Title :
Unsupervised Land Cover Change Detection: Meaningful Sequential Time Series Analysis
Author :
Salmon, Brian P. ; Olivier, Jan Corne ; Wessels, Konrad J. ; Kleynhans, Waldo ; Van den Bergh, Frans ; Steenkamp, Karen C.
Author_Institution :
Dept. of Electr., Electron. & Comput. Eng., Univ. of Pretoria, Pretoria, South Africa
fDate :
6/1/2011 12:00:00 AM
Abstract :
An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short term Fourier transform coefficients computed over subsequences of 8-day composite MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance data that were extracted with a temporal sliding window. The method uses a feature extraction process that creates meaningful sequential time series that can be analyzed and processed for change detection. The method was evaluated on real and simulated land cover change examples and obtained a change detection accuracy exceeding 76% on real land cover conversion and more than 70% on simulated land cover conversion.
Keywords :
Fourier transforms; geophysical image processing; image resolution; radiometers; terrain mapping; time series; Fourier transform coefficient; Moderate-Resolution Imaging Spectroradiometer surface reflectance data; automated land cover change detection method; coarse spatial resolution; feature extraction process; hypertemporal observation satellite time series data; land cover change simulation; land cover conversion simulation; sequential time series analysis; unsupervised land cover change detection method; Clustering algorithms; Data mining; Feature extraction; MODIS; Partitioning algorithms; Satellites; Time series analysis; Change detection; clustering; satellite; time series;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2010.2053918
