TITLE:
Investigation of Spatial and Temporal Distribution of Snow Cover by Using Satellite Imagery (Case Study: Sheshpirdam Basin)
AUTHORS:
Ali Liaghat, Nima Tavanpour
KEYWORDS:
RS, GIS, Maximum Likelihood Algorithm, Snow Cover, Spatial and Temporal Distribution
JOURNAL NAME:
Open Journal of Geology,
Vol.6 No.5,
May
30,
2016
ABSTRACT: About one third of the water needed for agriculture in the world is
generated by melting snow. Snow cover, surface and ground water recharge are
considered as sustainable and renewable resources. It is therefore necessary to
identify and study these criteria. The aim of this study is to determine the
spatial and temporal distribution of snow cover in the district of the Sheshpir
basin in Fars province (in south of Iran). Ground-based observation of snow
covers, especially in mountainous areas, is associated with many problems due
to the insufficient accuracy of optical observation, as opposed to digital
observation. Therefore, GIS and remote sensing technology can be partially
effective in solving this problem. Images of Landsat 5TM and Landsat
7TM satellites were used to derive snow cover maps. The images in
ENVI 4.8 software were classified by using the maximum likelihood algorithm.
Other spatial analyses were performed in ARC-GIS 9.3 software. The maximum
likelihood method was accuracy assessed by operation points of testing. The
least and the average of overall accuracy of produced maps were found to be 91%
and 98%, respectively. This demonstrates that the maximum likelihood method has
high performance in the classification of images. Overall snow cover and the
review of terrain through the years 2008-2009 and
2009-2010 showed that snow cover begins to accumulate in November and reaches
its highest magnitude in February. Finally, no trace of snow can be
observed on the surface of the basin in the month of May. By average, 34% of
the basin is covered in snow from November through to May.