{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T00:25:04Z","timestamp":1791937504389,"version":"4.3.4"},"reference-count":78,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,21]],"date-time":"2021-12-21T00:00:00Z","timestamp":1640044800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (&gt;7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6\/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer\u2019s accuracy for all classes was higher than 90%, except for rubber (65%), and user\u2019s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia\u2019s national forest monitoring system and inform monitoring of plantation expansion.<\/jats:p>","DOI":"10.3390\/rs14010003","type":"journal-article","created":{"date-parts":[[2021,12,21]],"date-time":"2021-12-21T09:50:43Z","timestamp":1640080243000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia"],"prefix":"10.3390","volume":"14","author":[{"given":"Inggit Lolita","family":"Sari","sequence":"first","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, Australia"},{"name":"Technology Center and Remote Sensing Data, National Institute of Aeronautics and Space of Indonesia\u2013National Research and Innovation Agency (LAPAN\u2013BRIN), Jakarta 13710, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4675-0486","authenticated-orcid":false,"given":"Christopher J.","family":"Weston","sequence":"additional","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6913-1258","authenticated-orcid":false,"given":"Glenn J.","family":"Newnham","sequence":"additional","affiliation":[{"name":"CSIRO Land and Water, Private Bag 10, Clayton South, VIC 3169, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4556-3478","authenticated-orcid":false,"given":"Liubov","family":"Volkova","sequence":"additional","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,21]]},"reference":[{"key":"ref_1","unstructured":"FAO (2021, June 06). FAOSTAT. Available online: http:\/\/www.fao.org\/faostat\/en\/#data."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1088\/1748-9326\/aaf6db","article-title":"What causes deforestation in Indonesia?","volume":"14","author":"Austin","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"53","DOI":"10.3389\/ffgc.2020.00053","article-title":"Impacts of four decades of forest loss on vertebrate functional habitat on Borneo","volume":"3","author":"Kornecki","year":"2020","journal-title":"Front. For. Glob. Chang."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7559","DOI":"10.1073\/pnas.1200452109","article-title":"Committed carbon emissions, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia","volume":"109","author":"Carlson","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","unstructured":"Ustin, S.L. (2004). Remote Sensing for Natural Resource Management and Environmental Monitoring, John Wiley."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"eabe1603","DOI":"10.1126\/sciadv.abe1603","article-title":"Long-term (1990\u20132019) monitoring of forest cover changes in the humid tropics","volume":"7","author":"Vancutsem","year":"2021","journal-title":"Sci. Adv."},{"key":"ref_7","unstructured":"Achard, F., and Hansen, M.C. (2013). Long-term monitoring of Australian land cover change using Landsat data: Development, implementation, and operation. Global Forest Monitoring from Earth Observation, Taylor & Francis."},{"key":"ref_8","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_9","doi-asserted-by":"crossref","first-page":"7","DOI":"10.22146\/ijg.12496","article-title":"Indonesia\u2019s forest resource monitoring","volume":"48","author":"Margono","year":"2016","journal-title":"Indones. J. Geogr."},{"key":"ref_10","unstructured":"LAPAN (2019, January 04). The Remote Sensing Monitoring Program of Indonesia\u2019s National Carbon Accounting System: Methodology and Products, Version 1, Available online: http:\/\/incas.menlhk.go.id\/methodology\/incas-standard-method-forest-cover-change\/."