نظارت بر پوشش برف با استفاده از تصاویر ماهواره‌ای MODIS (مطالعه موردی حوزه ‌آبخیز قره‌چای)

نویسندگان

چکیده

در حوزه‌های آبخیز تعیین سطح پوشش برف به‌عنوان یکی از پارامترهای مهم برف‌سنجی،‏ نقش مهمی در بررسی‌های هیدرولوژی و اقلیمی دارد.در بررسی سطح پوشش برف و ویژگی‌های هیدرولوژیکی حوزه‌های آبخیز از داده‌های سنجش از دور استفاده شد. در این پژوهش برای تهیه نقشه پوشش برف از تصویر‌های MODIS و شاخص NDSI استفاده شد. در الگوریتم برف‌سنجی،‏ با تعریف شاخص NDSI جداسازی برف انجام شد اما با توجه به عدم توانایی این شاخص در جداسازی برف از سایر منابع رطوبتی،‏ با تعریف حدود آستانه برای باندهای 2،‏ 4 و 6 این مسئله حل شد. در پایان با استفاده از الگوریتم مالچر سطح پوشش برف برای روز‌های بدون تصویر در‌نظر گرفته شد. نتایج نشان از توانایی شاخص NDSI در جداسازی پیکسل‌های دارای برف همراه با اعمال آستانه‌های ذکر شده،‏ دارد. نقشه‌های سطح پوشیده از برف در این پژوهش با احتساب خطای شاخص NDSI به طور متوسط کمتر از 20 درصد خطا به دست آمد. درنهایت مساحت پوشش برف برای سال آبی 1386-1385به کمک الگوریتم مالچر و شاخص NDSI برای سه زون ارتفاعی با اختلاف ارتفاع 500 متر محاسبه شد.

کلیدواژه‌ها


عنوان مقاله [English]

Snow covers monitoring using MODIS data (Case study: Ghara-Chay Watershed, Hamedan, IRAN)

نویسندگان [English]

  • mahtab safari shad
  • mahmoud habibnejad rooshan
  • Alireza ildoromi
  • Mirhasan Miryaghoobzadeh
چکیده [English]

Snow is one of the major sources of water in most part of the world. In the hydrology and climate studies, determination of the snow cover surface area is one of the most important parameters. One of the tools that have a lot of use in the watershed snow cover survey and hydrological properties is remote monitoring by satellite images. In this research, we used the MODIS images and NDSI index for mapping of snow cover. We calculated the NDSI index and we used the threshold in 2, 4 and 6 bands for discrimination between snow and other wet lands. After calculating NDSI, the snow-covered surface was then interpolated for days without satellite images by Malcher algorithm. The results showed that the NDSI index assistant with the thresholds and Malcher algorithm had good performances in determining the snow cover surface area. In this research, the average error of snow cover maps, including the error of NDSI index is less than 20%. At the end, we calculated the snow cover with Malcher algorithm and NDSI index for 2006-2007.


Snow is one of the major sources of water in most part of the world. In the hydrology and climate studies, determination of the snow cover surface area is one of the most important parameters. One of the tools that have a lot of use in the watershed snow cover survey and hydrological properties is remote monitoring by satellite images. In this research, we used the MODIS images and NDSI index for mapping of snow cover. We calculated the NDSI index and we used the threshold in 2, 4 and 6 bands for discrimination between snow and other wet lands. After calculating NDSI, the snow-covered surface was then interpolated for days without satellite images by Malcher algorithm. The results showed that the NDSI index assistant with the thresholds and Malcher algorithm had good performances in determining the snow cover surface area. In this research, the average error of snow cover maps, including the error of NDSI index is less than 20%. At the end, we calculated the snow cover with Malcher algorithm and NDSI index for 2006-2007.


Snow is one of the major sources of water in most part of the world. In the hydrology and climate studies, determination of the snow cover surface area is one of the most important parameters. One of the tools that have a lot of use in the watershed snow cover survey and hydrological properties is remote monitoring by satellite images. In this research, we used the MODIS images and NDSI index for mapping of snow cover. We calculated the NDSI index and we used the threshold in 2, 4 and 6 bands for discrimination between snow and other wet lands. After calculating NDSI, the snow-covered surface was then interpolated for days without satellite images by Malcher algorithm. The results showed that the NDSI index assistant with the thresholds and Malcher algorithm had good performances in determining the snow cover surface area. In this research, the average error of snow cover maps, including the error of NDSI index is less than 20%. At the end, we calculated the snow cover with Malcher algorithm and NDSI index for 2006-2007.


Snow is one of the major sources of water in most part of the world. In the hydrology and climate studies, determination of the snow cover surface area is one of the most important parameters. One of the tools that have a lot of use in the watershed snow cover survey and hydrological properties is remote monitoring by satellite images. In this research, we used the MODIS images and NDSI index for mapping of snow cover. We calculated the NDSI index and we used the threshold in 2, 4 and 6 bands for discrimination between snow and other wet lands. After calculating NDSI, the snow-covered surface was then interpolated for days without satellite images by Malcher algorithm. The results showed that the NDSI index assistant with the thresholds and Malcher algorithm had good performances in determining the snow cover surface area. In this research, the average error of snow cover maps, including the error of NDSI index is less than 20%. At the end, we calculated the snow cover with Malcher algorithm and NDSI index for 2006-2007.

کلیدواژه‌ها [English]

  • MODIS-NDSI-Malchr algorithm-Snow mapping algorithm-Ghara-Chay Watershed.-