Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques
Rat damage in oil palm plantation brings significant economic losses. In this study, factors that influence rat occurrence were investigated using live trapping and GIS-based multicriteria analysis. 255 rats, mostly Rattus rattus diardii were captured using live trapping from nearly two thousands tr...
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my-ums-ep.118232017-11-07T07:20:34Z Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques 2012 Chong, Chee Wey QL Zoology Rat damage in oil palm plantation brings significant economic losses. In this study, factors that influence rat occurrence were investigated using live trapping and GIS-based multicriteria analysis. 255 rats, mostly Rattus rattus diardii were captured using live trapping from nearly two thousands trap-night efforts. In oil palm plantation, rat species captured is R. r. diardii, R. argentiventer, Maxomys whiteheadi. In forest, rat species captured is R. r. diardii, M. whiteheadi, and M. surifer. Rat capture data was examined using several spatial factors. Factors that influence rat occurrence are found to be palm age, distance from road, distance from mill, and Normalized Difference Vegetation Index (NDVI) value. Binomial and multinomial logistic regression models were developed for prediction of rat occurrence In oil palm plantation. This study identified high, medium, and low rat occurrence area in oil palm plantation; highest rat occurrence (25.35% success rate, 95.31 % points with rat) was recorded in replanting area. Identification of high rat occurrence area allow effective placement of barn owl nest box, for addressing rat problems in resource saving and environmental friendly way. 2012 Thesis https://eprints.ums.edu.my/id/eprint/11823/ https://eprints.ums.edu.my/id/eprint/11823/1/mt0000000647.pdf text en public masters Universiti Malaysia Sabah School of International Tropical Forestry |
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English |
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QL Zoology |
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QL Zoology Chong, Chee Wey Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
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Rat damage in oil palm plantation brings significant economic losses. In this study, factors that influence rat occurrence were investigated using live trapping and GIS-based multicriteria analysis. 255 rats, mostly Rattus rattus diardii were captured using live trapping from nearly two thousands trap-night efforts. In oil palm plantation, rat species captured is R. r. diardii, R. argentiventer, Maxomys
whiteheadi. In forest, rat species captured is R. r. diardii, M. whiteheadi, and M. surifer. Rat capture data was examined using several spatial factors. Factors that influence rat occurrence are found to be palm age, distance from road, distance from mill, and Normalized Difference Vegetation Index (NDVI) value. Binomial and multinomial logistic regression models were developed for prediction of rat occurrence In oil palm plantation. This study identified high, medium, and low rat occurrence area in oil palm plantation; highest rat occurrence (25.35% success rate,
95.31 % points with rat) was recorded in replanting area. Identification of high rat occurrence area allow effective placement of barn owl nest box, for addressing rat problems in resource saving and environmental friendly way. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Chong, Chee Wey |
author_facet |
Chong, Chee Wey |
author_sort |
Chong, Chee Wey |
title |
Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
title_short |
Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
title_full |
Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
title_fullStr |
Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
title_full_unstemmed |
Evaluation of rat occurrence in oil palm plantations using GIS and remote sensing techniques |
title_sort |
evaluation of rat occurrence in oil palm plantations using gis and remote sensing techniques |
granting_institution |
Universiti Malaysia Sabah |
granting_department |
School of International Tropical Forestry |
publishDate |
2012 |
url |
https://eprints.ums.edu.my/id/eprint/11823/1/mt0000000647.pdf |
_version_ |
1747836429711441920 |