一种结合阴影信息的建筑物层数识别方法

doi:10.6046/zrzyyg.2022226

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摘要

建筑物层数获取可为城市安全和灾害隐患提供数据支撑和决策服务。目前,建筑物层数往往是基于人工调研和统计为主; 基于遥感影像的建筑物高度自动反演,也存在算法效率低、提取不完整、自动化程度偏低等问题。为解决这些问题,实现快速和大范围获取建筑物层数,基于GF-7卫星影像,设计、实现了一种楼层数识别的算法,在主成分分析等预处理的基础上,采用渔网法阴影线自动提取算法,并利用阴影形成的几何关系计算楼高并转换为楼层数,最终为消除阴影长度测量误差的影响,采用支持向量机回归对算法提取结果进行误差改正。以北京市朝阳区为研究区,进行模型的训练与测试; 以河南省郑州市为验证区的实验结果表明,建筑物层数总体识别精度为90.21%,6~50层的建筑物层数识别误差在3层以内。研究可为基于卫星数据快速和大范围自动获取建筑物层数提供全新的技术支撑和应用服务。

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	李志新
	王梦飞
	贾伟洁
	纪松
	王宇飞

关键词 ：建筑物阴影检测, 特征优化, 渔网法阴影线自动提取, 支持向量机回归, 建筑物层数识别

Abstract：

Acquiring the number of building floors can provide data support and decision-making services for urban safety and disaster hazards. The number is primarily acquired through manual investigation and statistics currently. Furthermore, the automatic inversion of building heights based on remote sensing images suffers from low algorithmic efficiency, incomplete extraction, and a low automation degree. To acquire the number of building floors quickly and extensively, this study designed an identification algorithm based on GF-7 satellite images. First, shadow lines were automatically extracted using the fishing net method based on preprocessing such as principal component analysis. Then, the building height was calculated based on the geometric relationship formed by the shadow, and the building height was then converted into the number of building floors. Finally, the error in the extraction results was corrected through support vector machine regression, aiming to eliminate the influence of the measurement error of the shadow length. With Chaoyang District in Beijing as the study area, this study conducted model training and testing of the identification algorithm. As shown by the experimental results with Zhengzhou City in Henan Province as the verification area, the overall identification accuracy was 90.21%, with an identification error of three floors at most for buildings with 6~50 floors. This study provides novel technical support and application service for automatically acquiring the number of building floors rapidly and extensively based on satellite data.

Key words： detection of building shadow feature optimization automatic extraction of shadow lines based on the fishing net method support vector machine regression identification of the number of building floors

收稿日期: 2022-06-01 出版日期: 2023-09-19

ZTFLH:

TP79

基金资助:国家自然科学基金项目“高分辨率卫星影像协同处理与定位能力星间传递技术研究”(41971427);国防科工局项目“高分遥感测绘应用示范系统(二期)”(42-Y30B04-9001-19/21)

通讯作者: 王梦飞(1980-),男,博士,正高级工程师,主要从事遥感地质研究。Email: wmf1980@qq.com。

作者简介: 李志新(1997-),男,硕士研究生,主要从事数字摄影测量研究。Email: 1294622314@qq.com。

引用本文:

李志新, 王梦飞, 贾伟洁, 纪松, 王宇飞. 一种结合阴影信息的建筑物层数识别方法[J]. 自然资源遥感, 2023, 35(3): 97-106.
LI Zhixin, WANG Mengfei, JIA Weijie, JI Song, WANG Yufei. A method for identifying the number of building floors based on shadow information. Remote Sensing for Natural Resources, 2023, 35(3): 97-106.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2022226 或 https://www.gtzyyg.com/CN/Y2023/V35/I3/97

