DocumentCode :
2511072
Title :
Recognizing and estimating rainfall using cloud images
Author :
Mano, S. Oswalt ; Kavitha, V. ; Ananth, J.P. ; SahayaAru, J.
Author_Institution :
Sri Ramakrishna Inst. of Technol., Coimbatore, India
fYear :
2010
fDate :
13-15 Nov. 2010
Firstpage :
394
Lastpage :
399
Abstract :
Water is elixir of life. So rainfall becomes the inevitable part of every nation which decides the prosperity and economic scenario of a country. In this fast moving world, estimation of rainfall has become a necessity especially when the global heat levels are soaring. The proposed approach here is to use the digital cloud images to predict rainfall. Considering the cost factors and security issues, it is better to predict rainfall from digital cloud images rather than satellite images. The status of sky is found using wavelet. The status of cloud is found using the Cloud Mask Algorithm. The type of cloud can be evolved using the K-Means Clustering technique. As per previous research works done by the researchers, it is stated the Nimbostratus and Cumulonimbus are the rainfall clouds and other clouds like cumulus will produce rain at some rare chances. The type of rainfall cloud is predicted by analyzing the color and density of the cloud images. The cloud images are stored as JPEG file in the file system. Analysis was done over several images. The result predicts the type of cloud with its information like classification, appearance and altitude and will provide the status of the rainfall. The proposed approach can be utilized by common people to just take the photograph of cloud and can come to conclusion about the status of rainfall and to get the desired detail.
Keywords :
atmospheric techniques; atmospheric temperature; clouds; geophysics computing; rain; Cumulonimbus cloud; JPEG file; K-means clustering technique; Nimbostratus cloud; cloud mask algorithm; cost factors; digital cloud images; file system; global heat levels; rainfall clouds; satellite images; security issues; Classification algorithms; Cloud computing; Clouds; Clustering algorithms; File systems; Rain; Cloud Images; Cloud Mask Algorithm; K-Means Clustering; Rainfall;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances in Space Technology Services and Climate Change (RSTSCC), 2010
Conference_Location :
Chennai
Print_ISBN :
978-1-4244-9184-1
Type :
conf
DOI :
10.1109/RSTSCC.2010.5712875
Filename :
5712875
Link To Document :
بازگشت