Using Bayesian multitemporal classification to monitor tropical forest cover changes in Kalimantan, Indonesia

References

• Achard, Frédéric, and Matthew C Hansen. 2012. Global Forest Monitoring from Earth Observation. Boca Raton, FL: Taylor & Francis.
   Google Scholar
• Ahmed, Ahmed Abdulkareem, Biswajeet Pradhan, Maher Ibrahim Sameen, and Ali Muayad Makky. 2018. “An Optimized Object-Based Analysis for Vegetation Mapping Using Integration of Quickbird and Sentinel-1 Data.” Arabian Journal of Geosciences 11 (11): 280. doi:10.1007/s12517-018-3632-1.
   Web of Science ®Google Scholar
• Altunel, Arif Oguz, Emre Akturk, and Tayyibe Altunel. 2020. “Examining the PALSAR-2 Global Forest/non-Forest Maps Through Turkish Afforestation Practices.” International Journal of Remote Sensing 41 (16): 6071–6088. doi:10.1080/01431161.2020.1760397.
   Web of Science ®Google Scholar
• ASF. 2019. “Sentinel-1.” Accessed 3 July 2019. https://search.asf.alaska.edu/#/.
   Google Scholar
• Austin, K. G., A. Mosnier, J. Pirker, I. McCallum, S. Fritz, and P. S. Kasibhatla. 2017. “Shifting Patterns of oil Palm Driven Deforestation in Indonesia and Implications for Zero-Deforestation Commitments.” Land Use Policy 69: 41–48. doi:10.1016/j.landusepol.2017.08.036.
   Web of Science ®Google Scholar
• Badan Informasi Geospasial. 2014. Peraturan Kepala Badan Informasi Geospasial Nomor 15 Tahun 2014 Tentang Pedoman Teknis Ketelitian Peta Dasar (Head of Geospatial Information Agency: Technical Guidelines to Determine the Accuracy of the Base Map Number 15 Year 2014). Cibinong, Indonesia. Accessed 12 July 2021. https://jdih.big.go.id/media/resources/files/law/tUF25Yj2xW_Perka_Ketelitian_Peta_Dasar_-_Salinan.pdf.
   Google Scholar
• Badan Pusat Statistik. 2010b. Kabupaten Tabalong Dalam Angka 2010 (Tabalong Regency In Figures 2010). Tanjung: BPS-Statistics of Tabalong Regency. Accessed 14 February 2022. https://tabalongkab.bps.go.id/publication/2010/12/06/c58b044270e5e00272057388/kabupaten-tabalong-dalam-angka-tahun-2010.html.
   Google Scholar
• Badan Pusat Statistik. 2010a. Kabupaten Balangan Dalam Angka 2010 (Balangan Regency In Figures 2010). Paringin: BPS-Statistics of Balangan Regency. Accessed 11 February 2022. https://balangankab.bps.go.id/publication/2017/08/04/337024047f1f89cc57cffe57/kabupaten-balangan-dalam-angka-2010.html
   Google Scholar
• Badan Pusat Statistik. 2010c. Provinsi Kalimantan Tengah Dalam Angka 2010 (Kalimantan Tengah Province In Figures 2010). Palangka Raya: BPS-Statistics of Kalimantan Tengah Province. Accessed 14 February 2022. https://kalteng.bps.go.id/publication/2011/03/08/87bd80e03b750dcfd5ba9ed9/provinsi-kalimantan-tengah-dalam-angka-2010.html.
   Google Scholar
• Badan Pusat Statistik. 2010d. Provinsi Kalimantan Timur Dalam Angka 2010 (Kalimantan Timur Province In Figures 2010). Samarinda: BPS-Statistics of Kalimantan Timur Province. Accessed 14 February 2022. https://kaltim.bps.go.id/publication/2010/11/15/72791ce3392060467b266036/kalimantan-timur-dalam-angka-2010.html
   Google Scholar
• Badan Pusat Statistik. 2019a. Provinsi Kalimantan Selatan Dalam Angka 2019 (Kalimantan Selatan Province In Figures 2019). Banjarbaru: BPS-Statistics of Kalimantan Selatan Province. Accessed 14 February 2022. https://kalsel.bps.go.id/publication/2019/08/16/903c009fdaf5616cd7982d8a/provinsi-kalimantan-selatan-dalam-angka-2019.html
   Google Scholar
• Badan Pusat Statistik. 2019b. Provinsi Kalimantan Tengah Dalam Angka 2019 (Kalimantan Tengah Province In Figures 2019). Palangka Raya: BPS-Statistics of Kalimantan Tengah Province. Accessed 14 February 2022. https://kalteng.bps.go.id/publication/2019/08/16/265deb0d37728f33459e1303/provinsi-kalimantan-tengah-dalam-angka-2019.html.
