کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1763993 | 1020033 | 2014 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علوم فضا و نجوم
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall](/preview/png/1763993.png)
چکیده انگلیسی
In the present paper, an artificial neural network (ANN) based technique has been developed to estimate instantaneous rainfall by using brightness temperature from the IR sensors of SEVIRI radiometer, onboard Meteosat Second Generation (MSG) satellite. The study is carried out over north of Algeria. For estimation of rainfall, weight matrices of two ANNs namely MLP1 and MLP2 are developed. MLP1 is to identify raining or non-raining pixels. When rainy pixels are identified, then for those pixels, instantaneous rainfall is estimated by using MLP2. For identification of raining and non raining pixels, 7 input parameters from the IR sensors are utilized. Corresponding data of raining/non-raining pixels are taken from radar. For instantaneous rainfall estimation, 14 input parameters are utilized, where 7 parameters are information about raining pixels and 7 parameters are related with cloud features. The results obtained show the neural network performs reasonably well.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Space Research - Volume 53, Issue 1, 1 January 2014, Pages 138-155
Journal: Advances in Space Research - Volume 53, Issue 1, 1 January 2014, Pages 138-155
نویسندگان
Mourad Lazri, Soltane Ameur, Yacine Mohia,