Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles

Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aer...

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Main Authors: Wong, Yong Bin, Gibbins, Chris, Azhar, Badrul, Phan, Su Shen, Scholefield, Paul, Azmi, Reza, Lechner, Alex M.
Format: Article
Published: Springer 2023
Online Access:http://psasir.upm.edu.my/id/eprint/109386/
https://link.springer.com/article/10.1007/s10661-023-11113-z
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.1093862024-08-05T03:47:50Z http://psasir.upm.edu.my/id/eprint/109386/ Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles Wong, Yong Bin Gibbins, Chris Azhar, Badrul Phan, Su Shen Scholefield, Paul Azmi, Reza Lechner, Alex M. Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aerial vehicles (UAV) to map smallholder farms and applied multi-criteria analysis to data generated from orthomosaics, to provide a set of sustainability indicators for the farms. Images were acquired from a UAV, with structure from motion (SfM) photogrammetry then used to produce orthomosaics and digital elevation models of the farm areas. Some of the inherent problems using high spatial resolution imagery for land cover classification were overcome by using texture analysis and geographic object-based image analysis (OBIA). Six spatially explicit environmental metrics were developed using multi-criteria analysis and used to generate sustainability indicator layers from the UAV data. The SfM and OBIA approach provided an accurate, high-resolution (~5 cm) image-based reconstruction of smallholder farm landscapes, with an overall classification accuracy of 89%. The multi-criteria analysis highlighted areas with lower sustainability values, which should be considered targets for adoption of sustainable management practices. The results of this work suggest that UAVs are a cost-effective tool for sustainability assessments of oil palm plantations, but there remains the need to plan surveys and image processing workflows carefully. Future work can build on our proposed approach, including the use of additional and/or alternative indicators developed through consultation with the oil palm industry stakeholders, to support certification schemes such as the Roundtable on Sustainable Palm Oil (RSPO). Springer 2023-04-17 Article PeerReviewed Wong, Yong Bin and Gibbins, Chris and Azhar, Badrul and Phan, Su Shen and Scholefield, Paul and Azmi, Reza and Lechner, Alex M. (2023) Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles. Environmental Monitoring and Assessment, 195. art. no. 577. pp. 1-29. ISSN 0167-6369; ESSN: 1573-2959 https://link.springer.com/article/10.1007/s10661-023-11113-z 10.1007/s10661-023-11113-z
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aerial vehicles (UAV) to map smallholder farms and applied multi-criteria analysis to data generated from orthomosaics, to provide a set of sustainability indicators for the farms. Images were acquired from a UAV, with structure from motion (SfM) photogrammetry then used to produce orthomosaics and digital elevation models of the farm areas. Some of the inherent problems using high spatial resolution imagery for land cover classification were overcome by using texture analysis and geographic object-based image analysis (OBIA). Six spatially explicit environmental metrics were developed using multi-criteria analysis and used to generate sustainability indicator layers from the UAV data. The SfM and OBIA approach provided an accurate, high-resolution (~5 cm) image-based reconstruction of smallholder farm landscapes, with an overall classification accuracy of 89%. The multi-criteria analysis highlighted areas with lower sustainability values, which should be considered targets for adoption of sustainable management practices. The results of this work suggest that UAVs are a cost-effective tool for sustainability assessments of oil palm plantations, but there remains the need to plan surveys and image processing workflows carefully. Future work can build on our proposed approach, including the use of additional and/or alternative indicators developed through consultation with the oil palm industry stakeholders, to support certification schemes such as the Roundtable on Sustainable Palm Oil (RSPO).
format Article
author Wong, Yong Bin
Gibbins, Chris
Azhar, Badrul
Phan, Su Shen
Scholefield, Paul
Azmi, Reza
Lechner, Alex M.
spellingShingle Wong, Yong Bin
Gibbins, Chris
Azhar, Badrul
Phan, Su Shen
Scholefield, Paul
Azmi, Reza
Lechner, Alex M.
Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
author_facet Wong, Yong Bin
Gibbins, Chris
Azhar, Badrul
Phan, Su Shen
Scholefield, Paul
Azmi, Reza
Lechner, Alex M.
author_sort Wong, Yong Bin
title Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
title_short Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
title_full Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
title_fullStr Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
title_full_unstemmed Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
title_sort smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles
publisher Springer
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/109386/
https://link.springer.com/article/10.1007/s10661-023-11113-z
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