• صفحه اصلی
  • پایش تغییرات آب و پوشش گیاهی سطح دریاچه زریوار با استفاده از تصاویر ماهواره‌ای چند زمانه

اشتراک گذاری

آدرس مقاله


کد مقاله : HE-1907-1818 (R3) بازدید : 145 صفحه: 9 - 17

نوع مقاله: پژوهشی

پایش تغییرات آب و پوشش گیاهی سطح دریاچه زریوار با استفاده از تصاویر ماهواره‌ای چند زمانه

محورهای موضوعی : سیستم اطلاعات جغرافیایی

داود حیدری 1 , زهرا عزیزی 2 , سعید بهزادی 3

1 - دانشجوی کارشناسی ارشد سنجش از دور و GIS، دانشکده منابع طبیعی و محیط زیست، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
2 - استادیار گروه سنجش از دور و GIS – دانشکده منابع طبیعی و محیط زیست، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران. *(مسوول مکاتبات)
3 - استادیار گروه مهندسی نقشه‌برداری، دانشکدۀ مهندسی عمران، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران.

تاریخ دریافت : 1398/04/25 تاریخ پذیرش : 1400/04/28 تاریخ انتشار : 1402/04/01

کلید واژه: دریاچه زریوار(زریبار), چند زمانه, تصاویر ماهواره‌ای,

چکیده مقاله :

زمینه و هدف: پایش تغییرات پهنه‌های آبی از جمله موارد حایز اهمیت در مدیریت آن‌هاست. دریاچه‌ زریوار به سبب شرایط اکوسیستمی ویژه طی سال‌های اخیر با پیچیدگی‌های اقلیمی رخ داده دستخوش تغییرات بسزایی شده است. روش بررسی: در این تحقیق تغییرات ایجاد شده در سطح پهنه آبی دریاچه با تکنیک های سنجش از دور مورد پایش و ارزیابی قرار گرفت. بدین منظور ابتدا تصاویر چندطیفی ماهواره‌ لندست مربوط به سال‌های 1985 تا 2015 از منطقه مورد نظر اخذ شده و پس از انجام پردازش‌های رادیومتریک، اعمال طبقه بندی و استخراج شاخص‌های گیاهی سطوح آبی دریاچه از پوشش گیاهی و خاک تفکیک شد. یافته ها: نتایج نشان داد در بازه 30 ساله برررسی دریاچه زریوار تغییر سطح آبی اختلاف بارزی ندارد و آغاز تا پایان دوره بررسی 5/2 درصد افزایش سطح در پهنه آبی مشاهده شده است. بحث و نتیجه گیری:بالاآمدن کف دریاچه در اثر رسوبات و از بین بردن نیزارهای حاشیه دریاچه موجب شده است که مساحت پهنه آبی دریاچه علی رغم کاهش حجم آن تغییر بارزی را نشان ندهد.

چکیده انگلیسی:

Background and Objective: Remote sensing science plays a crucial role in the management of water resources, particularly in monitoring changes in these resources. Recently, Zarivar lake has garnered attention from various environmental organizations due to concerns about its future based on observed changes. The objective of this study is to monitor and evaluate changes in the surface area of Zarivar lake using remote sensing techniques. Material and Methodology: In order to achieve this objective, Landsat satellite images from 1985 to 2015 were obtained and subjected to radiometric processing, classification, and extraction of vegetation indices. This allowed for the separation of the lake water surface from surrounding vegetation and soil. Findings: Analysis of the data revealed that there was no significant difference in the change of water level in Zarivar Lake over the 30-year period studied. Discussion and Conclusion: Despite concerns about Zarivar lake's future, our findings suggest that there has been no significant change in its water level over time. However, it is important to note that sediment buildup on the lake floor and elimination of its margins have resulted in a decrease in volume without a corresponding decrease in surface area.

منابع و مأخذ:


  1. Vörösmarty C.J., et al. (2010) Global threats to human water security and river biodiversity. Nature 467(7315): 555-561.
    2.
  2. Wada Y., et al. (2016) Global depletion of groundwater resources. Geophysical Research Letters 43(14): 7611-7620.
    3.
  3. Ghaffari G., et al. (2019) Water crisis in Iran: causes, effects, and management strategies. Journal of Environmental Management 231: 891-901.
    4.
  4. Mohammadi M., et al. (2018) Assessment of environmental factors affecting Zarivar Lake using multivariate statistical analysis. Environmental Monitoring and Assessment 190(12): 736.
    5.
  5. Wu J., et al. (2020) Sustainable management practices for freshwater conservation: a review of research progress over the past decade. Journal of Cleaner Production 256:120386.
    6.


