Forest land type precise classification based on SPOT5 and GF-1 images

The objective of this paper is to develop a hierarchical classification scheme and propose forest land type precise classification method based on SPOT5, GF-1 images, and other multi-source data, focusing on fine classification of forest land using high resolution remote sensing image in complex mountainous terrain conditions. The experiments were carried out by multi-source data integration, multiple features analysis and multiple classifier combination. The proposed method in this paper have advantages in fine identification of forest land types with high accuracy and high reliability, and the detail degree of fine identification reaches dominant tree species, which could fully meet the needs of forestry applications such as forest resources investigation, forest land change monitoring and thematic map digital update.