Detection-based spatial mapping of sika deer using nighttime thermal UAV surveys in a satoyama landscape in Japan

We analysed 159 sika deer ( Cervus nippon Temminck, 1838) detection events recorded during a nighttime thermal unmanned aerial vehicle (UAV) survey in a satoyama landscape. Four statistical models were compared, and a generalized additive model was selected to generate a detection-based spatial map. Relative detection likelihood was highest near forest edges and agricultural land. The resulting map visualized spatial variation in nocturnal detection patterns. This study presents a preliminary example of detection-based spatial mapping. Because the analysis was based on a single-night survey, the results should be interpreted as relative detection likelihood rather than habitat use, occurrence probability, or abundance.