Remote Sensing and GIS Applications in Environmental Sciences

Evaluation of water indicators using Landsat and Sentinel satellite images (case area: Zaribar Lake)

Document Type : Original Article

Authors

1 Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

2 - Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

10.22034/rsgi.2024.64194.1111

Abstract

In recent years, remote sensing data have played an important role in natural resource management studies, especially in water resources research. Among the studies related to water resources, the use of water indicators has been highly considered. With the advancement of technology and the production of satellite images, these indicators have grown and developed more and their accuracy has increased significantly. In this research, Landsat 8 and Sentinel 2A images related to a 9-year period have been used to analyze and identify water areas in the target area. The indices used in the research are NDWI, NDWIPlus, MNDWI, WRI and AWEI indices in two shaded and unshaded versions. The results showed that the AWEIshadow index with an average kappa coefficient of 0.9901 in Sentinel and 0.9692 in Landsat 8 was the best index and the worst result was AWEINoShadow index with an average kappa coefficient of 0.4997 in Sentinel and 0.618 in Landsat 8 for water identification.The results of this research showed that the use of water extraction indicators and high-precision satellite images can be an effective tool for monitoring and sustainable management of water resources. The results can help planners and managers to make more optimal decisions regarding the protection and exploitation of natural resources

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Main Subjects

در این مطالعه از تصاویر لندست 8 و سنتینل 2A برای تجزیه و تحلیل و شناسایی مناطق آبی دریاچه‌ی زریبار استفاده شد. در سال‌های اخیر، داده‌های سنجش از دور برای مطالعات مدیریت منابع طبیعی، به‌ویژه در تحقیقات منابع آب، حیاتی بوده‌اند. در میان مطالعات مربوط به منابع آب، استفاده از شاخص‌های آب بسیار مورد توجه قرار گرفته است و با پیشرفت تکنولوژی و تولید تصاویر ماهواره‌ای، این شاخص‌ها رشد و توسعه بیشتری یافته و دقت آنها افزایش چشمگیری داشته است. شاخص AWEIshadow با میانگین ضریب کاپا 9901/0 در سنتینل 2A و 9692/0 در لندست 8، بهترین شاخص برای شناسایی آب بود، در حالی که شاخص AWEINoShadow با میانگین ضریب کاپا 4997/0 در سنتینل 2A و 618/0 در لندست 8 ضعیف‌ترین شاخص بود. به طور کلی، تصاویر سنتینل  2A دقت بسیار بالاتری نسبت به لندست 8 داشتند که به دلیل قدرت تفکیک مکانی بالای سنتینل است. بر اساس یافته های این مطالعه، تصاویر ماهواره‌ای با دقت بالا و شاخص های استخراج آب می‌توانند ابزارهای مفیدی برای مدیریت و پایش پایدار منابع آب باشند. یافته‌ها می‌تواند به مدیران و برنامه‌ریزان در تصمیم گیری بهتر در مورد حفظ و استفاده از منابع آبی کمک کند.

