Fethi Ouallouche; Mourad Lazri; Soltane Ameur; Jean Michel Brucker; Mounir Sehad

Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria

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Author(s)

Fethi Ouallouche ^1,* Mourad Lazri ¹ Soltane Ameur ¹ Jean Michel Brucker ² Mounir Sehad ²

1. LAMPA laboratory, University of Tizi Ouzou, Algeria

2. School EPMI, 13 Boulevard de l’Hautil, 95092 Cergy Pontoise Cedex, Paris, France

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.06.02

Received: 15 Jan. 2014 / Revised: 1 Mar. 2014 / Accepted: 10 Apr. 2014 / Published: 8 May 2014

Index Terms

Rainfall estimation, data fusion, MSG, TRMM, ANN

Abstract

Rain areas delineation proposed in this paper is based on the image fusion from geostationary Meteosat Second Generation (MSG) satellite, with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) satellite. The fusion technique described in this work used an artificial neural network (ANN). It's has been developed to detect instantaneous rainfall by using information from the IR images of MSG satellite and from TRMM Microwave Imager (TMI). The study is carried out over north of Algeria. Seven spectral parameters are used as input data of ANN to identify raining or non - raining pixels. Corresponding data of raining /non-raining pixels are taken from a PR (precipitation radar) issued from TRMM. Results from the developed scheme are compared with the results of SI method (Scattering Index) taken as reference method. The results show that the developed model performs very well and overcomes the deficiencies of use a single satellite.

Cite This Paper

Fethi Ouallouche, Mourad Lazri, Soltane Ameur, Jean Michel Brucker, Mounir Sehad,"Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria", IJIGSP, vol.6, no.6, pp.11-18, 2014. DOI: 10.5815/ijigsp.2014.06.02

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