A Flexible Method for Urban Vegetation Cover Measurement Based on Remote Sensing Images
نویسندگان
چکیده
Traditional methods use NDVI to investigate vegetation cover from remote sensing imagery. These methods provide per-pixel vegetation distribution, and cause a modifiable areal unit problem (MAUP), when a meaningful statistical result is issued. In this paper, a new method based on advanced segmentation techniques and classification is proposed for urban vegetation investigation extraction. This method utilizes ASTER data to build a hierarchical multi-resolution structure, so as to reflecting the inherent relationship between ground features under various scale levels. By analyzing the hierarchical structure, a flexible measurement of urban vegetation cover index (VCI) is issued based on remote sensing imageries.
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