A novel spectral index for mapping blue colour-coated steel roofs(BCCSRs)in urban areas using Sentinel-2 data

作     者：Chuanwu Zhao Yaozhong Pan 

作者机构：State Key Laboratory of Remote SensingFaculty of Geographical ScienceBeijing Normal UniversityBeijingPeople’s Republic of China Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of EducationBeijing Normal UniversityBeijingPeople’s Republic of China Academy of Plateau Science and SustainabilityQinghai Normal UniversityXiningPeople’s Republic of China Beijing Engineering Research Center for Global Land Remote Sensing ProductsFaculty of Geographical ScienceBeijing Normal UniversityBeijingPeople’s Republic of China 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2023年第16卷第1期

页      面：2862-2884页

核心收录：

学科分类：08[工学] 0708[理学-地球物理学] 080203[工学-机械设计及理论] 0804[工学-仪器科学与技术] 0816[工学-测绘科学与技术] 0802[工学-机械工程] 

基　　金：funded by the National Natural Science Foundation of China(grant number 42192581) Open Fund of State Key Laboratory of Remote Sensing Science and Beijing Engineering Research Center for Global Land Remote Sensing Products(grant number 12800-310430005) 

主　　题：Blue colour-coated steel roof Large-scale mapping Surface energy budget Sentinel 2 Landsat 8 

摘      要：Blue colour-coated steel roofs(BCCSRs)offer a lightweight and economical option to concrete and other cladding in buildings,but they are also controversial for altering the surface energy budget and water *** spatial information about BCCSRs is crucial for exploring the environmental impacts of man-made ***,existing methods are not always effective due to the variety of BCCSR types and background *** overcome these limitations,we proposed a new index(called BCCSI)based on Sentinel-2 multispectral images to map the commonly used *** typical study areas were chosen worldwide to develop and validate the *** on spectral analysis,we constructed the BCCSl using the blue,red,green,and shortwave infrared 2(SWIR2)bands to highlight the BCCSR while suppressing the background *** with five existing indices,the BCCSl was effective in the visual evaluation,separability analysis and BCCSR ***,the BCCSI achieved similar accuracy to the supervised classifier while avoiding the time-consuming and laborious effort of sample ***,the BCCSl showed its applicability in medium-resolution satellite data,such as Landsat-8 ***,the proposed BCCSI provides a viable scheme for global BCCSR mapping and analysis.