Land cover change detection using autocorrelation analysis on MODIS time-series data : detection of new human settlements in the Gauteng province of South Africa

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Authors

Kleynhans, Waldo
Salmon, Brian Paxton
Olivier, Jan Corne
Van den Bergh, Frans
Wessels, K.J. (Konrad)
Grobler, Trienko Lups
Steenkamp, Karen C.

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Institute of Electrical and Electronics Engineers

Abstract

Human settlement expansion is one of the most pervasive forms of land cover change in the Gauteng province of South Africa. A method for detecting new settlement developments in areas that are typically covered by natural vegetation using 500 m MODIS time-series satellite data is proposed. The method is a per pixel change alarm that uses the temporal autocorrelation to infer a change index which yields a change or no-change decision after thresholding. Simulated change data was generated and used to determine a threshold during an off-line optimization phase. After optimization the method was evaluated on examples of known land cover change in the study area and experimental results indicate a 92% change detection accuracy with a 15% false alarm rate. The method shows good performance when compared to a traditional NDVI differencing method that achieved a 75% change detection accuracy with a 24% false alarm rate for the same study area.

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Keywords

Autocorrelation, Change detection, MODIS, Time series

Sustainable Development Goals

Citation

Kleynhans, W, Salmon, BP, Olivier, JC, Van Den Bergh, F, Wessels, KJ, Grobler, TL & Steenkamp, KC 2012, 'Land cover change detection using autocorrelation analysis on MODIS time-series data : detection of new human settlements in the gauteng province of South Africa', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 3, pp. 777-783.