Asghari Sarskanrood, Sayyad, and Mahdi Poorahmed. 2016. 'Detection and Extraction of Changes in Zarineh Rud River’s Variation between 1989 and 2014 via Remote Sensing Data', Hydrogeomorphology, 2: 1-16. (In Persian)
Dominici, Donatella, Sara Zollini, Maria Alicandro, Francesca Della Torre, Paolo Massimo Buscema, and Valerio Baiocchi. 2019. 'High resolution satellite images for instantaneous shoreline extraction using new enhancement algorithms', Geosciences, 9: 123.
Du, Zhiqiang, Wenbo Li, Dongbo Zhou, Liqiao Tian, Feng Ling, Hailei Wang, Yuanmiao Gui, and Bingyu Sun. 2014. 'Analysis of Landsat-8 OLI imagery for land surface water mapping', Remote sensing letters, 5: 672-81.
Feyisa, Gudina L, Henrik Meilby, Rasmus Fensholt, and Simon R Proud. 2014. 'Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery', Remote sensing of environment, 140: 23-35.
Gautam, Vivek Kumar, Piyush Kumar Gaurav, P Murugan, and MJAP Annadurai. 2015. 'Assessment of surface water Dynamicsin Bangalore using WRI, NDWI, MNDWI, supervised classification and KT transformation', Aquatic Procedia, 4: 739-46.
Gong, Wenfeng, Tiedong Liu, Yan Jiang, and Philip Stott. 2020. 'Applicability of the Surface Water Extraction Methods Based on China's GF-2 HD Satellite in Ussuri River, Tonghe County of Northeast China', Nature Environment & Pollution Technology, 19.
Hashemi, Seyedeh Nastaran, Mohammad Akbarinasab, and Taher Safarrad. 2018. 'The Detection of the Plume of the Arvand River Using Satellite Images', Hydrogeomorphology, 4: 147-64. (In Persian)
Jiang, Hao, Min Feng, Yunqiang Zhu, Ning Lu, Jianxi Huang, and Tong Xiao. 2014. 'An automated method for extracting rivers and lakes from Landsat imagery', Remote Sensing, 6: 5067-89.
Kaplan, Gordana, and Ugur Avdan. 2017. 'Object-based water body extraction model using Sentinel-2 satellite imagery', European Journal of Remote Sensing, 50: 137-43.
Kwang, Clement, Edward Matthew Osei Jnr, and Adwoa Sarpong Amoah. 2017. 'Comparing of landsat 8 and sentinel 2A using water extraction indexes over Volta River', Journal of Geography and Geology, 10: 1-7.
Lacaux, JP, YM Tourre, Cecile Vignolles, JA Ndione, and M Lafaye. 2007. 'Classification of ponds from high-spatial resolution remote sensing: Application to Rift Valley Fever epidemics in Senegal', Remote sensing of environment, 106: 66-74.
Li, Wenbo, Zhiqiang Du, Feng Ling, Dongbo Zhou, Hailei Wang, Yuanmiao Gui, Bingyu Sun, and Xiaoming Zhang. 2013. 'A comparison of land surface water mapping using the normalized difference water index from TM, ETM+ and ALI', Remote Sensing, 5: 5530-49.
Lu, Dengsheng, and Qihao Weng. 2007. 'A survey of image classification methods and techniques for improving classification performance', International Journal of Remote Sensing, 28: 823-70.
McFeeters, Stuart K. 1996. 'The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features', International Journal of Remote Sensing, 17: 1425-32.
Pi, Xuehui, Qiuqi Luo, Lian Feng, Yang Xu, Jing Tang, Xiuyu Liang, Enze Ma, Ran Cheng, Rasmus Fensholt, and Martin Brandt. 2022. 'Mapping global lake dynamics reveals the emerging roles of small lakes', Nature communications, 13: 5777.
Rundquist, Donald C, Merlin P Lawson, Lloyd P Queen, and Randall S Cerveny. 1987. 'THE RELATIONSHIP BETWEEN SUMMER‐SEASON RAINFALL EVENTS AND LAKE‐SURFACE AREA 1', JAWRA Journal of the American Water Resources Association, 23: 493-508.
Sarp, Gulcan, and Mehmet Ozcelik. 2017. 'Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey', Journal of Taibah University for Science, 11: 381-91.
Shen, Li, and Changchun Li. 2010. "Water body extraction from Landsat ETM+ imagery using adaboost algorithm." In 2010 18th International Conference on Geoinformatics, 1-4. IEEE.
Sotoudehpour, Afshin, Aghil Madadi, and Sayyad Asghari. 2024. 'Comparing water extraction indexes using landsat8 and sentinel2A images. Case study: Bushehr shoreline', Journal of Marine Science and Technology, 23: 59-83. (In Persian)
Vos, Kilian, Kristen D Splinter, Mitchell D Harley, Joshua A Simmons, and Ian L Turner. 2019. 'CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery', Environmental Modelling & Software, 122: 104528.
Xie, Huan, Xin Luo, Xiong Xu, Haiyan Pan, and Xiaohua Tong. 2016. 'Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction', International Journal of Remote Sensing, 37: 1826-44.
Xu, Hanqiu. 2006. 'Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery', International Journal of Remote Sensing, 27: 3025-33.
 Zhou, Y., Dong, J., Xiao, X., Xiao, T., Yang, Z., Zhao, G., ... & Qin, Y. (2017). Open surface water mapping algorithms: A comparison of water-related spectral indices and sensors. Water, 9(4), 256.‏
Remote Sensing and GIS Applications in Environmental Sciences
Volume 4, Issue 12
November 2024
Pages 115-95
  • Receive Date: 26 October 2024
  • Revise Date: 06 November 2024
  • Accept Date: 11 November 2024