Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

Forests

Tetsuji Ota⁴  Miyuki Ogawa¹  Katsuto Shimizu¹  Tsuyoshi Kajisa⁶  Nobuya Mizoue⁸  Shigejiro Yoshida⁸  Gen Takao²  Yasumasa Hirata²  Naoyuki Furuya⁵  Takio Sano⁹  Heng Sokh⁷  Vuthy Ma⁷  Eriko Ito⁵  Jumpei Toriyama²  Yukako Monda³  Hideki Saito²  Yoshiyuki Kiyono²  Sophal Chann⁷  Nang Ket⁷ 

[1] Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, 6-10-1 Hakozaki, Fukuoka 812-8581, Japan; E-Mails:;Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba 305-8687, Japan; E-Mails:;Tano Forest Science Station of Field Science Center, Faculty of Agriculture, University of Miyazaki, 11300 Tano-Otsu, Miyazaki, Miyazaki 889-1712, Japan; E-Mail:;Institute of Decision Science for a Sustainable Society, Kyushu University, 6-10-1 Hakozaki, Fukuoka 812-8581, Japan;Hokkaido Research Center, Forestry and Forest Products Research Institute, 7 Hitsujigaoka, Toyohiraku, Sapporo 062-8516, Japan; E-Mails:;Faculty of Agriculture, Kagoshima University, 1-21-24 Korimoto, Kagoshima 890-8580, Japan; E-Mail:;Forestry Administration, Khan Sen Sok, Phnom Penh 12157, Cambodia; E-Mails:;Faculty of Agriculture, Kyushu University, 6-10-1 Hakozaki, Fukuoka 812-8581, Japan; E-Mails:;Asia Air Survey Co., Ltd., Shinyuri 21 Building, 1-2-2 Manpukuji, Asao-ku, Kawasaki 215-0004, Japan; E-Mail:

关键词: aboveground biomass;    aerial photograph;    Airborne LiDAR;    seasonal tropical forest;    SfM;   

DOI  :  10.3390/f6113882

来源: mdpi

【 摘 要 】

We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSM_P). We also created a DSM from airborne LiDAR data (DSM_L). From each of DSM_P and DSM_L, we constructed digital terrain models (DTM), which are DTM_P and DTM_L, respectively. We created four CHMs, which were calculated from (1) DSM_P and DTM_P (CHM_PP); (2) DSM_P and DTM_L (CHM_PL); (3) DSM_L and DTM_P (CHM_LP); and (4) DSM_L and DTM_L (CHM_LL). Then, we estimated AGB using these CHMs. The model using CHM_LL yielded the highest accuracy in four CHMs (R² = 0.94) and was comparable to the model using CHM_PL (R² = 0.93). The model using CHM_PP yielded the lowest accuracy (R² = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.