  1. Ballatore, T., Bradt, S., Olaka, L., Loiselle, S., 2014: Remote Sensing of African Lakes: A Review, Remote Sensing of the African Seas, Chapter: 20, Publisher: Springer, Editors: Vittorio Barale, Martin Gade.
    2.
  2. T Ali Bakhshi, Z Azizi, A Vafaeinejad, H Aghamohammadi Zanjirabadi, 2020: Survey of Area Changes in Water Basins of Shahid Abbaspour Dam Caused by 2019 Floods Using Google Earth Engine, Iranian journal of Ecohydrology 7 (2), 345-357. (In Persian)
    3.
  3. Dörnhöfer, k., Oppelt, N., 2016: Remote sensing for lake research and monitoring – Recent advances, Ecological Indicators, 64: 105-122.
    4.
  4. M Abedinim, A Sotoudehpour , 2016: Detection of Lakes Changes Trends with Using Geography Information System (GIS) and Remote Sensing (Rs).Case Study: Tectonically Zarivar Lake, Natural Geography Quarterly, Vol. 10(53): 45-60 .(In Persian)
    5.
  5. Z Azizi, A Najafi, P Fatehi, M Pirbavaghar, 2010: Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon), Iranian Journal of Forest and Poplar Research 18 (1), 151-143.(In Persian)
    6.
  6. Y Liu, G Wu, X Zhao, 2013: Recent declines in China's largest freshwater lake: trend or regime shift? Environmental Research Letters, Vol. 8(1): 10.1088/1748-9326/8/1/014010
    7.
  7. Guo, W., Ni, X., Jing, D, Li, S, 2014. Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data. J. Geogr. Sci. 24, 1009–1021. https://doi.org/10.1007/s11442-014-1134-y
    8.
  8. Z Yin, J Li, Y Liu, Y Xie, F Zhang, S Wang, X Sun, B Zhang, 2021: Water clarity changes in Lake Taihu over 36 years based on Landsat TM and OLI observations, International Journal of Applied Earth Observation and Geoinformation, Vol.102: 102457.
    9.
  9. Markogianni v, Dimitriou e, Kalivas dp, Land-use and vegetation change detection in Plastira artificial lake catchment (Greece) by using remote-sensing and GIS techniques. 2013. International journal of remote sensing 34 (4), 1265-1281
    10.
  10. Datas and Statistics info of water org, 2006:87-98. (In Persian)
    11.
  11. Bruzzone, L., Carlin, L., & Prieto, D. F. (2010). Impact of mechanical errors on remote sensing data analysis: a review of the ESA Landsat 7 failure. Remote Sensing, 2(10), 2428-2447.
    12.
  12. Chen, X., Liang, S., Liu, R., & Wang, J. (2012). Impact of mechanical errors on remote sensing data analysis: a case study of Landsat 7 ETM+ SLC-off data over China. Remote Sensing Letters, 3(6), 503-512.
    13.
  13. Wang, H., Zhang, Y., & Liang, T. (2020). The impact of meteorological conditions on remote sensing data analysis: a case study of Landsat 8 image over a lake in China. Journal of Applied Remote Sensing, 14(4), 046501.
    14.
  14. Wang, Y., Liang, T., & Zhang, Y. (2019). Sedimentation as a major factor affecting lake water level changes: a case study of Poyang Lake in China using satellite altimetry and optical imagery data. Water Resources Research, 55(11), 9405-9421.
    15.
  15. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Cambridge University Press.
    16.
  16. Ramsar Convention Secretariat. (n.d.). Wetlands and Water: Why are they important? Retrieved from https://www.ramsar.org/wetlands-and-water-why-are-they-important.
    17.

 

 

 

 

 

_||_

  1. Vörösmarty C.J., et al. (2010) Global threats to human water security and river biodiversity. Nature 467(7315): 555-561.
    2.
  2. Wada Y., et al. (2016) Global depletion of groundwater resources. Geophysical Research Letters 43(14): 7611-7620.
    3.
  3. Ghaffari G., et al. (2019) Water crisis in Iran: causes, effects, and management strategies. Journal of Environmental Management 231: 891-901.
    4.
  4. Mohammadi M., et al. (2018) Assessment of environmental factors affecting Zarivar Lake using multivariate statistical analysis. Environmental Monitoring and Assessment 190(12): 736.
    5.
  5. Wu J., et al. (2020) Sustainable management practices for freshwater conservation: a review of research progress over the past decade. Journal of Cleaner Production 256:120386.
    6.


