Automatic Habitat Classification Using Aerial Imagery

Habitat classification and its applications (e.g. habitat monitoring, identification of rare species, etcetera) are important challenges researched by environmental bodies and mapping agencies. However, manual habitat classification is labour intensive, costly, subjective and time consuming (Chen and Rau, 1997). From an image processing perspective, habitat classification can be achieved using two different approaches: a retrieval approach, whose objective is to retrieve photos from the same habitat as the query, and a classification approach, whose objective is to correctly classify the query image using photos from a database. In this paper, a content-based approach based on feature extraction from aerial imagery is described and its performance in these two scenarios is evaluated.