Three Cases of a New Multichannel Threshold Technique to Detect Fog/Low Stratus during Nighttime Using SNPP DataSource: Weather and Forecasting:;2015:;volume( 030 ):;issue: 006::page 1763Author:Jiang, Jun
,
Yan, Wei
,
Ma, Shuo
,
Jie, Yangyang
,
Zhang, Xiarong
,
Hu, Shensen
,
Fan, Lei
,
Xia, Linyu
DOI: 10.1175/WAF-D-15-0050.1Publisher: American Meteorological Society
Abstract: he day?night band (DNB) low-light-level visible sensor, mounted on the Suomi?National Polar-Orbiting Partnership (SNPP) satellite, can measure visible radiances from the earth and atmosphere (solar/lunar reflection, and natural/anthropogenic nighttime light emissions) during both day and night and can achieve unprecedented nighttime low-light-level imaging with its accurate radiometric calibration and fine spatiotemporal resolution. Based on the good characteristics of DNB, a multichannel threshold (MCT) algorithm combining DNB with other Visible?Infrared Imager?Radiometer Suite (VIIRS) channels is proposed to monitor nighttime fog/low stratus. Through a gradual separation of the underlying surface (land, vegetation, water bodies, and city lights), snow, and high/medium clouds, a fog/low-stratus region can ultimately be extracted by the algorithm. Then, the algorithmic feasibility is verified by three typical cases of heavy fog/low stratus in China. The experimental results demonstrate that the outcomes of the MCT algorithm approximately coincide with the ground-measured results. Furthermore, the MCT algorithm shows promise for nighttime fog/low-stratus detection in some example cases with about a 0.84 average probability of detection (POD), a 0.73 average critical success index (CSI), and a 0.15 average false alarm ratio (FAR), which reveals some improvement over the conventional dual-channel difference (DCD) algorithm.
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| contributor author | Jiang, Jun | |
| contributor author | Yan, Wei | |
| contributor author | Ma, Shuo | |
| contributor author | Jie, Yangyang | |
| contributor author | Zhang, Xiarong | |
| contributor author | Hu, Shensen | |
| contributor author | Fan, Lei | |
| contributor author | Xia, Linyu | |
| date accessioned | 2017-06-09T17:37:01Z | |
| date available | 2017-06-09T17:37:01Z | |
| date copyright | 2015/12/01 | |
| date issued | 2015 | |
| identifier issn | 0882-8156 | |
| identifier other | ams-88133.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4231880 | |
| description abstract | he day?night band (DNB) low-light-level visible sensor, mounted on the Suomi?National Polar-Orbiting Partnership (SNPP) satellite, can measure visible radiances from the earth and atmosphere (solar/lunar reflection, and natural/anthropogenic nighttime light emissions) during both day and night and can achieve unprecedented nighttime low-light-level imaging with its accurate radiometric calibration and fine spatiotemporal resolution. Based on the good characteristics of DNB, a multichannel threshold (MCT) algorithm combining DNB with other Visible?Infrared Imager?Radiometer Suite (VIIRS) channels is proposed to monitor nighttime fog/low stratus. Through a gradual separation of the underlying surface (land, vegetation, water bodies, and city lights), snow, and high/medium clouds, a fog/low-stratus region can ultimately be extracted by the algorithm. Then, the algorithmic feasibility is verified by three typical cases of heavy fog/low stratus in China. The experimental results demonstrate that the outcomes of the MCT algorithm approximately coincide with the ground-measured results. Furthermore, the MCT algorithm shows promise for nighttime fog/low-stratus detection in some example cases with about a 0.84 average probability of detection (POD), a 0.73 average critical success index (CSI), and a 0.15 average false alarm ratio (FAR), which reveals some improvement over the conventional dual-channel difference (DCD) algorithm. | |
| publisher | American Meteorological Society | |
| title | Three Cases of a New Multichannel Threshold Technique to Detect Fog/Low Stratus during Nighttime Using SNPP Data | |
| type | Journal Paper | |
| journal volume | 30 | |
| journal issue | 6 | |
| journal title | Weather and Forecasting | |
| identifier doi | 10.1175/WAF-D-15-0050.1 | |
| journal fristpage | 1763 | |
| journal lastpage | 1780 | |
| tree | Weather and Forecasting:;2015:;volume( 030 ):;issue: 006 | |
| contenttype | Fulltext |