  1. Ballatore, T., Bradt, S., Olaka, L., Loiselle, S., 2014: Remote Sensing of African Lakes: A Review, Remote Sensing of the African Seas, Chapter: 20, Publisher: Springer, Editors: Vittorio Barale, Martin Gade.
    2.
  2. T Ali Bakhshi, Z Azizi, A Vafaeinejad, H Aghamohammadi Zanjirabadi, 2020: Survey of Area Changes in Water Basins of Shahid Abbaspour Dam Caused by 2019 Floods Using Google Earth Engine, Iranian journal of Ecohydrology 7 (2), 345-357. (In Persian)
    3.
  3. Dörnhöfer, k., Oppelt, N., 2016: Remote sensing for lake research and monitoring – Recent advances, Ecological Indicators, 64: 105-122.
    4.
  4. M Abedinim, A Sotoudehpour , 2016: Detection of Lakes Changes Trends with Using Geography Information System (GIS) and Remote Sensing (Rs).Case Study: Tectonically Zarivar Lake, Natural Geography Quarterly, Vol. 10(53): 45-60 .(In Persian)
    5.
  5. Z Azizi, A Najafi, P Fatehi, M Pirbavaghar, 2010: Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon), Iranian Journal of Forest and Poplar Research 18 (1), 151-143.(In Persian)
    6.
  6. Y Liu, G Wu, X Zhao, 2013: Recent declines in China's largest freshwater lake: trend or regime shift? Environmental Research Letters, Vol. 8(1): 10.1088/1748-9326/8/1/014010
    7.
  7. Guo, W., Ni, X., Jing, D, Li, S, 2014. Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data. J. Geogr. Sci. 24, 1009–1021. https://doi.org/10.1007/s11442-014-1134-y
    8.
  8. Z Yin, J Li, Y Liu, Y Xie, F Zhang, S Wang, X Sun, B Zhang, 2021: Water clarity changes in Lake Taihu over 36 years based on Landsat TM and OLI observations, International Journal of Applied Earth Observation and Geoinformation, Vol.102: 102457.
    9.
  9. Markogianni v, Dimitriou e, Kalivas dp, Land-use and vegetation change detection in Plastira artificial lake catchment (Greece) by using remote-sensing and GIS techniques. 2013. International journal of remote sensing 34 (4), 1265-1281
    10.
  10. Datas and Statistics info of water org, 2006:87-98. (In Persian)
    11.
  11. Bruzzone, L., Carlin, L., & Prieto, D. F. (2010). Impact of mechanical errors on remote sensing data analysis: a review of the ESA Landsat 7 failure. Remote Sensing, 2(10), 2428-2447.
    12.
  12. Chen, X., Liang, S., Liu, R., & Wang, J. (2012). Impact of mechanical errors on remote sensing data analysis: a case study of Landsat 7 ETM+ SLC-off data over China. Remote Sensing Letters, 3(6), 503-512.
    13.
  13. Wang, H., Zhang, Y., & Liang, T. (2020). The impact of meteorological conditions on remote sensing data analysis: a case study of Landsat 8 image over a lake in China. Journal of Applied Remote Sensing, 14(4), 046501.
    14.
  14. Wang, Y., Liang, T., & Zhang, Y. (2019). Sedimentation as a major factor affecting lake water level changes: a case study of Poyang Lake in China using satellite altimetry and optical imagery data. Water Resources Research, 55(11), 9405-9421.
    15.
  15. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Cambridge University Press.
    16.
  16. Ramsar Convention Secretariat. (n.d.). Wetlands and Water: Why are they important? Retrieved from https://www.ramsar.org/wetlands-and-water-why-are-they-important.
    17.

 

 

 

 

 

سکوی نشر دانش

سند یا سکوی نشر دانش ،سامانه ای جهت مدیریت حوزه علمی و پژوهشی نشریات دانشگاه آزاد می باشد

پیوندهای سایت

مراکز مرتبط

پشتیبانی

صفحات رسمی

حقوق این وب‌سایت متعلق به سامانه مدیریت نشریات دانشگاه آزاد اسلامی است.
حق نشر © 1403-1400

صفحه اصلی| عضویت/ ورود| درباره سند| تماس با ما|
[English] [العربية] [en] [ar]