Exploring the synergistic use of multi-scale image object metrics for land-use/land-cover mapping using an object-based approach

Abstract

This study presents a new method for the synergistic use of multi-scale image object metrics for land-use/land-cover mapping using an object-based classification approach. This new method can integrate an object with its super-objects’ metrics. The entire classification involves two object hierarchies: (1) a five-level object hierarchy to extract object metrics at five scales, and (2) a three-level object hierarchy for the classification process. A five-level object hierarchy was developed through multi-scale segmentation to calculate and extract both spectral and textural metrics. Layers representing the hierarchy at each of the five scales were then intersected by using the overlay tool, an intersected layer was created with metrics from all five scales, and the same geometric elements were retained as those of the objects of the lowest level. A decision tree analysis was then used to build rules for the classification of the intersected layer, which subsequently served as the thematic layer in a three-level object hierarchy to identify shadow regions and produce the final map. The use of multi-scale object metrics yielded improved classification results compared with single-scale metrics, which indicates that multi-scale object metrics provide valuable spatial information. This method can fully utilize metrics at multiple scales and shows promise for use in object-based classification approaches.

Acknowledgement

We would like to thank the Anji Forestry Bureau for providing assistance in fieldwork.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [31300535, 41371411, and 41201365], Natural Science Foundation of Zhejiang Province [LQ12D01006, LQ13C160002 and LR14C160001], Project for Innovation in Forest Carbon Sequestration and Measurement of Zhejiang Province [2012R10030-01], Zhejiang A & F University Research and Development Fund [2012FR073], and Research Centre of Agricultural and Forestry Carbon Sinks and Ecological Environmental Remediation, Zhejiang A & F University.