文献类型：期刊文献

英文题名：Developing a spectral angle based vegetation index for detecting the early dying process of Chinese fir trees

作者：Zang, Zhuo[1,2,3] Wang, Guangxing[3] Lin, Hui[1,2] Luo, Peng[4]

第一作者：Zang, Zhuo

通信作者：Wang, GX[1]

机构：[1]Cent South Univ Forestry & Technol, Changsha 410004, Peoples R China;[2]Key Lab Forestry Remote Sensing Based Big Data &, Changsha 410004, Peoples R China;[3]Southern Illinois Univ Carbondale, Dept Geog & Environm Resources, Carbondale, IL 62901 USA;[4]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

年份：2021

卷号：171

起止页码：253-265

外文期刊名：ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

收录：;EI(收录号：20205109625931);Scopus(收录号：2-s2.0-85097581155);WOS:【SCI-EXPANDED(收录号:WOS:000604406500017)】；

基金：This research was funded by National Natural Science Foundation of China (N#31370639) and China Scholarship Council (N#201808430314), and Youth Foundation from Central South University of Forestry and Technology(N#QJ2013004A).

语种：英文

外文关键词：Hyperspectral data; Spectral angle; GRRSGI; Early stage damage detection; Chinese fir

摘要：Forests play an important role in global ecosystems, but natural disasters such as drought and disease and pest-induced damages often affect growth of trees and even lead to tree death. There have been various vegetation indices (VIs) developed to detect the damages of trees using remote sensing technologies. However, developing an effective and accurate VI for detecting forest damages at an earlier stage is still challenging. In this study, a total of 32 target trees and 17 reference trees were selected from one of Chinese fir plantations that account for 24% of the afforested area in China. The barks of the target trees at 20 cm and 70 cm above the ground were respectively peeled off in August of 2016 to let the trees die. The hyperspectral data were collected from the selected branches with leaves using a high-performance spectrometer HR-1024i (Spectra Vista Corporation) with 1024 bands covering the region of wavelengths from 350 nm to 2500 nm. The spectral data collection was conducted from both the target and reference trees by non-imaging monthly from August of 2016 to February of 2017 until the target trees died. Based on statistical analysis, a Green to Red Region Spectral anGle Index (GRRSGI) was proposed and compared with other ten widely used VIs to detect the early dying process of the damaged trees. The results showed that compared with the reference trees, the damaged trees reduced the reflectance peaks of green bands and the absorption valleys of red bands and the frequency distributions of spectral reflectance from the damaged trees turned from statistically normal to non-normal in the region of 550-640 nm. This indicated that the spectral bands in the region of green to red bands were sensitive to the dying process of the target trees. Moreover, the performance of the VIs for detecting the dying process of the damaged trees varied depending on the time period after the trees damaged. The proposed GRRSGI based on the spectral bands of 550-640 nm led to the performance similar to all other VIs after three months of the damages but significantly better than them in the first two months after the damages. Except for GRRSGI, the Green-Red Spectral Area Index (GRSAI) also performed better than other VIs. Compared with GRSAI, however, the proposed GRRSGI performed slight better when the spectral data of 550-640 nm were re-sampled using the spectral intervals of 5-40 nm with an increase of 5 nm and significantly better when the re-sampling of the hyperspectral data was conducted in the region of 550-670 nm. This implied the proposed GRRSGI provided the greater potential of detecting the early dying process of the damage trees.