توسعة شاخص‌های دما/ پوشش گیاهی جهت برآورد رطوبت خاک با استفاده از خطوط هم‌رطوبت به‌دست‌آمده از تصاویر سری زمانی سنجندة MODIS

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد رشتة مهندسی نقشه‌برداری گرایش سنجش از دور، دانشگاه صنعتی خواجه نصیرالدین طوسی

2 دانشیار گروه فتوگرامتری و سنجش از دور دانشگاه صنعتی خواجه نصیرالدین طوسی

چکیده

رطوبت خاک در فرایندهای تعاملی بین جو و زمین و تغییرات جهانی اقلیم نقش مهمی ایفا می‌کند. در سه دهة گذشته، محققان بسیاری به تعیین رطوبت خاک، با استفاده از داده‌های سنجش از دوری، توجه داشته‌اند. روش‌های مثلثی و ذوزنقه‌ای از روش‌های سنجش از دوری‌اند که با ترکیب داده‌های حرارتی و مرئی، شاخصی برای میزان رطوبت را تعیین می‌کنند. یکی از مهم‌ترین موارد تأثیرگذار در دقت این روش‌ها، ‌دقت تعیین لبه‌های خشک و مرطوب در نمودار پراکندگی دما/ پوشش گیاهی است. درنتیجه، ناتوانی در تعیین لبه‌های مذکور، در برخی روزها و شرایط، امکان استفاده از این روش‌ها را محدود می‌کند. هدف این مطالعه مطرح‌کردن روشی برای تعیین دقیق لبه‌های خشک و اشباع، در تمامی روزها و شرایط، با استفاده از تلفیق داده‌های سری زمانی دما و پوشش گیاهی است. به‌منظور تحقق این هدف، خطوط هم‌رطوبت به‌منزلة خطوطی معرفی می‌شوند که رطوبت در امتداد آن‌ها مقدار ثابتی است و برای تعیین لبه‌های خشک و مرطوب در هر روز به‌کار رفته‌اند. شاخص میزان رطوبت خاک پیشنهادی برای 28 روز در سال 2014، در منطقه‌ای از شهر مونیتوبا در کشور کانادا، با استفاده از ویژگی‌های دو خط انتخاب‌شده از میان خطوط هم‌رطوبت به‌دست‌آمده ازطریق داده‌های دمای سطح، دمای هوا و شاخص پوشش گیاهی سنجندة MODIS، محاسبه و با استفاده از داده‌های زمینی ایستگاه‌های رطوبت‌سنجی شبکة RISMA واقع در این منطقه، ارزیابی شده است. در تمامی 28 روز، تصویر شاخص پیشنهادی که معرف میزان رطوبت خاک است، به‌منزلة خروجی روش پیشنهادی به‌دست آمد. ضریب همبستگی شاخص به‌دست‌آمده با میزان رطوبت خاک در روزهای بدون پوشش گیاهی به 92/0 رسیده و این مقدار ضریب همبستگی، در روزهای با پوشش گیاهی انبوه، کمتر بوده است.

کلیدواژه‌ها

عنوان مقاله [English]

Development of Temperature/ Vegetation Indexes for Estimating Soil Moisture Content Using Co- Moisture Lines Extracted from a One- Year Temperature/ Vegetation Scatter Plot of MODIS Data

نویسندگان [English]

  • F Mohseni 1
  • M Mokhtarzadeh 2
1 M.Sc. Student of K.N. Toosi University of Technology, Dep. of Remote Sensing
2 Associate Prof. of K.N. Toosi University of Technology, Dep. of Remote Sensing
چکیده [English]

Soil moisture plays an important role in interactive processes between earth and atmosphere and global climate changes. In recent decades, there has been a great research interest to determine soil moisture from remote sensing methods. Triangular or trapezoidal methods are the most common remote sensing methods that apply the combination of thermal and optical satellite images to estimate soil moisture content. The accuracy of methods governed by the accuracy of saturated and dry edges that define from vegetation/ temperature scatter plot. A main limitation of these methods arose in some days or in some vegetation condition that dry and wet edges cannot be defined correctly. This concern is addressed in this paper by using the temperature and vegetation information during one year interval to form the temperature-vegetation scatter plot, saturated edge and dry edge exactly. The main contribution of the paper is, however, the introduction of co­-moisture lines in the one-year scatter plot. These lines are later applied to define the wet and dry edges of each individual day which are taken as the two closest co-moisture lines that contain all corresponding pixels of that day. The soil moisture index as a parameter dependent to evaporation efficiency is finally estimated from the slope and intercept of these two co-moisture lines. The proposed soil moisture index calculated from co-moisture was implemented and validated in Manitoba, Canada area while MODIS satellite images, taken in 28 cloudless days of year 2014, were used as the input data. The correlation between ground soil moisture data and proposed soil moisture index was estimated. Correlation of 0.92 was achieved for low vegetation days and lower in days with higher vegetation densities.

کلیدواژه‌ها [English]

  • Soil moisture content
  • remote sensing
  • Triangular and trapezoidal methods
  • Dry and wet edges in scatter plot
  • Co-moisture lines

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