Analysis of Snow Cover Changes in the Western Watersheds of Lake Urmia through Optimization and Fusion of Sentinel-2 and Landsat (8 and 9) Images

Document Type : Research Paper

Authors

1 Ph.D. student, Department of Hydrology and Meteorology, Marand Branch, Islamic Azad University, Marand, Iran

2 Professor, Department of Meteorology, Faculty of Planning and Environmental Sciences, Tabriz University

3 Professor of Geomorphology Department, Faculty of Planning and Environmental Sciences, Tabriz University, Iran

4 Professor of Remote Sensing and GIS Department, Faculty of Planning and Environmental Sciences, Tabriz University, Ira

10.22034/gp.2024.60313.3230

Abstract

The main aim of the current study was to detect changes in snow cover within the Western watersheds of Lake Urmia, situated in the Silvaneh mountain range, using the processing of multi-sensor and multi-spectral satellite images for high-precision identification of snow-covered areas. Sentinel-2 and Landsat (8 and 9) satellite images were acquired and underwent preprocessing operations, such as atmospheric and radiometric corrections, using ENVI software version 1/10. Projects for the May months of the years 2016 to 2023 were then established. Initially, normalized difference snow indices were employed to independently generate snow cover maps for Landsat and Sentinel images for the entire watersheds of Nazluchay, Ruzechay, Shahrchay, and Barandozchay. In the next stage, an optimized color-sensitive object-based approach, based on object-oriented functions, was applied to the main bands of the Sentinel-2 sensor. To enhance the accuracy of the final results, Landsat images were fused with Sentinel images through a coordinated fusion method, producing various products, especially high-resolution optimized color images and classified scene maps. Ultimately, high-precision snow cover maps for temporal series were extracted for each of the mentioned watersheds through processing the fused images. Examination of the snow cover maps revealed that despite its smaller area compared to the Nazluchay and Barandozchay watersheds, the Shahrchay watershed has a higher snow accumulation coefficient, allowing for greater snow cover storage. Additionally, the comparison of the snow cover density map (years 2016 to 2023) with the elevation model of Alouspalsar at a resolution of 5/12 meters indicates a significant distribution of snow cover in higher elevations above 2300 meters in the study area. Therefore, accurate identification of snow cover, even on a daily and weekly scale, can provide essential and precise information for proactive water resource management, resulting from snowmelt, with multiple objectives in the watersheds surrounding Lake Urmia.

Keywords

Main Subjects

Full Text

هدف اصلی تحقیق فعلی، تشخیص تغییرات سطح پوشش برف در حوضه‌های غربی دریاچه ارومیه، واقع در رشته کوه سیلوانه، با استفاده از پردازش تصاویر ماهواره‌ای چند سنجنده‌ای و چند طیفی برای شناسایی دقیق مناطق پوشش برف می‌باشد. تصاویر ماهواره‌ای سنتینل-۲ و لندست (۸ و ۹) قابل دسترس عملیات پیش‌پردازش از قبیل تصحیحات جوی و رادیومتریک با استفاده از نرم‌افزار ENVI نسخه 1/10 انجام شد. پروژه‌ها برای ماه‌های مه سال‌های ۲۰۱۶ تا ۲۰۲۳ ایجاد گردید. ابتدا، با استفاده از شاخص‌های تفاضلی نرمال شده برف، نقشه‌های پوشش برف مستقل برای تصاویر لندست و سنتینل برای کل حوضه‌های آبریز نازلو‌چای، روضه‌چای، شهرچای و باراندوزچای تولید گردید. در مرحله بعد، با بکارگیری یک روش بهینه سازی شده بر اساس توابع شیء‌گرا وابسته به رنگ بر روی باندهای اصلی سنجنده سنتینل-۲، تصاویر لندست با تصاویر سنتینل تلفیق شدند. این تلفیق به تولید محصولات متنوع، به ویژه تصاویر بهینه رنگی با وضوح بالا و نقشه‌های طبقه‌بندی صحنه مطالعه منجر شد. در نهایت، نقشه‌های سطح پوشش برف با دقت بالا برای دوره‌های زمانی مختلف برای هر یک از حوضه‌های گفته شده از تصاویر تلفیق شده استخراج گردید. بررسی نقشه‌های پوشش برف نشان داد که حوضه آبریز شهرچای علیرغم مساحت کمتر نسبت به حوضه‌های نازلوچای و باراندوزچای، دارای ضریب تجمع برف بالاتری بوده و در نتیجه امکان ذخیره پوشش برف بیشتری را دارا است. همچنین، مقایسه نقشه تراکم پوشش برف (سال‌های ۲۰۱۶ تا ۲۰۲۳) با مدل ارتفاعی آلوس‌پالسار با وضوح ۵/۱۲ متر نشان می‌دهد که مساحت قابل توجهی از پوشش برف در ارتفاعات بالاتر از ۲۳۰۰ متر در محدوده مطالعه توزیع شده است. بنابراین، شناسایی دقیق پوشش برف، حتی در مقیاس روزانه و هفتگی، اطلاعات ضروری و دقیقی را برای مدیریت پیشگیرانه منابع آب به دنبال ذوب برف با اهداف متعدد در حوضه‌های آبریز اطراف دریاچه ارومیه فراهم می‌آورد.