   Google Scholar
• Badan Pusat Statistik. 2019c. Provinsi Kalimantan Timur Dalam Angka 2019 (Kalimantan Timur Province In Figures 2019). Samarinda: BPS-Statistics of Kalimantan Timur Province. Accessed 11 February 2022. https://kaltim.bps.go.id/publication/2019/08/16/a9deb9809e0b2606ce96573f/provinsi-kalimantan-timur-dalam-angka-2019.html.
   Google Scholar
• Badan Standardisasi Nasional. 2010. Klasifikasi Penutup Lahan SNI 7645:2010 (Indonesian National Standard on Land Cover Classification SNI 7645:2010). Jakarta: Badan Standardisasi Nasional. Accessed 25 January 2022. https://www.big.go.id/assets/download/sni/SNI/15.%20SNI%207645-2010%20Klasifikasi%20penutup%20lahan.pdf.
   Google Scholar
• Ban, Yifang. 2003. “Synergy of Multitemporal ERS-1 SAR and Landsat TM Data for Classification of Agricultural Crops.” Canadian Journal of Remote Sensing 29 (4): 518–526. doi:10.5589/m03-014.
   Web of Science ®Google Scholar
• Bannari, Abdou, Daniel Morin, F. Bonn, and AjRsr Huete. 1995. “A Review of Vegetation Indices.” Remote Sensing Reviews 13 (1-2): 95–120. doi:10.1080/02757259509532298.
   Google Scholar
• Blaes, Xavier, Laurent Vanhalle, and Pierre Defourny. 2005. “Efficiency of Crop Identification Based on Optical and SAR Image Time Series.” Remote Sensing of Environment 96 (3): 352–365. doi:10.1016/j.rse.2005.03.010.
   Web of Science ®Google Scholar
• Caccetta, Peter, Suzanne Furby, Jeremy Wallace, Xiaoliang Wu, Gary Richards, and Robert Waterworth. 2016. “Long-Term Monitoring of Australian Land Cover Change Using Landsat Data: Development, Implementation, and Operation.” In In Global Forest Monitoring from Earth Observation, edited by Frédéric Achard and Matthew C. Hansen, 229–242. New York, NY: Taylor & Francis.
   Google Scholar
• CEOS. 2014. “Global Baseline Data Acquisition Strategy for the Global Forest Observations Initiative (GFOI).” Accessed 11 February 2022. https://ceos.org/document_management/Ad_Hoc_Teams/SDCG_for_GFOI/SDCG_Global-Baseline-Data-Acquisition-Strategy-Annex-B-2013-Implementation-Report_Apr2014.pdf.
   Google Scholar
• CEOS. 2018. “A Layman’s Interpretation to L-Band and C-Band Synthetic Aperture Radar Data.” Accessed on 11 June 2021. https://ceos.org/document_management/SEO/DataCube/Laymans_SAR_Interpretation_Guide_2.0.pdf.
   Google Scholar
• Chen, Zuoqi, Bailang Yu, Yuyu Zhou, Hongxing Liu, Chengshu Yang, Kaifang Shi, and Jianping Wu. 2019. “Mapping Global Urban Areas from 2000 to 2012 Using Time-Series Nighttime Light Data and MODIS Products.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 (4): 1143–1153. doi:10.1109/JSTARS.2019.2900457.
