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The use of a Multilayer Perceptron for detecting new human settlements from a time series of MODIS images

Citation

Salmon, BP and Olivier, JC and Kleynhans, W and Wessels, KJ and van den Bergh, F and Steenkamp, KC, The use of a Multilayer Perceptron for detecting new human settlements from a time series of MODIS images, International Journal of Applied Earth Observation and Geoinformation, 13, (2) pp. 873-883. ISSN 0303-2434 (2011) [Refereed Article]

Abstract

This paper presents a novel land cover change detection method that employs a sliding window over hyper-temporal multi-spectral images acquired from the 7 bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product. The method uses a Feedforward Multilayer Perceptron (MLP) for supervised change detection that operates on multi-spectral time series extracted with a sliding window from the dataset. The method was evaluated on both real and simulated land cover change examples. The simulated land cover change comprises of concatenated time series that are produced by blending actual time series of pixels from human settlements to those from adjacent areas covered by natural vegetation. The method employs an iteratively retrained MLP to capture all local patterns and to compensate for the time-varying climate change in the geographical area. The iteratively retrained MLP was compared to a classical batch mode trained MLP. Depending on the length of the temporal sliding window used, an overall change detection accuracy between 83% and 90% was achieved. It is shown that a sliding window of 6 months using all 7 bands of MODIS data is sufficient to detect land cover change reliably. Window sizes of 18 months and longer provide minor improvements to classification accuracy and change detection performance at the cost of longer time delays.

Item Details

Item Type:Refereed Article
Keywords:change detection, classification, feedforward neural networks, satellite, time series
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Electrical and Electronic Engineering not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Salmon, BP (Dr Brian Salmon)
Author:Olivier, JC (Professor JC Olivier)
ID Code:77850
Year Published:2011
Deposited By:Engineering
Deposited On:2012-06-01
Last Modified:2014-12-05
Downloads:0

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