References

Amidi, Qale; Mohammadi, Mahboobeh (2014) Investigation of changes in snow cover levels in the heights of Zardkouh Bakhtiari using remote sensing. Master's thesis, University of Sistan and Baluchestan. [In Persian]
Amininia, Karim; Lashkari, Hassan; Alijani, Bahloul (2010) Investigation and analysis of heavy snowfall fluctuations in northwest Iran, Geographical Space Journal, No. 29. [In Persian]
Janparvar, Mohsen; Abbasi, Farid; Ghabasfidi, Elham; Mazandarani, Darya (2010) Parameters affecting environmental issues in northwest Iran (case study: drying of Lake Urmia); Scientific Journal of Geography and Environmental Hazards, Volume 9, No. 3 (35th issue), 143-157. [In Persian]
Jahanbakhsh Asl, Saeed; Dinpajouh, Yaghoub; Alinejad, Mohammadhossein; Valizadeh Kamran, Khalil; Parhizkar, Morteza (2016) Simulation of snowmelt runoff in Shahrchay basin using SRM model, Journal of Geography and Environmental Planning (Humanities Research Journal of Isfahan University) Volume 27, Issue 3 (63), 1-14. [In Persian]
Jooybari Moghadam, Yaser; Akhondzadeh, Mehdi; Sarajian, Mohammad Reza (2014) Estimation of snow cover using Landsat 8 satellite images. First International Conference on Environmental Engineering, Tehran, Center for Sustainable Development Solutions. [In Persian]
Heydari, Hassan (2016) Analysis of changes in snowfall and rainfall in selected stations of West Azerbaijan Province, Journal of Geographical Studies of Arid Regions, Volume 7, Issue 26, 110-92. [In Persian]
Khatami, Mahdieh (2019) Spatial analysis of snow cover in the Urmia Lake watershed using MODIS sensor. Thesis for obtaining a master's degree in the field of water and meteorology, Faculty of Planning and Environmental Sciences, University of Tabriz. [In Persian]
Rasouli, Ali Akbar; Abdian, Mohammad; Ranjbar, Farhad (2015) Study of changes in snow and ice cover of Sabalan Mountain heights during the past three decades using remote sensing and GIS. The First International Congress on Earth, Space and Clean Energy, November 5, 2015, Ardabil, University of Mohaghegh Ardabili. [In Persian]
Zeinali, B.; Ghale, E.; Safari, Shiva (2017) Extraction of snow cover area of Sabalan Mountain using Landsat satellite images using object-oriented classification method. Journal of Hydrogeomorphology, 8 (26). [In Persian]
Sari-Saraf, Behrouz; Nagizadeh, Habibeh; Rasouli, Ali Akbar; Jahanbakhsh, Saeed; Babaiyan, Iman (2019) Spatial modeling and analysis of snow depth in the northern part of Iran. Physical Geography Research, Volume 5, Issue 4, 651-671. [In Persian]
Soleimani, Karim; Darvishi, Shadman; Shokrian, Fatemeh; Rashidpour, Mustafa (2018) Spatial-temporal monitoring of snow cover in Kurdistan province using MODIS satellite images. Iranian Journal of Remote Sensing and GIS, 10(3), 104-77. [In Persian]
Seifi, Houshang (2019) Estimating snow cover level through object-oriented techniques using OLI and TIRS sensor images, case study: Sabalan Mountain, Journal of Applied Research in Geographical Sciences, 21(63). [In Persian]
Shakiba, Amineh; Sadeghi, Soleiman; Dostan, Reza (2015) Activity centers and synoptic patterns of heavy snowfall in northwest Iran, Journal of Geography and Environmental Hazards, No. 4, serial number 16, 104-87. [In Persian]
Kashki, Abdolreza; Hosseini, Seyed Mohammad; Zandi, Rahman; Hajimohammadi, Hassan (2018) Satellite-synoptic survey of widespread snowfall in western Iran, Scientific Journal of Geography and Planning; Year 26, Issue 82, 189-210. [In Persian]
Matinnia, Vahid (2018) Study of the trend of changes in the snow cover level in the Urmia Lake basin. Master's thesis in civil engineering, Shahrood University of Technology. [In Persian]
Moharrami, Meysam; Rasouli, Ali Akbar; Rostamzadeh Hashem (2016) Modeling the effects of Lake Urmia's recession on the villages on the eastern shore of Lake Urmia using object-oriented processing of satellite images. Spatial Analysis of Environmental Hazards; Volume 3, Issue 3, 81-98. [In Persian]
