Abstract
Following the advancement and progression of urbanization, management problems of the wildland–urban interface (WUI) have become increasingly serious. WUI regional governance issues involve many factors including climate, humanities, etc., and have attracted attention and research from all walks of life. Building research plays a vital part in the WUI area. Building location is closely related with the planning and management of the WUI area, and the number of buildings is related to the rescue arrangement. There are two major methods to obtain this building information: one is to obtain them from relevant agencies, which is slow and lacks timeliness, while the other approach is to extract them from high-resolution remote sensing images, which is relatively inexpensive and offers improved timeliness. Inspired by the recent successful application of deep learning, in this paper, we propose a method for extracting building information from high-resolution remote sensing images based on deep learning, which is combined with ensemble learning to extract the building location. Further, we use the idea of image anomaly detection to estimate the number of buildings. After verification on two datasets, we obtain superior semantic segmentation results and achieve better building contour extraction and number estimation.
Highlights
The wildland–urban interface (WUI), a formal land classification specification, first appeared in the research budget of the US Forest Service in 1978
By adjusting the model structure and training parameters, we obtain the prediction models under different conditions and use the idea of ensemble learning to obtain the final result of our semantic segmentation
We proposed a method for calculating the number of buildings based on deep learning
Summary
The wildland–urban interface (WUI), a formal land classification specification, first appeared in the research budget of the US Forest Service in 1978. It is used for urban areas that need to be strengthened for fire protection [1]. Because the WUI is located at the boundary between the city and the wasteland, mountain fires caused by climate change or human factors are likely to affect the residential areas. The management of this kind of area cannot be considered the same as that for a wasteland. With the acceleration of urbanization and the deepening of climate change, extreme weather events of forest fires have become more frequent and serious [3]. With the emergence of several global fires in recent years, researchers worldwide are very concerned about fires in WUI areas and their prevention
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