太阳成8722(中国)有限公司-GREEN NO.1

标题：Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data作者：Guo, Wei; Lu, Dengsheng; Wu, Yanlan; Zhang, Jixian

来源出版物：REMOTE SENSING 卷：7 期：9 页：12459-12477 DOI：10.3390/rs70912459 出版年：SEP 2015

摘要：Data from the U.S. Defense Meteorological Satellite Program's Operational Line-scan System are often used to map impervious surface area (ISA) distribution at regional and global scales, but its coarse spatial resolution and data saturation produce high inaccuracy in ISA estimation. Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite's Day/Night Band (VIIRS-DNB) with its high spatial resolution and dynamic data range may provide new insights but has not been fully examined in mapping ISA distribution. In this paper, a new variableLarge-scale Impervious Surface Index (LISI)is proposed to integrate VIIRS-DNB and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data for mapping ISA distribution. A regression model was established, in which LISI was used as an independent variable and the reference ISA from Landsat images was a dependent variable. The results indicated a better estimation performance using LISI than using a single VIIRS-DNB or MODIS NDVI variable. The LISI-based approach provides accurate spatial patterns from high values in core urban areas to low values in rural areas, with an overall root mean squared error of 0.11. The LISI-based approach is recommended for fractional ISA estimation in a large area.

入藏号：WOS:000362511400069

文献类型：Article

语种：English

作者关键词：impervious surface area, VIIRS-DNB, MODIS NDVI, Landsat 8 OLI, large-scale impervious surface index

扩展关键词：NIGHTTIME SATELLITE IMAGERY; SPECTRAL MIXTURE ANALYSIS; OPEN WATER FEATURES; MAP URBAN AREA; DMSP-OLS DATA; URBANIZATION DYNAMICS; LIGHT DATA; LAND-USE; SOCIOECONOMIC ACTIVITY; VEGETATION INDEXES

通讯作者地址：Lu, Dengsheng; Zhejiang A&F Univ, Zhejiang Prov Key Lab Carbon Cycling Forest Ecosy, Sch Environm & Resource Sci, Linan 311300, Peoples R China.

电子邮件地址：guowei_rs@163.com; luds@zafu.edu.cn; wylmq@sina.com; zhangjx@casm.ac.cn

地址：

[Guo, Wei; Wu, Yanlan] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Lu, Dengsheng]Zhejiang A&F Univ, Zhejiang Prov Key Lab Carbon Cycling Forest Ecosy, Sch Environm & Resource Sci, Linan 311300, Peoples R China.

[Zhang, Jixian] Chinese Acad Surveying & Mapping, Inst Photogrammetry & Remote Sensing, Beijing 100830, Peoples R China.

研究方向：Remote Sensing

ISSN：2072-4292

影响因子（2014）：3.180