Monitoring the spatial changes of the snow cover of Central Alborz using the SVM algorithm and landsat images

Document Type : Original Article

Authors

1 Department of Geography, Faculty of Literature and Humanities, Lorestan University, Khorramabad, Iran

2 Department of Geography, Faculty of Literature and Humanities, Firouzabad Institute of Higher Education, Firouzabad, Iran

Abstract

Introduction: The snows of the Alborz mountain range play an important role in providing underground and surface water for the settlements around it and the densely populated Caspian Plain. Global warming has caused changes in the atmospheric-climatic parameters of Iran. These changes will cause changes in the dependent variable, which is the snow cover of the high points of the Alborz Mountains. Its consequences can be accelerating the melting of snow, increasing the process of flooding of rivers and the destruction of habitats and settlements downstream. Therefore, the monitoring of Alborz snow area can be used in formulating water management strategies and sustainable development.
Materials and methods: In this study, the temporal-spatial variations of the Central Alborz snow cover on a seasonal scale for the years 1985 to 2020 were monitored using Landsat TM, ETM+ and OLI for 1985, 1995, 2005, 2015 and 2020. SVM algorithm was used to extract the snow cover.
Results and discussion: The average snow covers for winter, autumn, spring and summer were 1.19, 0.47, 0.14 and 0.004 million hectares, respectively. Snow covers have been declining from 1985 to 2020, reaching 1.98 million hectares in 2020 from 1.68 in 1985 to 1.68 in winter. In the autumn, it increased from 0.84 in 1985 to 0.15 million hectares in 2020. In the winter of 1985, snow started at an altitude of 1,500 meters, but by 2020 it reached 2,500 meters. In the summer, snow was more than 3,900 meters high in 1985, but peaks more than 4,200 meters in 2015 and 2020. The area of snow cover in Central Alborz has a decreasing trend, which has the highest rate in winter.
Conclusion: The results of this study showed that the accuracy of the support vector machine algorithm is more than 0.91% in the classification of Landsat images, this method can be used to extract snow patches; in such a way that it separated the shadow snow and cloud from the snow and identified the accumulation of snow in the valleys. Also using images with spatial resolution of 30 meters and applying classification algorithms for snow extraction is better than using NDSI index and MODIS images. On the other hand, the process of snow cover in central Alborz has been such that during 25 years, the area of snow has decreased from about 0.7 million hectares and a large amount of fresh water storage in Alborz has been lost.

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References

منابع (References)
 
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