Cargando…
Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions
Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterat...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063057/ https://www.ncbi.nlm.nih.gov/pubmed/24811079 http://dx.doi.org/10.3390/s140508259 |
_version_ | 1782321739164811264 |
---|---|
author | Razali, Sheriza Mohd Marin, Arnaldo Nuruddin, Ahmad Ainuddin Shafri, Helmi Zulhaidi Mohd Hamid, Hazandy Abdul |
author_facet | Razali, Sheriza Mohd Marin, Arnaldo Nuruddin, Ahmad Ainuddin Shafri, Helmi Zulhaidi Mohd Hamid, Hazandy Abdul |
author_sort | Razali, Sheriza Mohd |
collection | PubMed |
description | Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. |
format | Online Article Text |
id | pubmed-4063057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-40630572014-06-19 Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions Razali, Sheriza Mohd Marin, Arnaldo Nuruddin, Ahmad Ainuddin Shafri, Helmi Zulhaidi Mohd Hamid, Hazandy Abdul Sensors (Basel) Article Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. Molecular Diversity Preservation International (MDPI) 2014-05-07 /pmc/articles/PMC4063057/ /pubmed/24811079 http://dx.doi.org/10.3390/s140508259 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Razali, Sheriza Mohd Marin, Arnaldo Nuruddin, Ahmad Ainuddin Shafri, Helmi Zulhaidi Mohd Hamid, Hazandy Abdul Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title | Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title_full | Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title_fullStr | Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title_full_unstemmed | Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title_short | Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions |
title_sort | capability of integrated modis imagery and alos for oil palm, rubber and forest areas mapping in tropical forest regions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4063057/ https://www.ncbi.nlm.nih.gov/pubmed/24811079 http://dx.doi.org/10.3390/s140508259 |
work_keys_str_mv | AT razalisherizamohd capabilityofintegratedmodisimageryandalosforoilpalmrubberandforestareasmappingintropicalforestregions AT marinarnaldo capabilityofintegratedmodisimageryandalosforoilpalmrubberandforestareasmappingintropicalforestregions AT nuruddinahmadainuddin capabilityofintegratedmodisimageryandalosforoilpalmrubberandforestareasmappingintropicalforestregions AT shafrihelmizulhaidimohd capabilityofintegratedmodisimageryandalosforoilpalmrubberandforestareasmappingintropicalforestregions AT hamidhazandyabdul capabilityofintegratedmodisimageryandalosforoilpalmrubberandforestareasmappingintropicalforestregions |