A spatio-temporal approach to detecting land cover change using an extended Kalman filter on MODIS time series data

A method for detecting land cover change using NDVI timeseries data derived from MODerate-resolution Imaging Spectroradiometer (MODIS) satellite data is proposed. The algorithm acts as a per pixel change alarm and takes as input the NDVI time-series of a 3x3 grid of MODIS pixels. An Extended Kalman Filter was used to estimate a series of parameters related to each NDVI signal. A spatial comparison between the center pixel of the the 3x3 grid and each of its neighboring pixels’ parameters was done to calculate a change metric which compared to a threshold yielded a change or no-change decision. The method was tested on real change examples in the study area and results indicate 90% detection of new settlements occurring in naturally vegetated areas.