   Web of Science ®Google Scholar
• Cracknell, Arthur Phillip, Kasturi Devi Kanniah, Kian Pang Tan, and Lei Wang. 2013. “Evaluation of MODIS Gross Primary Productivity and Land Cover Products for the Humid Tropics Using oil Palm Trees in Peninsular Malaysia and Google Earth Imagery.” International Journal of Remote Sensing 34 (20): 7400–7423. doi:10.1080/01431161.2013.820367.
   Web of Science ®Google Scholar
• Curtis, Philip G, Christy M Slay, Nancy L Harris, Alexandra Tyukavina, and Matthew C Hansen. 2018. “Classifying Drivers of Global Forest Loss.” Science 361 (6407): 1108–1111. doi:10.1126/science.aau3445.
   PubMed Web of Science ®Google Scholar
• Decree of the Ministry of Environment and Forestry No. SK.282/MENLHK/SETJEN/PLA.1/6/2017 regarding the Forest Fire Areas in 2015 and 2016. Accessed 25 June 2022. http://ditjenppi.menlhk.go.id/reddplus/images/adminppi/permen/SK282tahun2017.pdf.
   Google Scholar
• Dong, Runmin, Weijia Li, Haohuan Fu, Lin Gan, Le Yu, Juepeng Zheng, and Maocai Xia. 2020. “Oil Palm Plantation Mapping from High-Resolution Remote Sensing Images Using Deep Learning.” International Journal of Remote Sensing 41 (5): 2022–2046. doi:10.1080/01431161.2019.1681604.
   Web of Science ®Google Scholar
• Dong, Xichao, Shaun Quegan, Uryu Yumiko, Cheng Hu, and Tao Zeng. 2015. “Feasibility Study of C- and L-Band SAR Time Series Data in Tracking Indonesian Plantation and Natural Forest Cover Changes.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (7): 3692–3699. doi:10.1109/JSTARS.2015.2400439.
   Web of Science ®Google Scholar
• Fagan, Matthew E, Do-Hyung Kim, Wesley Settle, Lexie Ferry, Justin Drew, Haven Carlson, Joshua Slaughter, et al. 2022. “The Expansion of Tree Plantations Across Tropical Biomes.” Nature Sustainability 5: 681–688. doi:10.1038/s41893-022-00904-w.
   Web of Science ®Google Scholar
• FAO. 2020a. “Global Forest Resources Assessment 2020.” Accessed 6 June 2021. https://www.fao.org/3/ca8753en/CA8753EN.pdf.
   Google Scholar
• FAO. 2020b. “Open Foris.” Accessed 28 March 2020. http://www.openforis.org/.
   Google Scholar
• FAO. 2021. “FAOSTAT.” Accessed 6 June 2021. http://www.fao.org/faostat/en/#data.
   Google Scholar
• Feintrenie, Laurene, Wan Kian Chong, and Patrice Levang. 2010. “Why do Farmers Prefer Oil Palm? Lessons Learnt from Bungo District, Indonesia.” Small-scale Forestry 9 (3): 379–396. doi:10.1007/s11842-010-9122-2.
   Web of Science ®Google Scholar
• Field, Robert D, Guido R van der Werf, Thierry Fanin, Eric J Fetzer, Ryan Fuller, Hiren Jethva, Robert Levy, et al. 2016. “Indonesian Fire Activity and Smoke Pollution in 2015 Show Persistent Nonlinear Sensitivity to El Niño-Induced Drought.” Proceedings of the National Academy of Sciences 113 (33): 9204–9209. doi:10.1073/pnas.1524888113.
   PubMed Web of Science ®Google Scholar
• Gao, Bo-Cai. 1996. “NDWI—A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space.” Remote Sensing of Environment 58 (3): 257–266. doi:10.1016/S0034-4257(96)00067-3.
   Web of Science ®Google Scholar
• Ghahramani, Zoubin. 2001. “AN INTRODUCTION TO HIDDEN MARKOV MODELS AND BAYESIAN NETWORKS.” International Journal of Pattern Recognition and Artificial Intelligence 15 (01): 9–42. doi:10.1142/S0218001401000836.
   Google Scholar
• Guoping, Jiang, and Mingkui Ren. 2018. “Cyclic Bayesian Network for Software Project Iterative Process.” In Proceedings of Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018), 413–417.
