تهیه نقشه شوری خاک سطحی با استفاده از فن‌آوری سنجش از دور (مطالعه موردی: اراضی جنوب استان آذربایجان غربی)

نوع مقاله: مقاله پژوهشی

چکیده

شوری خاک یکی از مهم‌ترین عوامل محدودکننده‌ کشت محصولات کشاورزی است و بیش از 50% اراضی آبی دنیا دچار شوری با درجات مختلف هستند. یکی از مهم‌ترین مشکلات کشاورزی در ایران نیز، شوری خاک است که استان آذربایجان غربی نیز از این امر مستثنی نیست. هدف از انجام تحقیق حاضر، بررسی امکان تهیه نقشه شوری خاک سطحی در مساحتی برابر 68000 هکتار از اراضی جنوب استان آذربایجان ­غربی با کاربرد سنجش از دور می‌باشد. برای تهیه‌ نقشه‌ شوری خاک (cm 15-0)، از روش نمونه‌برداری سیستماتیک تصادفی (147 نمونه خاک 500 گرمی) و تجزیه­­و­تحلیل آزمایشگاهی استفاده شد. در این تحقیق، تصاویر ماهواره‌ IRS-P6 (باندهای چندطیفی و پانکروماتیک) به­کار گرفته شده و تصحیح هندسی تصاویر با کاربرد مدل رقومی ارتفاع و نقشه‌ جاده‌ها و آبراهه‌ها صورت گرفت. شاخص‌های متعددی با استفاده از روش‌های مختلف نسبت‌گیری‌ و تحلیل مولفه‌های اصلی، تهیه و در طبقه‌بندی‌ها استفاده شدند. پس از انتخاب نمونه‌های آموزشی مناسب، طبقه‌بندی با تعداد کلاسه‌های مختلف با روش نظارت‌شده و الگوریتم‌های مختلف صورت گرفت. نتایج ارزیابی صحت‌سنجی نشان داد که بیش‌ترین درصد صحت کلی و ضریب کاپا (96/87% و 77/0) مربوط به طبقه‌بندی دوکلاسه با ترکیب چهارباندی و الگوریتم حداکثر احتمال بود. همچنین نتایج بیان­گر قابلیت بالای سنجش از دور و داده‌های IRS-P6 برای تهیه نقشه شوری خاک سطحی در مقیاس محلی می­باشد.
 

کلیدواژه‌ها


عنوان مقاله [English]

Mapping Soil Salinity Using Remote Sensing Technology (Case Study: South Lands of West Azarbaijan province)

چکیده [English]

Soil salinity is one of the most important limiting factors in crop production and more than 50% of the world irrigated lands have different levels of salinity. Also, one of the most important agricultural problems in Iran is soil salinty where West Azerbaijan province is no exception from this problem. The aim of present study was investigating the possibility of surface soil salinity mapping in an area of 68000 ha in the south of West Azarbaijan province using remote sensing. A systematic random sampling method was used to prepare a ground truth map of surface soil salinity (including 147 soil samples from a depth of 0-15 cm). In this research, IRS-P6 satellite data (multispectral and panchromatic bands) were used. Geometric correction of images was done using digital elevation model and road and river maps. Various indices were generated, using ratioing and principal component analysis methods, and were used in the classifications. After selection of suitable training samples, classification was performed with different number of classes by a supervised method and different algorithms. The results of the accuracy assessment showed that the highest overall accuracy percentage and Kappa coefficient (87.96% and 0.77) were related to the classification of the two classes with 4-band combination and the maximum likelihood algorithm. Also, the results revealed high potential of remote sensing and IRS-P6 data for surface soil salinity mapping on a local scale.

کلیدواژه‌ها [English]

  • Accuracy assessment
  • classification
  • IRS-P6 data
  • Mapping
  • Soil Salinity
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