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Modelling forest canopy trends with on-demand spatial simulation

Understanding trends in forest canopy cover at local, national, and global scales is important for many applications, including policymaking related to forest carbon sequestration. Globally consistent land-cover data sets derived from MODerate-resolution Imaging Spectroradiometer (MODIS) are now available for a period of more than 10 years, long enough to detect trends both in deforestation and in afforestation. However, methods of modelling land-cover change normally require specialized software and expertise, limiting the availability of this information. This barrier to access can be eliminated through the use of web services that construct models on demand based on user-specified regions of interest, so that parameters are inferred from, and relevant to, local conditions. In this paper we present a proof-of-concept system for building and running spatial Markov chain models of forest-cover change on demand, and demonstrate how the on-demand approach may be implemented for similar applications.