Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but signs and mortality differ. Assessing the distribution and factors affecting AI incidence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hot spots or cold spots. We investigated potential factors affecting AI outbreaks in wild birds in Denmark and identified spatial clusters of virus positive and virus negative samples from 2006-2020. We obtained virus detection data from both passive (found dead, 2089 observations, with location coordinates) and active (healthy, 8912 observations, with location zip codes) AIV wild bird surveillance data from Dansk Fjerkræråd and the Danish Veterinary and Food Administration. For both the passive and active surveillance observations, we considered various landscape variables and fitted mixed logistic regression models to test landscape effects on the presence of AIV. In addition, for 2018 and 2019, we obtained data on release of game birds within Denmark, bred for hunting. We used mixed models to determine if these releases had an impact on AIV incidence during that period. Furthermore, we used SatScan to identify hot- and cold spots of AIV within Denmark. For the passive surveillance data, we found that distance to the coast (P<0.0001) and to wetlands were significant (P< 0.001), whereas none of the variables were significant for the active surveillance data. We used the passive surveillance data model (R2=0.51) to predict risk of AIV incidence throughout Denmark, and found that high-risk areas were mostly concentrated along the coast. For the game bird release, we found that the number of birds released had significant impact for the passive data (only years 2018-2019), and found no significance for the active surveillance data. The cluster analysis showed that, for both passive and active data, clusters varied over the years (some years having no significant clusters), but low risk clusters were seen in Jutland and northern Zealand, whereas high risk clusters were found both in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that AI may be affected by landscape variables, as coastal areas and wetlands attract waterfowl and migrating birds and may thus increase the potential for AIV transmission. Release of game birds for hunting might introduce AIV or increase local bird density and thus increase the transmission potential of AIV. These findings have enabled us to create risk maps of AIV incidence in wild birds based on passive surveillance data and pinpoint high-risk clusters within Denmark. This may aid targeted surveillance efforts within Denmark.