Elaeis guineensis Jacq. is a palm species of the Arecaceae’s family commonly called Oil palm; it is planted extensively in South-East Asia. Palm oil is the world highest yielding oil crop. Cultivation of oil palm in tropical countries, on one hand is an important economic factor, but, on the other hand, it endangers biodiversity and degrades the environment with a global impact. From this point of view, remote sensing can support a more efficient plantation management that takes into account their effects over environment. MODIS EVI maps obtained from the MODIS Vegetation Index, 16 days composite product (MOD13Q1), were used to monitoring tropical vegetation. In this work a EVI time series, covering 18 years, was processed to automatically detect new oil palm plantations an also giving an estimate of the age. The proposed methodology is simple enough, since automatic, to be retained useful to many stakeholders: governmental institutions and environmental associations could use it to continuously monitoring the state of the national natural/crop capital; landscape/territory planners can use it to read and drive pattern of changes; private owners and local farmers could be interested in assessing crop conditions for precision farming (a further improvement should be done).
MODIS DATA FOR DETECTION OF LANDSCAPE CHANGES BY OIL PALM PLANTATIONS IN BORNEO
DE PETRIS, Stefano;Drusi, B.;Borgogno Mondino, E.
Last
2018-01-01
Abstract
Elaeis guineensis Jacq. is a palm species of the Arecaceae’s family commonly called Oil palm; it is planted extensively in South-East Asia. Palm oil is the world highest yielding oil crop. Cultivation of oil palm in tropical countries, on one hand is an important economic factor, but, on the other hand, it endangers biodiversity and degrades the environment with a global impact. From this point of view, remote sensing can support a more efficient plantation management that takes into account their effects over environment. MODIS EVI maps obtained from the MODIS Vegetation Index, 16 days composite product (MOD13Q1), were used to monitoring tropical vegetation. In this work a EVI time series, covering 18 years, was processed to automatically detect new oil palm plantations an also giving an estimate of the age. The proposed methodology is simple enough, since automatic, to be retained useful to many stakeholders: governmental institutions and environmental associations could use it to continuously monitoring the state of the national natural/crop capital; landscape/territory planners can use it to read and drive pattern of changes; private owners and local farmers could be interested in assessing crop conditions for precision farming (a further improvement should be done).File | Dimensione | Formato | |
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