},{"key":"ref_11","unstructured":"Directorate General of Climate Change, Ministry of Environment and Forestry (2020, April 26). National Forest Reference Emission Level for Deforestation and Forest Degradation: In the Context of Decision 1\/CP.16 Para 70 UNFCCC (Encourages Developing Country Parties to Contribute to Mitigation Actions in the Forest Sector), Available online: https:\/\/redd.unfccc.int\/files\/frel_submission_by__indonesia_final.pdf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1126\/science.1248753","article-title":"Comment on \u201cHigh-resolution global maps of 21st-century forest cover change\u201d","volume":"344","author":"Tropek","year":"2014","journal-title":"Science"},{"key":"ref_13","first-page":"441","article-title":"Annual forest monitoring as part of the Indonesia\u2019s National Carbon Accounting System. Int. Arch. Photogramm","volume":"40\u201347","author":"Kustiyo","year":"2015","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Torbick, N., Ledoux, L., Salas, W., and Zhao, M. (2016). Regional mapping of plantation extent using multisensor imagery. Remote Sens., 8.","DOI":"10.3390\/rs8030236"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3855","DOI":"10.1080\/01431160010006926","article-title":"Cloud cover in Landsat observations of the Brazilian Amazon","volume":"22","author":"Asner","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","unstructured":"Ministry of Environment and Forestry, Republic of Indonesia (2019, May 14). The State of Indonesia\u2019s Forests 2018, Available online: https:\/\/www.menlhk.go.id\/site\/download?start=10."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1080\/17538947.2020.1729878","article-title":"Producing consistent visually interpreted land cover reference data: Learning from feedback","volume":"14","author":"Tarko","year":"2021","journal-title":"Int. J. Digit. Earth"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.envsci.2007.01.010","article-title":"Earth observations for esti-mating greenhouse gas emissions from deforestation in developing countries","volume":"10","author":"DeFries","year":"2007","journal-title":"Environ. Sci. Policy"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1080\/01431168508948447","article-title":"Radar backscattering of forest stands","volume":"6","author":"Hoekman","year":"1985","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","first-page":"183","article-title":"Assessment of ALOS-2 PALSAR-2 L-band and Sentinel-1 C-band SAR backscatter for discriminating between large-scale oil palm plantations and smallholdings on tropical peatlands","volume":"13","author":"Oon","year":"2019","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.rse.2014.04.014","article-title":"New global forest\/non-forest maps from ALOS PALSAR data (2007\u20132010)","volume":"155","author":"Shimada","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.rse.2014.09.034","article-title":"SAR and optical remote sensing: Assessment of complementarity and interoperability in the context of a large-scale operational forest monitoring sys-tem","volume":"156","author":"Lehmann","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Miettinen, J., Liew, S.C., and Kwoh, L.K. (2015, January 24\u201328). In Usability of Sentinel-1 dual polarization C-band data for plantation detection in insular Southeast Asia. Proceedings of the 36th Asian Conference on Remote Sensing (ACRS2015), Quezon City, Philippines."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1080\/01431161.2010.520345","article-title":"Separability of Insular Southeast Asian woody plantation species in the 50 m resolution ALOS PALSAR mosaic product","volume":"2","author":"Miettinen","year":"2011","journal-title":"Remote Sens. Lett."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"063597","DOI":"10.1117\/1.JRS.6.063597","article-title":"Supervised machine learning of fused radar and optical data for land cover classification","volume":"6","author":"Guido","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.landusepol.2016.05.034","article-title":"History of forest loss and degradation in Indonesia","volume":"57","author":"Tsujino","year":"2016","journal-title":"Land Use Pol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"e12622","DOI":"10.1111\/conl.12622","article-title":"Rise and fall of forest loss and industrial plantations in Borneo (2000\u20132017)","volume":"12","author":"Gaveau","year":"2018","journal-title":"Conserv. Lett."