Automatic Detection of Hedges and Orchards Using Very High Spatial Resolution Imagery

Automatic mapping and monitoring of agricultural landscapes using remotely sensed imagery has been an important research problem. This paper describes our work on developing automatic methods for the detection of target landscape features in very high spatial resolution images. The target objects of interest consist of hedges that are linear strips of woody vegetation and orchards that are composed of regular plantation of individual trees. We employ spectral, textural, and shape information in a multi-scale framework for automatic detection of these objects. Extensive experiments show that the proposed algorithms provide good localization of the target objects in a wide range of landscapes with very different characteristics.