Fully Convolutional Neural Networks for Mapping Oil Palm Plantations in Kalimantan

Baklanov A, Khachay M, & Pasynkov M (2019). Fully Convolutional Neural Networks for Mapping Oil Palm Plantations in Kalimantan. In: Learning and Intelligent Optimization. Eds. Battiti, R., Brunato, M., Kotsireas, I. & Pardalos, P., pp. 427-432 Cham, Switzerland: Springer. ISBN 978-3-030-05347-5 DOI:10.1007/978-3-030-05348-2_35.

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Abstract

This research is motivated by the global warming problem, which is likely influenced by human activity. Fast-growing oil palm plantations in the tropical belt of Africa, Southeast Asia and parts of Brazil lead to significant loss of rainforest and contribute to the global warming by the corresponding decrease of carbon dioxide absorption. We propose a novel approach to monitoring of the development of such plantations based on an application of state-of-the-art Fully Convolutional Neural Networks (FCNs) to solve Semantic Segmentation Problem for Landsat imagery.

Item Type: Book Section
Uncontrolled Keywords: Remote sensing; Mapping; Landsat; Fully convolutional neural network
Research Programs: Advanced Systems Analysis (ASA)
Depositing User: Luke Kirwan
Date Deposited: 07 Jan 2019 07:25
Last Modified: 07 Jan 2019 07:25
URI: http://pure.iiasa.ac.at/15655

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