Integrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping

Abstract

The combination of elevation data together with multispectral high-resolution images is a new methodology for obtaining land use/land cover classification. It represents a step forward for both the accuracy and automation of LULC applications and allows users to setup thematic assignments through rules based on feature attributes and human expert interpretation of land usage. The synergy between different types of information means that LiDAR can give new hints at both the segmentation and hybrid classification steps, leading to a joint use of multispectral, spatial and elevation data. The output is a thematic map characterized by a custom-designed legend that is able to discriminate between land cover classes with similar spectral characteristics (level 3 of the CLC legend). Experimental results from a hilly farmland area with some urban structures (Musone river basin, Ancona, Italy) are used to highlight how the proposed methodology enhances land cover classification in heterogeneous environments.

Keywords

• Hybrid (pixel/object) classification
• Land Use/Land Cover (LULC)
• LiDAR
• Multispectral images
• Data integration
• Winner-Takes-All (WTA)
• CLC