{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:48:30Z","timestamp":1764784110510,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,8,23]],"date-time":"2018-08-23T00:00:00Z","timestamp":1534982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP16K07978","16H05747"],"award-info":[{"award-number":["JP16K07978","16H05747"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010681","name":"Research Institute for Humanity and Nature","doi-asserted-by":"publisher","award":["14200117"],"award-info":[{"award-number":["14200117"]}],"id":[{"id":"10.13039\/501100010681","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The high demand for unmanned aerial systems (UASs) reflects the notable impact that these systems have had on the remote sensing field in recent years. Such systems can be used to discover new findings and develop strategic plans in related scientific fields. In this work, a case study is performed to describe a novel approach that uses a UAS with two different sensors and assesses the possibility of monitoring peatland in a small area of a plantation forest in West Kalimantan, Indonesia. First, a multicopter drone with an onboard camera was used to collect aerial images of the study area. The structure from motion (SfM) method was implemented to generate a mosaic image. A digital surface model (DSM) and digital terrain model (DTM) were used to compute a canopy height model (CHM) and explore the vegetation height. Second, a multicopter drone combined with a thermal infrared camera (Zenmuse-XT) was utilized to collect both spatial and temporal thermal data from the study area. The temperature is an important factor that controls the oxidation of tropical peats by microorganisms, root respiration, the soil water content, and so forth. In turn, these processes can alter the greenhouse gas (GHG) flux in the area. Using principal component analysis (PCA), the thermal data were processed to visualize the thermal characteristics of the study site, and the PCA successfully extracted different feature areas. The trends in the thermal information clearly show the differences among land cover types, and the heating and cooling of the peat varies throughout the study area. This study shows the potential for using UAS thermal remote sensing to interpret the characteristics of thermal trends in peatland environments, and the proposed method can be used to guide strategical approaches for monitoring the peatlands in Indonesia.<\/jats:p>","DOI":"10.3390\/rs10091345","type":"journal-article","created":{"date-parts":[[2018,8,24]],"date-time":"2018-08-24T03:42:31Z","timestamp":1535082151000},"page":"1345","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Visualizing the Spatiotemporal Trends of Thermal Characteristics in a Peatland Plantation Forest in Indonesia: Pilot Test Using Unmanned Aerial Systems (UASs)"],"prefix":"10.3390","volume":"10","author":[{"given":"Kotaro","family":"Iizuka","sequence":"first","affiliation":[{"name":"Center for Spatial Information Science, University of Tokyo, Kashiwa 277-8568, Japan"}]},{"given":"Kazuo","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Center for Southeast Asian Studies, Kyoto University, Kyoto 606-8501, Japan"}]},{"given":"Tsuyoshi","family":"Kato","sequence":"additional","affiliation":[{"name":"PT Mayangkara Tanaman Industri, Pontianak 787391\/PT Wana Subur Lestari, Jakarta 10270, Indonesia"}]},{"given":"Niken Andika","family":"Putri","sequence":"additional","affiliation":[{"name":"PT Mayangkara Tanaman Industri, Pontianak 787391\/PT Wana Subur Lestari, Jakarta 10270, Indonesia"}]},{"given":"Sisva","family":"Silsigia","sequence":"additional","affiliation":[{"name":"PT Mayangkara Tanaman Industri, Pontianak 787391\/PT Wana Subur Lestari, Jakarta 10270, Indonesia"}]},{"given":"Taishin","family":"Kameoka","sequence":"additional","affiliation":[{"name":"Graduate School of Asian and African Area Studies, Kyoto University, Kyoto 606-8501, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6487-7993","authenticated-orcid":false,"given":"Osamu","family":"Kozan","sequence":"additional","affiliation":[{"name":"Center for Southeast Asian Studies, Kyoto University, Kyoto 606-8501, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"26886","DOI":"10.1038\/srep26886","article-title":"Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997","volume":"6","author":"Huijnen","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.gloenvcha.2016.05.005","article-title":"Sources of anthropogenic fire ignitions on the peat-swamp landscape in Kalimantan, Indonesia","volume":"39","author":"Cattau","year":"2016","journal-title":"Glob. Environ. