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Journal of Applied Remote Sensing

Algorithm for daytime radiation fog detection based on MODIS/TERRA data over land
Author(s): Huiyun Ma; Xiaojing Wu; Bin Zou; Xuelian Meng; Neng Wan
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Paper 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 2,640,000 km2 (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 1×1 km2 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.

Paper Details

Date Published: 30 October 2012
PDF: 17 pages
J. Appl. Remote Sens. 6(1) 063589 doi: 10.1117/1.JRS.6.063589
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Huiyun Ma, Central South Univ. (China)
Xiaojing Wu, China Meteorological Administration (China)
Bin Zou, Central South Univ. (China)
Xuelian Meng, Louisiana State Univ. (United States)
Neng Wan, Univ. of Nebraska Medical Ctr. (United States)


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