Abstract
Spatial data modelling and consequential error estimation of the distribution function are key points of spatial analysis. For many practical problems, it is impossible to hypothesize distribution function firstly and some distribution models, such as Gaussian distribution, may not suit to complicated distribution in practice. The paper shows the possibility of the approach based on the maximum entropy theory that can optimally describe the spatial data distribution and gives  the actual error estimation. 
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