},{"key":"ref_29","unstructured":"Directorate General of Estate Crops, Ministry of Agriculture (2020, May 23). Tree Crop Estate Statistics of Indonesia: Palm Oil 2017\u20132019, Available online: https:\/\/drive.google.com\/file\/d\/1rlmMNUbPM99DA-Ywo-Prv3cmPnWoFUUp\/view."},{"key":"ref_30","unstructured":"Directorate General of Estate Crops, Ministry of Agriculture (2020, May 23). Tree Crop Estate Statistics of Indonesia: Rubber 2017\u20132019, Available online: https:\/\/drive.google.com\/file\/d\/1hF-ilorfxR8Hx5wxroRWOBpKoNzOlLBL\/view."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sari, I.L., Weston, C.J., Newnham, G.J., and Volkova, L. (2021). Assessing accuracy of land cover change maps derived from automated digital processing and visual interpretation in tropical forests in Indonesia. Remote Sens., 13.","DOI":"10.3390\/rs13081446"},{"key":"ref_32","unstructured":"Penman, J., Gytarsky, M., Hiraishi, T., Krug, T., Kruger, D., Pipatti, R., Buendia, L., Miwa, K., Ngara, T., and Tanabe, K. (2021, January 09). Good Practice Guidance for Land Use, Land-Use Change and Forestry, Available online: https:\/\/www.ipcc.ch\/site\/assets\/uploads\/2018\/03\/GPG_LULUCF_FULLEN.pdf."},{"key":"ref_33","unstructured":"Division of Integrated Data Processing Integration and Statistical Disemination, BPS-Statistics of Kalimantan Tengah Province (2020, May 23). Provinsi Kalimantan Tengah Dalam Angka 2018 (Kalimantan Tengah Province in Figures 2018), Available online: https:\/\/kalteng.bps.go.id\/publication\/2018\/08\/16\/ceed046d35684aefde786f04\/provinsi-kalimantan-tengah-dalam-angka-2018.html."},{"key":"ref_34","unstructured":"Division of Integrated Data Processing Integration and Statistical Disemination, BPS-Statistics of Kalimantan Timur Province (2020, May 23). Provinsi Kalimantan Timur Dalam Angka 2018 (Kalimantan Timur Province in Figures 2018), Available online: https:\/\/kaltim.bps.go.id\/publication\/2018\/08\/16\/9341dae4a1306ccfee98a393\/provinsi-kalimantan-timur-dalam-angka-2018.html."},{"key":"ref_35","unstructured":"Division of Integrated Data Processing Integration and Statistical Disemination, BPS-Statistics of Kalimantan Selatan Province (2020, May 23). Provinsi Kalimantan Selatan Dalam Angka 2018 (Kalimantan Selatan Province in Figures 2018), Available online: https:\/\/kalsel.bps.go.id\/publication\/2018\/08\/16\/f646d3011e4c3dfb0a4cbd74\/provinsi-kalimantan-selatan-dalam-angka-2018.html."},{"key":"ref_36","unstructured":"Sidiyasa, K. (,  2001). Tree diversity in the rain forest of Kalimantan. Proceedings of the Balance between Biodiversity Conservation and Sus-Tainable Use of Tropical Rain Forest, Wageningen, The Netherlands. Available online: https:\/\/www.tropenbos.org\/resources\/publications\/tree+diversity+in+the+rain+forest+of+kalimantan."},{"key":"ref_37","unstructured":"Mackinnon, K., Hatta, G., Halim, H., and Mangalik, A. (1996). The Ecology of Kalimantan, Periplus Editions (HK) Ltd."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.20886\/jped.2012.6.1.1-10","article-title":"Ekplorasi jenis-jenis Dipterokarpa di Kabupaten Paser, Kalimantan Timur (Exploration of Dipter-ocarps species in Paser Regency, East Kalimantan)","volume":"6","author":"Ngatiman","year":"2012","journal-title":"J. Penelit. Ekosist. Dipterokarpa"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Corley, R.H.V., and Tinker, P.B. (2016). The Oil Palm, Wiley-Blackwell.","DOI":"10.1002\/9781118953297"},{"key":"ref_40","unstructured":"Phuc, T.X., and Nghi, T.H. (2014). Rubber Expansion and Forest Protection in Vietnam, Tropenbos International Viet Nam. Available online: https:\/\/www.tropenbos.org\/resources\/publications\/rubber+expansion+and+forest+protection+in+vietnam."},{"key":"ref_41","unstructured":"World Agroforestry (2021, July 12). Agroforestree Database. Available online: http:\/\/apps.worldagroforestry.org\/treedb\/AFTPDFS\/Hevea_brasiliensis.PDF."},{"key":"ref_42","unstructured":"Setyawati, T., Narulita, S., Bahri, I.P., and Raharjo, G.T. (2015). A Guide Book to Invasive Plant Species in Indonesia, Research, Development and Innovation Agency, Ministry of Environment and Forestry Republic of Indonesia. Available online: http:\/\/ksdae.menlhk.go.id\/assets\/publikasi\/A_Guide_Book_of_Invasive_Plant_Species_in_Indonesia.pdf."