Sciweavers

Share
IGARSS
2009

The Quest for Automated Land Cover Change Detection using Satellite Time Series Data

9 years 5 months ago
The Quest for Automated Land Cover Change Detection using Satellite Time Series Data
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.
Brian P. Salmon, Jan C. Olivier, Waldo Kleynhans,
Added 20 Feb 2011
Updated 20 Feb 2011
Type Journal
Year 2009
Where IGARSS
Authors Brian P. Salmon, Jan C. Olivier, Waldo Kleynhans, Konrad J. Wessels, Frans van den Bergh
Comments (0)
books