Building height extraction method based on sub-meter remote sensing image and its verification

doi:10.13474/j.cnki.11-2246.2022.0244

Abstract

Abstract: Building height is the basic reference data in modern urban monitoring, planning, management and economic activities. In order to realize the extraction of building height information, this paper presents a method for inversion of building height based on Boltzmann curve. First of all, through the spectral characteristics of the building image, the method of multi-scale segmentation and remote sensing index classification are used to obtain the interesting area of the building shadow, then we obtain the sub-pixel position of the shadow according to the Boltzmann curve function in order to get the shadow boundary by linear fitting. After that, a height inversion model based on the geometric relationship between the sun, satellites, buildings and their shadows is built. Finally, Ninghai county is selected as the experimental area, and the main satellite remote sensing data of GF-2, GJ-1, Beijing-2 and WorldView-2 which spatial resolution are better than 1m on orbit for accuracy verification. The experimental results show that the medium error in the calculated building height is better than 2.5meters, which can be used for urban satellite remote sensing monitoring.

Key words: sub-meter remote sensing image, Boltzmann curve, sub-pixel shadow extraction, building height extraction and verification

CLC Number:

P237

LIU Xiaozhong, FENG Cunjun, DENG Xiaoyuan, ZHAN Yuanzeng, YU Hui, WANG Xingkun. Building height extraction method based on sub-meter remote sensing image and its verification[J]. Bulletin of Surveying and Mapping, 2022, 0(8): 128-132.

References

[1] 赫晓慧,李满堂,郭恒亮,等.高分二号卫星影像中城市建筑物阴影检测方法[J].中国科技论文,2019,14(7):789-796.
[2] MAGRUDAR L,NEUENSCHWANDER A,KLOTZ B.Digital terrain model elevation corrections using space-based imagery and ICESat-2 laser altimetry[J].Remote Sensing of Environment,2021,264: 112621.
[3] 李德仁.我国第一颗民用三线阵立体测图卫星——资源三号测绘卫星[J].测绘学报,2012,41(3):317-322.
[4] 陈冲,杨志勇,史晓亮,等.基于Google Earth遥感影像的城市建筑物高度反演[J].测绘通报,2020(1):98-101.
[5] 韩雪培,徐建刚,付小毛.基于高分辨率遥感影像的城市建筑容积率估算方法研究——以上海市中心城区为例[J].遥感信息,2005(2):24-28.
[6] 何国金,陈刚,何晓云,等.利用SPOT图象阴影提取城市建筑物高度及其分布信息[J].中国图象图形学报,2001,6(5):425-428.
[7] 张晓美,何国金,王威,等.基于ALOS卫星图像阴影的天津市建筑物高度及分布信息提取[J].光谱学与光谱分析,2011,31(7):2003-2006.
[8] 冉琼,迟耀斌,王智勇,等.基于“北京一号”小卫星影像阴影的建筑物高度测算研究[J].遥感信息,2008,23(4): 18-21.
[9] 田新光,张继贤,张永红.利用QuickBird影像的阴影提取建筑物高度[J].测绘科学,2008,33(2):88-89.
[10] 赵强,杨志,苏红超,等.基于高分二号卫星遥感数据的建筑物高度提取[J].大气与环境光学学报,2019,14(6):455-462.
[11] LIASIS G,STAVROU S.Satellite images analysis for shadow detection and building height estimation[J].ISPRS Journal of Photogrammetry and Remote Sensing,2016,119: 437-450.
[12] 韩东成,杨世植,赵强,等.面向对象的高分辨率遥感影像建筑物信息提取[J].大气与环境光学学报,2021,16(4):358-364.
[13] 田峰,陈冬花,黄新利,等.基于形态学阴影指数的高分二号影像建筑物高度估计[J].遥感技术与应用,2017,32(5):844-850.
[14] 陈云浩,冯通,史培军,等.基于面向对象和规则的遥感影像分类研究[J].武汉大学学报(信息科学版),2006,31(4):316-320.

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