Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data
Rats (Rattus spp.) can cause substantial economic loss to oil palm (Elaeis quineensis Jacq.) plantations. Spatial occurrence of rat in oil palm plantation has not been adequately dealt. We evaluated the rat occurrence at an oil palm plantation in Sabah, Malaysia using habitat factors from GIS and Ge...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
2016
|
| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/20543/1/Predicting%20rat%20occurrence%20in%20oil.pdf |
| _version_ | 1796910007398170624 |
|---|---|
| author | Phua, Mui How Chee, Wey Chong Abdul Hamid Ahmad Mohd Noor Hafidzi |
| author_facet | Phua, Mui How Chee, Wey Chong Abdul Hamid Ahmad Mohd Noor Hafidzi |
| author_sort | Phua, Mui How |
| collection | UMS |
| description | Rats (Rattus spp.) can cause substantial economic loss to oil palm (Elaeis quineensis Jacq.) plantations. Spatial occurrence of rat in oil palm plantation has not been adequately dealt. We evaluated the rat occurrence at an oil palm plantation in Sabah, Malaysia using habitat factors from GIS and GeoEye data. Among the regression models examined, binomial logistic regression model best predicted the rat occurrence. Overall accuracy of the occurrence prediction calculated from an independent dataset was
nearly 80%. The results allow us to identify factors of rat occurrence and recommend necessary control measures to the
plantation management. |
| first_indexed | 2024-03-06T02:58:02Z |
| format | Article |
| id | ums.eprints-20543 |
| institution | Universiti Malaysia Sabah |
| language | English |
| last_indexed | 2024-03-06T02:58:02Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ums.eprints-205432018-07-24T01:23:26Z https://eprints.ums.edu.my/id/eprint/20543/ Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data Phua, Mui How Chee, Wey Chong Abdul Hamid Ahmad Mohd Noor Hafidzi QK Botany Rats (Rattus spp.) can cause substantial economic loss to oil palm (Elaeis quineensis Jacq.) plantations. Spatial occurrence of rat in oil palm plantation has not been adequately dealt. We evaluated the rat occurrence at an oil palm plantation in Sabah, Malaysia using habitat factors from GIS and GeoEye data. Among the regression models examined, binomial logistic regression model best predicted the rat occurrence. Overall accuracy of the occurrence prediction calculated from an independent dataset was nearly 80%. The results allow us to identify factors of rat occurrence and recommend necessary control measures to the plantation management. 2016 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/20543/1/Predicting%20rat%20occurrence%20in%20oil.pdf Phua, Mui How and Chee, Wey Chong and Abdul Hamid Ahmad and Mohd Noor Hafidzi (2016) Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data. Environmental Engineering and Management Journal, 15 (11). pp. 2511-2518. |
| spellingShingle | QK Botany Phua, Mui How Chee, Wey Chong Abdul Hamid Ahmad Mohd Noor Hafidzi Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title | Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title_full | Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title_fullStr | Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title_full_unstemmed | Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title_short | Predicting rat occurrence in oil-palm plantation using GIS and GeoEye data |
| title_sort | predicting rat occurrence in oil palm plantation using gis and geoeye data |
| topic | QK Botany |
| url | https://eprints.ums.edu.my/id/eprint/20543/1/Predicting%20rat%20occurrence%20in%20oil.pdf |
| work_keys_str_mv | AT phuamuihow predictingratoccurrenceinoilpalmplantationusinggisandgeoeyedata AT cheeweychong predictingratoccurrenceinoilpalmplantationusinggisandgeoeyedata AT abdulhamidahmad predictingratoccurrenceinoilpalmplantationusinggisandgeoeyedata AT mohdnoorhafidzi predictingratoccurrenceinoilpalmplantationusinggisandgeoeyedata |