In The Ugandan situation two decades ago, the country was faced with deteriorating economic, social and environmental conditions. The approach we use to link these problems uses statistical estimation techniques. Our approach to the analysis of the links between poverty and biomass using maps begins with the construction of a poverty map. A test is done to compare the means for the survey and census variables that pass the significance test are considered for the regression analysis. A logical next step is to make the connection between welfare and biophysical information. Obtaining information on biomass use for administrative units is not straightforward, because of confidentiality, different data formats, the intricacies of geo-analysis and because environmental conditions do not follow administrative boundaries. The preliminary poverty estimates for rural Uganda control for spatial autocorrelation solely by relying on Population Sampling Unit or (PSU) means calculated from the census. By controlling for biophysical characteristics of the estimation procedure, the efficiency of the derived poverty estimates may be improved, leading to more precise estimates and enhancing the level of spatial disaggregation that is attainable.