Near real-time deforestation monitoring in tropical ecosystems using satellite image time series

Here, we test and optimise an approach to monitor and detect tropical deforestation in near-real time by comparing it with a seasonal-trend model fitted onto the historical time series. The method detects disturbances in near-real time by comparing newly acquired satellite data with a modelled stable period based on historic satellite time series data. The method allows the differentiation between normal and abnormal change in near-real time and is based on the Break For Additive Seasonal Trend (BFAST) concept [5, 6, 7]. Testing is done by analysis of 16-day MODIS satellite image time series (MOD13Q1) for areas in the Brazilian Amazon region for which optimised deforestation systems (e.g. PRODESDETER, IMAZON) are available.