气候变化领域集成服务门户(CCPortal): Developing a method to estimate building height from Sentinel-1 data

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DOI	10.1016/j.rse.2020.111705
	Developing a method to estimate building height from Sentinel-1 data
	Li X.; Zhou Y.; Gong P.; Seto K.C.; Clinton N.
发表日期	2020
ISSN	00344257
卷号	240
英文摘要	Building height is one of the key variables in studying anthropogenic activities and built environments in the urban system. However, the information of urban building height over large areas is still limited due to the lack of available data. In this study, we developed an approach to estimate building height using the Sentinel-1 Ground Range Detected data. First, we proposed an indicator of VVH that integrates the dual-polarization information (i.e., VV and VH) from the Sentinel-1 synthetic aperture radar data. Second, we developed a building height model using the indicator of VVH and the reference building height from airborne light detection and ranging (LiDAR) images in seven cities in the United States (US). Third, we estimated building height of major cities with area larger than 500 km2 in the US using the developed model. The root mean square error between estimated and reference height is 1.5 m in seven study cities in the US. The comparison with the Laser observations from the Ice, Cloud, and land Elevation Satellite data in available footprints also indicates that the estimated building height from Sentinel-1 data is reliable. The estimated building height from Sentinel-1 data shows a better agreement with the reference data compared to the Advanced Land Observing Satellite data in seven US cities. Our results of building height in major US cities indicate that there are more cities with tall buildings in the Northeastern US compared to the Western and Southern US, with more aggregated tall buildings in central business districts of cities. The information of building height from this study is of great value in urban studies, such as estimating energy consumption and carbon emissions in urban areas. © 2020 Elsevier Inc.
英文关键词	Backscatter; Building height; Sentinel-1; Synthetic aperture radar; Urbanization
语种	英语
scopus关键词	Backscattering; Energy utilization; Mean square error; Optical radar; Synthetic aperture radar; Tall buildings; Advanced land observing satellites; Building height; Central business districts; Land elevation satellites; Light detection and ranging; Root mean square errors; Sentinel-1; Urbanization; Space-based radar; backscatter; estimation method; human activity; lidar; satellite data; Sentinel; synthetic aperture radar; urban region; urbanization; United States
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179406
作者单位	Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, United States; Department of Earth System Science, Tsinghua University, Beijing, 100084, China; School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, United States; Google, Inc., 1600 Amphitheatre Pkwy, Mountain View, CA 94043, United States
推荐引用方式 GB/T 7714	Li X.,Zhou Y.,Gong P.,et al. Developing a method to estimate building height from Sentinel-1 data[J],2020,240.
APA	Li X.,Zhou Y.,Gong P.,Seto K.C.,&Clinton N..(2020).Developing a method to estimate building height from Sentinel-1 data.Remote Sensing of Environment,240.
MLA	Li X.,et al."Developing a method to estimate building height from Sentinel-1 data".Remote Sensing of Environment 240(2020).