IEEE International Conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES-18) 14-15 September 2018
Potential of Information Fusion of Optical and SAR Data for Snow Cover Characterization Paper ID:56 MSc. Eng. Divyesh M Varade
Ajay K. Maurya, Onkar Dikshit
Sr. Student Research Associate O/o Prof. Onkar Dikshit WLE-303A, Geoinformatics, Department of Civil Engineering, Indian Institute of Technology Kanpur, Kalyanpur, Kanpur-208016, Uttar Pradesh, India. Ph: +91-512-259-6417
Geoinformatics, Department of Civil Engineering, Indian Institute of Technology Kanpur, Kalyanpur, Kanpur-208016, Uttar Pradesh, India.
[email protected],
[email protected],
[email protected]
Geoinformatics Civil Engineering Indian Institute of Technology Kanpur
Outline 1. 2. 3. 4. 5. 6. 7. 8.
Introduction Properties of snow Study area & test datasets Proposed methodology Generation of reference data Results Accuracy assessment Conclusion
Geoinformatics Civil Engineering Indian Institute of Technology Kanpur
Potential of Information Fusion of Optical and SAR Data for Snow Cover Characterization Divyesh Manohar Varade (
[email protected])
15 September 2018
2
1. Introduction • Motivation • Himalayan snow contributes significantly towards water resource in several countries in Asia. • In mountain hydrology timely information on the spatial and temporal variability of the extent of wet and dry snow is significant in snow melt runoff models.
• These maps are also significant input in climate models. • Snow studies become significant, especially in the northern states in India, such as Jammu and Kashmir, Uttarakhand and Himachal Pradesh,
• Where the water resource and power requirements are mostly met from the hydropower plants established over rivers that are governed by snow melt and or glacial runoffs. • The snow laden mountains in the Himalayas are important tourist destinations, which are often affected by natural disasters such as avalanches. Geoinformatics Civil Engineering Indian Institute of Technology Kanpur
Potential of Information Fusion of Optical and SAR Data for Snow Cover Characterization Divyesh Manohar Varade (
[email protected])
15 September 2018
3
1.1. Role of remote sensing • The seasonal runoffs and the avalanche forecasting, both are vastly dependent on the spatial and temporal variability of the snowpack.
• With the advances in remote sensing technology -The increase in availability of satellite data, the need for field survey for snow
characterization in difficult terrains as that in the Himalayan regions is also significantly reduced. • Recent advances in remote sensing technology have enabled us to study the extent of snow cover using different techniques based on remote sensing data. • Optical remote sensing can provide information on the type of land use land cover. • Information from either of these alone is insufficient for characterization of snow cover. • Thus, using either optical or active microwave data, identification of wet and dry snow for characterization of snow surface is a complicated problem. Geoinformatics Civil Engineering Indian Institute of Technology Kanpur
Potential of Information Fusion of Optical and SAR Data for Snow Cover Characterization Divyesh Manohar Varade (
[email protected])
15 September 2018
4
2. Properties of Snow 2.1. Optical • Snow exhibits distinct reflective properties with respect to different wavelengths in the electromagnetic radiation. • Reflectivity of snow depends upon a number of factors including the liquid water content and the grain size. • Fresh snow appears in powdered form with a very small grain size and liquid water content less than 1.
• Dry snow (LWC=5% by volume) has έ>2.75, • dry snow (LWC
