IDENTIFICATION OF ABANDONED OIL PALM AREAS FROM SATELLITE IMAGES

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Year:
2016
Type of Publication:
In Proceedings
Keywords:
Landsat, SPOT-6, crop phenology, object-oriented classification, remote sensing
Authors:
Yusoff, Noryusdiana Mohamad; Muharam, Farrah Melissa
Abstract:
Abandonment of agricultural land is a global issue; it is a waste of resources and brings a negative impact on local economy. It is also a key factor in certain environmental problems, such as soil erosion and increasing carbon sequestration. In order to address such problems related to land abandonment, their spatial distribution must first be precisely identified. This study utilized the satellite images together with crop phenology information, to identify abandoned oil palm areas. As acknowledged, oil palm is a commercial crop that is important for food value and as a biofuel, along with its other benefits towards human health. Currently, Malaysia cultivates approximately 5.64 million ha of oil palm, where 40% belongs to smallholders. To date, a study to identify abandoned oil palm areas using satellite images is almost non-existent. Conventionally, monitoring of abandoned oil palm lands, especially ones cultivated by smallholders is tedious and time consuming, especially over scattered, large areas. Hence, in this study, the capability of high resolution satellite image via SPOT-6 products to extract abandoned oil palm areas was explored, as was the use of multi-temporal Landsat Operational Land Imager (OLI) imageries to develop the phenology of abandoned oil palm sites. Homogeneity measures derived through SPOT images played a more important role to identify abandoned oil palm than crop phenology characteristics extracted from high spectral resolution of Landsat images. With the advancement of object-oriented classification, monitoring of abandoned oil palm areas can be done semi-automatically with an accuracy of 92%±1%.
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