Image and Signal Processing Methods

Haze detection by using modified normalized difference haze index in Beijing, Tianjin, and Hebei province

[+] Author Affiliations
Xinlei Han, Fengmei Yao

University of Chinese Academy of Sciences, College of Earth Sciences, Key Laboratory of Computational Geodynamics, Beijing 100049, China

Jiahua Zhang, Mirza Muhammad Waqar

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Yong Zha

Nanjing Normal University, College of Geographic Science, Nanjing, Jiangsu Province 210023, China

Junliang He

Shijiazhuang University, Department of Resources and Environment, Shijiazhuang, Hebei Province 050035, China

J. Appl. Remote Sens. 10(2), 025025 (Jun 20, 2016). doi:10.1117/1.JRS.10.025025
History: Received January 8, 2016; Accepted June 1, 2016
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Abstract.  This paper presents the development of index to detect haze from moderate resolution imaging spectroradiometer remote sensing data. Detection of haze over a large area has always been a problem. This study focuses on Beijing, Tianjin, and Shijiazhuang cities in China. These cities have suffered the worst hazy weather in recent years. The spectral influence of haze on surface features was determined through analysis of the spectral variations of surface covers between hazy and haze-free days. A spectral index known as modified normalized difference haze index (m-NDHI) is developed that can be used to monitor haze distribution and intensity. Correlation analysis of the derived m-NDHI and previously developed NDHI with in situPM2.5 (particulate matter with diameter <2.5  μm) data reveals that m-NDHI over water bodies has a coefficient of 0.7096, 0.5864, and 0.4857 and NDHI has coefficient of 0.5625, 0.5321, and 0.4618 with PM2.5 for Beijing, Tianjin, and Shijiazhuang, respectively, in winter. Moreover, the correlation of m-NDHI with PM2.5 is 0.4097, 0.8092, and 0.5546 during the spring, summer, and autumn, respectively, in Beijing. This developed index can be a much easier and more effective method to detect haze in large scales from remotely sensing data and characterize the situation of urban atmospheric pollution.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Xinlei Han ; Fengmei Yao ; Jiahua Zhang ; Mirza Muhammad Waqar ; Yong Zha, et al.
"Haze detection by using modified normalized difference haze index in Beijing, Tianjin, and Hebei province", J. Appl. Remote Sens. 10(2), 025025 (Jun 20, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.025025


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