Damaged building detection based on GF-1 satellite remote sensing image: A case study for Nepal M_S8.1 earthquake

The damaged buildings caused by an earthquake present different image features from that of the intact buildings, therefore the building damage information could be distinguished from a variety of target features. From this point of view, this paper proposed an approach for building damage detection by utilizing various features of the building blocks. Taking the GF-1 satellite image of the Nepal M_S8.1 earthquake occurred in 2015 as an example, this paper utilized blocks information provided by the GIS data, and classified the building blocks in the studied area into three categories of the intact, partly damaged and seriously destroyed, on the basis of the quantitative analysis results about texture features of remote sensing image and local spatial statistics of the building blocks. The test results demonstrated that the indicative key parameters extracted in this paper could effectively demonstrate the image characteristics of the damaged building, so that we can effectively conduct the classification and detection of building damage information caused by earthquakes with the proposed detection method in this paper. Also, it could provide guidance for earthquake emergency rescue, and it provides technical experiences and references for the building damage detection using the GF-1 data with independent intellectual property rights in our country.