   Google Scholar
• Hansen, Matthew C, Peter V Potapov, Rebecca Moore, Matt Hancher, Svetlana Turubanova, Alexandra Tyukavina, David Thau, S. V. Stehman, S. Goetz, and T. R. Loveland. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (6160): 850–853. doi:10.1126/science.1244693.
   PubMed Web of Science ®Google Scholar
• Hawker, Laurence, Peter Uhe, Luntadila Paulo, Jeison Sosa, James Savage, Christopher Sampson, and Jeffrey Neal. 2022. “A 30 m Global map of Elevation with Forests and Buildings Removed.” Environmental Research Letters 17 (2): 024016.
   Web of Science ®Google Scholar
• Hoekman, Dirk H. 1985. “Radar Backscattering of Forest Stands.” International Journal of Remote Sensing 6 (2): 325–343. doi:10.1080/01431168508948447.
   Web of Science ®Google Scholar
• Indonesia LTS-LCCR 2050. 2021. “Indonesia Long-Term Strategy for Low Carbon and Climate Resilience 2050 (Indonesia LTS-LCCR 2050).” Accessed 25 June 2022. https://unfccc.int/sites/default/files/resource/Indonesia_LTS-LCCR_2021.pdf.
   Google Scholar
• JAXA. 2016. “Global 25 m Resolution PALSAR-2/PALSAR Mosaic and Forest/Non-Forest Map (FNF) Dataset Description.” Accessed 25 October 2021. https://www.eorc.jaxa.jp/ALOS/en/dataset/pdf/DatasetDescription_PALSAR_Mosaic_FNF_revO.pdf.
   Google Scholar
• JAXA. 2019. “ALOS PALSAR.” Accessed 3 July 2019. https://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/data/index.htm.
   Google Scholar
• Keenan, Rodney J, Gregory A Reams, Frédéric Achard, Joberto V de Freitas, Alan Grainger, and Erik Lindquist. 2015. “Dynamics of Global Forest Area: Results from the FAO Global Forest Resources Assessment 2015.” Forest Ecology and Management 352: 9–20. doi:10.1016/j.foreco.2015.06.014.
   Web of Science ®Google Scholar
• Kou, Weili, Jinwei Dong, Xiangming Xiao, Alexander J Hernandez, Yuanwei Qin, Geli Zhang, Bangqian Chen, Ning Lu, and Russell Doughty. 2018. “Expansion Dynamics of Deciduous Rubber Plantations in Xishuangbanna, China During 2000–2010.” GIScience & Remote Sensing 55 (6): 905–925. doi:10.1080/15481603.2018.1466441.
   Web of Science ®Google Scholar
• Krishna, Vijesh, Michael Euler, Hermanto Siregar, and Matin Qaim. 2017. “Differential Livelihood Impacts of oil Palm Expansion in Indonesia.” Agricultural Economics 48 (5): 639–653. doi:10.1111/agec.12363.
   Web of Science ®Google Scholar
• LAPAN. 2014. The Remote Sensing Monitoring Program of Indonesia’s National Carbon Accounting System: Methodology and Products, Version 1. Jakarta, Indonesia: LAPAN-IAFCP. Accessed 4 January 2019. http://incas.menlhk.go.id/methodology/incas-standard-method-forest-cover-change/.
   Google Scholar
• Lee, Jacky, Jeffrey A Cardille, and Michael T Coe. 2020. “Agricultural Expansion in Mato Grosso from 1986–2000: A Bayesian Time Series Approach to Tracking Past Land Cover Change.” Remote Sensing 12 (4): 688. doi:10.3390/rs12040688.
   Web of Science ®Google Scholar
• Margono, Belinda Arunarwati, Ahmad Basyirudin Usman, and Ruandha Agung Sugardiman. 2016. “Indonesia’s Forest Resource Monitoring.” Indonesian Journal of Geography 48 (1). doi:10.22146/ijg.12496.
   Google Scholar
• Margono, Belinda Arunarwati, Peter V Potapov, Svetlana Turubanova, Fred Stolle, and Matthew C Hansen. 2014. “Primary Forest Cover Loss in Indonesia Over 2000–2012.” Nature Climate Change 4 (8): 730–735. doi:10.1038/nclimate2277.
