A method for identifying the number of building floors based on shadow information
LI Zhixin1(), WANG Mengfei2(), JIA Weijie2, JI Song1, WANG Yufei3
1. Institute of Geospatial Information,Information Engineering University, Zhengzhou 450001, China 2. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083,China 3. Journal of Management World, Beijing 100048,China
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.
Zhixin LI,Mengfei WANG,Weijie JIA, et al. A method for identifying the number of building floors based on shadow information[J]. Remote Sensing for Natural Resources,
2023, 35(3): 97-106.
Tab.2 Examples of floor extraction results in study area
提取结果
建筑物编号
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
初提取层数 改正后层数 实际层数 改正前误差 改正后误差
5 6 6 1 0
11 14 11 0 3
9 12 12 3 0
12 15 13 1 2
10 13 14 4 1
15 19 18 3 1
15 19 20 5 1
13 17 21 8 4
15 19 21 6 2
17 22 21 4 1
16 20 22 6 2
19 24 24 5 0
19 24 25 6 1
20 25 27 7 2
20 25 28 8 3
21 27 28 7 1
23 28 28 5 0
24 31 28 4 3
24 31 30 6 1
26 33 33 7 0
改正前平均误差楼层数①: 4.16; P=78.54%; σ前=1.263
改正后平均误差楼层数: 1.39; P=90.21%; σ后=0.972
Tab.3 Building floor test results
Fig.7 Histogram of experimental results
Fig.8 Building floor prediction results
建筑物楼层范围/层
平均提取误差/层
总体精度/%
标准差/层
6~10 11~20 21~30 >30
1.33 1.07 1.63 1.27
84.61 93.40 97.36 98.84
0.471 4 1.032 6 1.298 4 1.052 1
平均值
1.32
93.55
0.963 6
Tab.4 Building level verification results
[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
url: https://www.mdpi.com/2072-4292/14/7/1566
[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.
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
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.
Yu D F. Research on shadow-based automatic extractions of buildings from remote sensing images[D]. Changsha: National University of Defense Technology, 2008.
Huang X. Multiscale texture and shape feature extraction and object-oriented classification for very high resolution remotely sensed imagery[D]. Wuhan: Wuhan University, 2009.
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.
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.
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
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.
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.
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.
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.
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.
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
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.
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.
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.
[28]
Zhou Z H. Machine learning[M]. Beijing: Tsinghua University Press, 2016:133-139.