Research Papers

Algorithm for daytime radiation fog detection based on MODIS/TERRA data over land

[+] Author Affiliations
Huiyun Ma, Bin Zou

Central South University, School of Geosciences and Info-physics, Changsha 410083, China

Xiaojing Wu

National Satellite Meteorological Center, Beijing 100000, China

Xuelian Meng

Louisiana State University, Department of Geography & Anthropology, Baton Rouge, Louisiana 70803

Neng Wan

University of Nebraska Medical Center, Department of Health Services Research & Administration, Omaha, Nebraska 68198

J. Appl. Remote Sens. 6(1), 063589 (Oct 30, 2012). doi:10.1117/1.JRS.6.063589
History: Received October 17, 2011; Revised September 21, 2012; Accepted September 25, 2012
Text Size: A A A

Abstract.  We present an algorithm for daytime radiation fog detection (ADRFD) to characterize the fog distribution over land areas through two main steps: (1) detection of areas with clouds and radiation fog based on edge pixels and (2) separation of radiation fog from clouds based on object properties. The algorithm is tested in southeast China over an area of 2,640,000km2 (longitude extent: 105°E to 122°E, latitude extent: 23°N to 40°N), with 1 km resolution moderate resolution imaging spectroradiometer/TERRA images, digital elevation model of China (grid size is 1×1km2 and accuracy of elevation is 25 m), and the fog detection accuracies are evaluated using the observation results from 3590 ground observation stations. Results show that ADRFD can detect areas with clouds and radiation fog and effectively differentiate radiation fog from clouds based on object properties with a Kappa coefficient of 0.89 and critical success index at 0.87. It is concluded that ADRFD is a promising approach for daytime radiation fog detection over large land surfaces based on the condition that fog objects do not intersect with cloud objects or are not located under cloud objects. Extensions of this current study will be on improving the parameters determination method of ADRFD. ADRFD can be used to detect other types of fog in different regions and different seasons theoretically, but it should be tested further. In addition, more improvements are needed to allow for the detection of smaller areas of fog and fog regions intersecting with or under clouds.

Figures in this Article
© 2012 Society of Photo-Optical Instrumentation Engineers

Topics

Clouds ; MODIS ; Radiation

Citation

Huiyun Ma ; Xiaojing Wu ; Bin Zou ; Xuelian Meng and Neng Wan
"Algorithm for daytime radiation fog detection based on MODIS/TERRA data over land", J. Appl. Remote Sens. 6(1), 063589 (Oct 30, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063589


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.