Mapping Tropical Forest Biomass by Combining ALOS-2, Landsat 8, and Field Plots Data

Luong Viet Nguyen, Ryutaro Tateishi, Akihiko Kondoh, Ram C. Sharma, Hoan Thanh Nguyen, Tu Trong To and Dinh Ho Tong Minh
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Luong Viet Nguyen: Center for Environmental Remote Sensing, Chiba University, 1–33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
Ryutaro Tateishi: Center for Environmental Remote Sensing, Chiba University, 1–33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
Akihiko Kondoh: Center for Environmental Remote Sensing, Chiba University, 1–33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
Ram C. Sharma: Center for Environmental Remote Sensing, Chiba University, 1–33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
Hoan Thanh Nguyen: Institute of Geography, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet str., Cau Giay dist., Hanoi 100000, Vietnam
Tu Trong To: Space Technology Institute, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet str., Cau Giay dist., Hanoi 100000, Vietnam
Dinh Ho Tong Minh: Institut national de Recherche en Sciences et Technologies pour l’Environnement et l’Agriculture (IRSTEA), UMR TETIS, Maison de la Teledetection, 500 Rue Jean Francois Breton, Montpellier 34000, France

Land, 2016, vol. 5, issue 4, 1-15

Abstract: This research was carried out in a dense tropical forest region with the objective of improving the biomass estimates by a combination of ALOS-2 SAR, Landsat 8 optical, and field plots data. Using forest inventory based biomass data, the performance of different parameters from the two sensors was evaluated. The regression analysis with the biomass data showed that the backscatter from forest object (σ° forest ) obtained from the SAR data was more sensitive to the biomass than HV polarization, SAR textures, and maximum NDVI parameters. However, the combination of the maximum NDVI from optical data, SAR textures from HV polarization, and σ° forest improved estimates of the biomass. The best model derived by the combination of multiple parameters from ALOS-2 SAR and Landsat 8 data was validated with inventory data. Then, the best validated model was used to produce an up-to-date biomass map for 2015 in Yok Don National Park, which is an important conservation area in Vietnam. The validation results showed that 74% of the variation of in biomass could be explained by our model.

Keywords: forest biomass; SAR; L-band ALOS-2; backscatter; texture; Landsat 8; NDVI; accuracy; Vietnam (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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