Fig.1 建筑物楼层提取流程

Fig.2 阴影提取及优化流程

Fig.3 阴影线长度计算流程

Fig.4 太阳、卫星和建筑物关系示意图

Fig.5 研究区样本区域

Fig.6 百度全景四方位图

Tab.1 样本数据

Tab.2 研究区楼层提取结果示例

Tab.3 建筑物层数测试结果

Fig.7 实验结果折线图

Fig.8 建筑楼层识别结果

Tab.4 建筑物层数验证结果

[1]	Zhang C, Cui Y, Zhu Z, et al. Building height extraction from GF-7 satellite images based on roof contour constrained stereo matching[J]. Remote Sensing, 2022, 14(7):1566. doi: 10.3390/rs14071566
[2]	Nakajima T, Tao G, Yasuoka Y. Simulated recovery of information in shadow areas on IKONOS image by combing ALS data[C]// Proceeding of Asian Conference on Remote Sensing (ACRS), 2002.
[3]	姚华琴, 杨树文, 刘正军, 等. 基于QuickBird影像的城市高大地物阴影检测方法[J]. 国土资源遥感, 2015, 27(2):51-55.doi:10.6046/gtzyyg.2015.02.08. doi: 10.6046/gtzyyg.2015.02.08
	Yao H Q, Yang S W, Liu Z J, et al. Shadow detection method of urban tall objects based on QuickBird image[J]. Remote Sensing for Land and Resources, 2015, 27(2):51-55.doi:10.6046/gtzyyg.2015.02.08. doi: 10.6046/gtzyyg.2015.02.08
[4]	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.
	Zhang X M, He G J, Wang W, et al. Extraction of building height and distribution information in Tianjin based on ALOS satellite image shadow[J]. Spectroscopy and Spectral Analysis, 2011, 31(7):2003-2006.
[5]	Suzuki A, Shio A, Arai H, et al. Dynamic shadow com-pensation of aerial images based on color and spatial analysis[C]//Proceedings of the 15th International Conference on Patten Recognition. Barcelona:IEEE, 2000:317-320.
[6]	Arévalo V, Gonz lez J, Ambrosio G. Shadow detection in colour high-resolution satellite images[J]. International Journal of Remote Sensing, 2008, 29(7):1945-1963. doi: 10.1080/01431160701395302
[7]	赫晓慧, 李满堂, 郭恒亮, 等. 基于GF-2遥感影像的建筑物高度反演方法研究[J]. 测绘地理信息, 2020, 45(3):29-33.
	He X H, Li M T, Guo H L, et al. Research on buildiing height inversion based on GF-2 image[J]. Journal of Geomatics, 2020, 45(3):29-33.
[8]	于东方. 基于阴影的遥感图像中建筑物自动提取方法研究[D]. 长沙: 国防科学技术大学, 2008.
	Yu D F. Research on shadow-based automatic extractions of buildings from remote sensing images[D]. Changsha: National University of Defense Technology, 2008.
[9]	黄昕. 高分辨率遥感影像多尺度纹理、形状特征提取与面向对象分类研究[D]. 武汉: 武汉大学, 2009.
	Huang X. Multiscale texture and shape feature extraction and object-oriented classification for very high resolution remotely sensed imagery[D]. Wuhan: Wuhan University, 2009.
[10]	余孟泽, 刘正熙, 骆键, 等. 融合纹理特征和阴影属性的阴影检测方法[J]. 计算机工程与设计 2011, 32(10):3431-3434.
	Yu M Z, Liu Z X, Luo J, et al. A shadow detection method combining texture features and shadow attributes[J]. Computer Engineering and Design, 2011, 32(10):3431-3434.
[11]	Leone A, Distante C. Shadow detection for moving objects based on texture analysis[J]. Pattern Recognition, 2007, 40(4):1222-1233. doi: 10.1016/j.patcog.2006.09.017
[12]	Tsai V J D. A comparative study on shadow compensation of color aerial images in invariant color models[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(6):1661-1667. doi: 10.1109/TGRS.2006.869980
[13]	夏怀英, 郭平. 基于统计混合模型的遥感影像阴影检测[J]. 遥感学报, 2011, 15(4):778-791.
	Xia H Y, Guo P. A shadow detection of remote sensing images based on statistical texture features[J]. Journal of Remote Sensing, 2011, 15(4):778-791.
[14]	李存军, 刘良云, 王纪华, 等. 基于主成分融合信息失真的城市IKONOS影像阴影自动提取研究[J]. 武汉大学学报(信息科学版), 2008, 33(9):947-950.
	Li C J, Liu L Y, Wang J H, et al. IKONOS shadow extraction in urban region based on the principal component fusion information distortion[J]. Geomatics and Information Science of Wuhan University, 2008, 33(9):947-950.
