文献类型：期刊文献

英文题名：Using a Vegetation Index to Monitor the Death Process of Chinese Fir Based on Hyperspectral Data

作者：Tang, Xuemei[1,2,3] Zang, Zhuo[1,2,3] Lin, Hui[1,2,3] Wang, Xu[4] Wen, Zhang[1,2,3]

第一作者：Tang, Xuemei

通信作者：Zang, Z[1];Zang, Z[2];Zang, Z[3]

机构：[1]Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Peoples R China;[2]Hunan Prov Key Lab Forestry Remote Sensing Based B, Changsha 410004, Peoples R China;[3]Key Lab Natl Forestry & Grassland Adm Forest Resou, Changsha 410004, Peoples R China;[4]Chinese Acad Forestry, Res Inst Trop Forestry, Guangzhou 510520, Peoples R China

年份：2023

卷号：14

期号：12

外文期刊名：FORESTS

收录：;EI(收录号：20240115303396);Scopus(收录号：2-s2.0-85180730862);WOS:【SCI-EXPANDED(收录号:WOS:001131398100001)】；

基金：No Statement Available

语种：英文

外文关键词：remote sensing; hyperspectral imaging; vegetation index; early monitoring; Chinese fir; GRRSAI

摘要：Chinese fir is one of the most widely distributed and extensively planted timber species in China. Therefore, monitoring pests and diseases in Chinese fir plantations is directly related to national timber forest security and forest ecological security. This study aimed to identify appropriate vegetation indices for the early monitoring of pests and diseases in Chinese fir plantations. For this purpose, the researchers used an imaging spectrometer to capture hyperspectral images of both experimental and control groups. The experimental group consisted of Chinese fir trees with two sections of bark stripped off, while the control group consisted of healthy Chinese fir trees. The study then assessed the sensitivity of 11 vegetation indices to the physiological differences between the two groups using the Mann-Whitney U test. The results showed that both the green-to-red region spectral angle index (GRRSGI) and the red edge position index (REP) were able to monitor the difference as early as 16 days after damage. However, GRRSGI performs best in monitoring early death changes in Chinese fir trees because it is less affected by noise and is more stable. The green-red spectral area index (GRSAI) also had high stability, but the monitoring effect was slightly worse than that of GRRSGI and REP. Compared with other indices, GRRSGI and GRSAI can better exploit the advantages of hyperspectral data.