Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/22021
Title: Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera Tropiduchidae) habitat and population densities
Contributor(s): Al-Kindi, Khalifa M (author); Kwan, Paul  (author); Andrew, Nigel R  (author)orcid ; Welch, Mitchell  (author)orcid 
Publication Date: 2017
Open Access: Yes
DOI: 10.7717/peerj.3752Open Access Link
Handle Link: https://hdl.handle.net/1959.11/22021
Abstract: In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.
Publication Type: Journal Article
Source of Publication: PeerJ, v.5, p. 1-36
Publisher: PeerJ Ltd
Place of Publication: United Kingdom
ISSN: 2167-8359
Field of Research (FOR): 090905 Photogrammetry and Remote Sensing
070104 Agricultural Spatial Analysis and Modelling
089999 Information and Computing Sciences not elsewhere classified
Socio-Economic Outcome Codes: 970105 Expanding Knowledge in the Environmental Sciences
970110 Expanding Knowledge in Technology
960413 Control of Plant Pests, Diseases and Exotic Species in Farmland, Arable Cropland and Permanent Cropland Environments
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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