[15]	董东霞. 基于主分量变换的彩色图像分类数确定方法[J]. 微型电脑应用, 2004, 20(7):8-9.
	Dong D X. Method for determining the number of color image classification based on principal component transform[J]. Microcomputer Applications, 2004, 20(7):8-9
[16]	刘辉, 谢天文. 基于PCA与HIS模型的高分辨率遥感影像阴影检测研究[J]. 遥感技术与应用, 2013, 28(1):78-84.
	Liu H, Xie T W. Research on shadow detection of high resolution remote sensing image based on PCA and his model[J]. Remote Sensing Technology and Application, 2013, 28 (1):78-84.
[17]	Izadi M, Saeedi P. Three-dimensional polygonal building model estimation from single satellite images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(6):2254-2272. doi: 10.1109/TGRS.2011.2172995
[18]	Sirmacek B, Uensalan C. Urban-area and building detection using SIFT keypoints and graph theory[J]. IEEE Transactions on Geosciense and Romote Sensing, 2009, 47(4):1156-1167.
[19]	段光耀, 宫辉力, 李小娟, 等. 结合特征分量构建和面向对象方法提取高分辨率卫星影像阴影[J]. 遥感学报, 2014, 18(4):760-770.
	Duan G Y, Gong H L, Li X J, et al. Shadow extraction based on characteristic components and object-oriented method for high-resolution images[J]. Journal of Remote Sensing, 2014, 18(4):760-770.
[20]	艾维丽, 吴志红, 刘艳丽. 结合区域配对的室外阴影检测[J]. 中国图象图形学报, 2015, 20(4):551-558.
	Ai W L, Wu Z H, Liu Y L. Outdoor shadow detection combined with region pairing[J]. Journal of Image and Graphics, 2015, 20(4):551-558.
[21]	丁哲, 汪小钦, 邬群勇, 等. 遥感空间分辨率对城市建筑物高度估算精度的影响[J]. 遥感技术与应用, 2018, 33(3):418-427.
	Ding Z, Wang X Q, Wu Q Y, et al. Effects of different spatial resolution of remote sensing images on estimation accuracy of urban building height[J]. Remote Sensing Technology and Application, 2018, 33(3):418-427.
[22]	霍少峰, 顾行发, 占玉林, 等. 资源三号卫星前视影像的建筑物高度提取[J]. 测绘科学, 2017, 42(2):147-153.
	Huo S F, Gu X F, Zhan Y L, et al. Extraction of building height from forward-looking image of ZY-3 satellite[J]. Science of Surveying and Mapping, 2017, 42(2):147-153.
[23]	马川. 基于单幅高分辨率遥感影像的城市建筑物三维几何建模[D]. 成都: 西南交通大学, 2012.
	Ma C. 3d geometric modeling of urban buildings based on single high resolution remote sensing image[D]. Chengdu: Southwest Jiaotong University, 2012.
[24]	王永刚, 刘慧平. 利用角点最近距离统计平均法计算建筑物阴影长度[J]. 国土资源遥感, 2008, 20(3):32-36.doi:10.6046/gtzyyg.2008.03.08. doi: 10.6046/gtzyyg.2008.03.08
	Wang Y G, Liu H P. The shadow length of buildings is calculated by using the statistical average method of corner nearest distance[J]. Remote Sensing for Land and Resources, 2008, 20(3):32-36.doi:10.6046/gtzyyg.2008.03.08. doi: 10.6046/gtzyyg.2008.03.08
[25]	程国旗, 张继贤, 李阳春, 等. 高分影像建筑物阴影优化提取与高度估算[J]. 测绘科学, 2020, 45(8):103-109,137.
	Cheng G Q, Zhang J X, Li Y C, et al. Building shadow extraction and height estimation from high-resolution image[J]. Science of Surveying and Mapping, 2020, 45(8):103-109,137.
[26]	王炳忠. 太阳辐射计算讲座第一讲太阳能中天文参数的计算[J]. 太阳能, 1999(2):8-10.
	Wang B Z. The calculation of astronomical parameters in solar energy in the first lecture of solar radiation calculation[J]. The Solar Energy, 1999(2):8-10.
[27]	谢亚坤. 基于高分影像阴影的多种场景建筑物高度信息提取方法研究[D]. 成都: 西南交通大学, 2018.
	Xie Y K. Research on extraction method of building height information in multiple scenes based on high-resolution image shadow[D]. Chengdu: Southwest Jiaotong University, 2018.
[28]	周志华. 机器学习[M]. 北京: 清华大学出版社, 2016:133-139.
	Zhou Z H. Machine learning[M]. Beijing: Tsinghua University Press, 2016:133-139.

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