   Web of Science ®Google Scholar
• Miettinen, Jukka, and Soo Chin Liew. 2011. “Separability of Insular Southeast Asian Woody Plantation Species in the 50 m Resolution ALOS PALSAR Mosaic Product.” Remote Sensing Letters 2 (4): 299–307. doi:10.1080/01431161.2010.520345.
   Web of Science ®Google Scholar
• Miettinen, Jukka, Soo Chin Liew, and Leong Keong Kwoh. 2015. “Usability of Sentinel-1 Dual Polarization C-Band Data for Plantation Detection in Insular Southeast Asia.” Paper presented at the Proceedings of the 36th Asian Conference on Remote Sensing (ACRS2015).
   Google Scholar
• Ministry of Agriculture. 2017a. Statistik Perkebunan Indonesia 2015–2017: Karet (Tree Crop Estate Statistics of Indonesia 2015-2017: Rubber). Jakarta, Indonesia. Accessed 26 April 2020. http://ditjenbun.pertanian.go.id/tinymcpuk/gambar/file/statistik/2017/Karet-2015-2017.pdf.
   Google Scholar
• Ministry of Agriculture. 2017b. Statistik Perkebunan Indonesia 2015–2017: Kelapa sawit (Tree Crop Estate Statistics of Indonesia 2015-2017: Palm Oil). Jakarta, Indonesia. Accessed 26 April 2020. http://ditjenbun.pertanian.go.id/tinymcpuk/gambar/file/statistik/2017/Kelapa-Sawit-2015-2017.pdf.
   Google Scholar
• Ministry of Environment and Forestry, Republic of Indonesia. 2018. The State of Indonesia’s Forests 2018; Ministry of Environment and Forestry. Jakarta, Indonesia. Accessed 14 May 2019. https://www.menlhk.go.id/site/download?start=10.
   Google Scholar
• NASA. 2022. “FIRMS Fire Information for Resource Management System.” Accessed 28 June 2022. https://firms.modaps.eosdis.nasa.gov/country/.
   Google Scholar
• Olofsson, Pontus, Giles M Foody, Martin Herold, Stephen V Stehman, Curtis E Woodcock, and Michael A Wulder. 2014. “Good Practices for Estimating Area and Assessing Accuracy of Land Change.” Remote Sensing of Environment 148: 42–57. doi:10.1016/j.rse.2014.02.015.
   Web of Science ®Google Scholar
• Olsen, Jørgen L., Pietro Ceccato, Simon R. Proud, Rasmus Fensholt, Manuela Grippa, Eric Mougin, Jonas Ardö, and Inge Sandholt. 2013. “Relation Between Seasonally Detrended Shortwave Infrared Reflectance Data and Land Surface Moisture in Semi–Arid Sahel.” Remote Sensing 5 (6): 2898–2927. doi:10.3390/rs5062898.
   Web of Science ®Google Scholar
• Penman, Jim, Michael Gytarsky, Taka Hiraishi, Thelma Krug, Dina Kruger, Riitta Pipatti, Leandro Buendia, et al. 2003. Good Practice Guidance for Land use, Land-use Change and Forestry. Hayama: Institute for Global Environmental Strategies (IGES). Accessed 9 January 2021. https://www.ipcc.ch/site/assets/uploads/2018/03/GPG_LULUCF_FULLEN.pdf.
   Google Scholar
• Phuc, To Xuan, and Tran Huu Nghi. 2014. Rubber Expansion and Forest Protection in Vietnam. Hue: Tropenbos International Viet Nam. Accessed 28 May 2019. https://www.tropenbos.org/resources/publications/rubber+expansion+and+forest+protection+in+vietnam.
   Google Scholar
• Poker, Jutta, and Kenneth MacDicken. 2016. “Tropical Forest Resources: Facts and Tables.” In Tropical Forestry Handbook, edited by L. Pancel and M. Köhl, 3–45. Berlin: Springer Berlin Heidelberg.