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sumarga, E. (2017). Spatial Indicators for Human Activities May Explain the 2015 Fire Hotspot Distribution in Central Kalimantan Indonesia. Trop. Conserv. Sci., 10.","DOI":"10.1177\/1940082917706168"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"11711","DOI":"10.5194\/acp-16-11711-2016","article-title":"Field measurements of trace gases and aerosols emitted by peat fires in Central Kalimantan, Indonesia, during the 2015 El Ni\u00f1o","volume":"16","author":"Stockwell","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.5194\/bg-7-1505-2010","article-title":"Current and future CO2 emissions from drained peatlands in Southeast Asia","volume":"7","author":"Hooijer","year":"2010","journal-title":"Biogeosciences"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.catena.2013.10.009","article-title":"Canal blocking strategies for hydrological restoration of degraded tropical peatlands in Central Kalimantan, Indonesia","volume":"114","author":"Ritzema","year":"2014","journal-title":"CATENA"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.jhydrol.2011.03.010","article-title":"Water table dynamics in undisturbed, drained and restored blanket peat","volume":"302","author":"Holden","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.jenvman.2013.11.033","article-title":"Restoration of blanket peatlands","volume":"133","author":"Parry","year":"2014","journal-title":"J. Environ. Manag."},{"key":"ref_9","unstructured":"Jauhiainen, J., Page, S.S., and Vasander, H. (2016). Greenhouse gas dynamics in degraded and restored tropical peatland. Mires Peat, 17."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.5194\/bg-9-1053-2012","article-title":"Subsidence and carbon loss in drained tropical peatlands","volume":"9","author":"Hooijer","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"105013","DOI":"10.1088\/1748-9326\/9\/10\/105013","article-title":"Heterotrophic respiration in drained tropical peat is greatly affected by temperature\u2014A passive ecosystem cooling experiment","volume":"9","author":"Jauhiainen","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.soilbio.2013.08.009","article-title":"Temperature sensitivity of decomposition in a peat profile","volume":"67","author":"Hilasvuori","year":"2013","journal-title":"Soil Biol. Biochem."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1007\/s10745-005-5156-z","article-title":"Fire, People and Pixels: Linking Social Science and Remote Sensing to Understand Underlying Causes and Impacts of Fires in Indonesia","volume":"33","author":"Dennis","year":"2005","journal-title":"Hum. Ecol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1007\/s00267-011-9643-2","article-title":"Deforestation projections for carbon-rich peat swamp forests of Central Kalimantan, Indonesia","volume":"48","author":"Fuller","year":"2011","journal-title":"Environ. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Atwood, E.C., Englhart, S., Lorenz, E., Halle, W., Wiedemann, W., and Siegert, F. (2016). Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird). PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0159410"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.proenv.2016.03.051","article-title":"Identification of Agricultural Drought Extent Based on Vegetation Health Indices of Landsat Data: Case of Subang and Karawang, Indonesia","volume":"33","author":"Sholihah","year":"2016","journal-title":"Procedia Environ. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.1007\/s12665-016-6202-4","article-title":"Response of land cover types to land surface temperature derived from Landsat-5 TM in Nanjing Metropolitan Region, China","volume":"75","author":"Liu","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_18","unstructured":"Leng, L.Y., Ahmed, O.H., and Jalloh, M.B. (2018). Brief review on climate change and tropical peatlands. Geosci. Front., in press."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/nature04514","article-title":"Temperature sensitivity of soil carbon decomposition and feedbacks to climate change","volume":"440","author":"Davidson","year":"2006","journal-title":"Nature"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Iizuka, K., Yonehara, T., Itoh, M., and Kosugi, Y. (2018). Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest. Remote Sens., 10.","DOI":"10.3390\/rs10010013"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Jaud, M., Passot, S., Le Bivic, R., Delacourt, C., Grandjean, P., and Le Dantec, N. (2016). Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan\u00ae and MicMac\u00ae in Sub-Optimal Survey Conditions. Remote Sens., 8.","DOI":"10.3390\/rs8060465"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Luna, I., and Lobo, A. (2016). Mapping Crop Planting Quality in Sugarcane from UAV Imagery: A Pilot Study in Nicaragua. Remote Sens., 8.","DOI":"10.3390\/rs8060500"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1498180","DOI":"10.1080\/23312041.2018.1498180","article-title":"Advantages of unmanned aerial vehicle (UAV) photogrammetry for landscape analysis compared with satellite data: A case study of postmining sites in Indonesia","volume":"4","author":"Iizuka","year":"2018","journal-title":"Cogent