New method to identify sand and dust storm by using remote sensing technique - With inner mongolia autonomous region as example
The object emissivity characteristics and the theory of heat radiation were studied to detect sand dust storm by remote sensing technique. The results show that the material nature of sand dust, ground surface and clouds is different when the sand dust happens. The ratio between the ground and sand...
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Veröffentlicht in: | Hong wai yu hao mi bo xue bao 2009-04, Vol.28 (2), p.129-132 |
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description | The object emissivity characteristics and the theory of heat radiation were studied to detect sand dust storm by remote sensing technique. The results show that the material nature of sand dust, ground surface and clouds is different when the sand dust happens. The ratio between the ground and sand dust in pixel images is different when the strength of sand dust changes. And these differences lead to the variations of material nature in pixels and object emissivity. At last, by a combination of theoretical and experimental researches, it was found that the degree of approach between epsilon(29) and epsilon(31) was different among cloud area, ground surface, weak sand dust and strong sand dust areas. And in a whole range of 0-1 of epsilon(31), the order of epsilon(29) is cloud > strong sand dust > weak sand dust > ground surface. According to the results of the above, it was established a stable sand dust index (DSI) model to identify the sand dust strength. And the model can more accurately detect the range a |
doi_str_mv | 10.3724/SP.J.1010.2009.00129 |
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The results show that the material nature of sand dust, ground surface and clouds is different when the sand dust happens. The ratio between the ground and sand dust in pixel images is different when the strength of sand dust changes. And these differences lead to the variations of material nature in pixels and object emissivity. At last, by a combination of theoretical and experimental researches, it was found that the degree of approach between epsilon(29) and epsilon(31) was different among cloud area, ground surface, weak sand dust and strong sand dust areas. And in a whole range of 0-1 of epsilon(31), the order of epsilon(29) is cloud > strong sand dust > weak sand dust > ground surface. According to the results of the above, it was established a stable sand dust index (DSI) model to identify the sand dust strength. 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title | New method to identify sand and dust storm by using remote sensing technique - With inner mongolia autonomous region as example |
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