   Google Scholar
• Pollino, Carmel A, and Christian Henderson. 2010. Bayesian Networks: A Guide for Their Application in Natural Resource Management and Policy. Tasmania: Landscape Logic. Volume 14.
   Google Scholar
• Presidential Instruction No. 5/2019 regarding the Termination of Granting of New Permits and Improving Management of Primary Natural Forests and Peatlands. Accessed 25 June 2022. https://jdihn.go.id/search/pusat/detail/945310.
   Google Scholar
• Razak, Janatul Aziera binti Abd, Abdul Rashid bin M. Shariff, Noordin bin Ahmad, and Maher Ibrahim Sameen. 2017. “Mapping Rubber Trees Based on Phenological Analysis of Landsat Time Series Data-Sets.” Geocarto International 33 (6): 1–24.
   Web of Science ®Google Scholar
• Reiche, Johannes, Sytze De Bruin, Dirk Hoekman, Jan Verbesselt, and Martin Herold. 2015. “A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection.” Remote Sensing 7 (5): 4973–4996. doi:10.3390/rs70504973.
   Web of Science ®Google Scholar
• Reiche, Johannes, Eliakim Hamunyela, Jan Verbesselt, Dirk Hoekman, and Martin Herold. 2018. “Improving Near-Real Time Deforestation Monitoring in Tropical dry Forests by Combining Dense Sentinel-1 Time Series with Landsat and ALOS-2 PALSAR-2.” Remote Sensing of Environment 204: 147–161. doi:10.1016/j.rse.2017.10.034.
   Web of Science ®Google Scholar
• ResearchInChina. 2014. “Global and China Natural Rubber Industry Report, 2013–2016.” Accessed 25 January 2022. http://www.researchinchina.com/htmls/report/2014/6851.html.
   Google Scholar
• Rosenqvist, Å. 1996. “Evaluation of JERS-1, ERS-1 and Almaz SAR Backscatter for Rubber and oil Palm Stands in West Malaysia.” International Journal of Remote Sensing 17 (16): 3219–3231. doi:10.1080/01431169608949140.
   Web of Science ®Google Scholar
• Ruysschaert, Denis, Adji Darsoyo, Rizwan Zen, Gunung Gea, and Ian Singleton. 2011. “Developing Palm-Oil Production on Degraded Land.” Foundation PanEco, YEL, World Agroforestry Centre, Medan. Accessed 28 May 2019. https://www.ifc.org/wps/wcm/connect/534db066-91a5-4816-a277-97eb687c0dd5/Developing+OP+plantation+on+degraded+land-draft_Output+22.pdf?MOD=AJPERES&CVID=kjG1KkB.
   Google Scholar
• Santosa, Yanto, Arzyana Sunkar, and Rozza Tri Kwatrina. 2020. “Is It True That Oil Palm Plantations Are The Main Driver of Deforestation of Indonesia’s Tropical Forest?” International Journal of Oil Palm 3 (1): 1–10. doi:10.35876/ijop.v3i1.37.
   Google Scholar
• Sari, Inggit Lolita, Christopher J Weston, Glenn J Newnham, and Liubov Volkova. 2021. “Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia.” Remote Sensing 13 (8): 1446. doi:10.3390/rs13081446.
   Web of Science ®Google Scholar
• Sari, Inggit Lolita, Christopher J Weston, Glenn J Newnham, and Liubov Volkova. 2022. “Developing Multi-Source Indices to Discriminate Between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia.” Remote Sensing 14 (1): 3. doi:10.3390/rs14010003.
   Web of Science ®Google Scholar
• Sarzynski, Thuan, Xingli Giam, Luis Carrasco, and Janice Ser Huay Lee. 2020. “Combining Radar and Optical Imagery to Map Oil Palm Plantations in Sumatra, Indonesia, Using the Google Earth Engine.” Remote Sensing 12 (7): 1220. doi:10.3390/rs12071220.
   Web of Science ®Google Scholar
• Shimada, Masanobu, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Tomohiro Shiraishi, Rajesh Thapa, and Richard Lucas. 2014. “New Global Forest/non-Forest Maps from ALOS PALSAR Data (2007–2010).” Remote Sensing of Environment 155: 13–31. doi:10.1016/j.rse.2014.04.014.
