An Improved Urban Mapping Strategy Based on Collaborative Processing of Optical and SAR Remotely Sensed Data

作者：Han, Ruimei; Liu, Pei^*; Wang, Han; Yang, Leiku; Zhang, Hanwei; Ma, Chao

来源：Mathematical Problems in Engineering, 2017, 2017: 9361592.

DOI：10.1155/2017/9361592

• FUSION METHODS
• IMAGE
• CLASSIFICATION
• RECOGNITION
• EXTRACTION

Potential of combining SAR and optical remotely sensed data for rapid urbanmapping is highlight. Two groups of optical and SAR remotely sensed data are selected to evaluate the strategy. Outputs are verified and analyzed from 3 aspects. The single class and mergedmap accuracy are evaluated; the proposedmethod is compared with 2mature algorithms; the selected classifiers are applied to 7 different fusion algorithms to make further comprehension. The outcomes illustrate the potential of synergic optical and SAR data for monitoring urbanization status and demonstrate that the proposed SAR/optical information synergy method improved the capabilities of urban mapping compared with separately using SAR and optical data. The results demonstrate that the proposed method canmap built-up area, water body, and vegetation at accuracy of 99.31%, 91.92%, and 91.72%, respectively. These results are much better than when solo optical or SAR data was selected and better than classification results based onmature fusionmethods. The main contributions of this article are as follows: the proposal of a rapid urban mapping strategy based on integration of optical and SAR data and the verifying and analysis of potential of synergic optical and SAR data for rapid urban mapping.

• 出版日期2017
• 单位河南理工大学