文献类型：期刊文献

英文题名：Detection of Rise Damage by Leaf Folder (Cnaphalocrocis medinalis) Using Unmanned Aerial Vehicle Based Hyperspectral Data

作者：Liu, Tao[1,2];Shi, Tiezhu[3,4,5,6];Zhang, Huan[2];Wu, Chao[7,8]

第一作者：Liu, Tao

通讯作者：Wu, C[1];Wu, C[2]

机构：[1]Henan Univ Econ & Law, Coll Resources & Environm, Zhengzhou 450002, Peoples R China;[2]Henan Agr Univ, Key Lab New Mat & Facil Rural Renewable Energy MO, Zhengzhou 450002, Peoples R China;[3]Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, Shenzhen 518060, Peoples R China;[4]Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China;[5]Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;[6]Shenzhen Univ, Sch Architecture & Urban Planning, Shenzhen 518060, Peoples R China;[7]Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210023, Peoples R China;[8]Nanjing Univ Posts & Telecommun, Smart Hlth Big Data Anal & Locat Serv Engn Lab Ji, Nanjing 210023, Peoples R China

第一机构：河南财经政法大学资源与环境学院

通讯机构：[1]corresponding author), Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210023, Peoples R China;[2]corresponding author), Nanjing Univ Posts & Telecommun, Smart Hlth Big Data Anal & Locat Serv Engn Lab Ji, Nanjing 210023, Peoples R China.

年份：2020

卷号：12

期号：22

起止页码：1-15

外文期刊名：SUSTAINABILITY

收录：;WOS:【SSCI(收录号:WOS:000595047500001)，SCI-EXPANDED(收录号:WOS:000595047500001)】；

基金：This research was funded by National Natural Science Foundation of China (Nos. 41801376, 4170010438, 41901248, and 41901326), China Postdoctoral Science Foundation (No. 2020M682293), the National Special Research Fund for Non-Profit Sector (Agriculture) (No. 201303099); the Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20170302144323219), and the Natural Science Foundation of Jiangsu Province (BK20190742), the Natural Science Research of Jiangsu Higher Education Institutions of China (19KJB170009), and Key Research Projects of Henan Higher Education Institutions (19A420004).

语种：英文

外文关键词：UAV-based hyperspectral system; crop pests; leaf-roll rate; spectral index; photochemical reflectance index

摘要：Crop pests and diseases are key factors that damage crop production and threaten food security. Remote sensing techniques may provide an objective and effective alternative for automatic detection of crop pests and diseases. However, ground-based spectroscopic or imaging sensors may be limited in practically guiding the precision application and reduction of pesticide. Therefore, this study developed an unmanned aerial vehicle (UAV)-based remote sensing system to detect leaf folder (Cnaphalocrocis medinalis). Rice canopy reflectance spectra were obtained in the booting growth stage by using the UAV-based hyperspectral remote sensor. Newly developed and published multivariate spectral indices were initially calculated to estimate leaf-roll rates. The newly developed two-band spectral index (R490-R470), three-band spectral index (R400-R470)/(R400-R490), and published spectral index photochemical reflectance index (R550-R531)/(R550+R531) showed good applicability for estimating leaf-roll rates. The newly developed UAV-based micro hyperspectral system had potential in detecting rice stress induced by leaf folder. The newly developed spectral index (R490-R470) and (R400-R470)/(R400-R490) might be recommended as an indicator for estimating leaf-roll rates in the study area, and (R550-R531)/(R550+R531) might serve as a universal spectral index for monitoring leaf folder.