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Habitat relationships of northern bobwhite have been developed based on research that historically has been conducted at a scale of high resolution (grain) but small extent.� The relationships arising from such research trajectory therefore have been limited to study areas. �Large-scale studies assessing bobwhite-habitat relationships recently have tried to overcome this limitation by increasing the extent; however, in doing so, there often has been a corresponding decrease in resolution. To effectively evaluate wildlife-habitat relationships, a study should seek to maintain the resolution of a small-scale study while simultaneously increasing the extent to that of a large-scale study.� Although such an approach historically has been infeasible with prior field- and GIS-based methods, a high-grain/large-extent approach may be possible with recent developments in density surface modeling, which is a spatial extension of conventional distance sampling.� This method utilizes information regarding probability of detection as well as geographic information, and can provide density estimates at high grains (<1 ha) across fairly large extents (>10,000 ha).� Our objective was to investigate the spatial effects of habitat features on bobwhite density using a high-grain/large extent approach.� We determined bobwhite density across 20,560 ha of rangeland within southern Texas utilizing a helicopter-based, distance sampling approach.� We developed a binary classification of brush and open/herbaceous cover using National Agricultural Imagery Program aerial imagery. �From this initial classification we were able to determine multiple metrics of habitat quality. �We analyzed the effects of habitat features on bobwhite density using a density surface modeling framework, first fitting a detection function model to helicopter survey data, then fitting a density surface model, using individual habitat covariates as explanatory variables.� Through this method we were able to estimate both bobwhite density and its relationship to habitat features at a high-grain across a relatively large extent.