Bioenergy Crop Identification at Field Scale Using VHR Airborne CIR Imagery

Abstract

The present study is aimed at developing a methodology to extract maize, a predominant energy crop, and efficiently map its spatial distribution in a Natura 2000 region of northern Germany. Following a GEOBIA approach, segmentation was performed on two hierarchical levels. Level 1 consisted of field boundaries, and level 2 represented variations within level 1. Decision rules were developed for level 2 based on spectral information, vegetation indices, standard deviations and knowledge of crop phenology. For this purpose, first, level 2 image objects were classified. Subsequently classification was shifted to level 1. Maize covered 10.6 percent of total study area. The presented methodology gives the advanced user the flexibility to integrate expert knowledge in the classifier. In addition, the implementation time of decision rules was very fast and helped to produce results with high accuracy.