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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3978

Title: Quest for automated land cover change detection using satellite time series data
Authors: Salmon, BP
Olivier, JC
Kleynhans, W
Wessels, KJ
Van den Bergh, F
Keywords: MLP
Feedforward multilayer perceptron
Land cover
Satellites time series
Feedforward neural networks
MODIS data
MODerate-resolution imaging spectroradiometer
Remote sensing
Geosciences
Issue Date: Jul-2009
Publisher: IEEE
Citation: Salmon, BP, Olivier, JC et al. 2009. Quest for automated land cover change detection using satellite time series data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 244-247
Abstract: This paper shows that a feedforward Multilayer Perceptron (MLP) operating over a temporal sliding window of multispectral time series MODerate-resolution Imaging Spectroradiometer (MODIS) satellite data is able to detect land cover change that was artificially introduced by concatenating time series belonging to different types of land cover. The method employs an iteratively retrained MLP that is a supervised method, and thus captures all local environmental patterns. Depending on the length of the temporal sliding window used in the short-term Fourier transform, an overall change detection accuracy of between 87.62% and 97.02% was achieved. It is shown that for this type of simulated land cover change, where land cover change was abrupt, a short-term FFT window of 18 months or less, using only the two NDVI spectral bands of MODIS data was sufficient to detect change reliably.
Description: IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009
URI: http://hdl.handle.net/10204/3978
ISBN: 978-1-4244-3395-7
Appears in Collections:Radar and electronic warfare systems
Climate change
Earth observation
General science, engineering & technology
Earth observation technologies

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