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Osaki, M., and Tsuji, N. (2016). Ethnic plant resources in Central Kalimantan. Tropical Peatland Ecosystems, Springer.","DOI":"10.1007\/978-4-431-55681-7"},{"key":"ref_44","unstructured":"Barker, P.C.J. (2001). A Technical Manual for Vegetation Monitoring\/Phil Barker."},{"key":"ref_45","unstructured":"Mueller-Dombois, D., Bridges, K.W., and Deahler, C. (2008). Biodiversity Assessment of Tropical Island Ecosystems, PABITRA Manual for Interactive Ecology and Management, Bishop Museum Press."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Schomaker, M.E., Zarnoch, S.J., Bechtold, W.A., Latelle, D.J., Burkman, W.G., and Cox, S.M. (2007). Crown-Condition Classification: A Guide to Data Collection and Analysis, General Technical Report SRS-102.","DOI":"10.2737\/SRS-GTR-102"},{"key":"ref_47","unstructured":"Kvamme, C.D. (2010). A Comparison of Ground Cover and Frequency Estimation Methods for Post-Harvest Soil Monitoring. [Master\u2019s Thesis, Michigan Technological University]. Available online: https:\/\/digitalcommons.mtu.edu\/cgi\/viewcontent.cgi?article=1142&context=etds."},{"key":"ref_48","unstructured":"Hagl\u00f6f, A.B. (2002). Users Guide Vertex III and Transponder T3, Hagl\u00f6f Sweden, AB."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/S0034-4257(97)00049-7","article-title":"Decision Tree classification of land cover from remotely sensed data","volume":"61","author":"Friedl","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.3390\/rs70201206","article-title":"Mapping oil palm plantations in Cameroon using PALSAR 50-m orthorectified mosaic images","volume":"7","author":"Li","year":"2015","journal-title":"Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2310","DOI":"10.1109\/36.868888","article-title":"The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest","volume":"38","author":"Simard","year":"2000","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, C., Huang, C., Li, H., Liu, Q., Li, J., Bridhikitti, A., and Liu, G. (2020). Effect of textural features in remote sensed data on rubber plantation extraction at different levels of spatial resolution. Forests, 11.","DOI":"10.3390\/f11040399"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Kuffer, M., Sliuzas, R., Pfeffer, K., and Baud, I. (April, January 30). The utility of the co-occurrence matrix to extract slum areas from VHR imagery. Proceedings of the 2015 Joint Urban Remote Sensing Event (JURSE), Lausanne, Switzerland.","DOI":"10.1109\/JURSE.2015.7120514"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1109\/TGRS.1995.8746010","article-title":"An investigation of the textural characteristics associated with Gray Level Cooccurrence Matrix statistical parameters","volume":"33","author":"Baraldi","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_56","unstructured":"Jensen, J.R. (2005). Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice Hall. [3rd ed.]."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3172","DOI":"10.21105\/joss.03172","article-title":"Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS","volume":"6","author":"Congedo","year":"2021","journal-title":"J. Open Source Softw."},{"key":"ref_58","first-page":"627","article-title":"Mapping rubber trees based on phenological analysis of Landsat time series data-sets","volume":"33","author":"Razak","year":"2018","journal-title":"Geocarto Int."},{"key":"ref_59","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"},{"key":"ref_60","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 pix-el-based image compositing","volume":"196","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_61","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_62","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2014.02.015","article-title":"Good practices for estimating area and assessing accuracy of land change","volume":"148","author":"Olofsson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Anderson, J.R. