A review: application of remote sensing as a promising strategy for insect pests and diseases management

被引:104
作者
Abd El-Ghany, Nesreen M. [1 ]
Abd El-Aziz, Shadia E. [1 ]
Marei, Shahira S. [1 ]
机构
[1] Natl Res Ctr, Agr & Biol Div, Dept Pests & Plant Protect, 33 EL Buhouth St, Giza 12622, Egypt
关键词
Remote sensing; Applications; Plant protection; Insect pests; Plant disease; Management; TREE MORTALITY; INFRARED PHOTOGRAPHY; BARK BEETLE; IMAGERY; CLASSIFICATION; IDENTIFICATION; INFESTATIONS; LEPIDOPTERA; TECHNOLOGY; MIGRATION;
D O I
10.1007/s11356-020-09517-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The present review provides a perspective angle on the historical and cutting-edge strategies of remote sensing techniques and its applications, especially for insect pest and plant disease management. Remote sensing depends on measuring, recording, and processing the electromagnetic radiation reflected and emitted from the ground target. Remote sensing applications depend on the spectral behavior of living organisms. Today, remote sensing is used as an effective tool for the detection, forecasting, and management of insect pests and plant diseases on different fruit orchards and crops. The main objectives of these applications were to collate data that help in decision-making for insect pest management and decreasing the environmental pollution of chemical pesticides. Airborne remote sensing has been a promising and useful tool for insect pest management and weed detection. Furthermore, remote sensing using satellite information proved to be a promising tool in forecasting and monitoring the distribution of locust species. It has also been used to help farmers in the early detection of mite infestation in cotton fields using multi-spectral systems, which depend on color changes in canopy semblance over time. Remote sensing can provide fast and accurate forecasting of targeted insect pests and subsequently minimizing pest damage and the management costs.
引用
收藏
页码:33503 / 33515
页数:13
相关论文
共 78 条
[1]  
Abdullah A, 2004, P 7 INT C PREC AGR O, P14
[2]  
Acharya M. C., 2015, Journal of Agriculture and Environment, V16, P43
[3]   Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities [J].
Al-Kindi, Khalifa M. ;
Kwan, Paul ;
Andrew, Nigel R. ;
Welch, Mitchell .
PEERJ, 2017, 5
[4]  
Andreo V, 2013, TECHNICAL REPORT, P34
[5]  
Avery TE., 1992, FUNDAMENTALS REMOTE, P472
[6]   Infra-red photography and plant virus diseases [J].
Bawden, FC .
NATURE, 1933, 132 :168-168
[7]   Quantifying Fertilizer Application Response Variability with VHR Satellite NDVI Time Series in a Rainfed Smallholder Cropping System of Mali [J].
Blaes, Xavier ;
Chome, Guillaume ;
Lambert, Marie-Julie ;
Traore, Pierre Sibiry ;
Schut, Antonius G. T. ;
Defourny, Pierre .
REMOTE SENSING, 2016, 8 (06)
[8]   Advances in entomological laser radar [J].
Blydegaard, Mikkel ;
Jansson, Samuel .
JOURNAL OF ENGINEERING-JOE, 2019, 2019 (21) :7542-7545
[9]   AERIAL PHOTOGRAPHY FOR STUDY OF PLANT DISEASES [J].
BRENCHLE.GH .
ANNUAL REVIEW OF PHYTOPATHOLOGY, 1968, 6 :1-&
[10]   Development of vertical-looking radar technology for monitoring insect migration [J].
Chapman, JW ;
Smith, AD ;
Woiwod, IP ;
Reynolds, DR ;
Riley, JR .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 35 (2-3) :95-110