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

被引:6
|
作者
Zhao, Chuanwu [1 ,2 ,4 ]
Pan, Yaozhong [1 ,2 ,3 ]
机构
[1] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing, Beijing, Peoples R China
[2] Beijing Normal Univ, Key Lab Environm Change & Nat Disasters, Chinese Minist Educ, Beijing, Peoples R China
[3] Qinghai Normal Univ, Acad Plateau Sci & Sustainabil, Xining, Peoples R China
[4] Beijing Normal Univ, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing Pr, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Blue colour-coated steel roof; Large-scale mapping; Surface energy budget; Sentinel; 2; Landsat; 8;
D O I
10.1080/17538947.2023.2241427
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
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 cycle. Obtaining spatial information about BCCSRs is crucial for exploring the environmental impacts of man-made landscapes. However, existing methods are not always effective due to the variety of BCCSR types and background conditions. To overcome these limitations, we proposed a new index (called BCCSI) based on Sentinel-2 multispectral images to map the commonly used BCCSRs. Five typical study areas were chosen worldwide to develop and validate the BCCSI. Based on spectral analysis, we constructed the BCCSI using the blue, red, green, and shortwave infrared 2 (SWIR2) bands to highlight the BCCSR while suppressing the background condition. Compared with five existing indices, the BCCSI was effective in the visual evaluation, separability analysis and BCCSR mapping. Moreover, the BCCSI achieved similar accuracy to the supervised classifier while avoiding the time-consuming and laborious effort of sample collection. Furthermore, the BCCSI showed its applicability in medium-resolution satellite data, such as Landsat-8 imagery. Thus, the proposed BCCSI provides a viable scheme for global BCCSR mapping and analysis.
引用
收藏
页码:2862 / 2884
页数:23
相关论文
共 50 条
  • [1] Mapping vegetation in urban areas using Sentinel-2
    Mudele, Oladimeji
    Gamba, Paolo
    2019 JOINT URBAN REMOTE SENSING EVENT (JURSE), 2019,
  • [2] A Novel Spectral Index for Automatic Canola Mapping by Using Sentinel-2 Imagery
    Tian, Haifeng
    Chen, Ting
    Li, Qiangzi
    Mei, Qiuyi
    Wang, Shuai
    Yang, Mengdan
    Wang, Yongjiu
    Qin, Yaochen
    REMOTE SENSING, 2022, 14 (05)
  • [3] Development of a new index for mapping urban areas in Tu<spacing diaeresis>rkiye using Sentinel-2 images
    Matci, Dilek Kucuk
    ADVANCES IN SPACE RESEARCH, 2023, 72 (11) : 4677 - 4691
  • [4] Mapping winter rapeseed in South China using Sentinel-2 data based on a novel separability index
    Tao, Jian-bin
    Zhang, Xin-yue
    Wu, Qi-fan
    Wang, Yun
    JOURNAL OF INTEGRATIVE AGRICULTURE, 2023, 22 (06) : 1645 - 1657
  • [5] Mapping winter rapeseed in South China using Sentinel-2 data based on a novel separability index
    TAO Jian-bin
    ZHANG Xin-yue
    WU Qi-fan
    WANG Yun
    Journal of Integrative Agriculture, 2023, 22 (06) : 1645 - 1657
  • [6] A Novel Approach for Mapping Wheat Areas Using High Resolution Sentinel-2 Images
    Nasrallah, Ali
    Baghdadi, Nicolas
    Mhawej, Mario
    Faour, Ghaleb
    Darwish, Talal
    Belhouchette, Hatem
    Darwich, Salem
    SENSORS, 2018, 18 (07)
  • [7] Proposal for an index of roads and structures for the mapping of non-vegetated urban surfaces using OSM and Sentinel-2 data
    Justiniano, Eduardo Felix
    dos Santos Junior, Edimilson Rodrigues
    de Melo, Breno Malheiros
    Siqueira, Victor Nascimento
    Morato, Rubia Gomes
    Fantin, Marcel
    Pedrassoli, Julio Cesar
    Martines, Marcos Roberto
    Kawakubo, Fernando Shinji
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 109
  • [8] A Novel Spectral Index for Rapid Dust-Proof Net Mapping Based on Sentinel-2 Images
    Zhang, Chaoqun
    Zhou, Lei
    Du, Mingyi
    Chen, Qiang
    Liu, Yang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [9] An Operational Framework for Mapping Irrigated Areas at Plot Scale Using Sentinel-1 and Sentinel-2 Data
    Bazzi, Hassan
    Baghdadi, Nicolas
    Amin, Ghaith
    Fayad, Ibrahim
    Zribi, Mehrez
    Demarez, Valerie
    Belhouchette, Hatem
    REMOTE SENSING, 2021, 13 (13)
  • [10] On the Mapping of Burned Areas and Burn Severity Using Self Organizing Map and Sentinel-2 Data
    Lasaponara, R.
    Proto, A. M.
    Aromando, A.
    Cardettini, G.
    Varela, V.
    Danese, M.
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (05) : 854 - 858