Mirmousavi, Seyed Hossein; Sabour, Leila (2014) Monitoring snow cover changes using MODIS sensor images in the northwest region of Iran. Geography and Development, Issue 35. [In Persian]
Miriaghobzadeh, Mir Hossein; Ghanbarpour, Mohammad Reza (2010) Study of the application of snow cover maps obtained from MODIS satellite images in snowmelt runoff modeling (case study: Karaj Dam watershed). No. 76, 214-141. [In Persian]
Nikokhsal, Younes; Rasouli, Ali Akbar; Mokhtari, Davud; Valizadeh Kamran, Khalil (2013) Analysis of the relationship between precipitation changes and groundwater levels in the Marand Plain using the NRMC method. Scientific Journal of Geography and Planning; Year 26, No. 81, 265-276. [In Persian]
Hoshyar, Mahmoud; Javanbakht Shinabad, Nasrin (2018) Synoptic analysis of heavy snowfall in Urmia County, Second National Conference of Iran on Water and Meteorology.[In Persian]
Burges, C. (1998) A Tutorial on Support Vector Machines for Pattern Recognition, Data Mining, and Knowledge Discovery. Kluwer Academic Publishers.
Foster, J.L.; Hall, D.K.; Chang, Z. (1987) Remote sensing of snow. Eos Trans. Amer. Geophys. Union, 68, 682–684.
Gascoin, S.; Grizonnet, M.; Bouchet, M.; Salgues, G.; Hagolle, O. (2019) Theia Snow collection: High‐resolution operational snow cover maps from Sentinel‐2 and Landsat‐8 data. Earth Syst. Sci. Data, 11, 493–514.
Li, J.; Chen, B. (2020) Global Revisit Interval Analysis of Landsat-8 -9 and Sentinel-2A -2B Data for Terrestrial Monitoring, Sensors, 20 (22), 6631.
Li, J.; Roy, D.P.  (2017) A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring. Remote Sens, 9, 902.
Masek, J.G.; Wulder, M.A.; Markham, B.; McCorkel, J.; Crawford, C.J.; Storey, J.; Jenstrom, D.T.  (2020) Landsat 9: Empowering open science and applications through continuity. Remote Sens. Environ, 248, 111968.
Philipp, R.; Tobias, B.; Claudia, N.; Frank, P. A. (2014) Comparison of Pixel- and Object-Based Glacier Classification with Optical Satellite Images. IEEE J.-Stars., 3, 853–862.
Rasouli, A. A.; Milani, M.; Milani, B. (2021) Mastering Object-Based Image Analysis: “Imaging the Azerbaijan Geo-Environment”. iKSAD Publishing House, Turkey.
Rasouli, A.A.; Cheung, K.K.W.; Mohammadzadeh Alajujeh, K.; Ji, F. (2022) On the Detection of Snow Cover Changes over the Australian Snowy Mountains Using a Dynamic OBIA Approach. Journal of Atmosphere. 25 P.
Rasouli, A.A.; Mammadov, R. (2020) Preliminary Satellite Image Analysis Inside the ArcGIS Setting; Lambert Academy Publishing: Chis‐ inau, Republic of Moldova.
Sanchez‐Espinosa, A.; Schroder, C. (2019) Land use and land cover mapping in wetlands one step closer to the ground: Sentinel‐2 versus Landsat 8. J. Environ. Manag, 247, 484–498.
Sibandze, P. Mhangara, P.  Odindi, J. Kganyago, M. (2014) A comparison of Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDPCSI) techniques in distinguishing snow from related land cover types.  South African Journal of Geomatics, Vol. 3, No. 2. 197.
Singh, K. K., Singh, D. K., Thakur, N. K., Dewali, S. K., Negi, H. S., Snehmani, & Mishra, V. D. (2020) Detection and mapping of snow avalanche debris from Western Himalaya, India using remote sensing satellite images. Geocarto International, 37(9), 2561-2579.
Trimble eCognition Suite (2019) eCognition Developer 10.1 Reference Book, Munich, Germany. All rights reserved. Trimble Documentation, Munich, Germany.
U.S. Geological Survey (2022) Landsat 9 Data Users Handbook, Department of the Interior U.S.
U.S. Geological Survey. (2018) Landsat Analysis Ready Data: U.S. Geological Survey Fact Sheet; U.S. Geological Survey: Reston, VA, USA.
Wang, J., Li, W. (2003) Comparison of methods of snow cover mapping by analyzing the solar spectrum of satellite remote sensing data in China. Int. J. Remote Sens., 24, 4129–4136.
Yan, L., D.P. Roy, H. Zhang, J. Li, and H. Huang (2016) An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi-Spectral Instrument (MSI) imagery. Remote Sens. 8, 520.

Files

Share

How to cite

Statistics