تهیه نقشه رقومی شکل‏های مختلف آهن خاک با استفاده از داده‏های سنجنده OLI ماهواره لندست در ساحل شرقی دریاچه ارومیه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران/ دانشگاه تبریز، تبریز، ایران

2 عضو هیئت علمی گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

3 استاد دانشکده علوم محیطی و کشاورزی، دانشگاه سیدنی، سیدنی، استرالیا

چکیده

در این مطالعه با استفاده از دو روش داده­کاوی شامل مدل درخت تصمیم­گیری (DT) و مدل کیوبیست (Cu) نقشه رقومی مهم­ترین شکل­های آهن 131 نمونه خاک سطحی (عمق صفر تا 10 سانتی­متری) شامل آهن معادل کل (Fet)، آهن پدوژنیک (Fed) و آهن بی‌شکل (Feo) در منطقه­ای به مساحت 500 کیلومتر­مربع از دو سایت جداگانه در بستر خشک­ شده ساحل شرقی دریاچه ارومیه تهیه شد. در این پژوهش در مجموع تعداد 19 متغیر کمکی برگرفته از تصویر سنجنده OLI ماهواره لندست 8 مربوط به تیرماه سال 1396 مورد استفاده قرار گرفت. نتایج نشان داد که مدل کیوبیست با داشتن مقادیر (89/0 R2 =و 25/2RMSE=) برای پیش­بینی Fet، (85/0 R2 =و 57/0RMSE=) برای پیش­بینی Fed و (88/0 R2 =و 09/0RMSE=) برای پیش­بینی Feo دارای دقت بالاتری نسبت به مدل درخت تصمیم­گیری به­منظور پیش­بینی هر سه شکل آهن داشت. هم‌چنین نتایج میزان اهمیت و درصد مشارکت متغیرهای کمکی در هر دو مدل نشان‌دهنده اهمیت بالای برخی شاخص­های طیفی از جمله شاخص نسبت رطوبتی نرمال شده (NDMI) و شاخص اصلاح شده گیاهی تعدیل‌کننده اثر خاک (MSAVI) در پیش­بینی Fet، Fed و Feo می­باشد. به­طور کلی نتایج نشان داد که مدل کیوبیست در مقایسه با مدل درخت تصمیم­گیری دارای توانایی و کارایی بالاتری در مدل­سازی و تخمین پراکنش مکانی شکل­های مختلف آهن خاک در منطقه مورد مطالعه بوده است.

کلیدواژه‌ها

عنوان مقاله [English]

Digital Mapping of Different forms of Soil Iron in the Eastern Shore of Urmia Lake by using Landsat-8 OLI Imagery

نویسندگان [English]

  • Amin Mousavi 1
  • Farzin Shahbazi 2
  • Shahin Oustan 2
  • Ali Asghar Jafarzadeh 2
  • Budiman Minasny 3
1 Ph.D. Student, Department of Soil Science and Engineering, Faculty of Agriculture, University of Tabriz, Iran
2 Department of Soil Science and Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
3 Faculty of Science, Professor in Soil-Landscape Modelling, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia
چکیده [English]

In this study, digital mapping of the most important forms of soil Iron were done using two data mining techniques namely Decision Tree (DT) and Cubist (Cu) models. The study area includes 500 km2 of lands from two different sites located in the eastern shore of dried bed of Urmia Lake, northwest of Iran. 131 surface soil samples were taken from depth of 0-10 cm and three different forms of Iron including i): total iron (Fet); ii) pedogenic iron (Fed); and iii) amorphous iron (Feo) were measured. A total of 19 environmental covariates (auxiliary variables) derived from the Landsat-8 OLI imagery related to July 2017 were used in this study. It was found that Cu model has a higher precision than that of the DT model for predicting all three forms of  soil iron with the values R2=0.89 and RMSE= 2.25 g/kg , R2=0.85 and RMSE=0.57 g/kg and R2=0.88 and RMSE=0.09 g/kg for predicting Fet, Fed and Feo, respectively. In addition, the results of the importance and percentage of contribution of environmental covariates in both models indicated the high importance of some spectral indices such as Normalized Difference Moisture Index (NDMI) and Modified Soil Adjusted Vegetation Index (MSAVI) in the prediction of Fet, Fed and Feo. Generally, the Cu model has a higher ability and performance in modeling and predicting the spatial distribution of different forms of soil iron in the study area compared to the DT model.

کلیدواژه‌ها [English]

  • Cubist
  • Data mining
  • Decision tree
  • Different forms of iron
  • Environmental covariates

مراجع

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تحقیقات کاربردی خاک
دوره 9، شماره 2
شهریور 1400
صفحه 47-60

فایل ها

سابقه مقاله

  • تاریخ دریافت: 24 بهمن 1398
  • تاریخ بازنگری: 14 مرداد 1399
  • تاریخ پذیرش: 08 شهریور 1399

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