Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data
Rats are an important vertebrate pest of oil palm in Malaysia. This damage translates into substantial economic loss to the oil palm plantation sector. We used habitat factors dervived from GIS data to develop a logistic regression model to predict rat occurrence in a FELDA oil palm plantation in Sa...
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ftunivmalaysab:oai:eprints.ums.edu.my:24362 2023-05-15T18:05:20+02:00 Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data Phua, Mui How C. W. Chong A. H. Ahmad M. N. Hafidzi 2018 text http://eprints.ums.edu.my/id/eprint/24362/ http://eprints.ums.edu.my/id/eprint/24362/1/Understanding%20rat%20occurrences%20in%20oil%20palm%20plantation%20using%20high-resolution%20satellite%20image%20and%20GIS%20data.pdf https://doi.org/10.1007/s11119-016-9496-z en eng http://eprints.ums.edu.my/id/eprint/24362/1/Understanding%20rat%20occurrences%20in%20oil%20palm%20plantation%20using%20high-resolution%20satellite%20image%20and%20GIS%20data.pdf Phua, Mui How and C. W. Chong and A. H. Ahmad and M. N. Hafidzi (2018) Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data. Precision Agric, 19. pp. 42-54. QL Zoology SF Animal culture Article PeerReviewed 2018 ftunivmalaysab https://doi.org/10.1007/s11119-016-9496-z 2022-03-29T15:39:40Z Rats are an important vertebrate pest of oil palm in Malaysia. This damage translates into substantial economic loss to the oil palm plantation sector. We used habitat factors dervived from GIS data to develop a logistic regression model to predict rat occurrence in a FELDA oil palm plantation in Sabah, Malaysia. Our logistic regression results predicted a high occurrence of rats in young palms areas (\3 years) and in areas near the plantation roads. The rat occurrence areas were further examined using a detailed land cover types generated from a high-resolution satellite image (GeoEye, spatial resolution: 0.5 m). Our results showed that the combination of bare or open areas bushes mixed with partial shades of young palms is important to the survival of Rattus rattus diardii, a highly adaptable rat species that dominated the plantation. The combined use of GIS and high-resolution satellite remote sensing techniques enhanced our understanding of rat occurrence in oil palm plantation. Our results suggest these techniques can be used to predict rat occurrence and can be used to guide the rat baiting program in the oil palm plantation. Article in Journal/Newspaper Rattus rattus Universiti Malaysia Sabah: UMS Institutional Repository Precision Agriculture 19 1 42 54 |
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Open Polar |
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Universiti Malaysia Sabah: UMS Institutional Repository |
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ftunivmalaysab |
language |
English |
topic |
QL Zoology SF Animal culture |
spellingShingle |
QL Zoology SF Animal culture Phua, Mui How C. W. Chong A. H. Ahmad M. N. Hafidzi Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
topic_facet |
QL Zoology SF Animal culture |
description |
Rats are an important vertebrate pest of oil palm in Malaysia. This damage translates into substantial economic loss to the oil palm plantation sector. We used habitat factors dervived from GIS data to develop a logistic regression model to predict rat occurrence in a FELDA oil palm plantation in Sabah, Malaysia. Our logistic regression results predicted a high occurrence of rats in young palms areas (\3 years) and in areas near the plantation roads. The rat occurrence areas were further examined using a detailed land cover types generated from a high-resolution satellite image (GeoEye, spatial resolution: 0.5 m). Our results showed that the combination of bare or open areas bushes mixed with partial shades of young palms is important to the survival of Rattus rattus diardii, a highly adaptable rat species that dominated the plantation. The combined use of GIS and high-resolution satellite remote sensing techniques enhanced our understanding of rat occurrence in oil palm plantation. Our results suggest these techniques can be used to predict rat occurrence and can be used to guide the rat baiting program in the oil palm plantation. |
format |
Article in Journal/Newspaper |
author |
Phua, Mui How C. W. Chong A. H. Ahmad M. N. Hafidzi |
author_facet |
Phua, Mui How C. W. Chong A. H. Ahmad M. N. Hafidzi |
author_sort |
Phua, Mui How |
title |
Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
title_short |
Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
title_full |
Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
title_fullStr |
Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
title_full_unstemmed |
Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data |
title_sort |
understanding rat occurrences in oil palm plantation using high-resolution satellite image and gis data |
publishDate |
2018 |
url |
http://eprints.ums.edu.my/id/eprint/24362/ http://eprints.ums.edu.my/id/eprint/24362/1/Understanding%20rat%20occurrences%20in%20oil%20palm%20plantation%20using%20high-resolution%20satellite%20image%20and%20GIS%20data.pdf https://doi.org/10.1007/s11119-016-9496-z |
genre |
Rattus rattus |
genre_facet |
Rattus rattus |
op_relation |
http://eprints.ums.edu.my/id/eprint/24362/1/Understanding%20rat%20occurrences%20in%20oil%20palm%20plantation%20using%20high-resolution%20satellite%20image%20and%20GIS%20data.pdf Phua, Mui How and C. W. Chong and A. H. Ahmad and M. N. Hafidzi (2018) Understanding rat occurrences in oil palm plantation using high-resolution satellite image and GIS data. Precision Agric, 19. pp. 42-54. |
op_doi |
https://doi.org/10.1007/s11119-016-9496-z |
container_title |
Precision Agriculture |
container_volume |
19 |
container_issue |
1 |
container_start_page |
42 |
op_container_end_page |
54 |
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1766176798744248320 |