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Remote Sens. 2018, 10(9), 1345; https://doi.org/10.3390/rs10091345

Visualizing the Spatiotemporal Trends of Thermal Characteristics in a Peatland Plantation Forest in Indonesia: Pilot Test Using Unmanned Aerial Systems (UASs)

1
Center for Spatial Information Science, University of Tokyo, Kashiwa 277-8568, Japan
2
Center for Southeast Asian Studies, Kyoto University, Kyoto 606-8501, Japan
3
PT Mayangkara Tanaman Industri, Pontianak 787391/PT Wana Subur Lestari, Jakarta 10270, Indonesia
4
Graduate School of Asian and African Area Studies, Kyoto University, Kyoto 606-8501, Japan
*
Author to whom correspondence should be addressed.
Received: 31 July 2018 / Revised: 18 August 2018 / Accepted: 21 August 2018 / Published: 23 August 2018
(This article belongs to the Special Issue Remote Sensing from Unmanned Aerial Vehicles (UAVs))
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Abstract

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. View Full-Text
Keywords: UAS; UAV; thermal; structure from motion; peatland; Zenmuse-XT; plantation; principal component analysis UAS; UAV; thermal; structure from motion; peatland; Zenmuse-XT; plantation; principal component analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Iizuka, K.; Watanabe, K.; Kato, T.; Putri, N.A.; Silsigia, S.; Kameoka, T.; Kozan, O. Visualizing the Spatiotemporal Trends of Thermal Characteristics in a Peatland Plantation Forest in Indonesia: Pilot Test Using Unmanned Aerial Systems (UASs). Remote Sens. 2018, 10, 1345.

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