Geosci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"12815","DOI":"10.3390\/rs61212815","article-title":"Remote sensing of submerged aquatic vegetation in a shallow non-turbid river using an unmanned aerial vehicle","volume":"6","author":"Flynn","year":"2014","journal-title":"Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Aghaei, M., Gandelli, A., Grimaccia, F., Leva, S., and Zich, R.E. (2015, January 17\u201319). IR real-time analyses for PV system monitoring by digital image processing techniques. Proceedings of the International Conference on Event-based Control Communication and Signal Processing (EBCCSP), Krakow, Poland.","DOI":"10.1109\/EBCCSP.2015.7300708"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gonzalez, L.F., Montes, G.A., Puig, E., Johnson, S., Mengersen, K., and Gaston, K.J. (2016). Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation. Sensors, 16.","DOI":"10.3390\/s16010097"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"6031","DOI":"10.5194\/hess-21-6031-2017","article-title":"Hydrogeological controls on spatial patterns of groundwater discharge in peatlands","volume":"21","author":"Hare","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Maes, W.H., Huete, A.R., and Steppe, K. (2017). Optimizing the Processing of UAV-Based Thermal Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9050476"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Guerra-Hern\u00e1ndez, J., Gonz\u00e1lez-Ferreiro, E., Monle\u00f3n, V.J., Faias, S.P., Tom\u00e9, M., and D\u00edaz-Varela, R.A. (2017). Use of Multi-Temporal UAV-Derived Imagery for Estimating Individual Tree Growth in Pinus pinea Stands. Forests, 8.","DOI":"10.3390\/f8080300"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.3390\/rs2102369","article-title":"Applicability of Green-Red Vegetation Index for Remote Sensing of Vegetation Phenology","volume":"2","author":"Motohka","year":"2010","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ma, H., Qin, Q., and Shen, X. (2008, January 7\u201311). Shadow segmentation and compensation in high resolution satellite images. Proceedings of the 2008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, USA.","DOI":"10.1109\/IGARSS.2008.4779175"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s10661-015-5072-7","article-title":"Artificial neural network for multifunctional areas","volume":"188","author":"Riccioli","year":"2016","journal-title":"Environ. Monit. Assess."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Tang, F., and Xu, H. (2017). Impervious Surface Information Extraction Based on Hyperspectral Remote Sensing Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9060550"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1002\/joc.1888","article-title":"Interpreting variability in global SST data using independent component analysis and principal component analysis","volume":"30","author":"Westra","year":"2010","journal-title":"Int. J. Clim."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"140","DOI":"10.3189\/172756411795931741","article-title":"Spatial fields of Antarctic sea-ice concentration anomalies for summer\u2013autumn and their relationship to Southern Hemisphere atmospheric circulation during the period 1979\u20132009","volume":"52","author":"Barreira","year":"2011","journal-title":"Ann. Glaciol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"5969","DOI":"10.3390\/rs5115969","article-title":"Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh","volume":"5","author":"Ahmed","year":"2013","journal-title":"Remote Sens."},{"key":"ref_37","first-page":"2271","article-title":"System for Automated Geoscientific Analyses (SAGA) v. 2.1.4","volume":"8","author":"Conrad","year":"2015","journal-title":"Geosci. Model Dev. Discuss."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"695629","DOI":"10.1155\/2014\/695629","article-title":"Characteristics of Wind Velocity and Temperature Change near an Escarpment-Shaped Road Embankment","volume":"2014","author":"Kim","year":"2014","journal-title":"Sci. World J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0021-8634(05)80152-0","article-title":"Influence of soil moisture content on soil temperature and heat storage under greenhouse conditions","volume":"45","author":"Hasson","year":"1990","journal-title":"J. Agric. Eng. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3041","DOI":"10.1002\/hyp.1275","article-title":"Soil moisture-temperature relationships: Results from two field experiments","volume":"17","author":"Lakshmi","year":"2003","journal-title":"Hydrol. Process."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/9\/1345\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:20:32Z","timestamp":1760196032000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/9\/1345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,23]]},"references-count":40,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["rs10091345"],"URL":"https:\/\/doi.org\/10.3390\/rs10091345","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,8,23]]}}}