   Web of Science ®Google Scholar
• Suzuki, Rikie, Yongwon Kim, and Reiichiro Ishii. 2013. “Sensitivity of the Backscatter Intensity of ALOS/PALSAR to the Above-Ground Biomass and Other Biophysical Parameters of Boreal Forest in Alaska.” Polar Science 7 (2): 100–112. doi:10.1016/j.polar.2013.03.001.
   Web of Science ®Google Scholar
• Symeonakis, Elias, Peter A. Caccetta, Sotirios Koukoulas, Suzanne Furby, and Nikolaos Karathanasis. 2012. “Multi-temporal Land-Cover Classification and Change Analysis with Conditional Probability Networks: The Case of Lesvos Island (Greece).” International Journal of Remote Sensing 33 (13): 4075–4093. doi:10.1080/01431161.2011.640961.
   Web of Science ®Google Scholar
• Torbick, Nathan, Lindsay Ledoux, William Salas, and Meng Zhao. 2016. “Regional Mapping of Plantation Extent Using Multisensor Imagery.” Remote Sensing 8 (3): 236. doi:10.3390/rs8030236.
   Web of Science ®Google Scholar
• Tropek, Robert, Ondřej Sedláček, Jan Beck, Petr Keil, Zuzana Musilová, Irena Šímová, and David Storch. 2014. “Comment on “High-Resolution Global Maps of 21st-Century Forest Cover Change”.” Science 344 (6187): 981–981. doi:10.1126/science.1248753.
   PubMed Web of Science ®Google Scholar
• Tsutsumida, Narumasa, and Alexis J Comber. 2015. “Measures of Spatio-Temporal Accuracy for Time Series Land Cover Data.” International Journal of Applied Earth Observation and Geoinformation 41: 46–55. doi:10.1016/j.jag.2015.04.018.
   Web of Science ®Google Scholar
• Tucker, Compton J. 1980. “Remote Sensing of Leaf Water Content in the Near Infrared.” Remote Sensing of Environment 10 (1): 23–32. doi:10.1016/0034-4257(80)90096-6.
   Web of Science ®Google Scholar
• Turubanova, Svetlana, Peter V Potapov, Alexandra Tyukavina, and Matthew C Hansen. 2018. “Ongoing Primary Forest Loss in Brazil, Democratic Republic of the Congo, and Indonesia.” Environmental Research Letters 13 (7): 074028. doi:10.1088/1748-9326/aacd1c.
   Web of Science ®Google Scholar
• USGS. 2019. “Landsat.” Accessed 3 July 2019. https://earthexplorer.usgs.gov/.
   Google Scholar
• Verbesselt, Jan, Rob Hyndman, Glenn Newnham, and Darius Culvenor. 2010. “Detecting Trend and Seasonal Changes in Satellite Image Time Series.” Remote Sensing of Environment 114 (1): 106–115. doi:10.1016/j.rse.2009.08.014.
   Web of Science ®Google Scholar
• Wicke, Birka, Richard Sikkema, Veronika Dornburg, and André Faaij. 2011. “Exploring Land use Changes and the Role of Palm oil Production in Indonesia and Malaysia.” Land Use Policy 28 (1): 193–206. doi:10.1016/j.landusepol.2010.06.001.
   Web of Science ®Google Scholar
• Xu, Yidi, Le Yu, Wei Li, Philippe Ciais, Yuqi Cheng, and Peng Gong. 2020. “Annual oil Palm Plantation Maps in Malaysia and Indonesia from 2001 to 2016.” Earth System Science Data 12 (2): 847–867. doi:10.5194/essd-12-847-2020.
   Web of Science ®Google Scholar
• Yan, Jining, Lizhe Wang, Weijing Song, Yunliang Chen, Xiaodao Chen, and Ze Deng. 2019. “A Time-Series Classification Approach Based on Change Detection for Rapid Land Cover Mapping.” ISPRS Journal of Photogrammetry and Remote Sensing 158: 249–262. doi:10.1016/j.isprsjprs.2019.10.003.
   Web of Science ®Google Scholar