A Fused Variable by Night Light Images and MODIS Products for Improving Urban Built-Up Area Extraction

被引:5
|
作者
Yang, Guang [1 ,2 ,3 ]
Ma, Yuntao [4 ,5 ]
Hu, Jiaqi [6 ]
机构
[1] South China Normal Univ, Sch Geog, Guangzhou 510631, Peoples R China
[2] SCNU Qingyuan Inst Sci & Technol Innovat Co Ltd, Qingyuan 511517, Peoples R China
[3] Guangdong Normal Univ, Weizhi Informat Technol Co Ltd, Qingyuan 511517, Peoples R China
[4] Shenyang Jianzhu Univ, Sch Transportat Engn, Shenyang 710075, Peoples R China
[5] Beijing Hanbolin Remote Sensing Mapping Informat, Beijing 100080, Peoples R China
[6] China Univ Min & Technol, Sch Transportat Engn, Beijing 100083, Peoples R China
基金
中国博士后科学基金;
关键词
urban built-up areas; night light images; land surface temperature; fused variable; optimal thresholds; LAND-SURFACE TEMPERATURE; WATER INDEX NDWI; VEGETATION ABUNDANCE; REFLECTANCE FUSION; TIME-SERIES; CHINA; URBANIZATION; CITY; DMSP/OLS; POPULATION;
D O I
10.3390/technologies9020040
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The boundary of urban built-up areas is the baseline data of a city. Rapid and accurate monitoring of urban built-up areas is the prerequisite for the boundary control and the layout of urban spaces. In recent years, the night light satellite sensors have been employed in urban built-up area extraction. However, the existing extraction methods have not fully considered the properties that directly reflect the urban built-up areas, like the land surface temperature. This research first converted multi-source data into a uniform projection, geographic coordinate system and resampling size. Then, a fused variable that integrated the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night light images, the Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature product and the normalized difference vegetation index (NDVI) product was designed to extract the built-up areas. The fusion results showed that the values of the proposed index presented a sharper gradient within a smaller spatial range, compared with the only night light images. The extraction results were tested in both the area sizes and the spatial locations. The proposed index performed better in both accuracies (average error rate 1.10%) and visual perspective. We further discussed the regularity of the optimal thresholds in the final boundary determination. The optimal thresholds of the proposed index were more stable in different cases on the premise of higher accuracies.
引用
收藏
页数:12
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