A new method for estimating the geographical distribution of plant and animal species from incomplete field survey data is developed. Wildlife surveys are often conducted by dividing a study region into a regular grid and collecting data on abundance or on presence/absence from some or all of the squares in the grid. Generalized linear models can be used to model the spatial distribution of a species within such a grid by relating the response variable (abundance or presence/absence) to spatially referenced covariates. Such models ignore or at best indirectly model dependence or unmeasured covariates, and the intrinsic spatial autocorrelation arising for example in gregarious populations. A procedure for use with presence/absence data in which spatial autocorrelation is modelled explicitly is achieved by extending a logistic model to include an extra covariate which is derived from the responses at neighbouring squares. The extended model is known as an autologistic model.