gross primary production in an evergreen needleleaf forest","volume":"89","author":"Xiao","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1713","DOI":"10.1007\/s10113-019-01509-4","article-title":"After the rubber boom: Good news and bad news for biodiversity in Xishuangbanna, Yunnan, China","volume":"19","author":"Zhang","year":"2019","journal-title":"Reg. Environ. Chang."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.1007\/s10531-006-9052-7","article-title":"Demand for rubber is causing the loss of high diversity rain forest in SW China","volume":"16","author":"Li","year":"2007","journal-title":"Biodivers. Conserv."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2018.02.026","article-title":"A comparison of resampling methods for remote sensing classification and accuracy assessment","volume":"208","author":"Lyons","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ding, H., Na, J., Jiang, S., Zhu, J., Liu, K., Fu, Y., and Li, F. (2021). Evaluation of Three Different Machine Learning Methods for Object-Based Artificial Terrace Mapping\u2014A Case Study of the Loess Plateau, China. Remote Sens., 13.","DOI":"10.3390\/rs13051021"},{"key":"ref_40","first-page":"40","article-title":"An updated delineation of stand ages of deciduous rubber plantations during 1987-2018 using Landsat-derived bi-temporal thresholds method in an antichronological strategy","volume":"76","author":"Xiao","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.gloenvcha.2015.06.002","article-title":"Current trends of rubber plantation expansion may threaten biodiversity and livelihoods","volume":"34","author":"Ahrends","year":"2015","journal-title":"Glob. Environ. Chang."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.landusepol.2013.12.013","article-title":"Can carbon-trading schemes help to protect China\u2019s most diverse forest ecosystems? A case study from Xishuangbanna, Yunnan","volume":"38","author":"Yi","year":"2014","journal-title":"Land Use Pol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.jenvman.2011.10.011","article-title":"Rubber and pulp plantations represent a double threat to Hainan\u2019s natural tropical forests","volume":"96","author":"Zhai","year":"2012","journal-title":"J. Environ. Manag."},{"key":"ref_44","first-page":"273","article-title":"Leaf shedding as an adaptive strategy for water deficit: A case study in Xishuangbannas rainforest","volume":"36","author":"Tan","year":"2014","journal-title":"J. Yunnan Univ. Nat. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2005.05.008","article-title":"Decision tree regression for soft classification of remote sensing data","volume":"97","author":"Xu","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"9184","DOI":"10.3390\/rs70709184","article-title":"Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches","volume":"7","author":"Han","year":"2015","journal-title":"Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1007\/s11063-020-10280-1","article-title":"A Novel Technique for Segmentation of High Resolution Remote Sensing Images Based on Neural Networks","volume":"52","author":"Barr","year":"2020","journal-title":"Neural. Process. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Mariana","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2011.11.002","article-title":"An assessment of the effectiveness of a random forest classifier for land-cover classification","volume":"67","author":"Ghimire","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"111702","DOI":"10.1016\/j.rse.2020.111702","article-title":"A remote sensing approach to mapping fire severity in south-eastern Australia using sentinel 2 and random forest","volume":"240","author":"Gibson","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1016\/j.rse.2005.10.014","article-title":"Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (randomForest)","volume":"100","author":"Lawrence","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.rse.2017.04.003","article-title":"Obtaining rubber plantation age information from very dense Landsat TM & ETM+ time series data and pixel-based image compositing","volume":"196","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_53","first-page":"475","article-title":"Asymmetric response of farmers\u2019 production adjustment to the expected price volatility: Evidence from smallholder rubber farmers in Xishuangbanna","volume":"38","author":"Min","year":"2017","journal-title":"Res. Agric. Mod."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"687","DOI":"10.14358\/PERS.85.9.687","article-title":"How Did Deciduous Rubber Plantations Expand Spatially in China\u2019s Xishuangbanna Dai Autonomous Prefecture During 1991-2016?","volume":"85","author":"Xiao","year":"2019","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_55","first-page":"320","article-title":"Forecasting of Natural Rubber Production Capacity in China (2019-2025)","volume":"40","author":"He","year":"2020","journal-title":"Issues For. Econ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.forpol.2017.11.009","article-title":"Willingness of smallholder rubber farmers to participate in ecosystem protection: Effects of household wealth and environmental awareness","volume":"87","author":"Min","year":"2018","journal-title":"For. Policy Econ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1475","DOI":"10.1016\/j.scitotenv.2016.12.126","article-title":"Scaling green rubber cultivation in Southwest China\u2014An integrative analysis of stakeholder perspectives","volume":"580","author":"Wigboldus","year":"2017","journal-title":"Sci. Total Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2793\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:30:45Z","timestamp":1760164245000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2793"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,16]]},"references-count":57,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13142793"],"URL":"https:\/\/doi.org\/10.3390\/rs13142793","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,16]]}}}