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data.","DOI":"10.3133\/pp964"},{"key":"ref_64","unstructured":"Karsidi, A., and Geospatial Information Agency of Indonesia (2021, July 12). Peraturan Kepala Badan Informasi Geospasial Nomor 15 Tahun 2014 Ten-Tang Pedoman Teknis Ketelitian Peta Dasar (Head of Geospatial Information Agency: Technical Guidelines to Determine the Accuracy of the Base Map Number 15 Year 2014), Available online: https:\/\/jdih.big.go.id\/media\/resources\/files\/law\/tUF25Yj2xW_Perka_Ketelitian_Peta_Dasar_-_Salinan.pdf."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"3219","DOI":"10.1080\/01431169608949140","article-title":"Evaluation of JERS-1, ERS-1 and Almaz SAR backscatter for rubber and oil palm stands in West Malaysia","volume":"17","author":"Rosenqvist","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","unstructured":"CEOS\u2013Committee on Earth Observation Satellites (2021, June 11). A Layman\u2019s Interpretation to L-Band and C-Band Synthetic Aperture Radar Data. Available online: https:\/\/ceos.org\/document_management\/SEO\/DataCube\/Laymans_SAR_Interpretation_Guide_2.0.pdf."},{"key":"ref_67","first-page":"605","article-title":"PALSAR wide-area mapping of Borneo: Methodology and map validation. IEEE J. Sel. Top. Appl. Earth Observ","volume":"3","author":"Hoekman","year":"2010","journal-title":"Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.jag.2018.10.020","article-title":"An updated delineation of stand ages of deciduous rubber plantations during 1987\u20132018 using Landsat-derived bi-temporal thresholds method in an anti-chronological strategy","volume":"76","author":"Xiao","year":"2019","journal-title":"Int. J. Appl. Earth Obs.-Vation Geoinf."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices over a global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.rse.2015.03.001","article-title":"Cross-border forest disturbance and the role of natural rubber in mainland Southeast Asia using annual Landsat time series","volume":"169","author":"Grogan","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_71","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 Xishuang-banna, Southwest China","volume":"6","author":"Li","year":"2015","journal-title":"Remote Sens. Lett."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1080\/14735903.2014.986321","article-title":"The assessment of the impact of oil palm and rubber plantations on the biotic and abiotic properties of tropical peat swamp soil in Indonesia","volume":"13","author":"Nurulita","year":"2015","journal-title":"Int. J. Agric. Sustain."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"2163","DOI":"10.1080\/01431160050029495","article-title":"Mapping montane tropical forest successional stage and land use with multi-date Landsat imagery","volume":"21","author":"Helmer","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_75","first-page":"134","article-title":"Remote sensing research priorities in tropical dry forest en-vironments","volume":"35","author":"Castro","year":"2003","journal-title":"Biotropica"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"026011","DOI":"10.1117\/1.JRS.11.026011","article-title":"Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method","volume":"11","author":"Zhongchang","year":"2017","journal-title":"J. Appl. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"4075","DOI":"10.1080\/01431161.2011.640961","article-title":"Multi-temporal land-cover classification and change analysis with conditional probability networks: The case of Lesvos Island (Greece)","volume":"33","author":"Symeonakis","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"4973","DOI":"10.3390\/rs70504973","article-title":"A Bayesian approach to combine Landsat and ALOS PALSAR time series for Near Real-Time deforestation detection","volume":"7","author":"Reiche","year":"2015","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/3\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:50:19Z","timestamp":1760169019000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,21]]},"references-count":78,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010003"],"URL":"https:\/\/doi.org\/10.3390\/rs14010003","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,21]]}}}