نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، اهواز، ایران

2 گروه خاکشناسی دانشکده کشاورزی دانشگاه شهید چمران اهواز

3 دانشگاه شهید چمران اهواز

4 هیئت علمی پژوهشی، پژوهشکده حفاظت خاک و آبخیزداری، تهران، ایران

5 گروه خاکشناسی، دانشکده کشاورزی، دانشگاه تربیت مدرس (TMU)

چکیده

با توجه به گستردگی مناطق مستعد تولید گرد و غبار در استان خوزستان، می‌توان از روش‌های نوینی مانند تصاویر ابر طیفی و بازتاب خاک، برای تعیین ویژگی‌های خاک این مناطق  استفاده کرد. از جمله چالش‌های استفاده از تصاویر ابر طیفی در ارزیابی ویژگی‌های خاک، رنگ روشن خاک در اثر وجود ترکیباتی مانند گچ است که ممکن است در برآورد سایر ویژگی‌های خاک، منجر به خطا شود. این پژوهش با هدف تعیین طول موج کلیدی گچ خاک در اراضی مستعد تولید گرد و غبار استان خوزستان انجام گرفته است. برای این منظور، ابتدا طیف اصلی خاک با استفاده از دستگاه FieldSpec3 تعیین شد. طیف اصلی با 5 روش فیلتر ساویتزی گولای (SG)، مشتق اول صاف شده با فیلتر ساویتزی گولای(FD-SG) ، مشتق دوم صاف شده با فیلتر ساویتزی گولای(SD-SG) ، واریانس استاندارد نرمال (SNV) و حذف پیوستار (CR)، پیش‌پردازش شد. سپس، عملکرد برآورد گچ خاک در دو مدل رگرسیونی چند متغیره رگرسیون حداقل مربعات جزئی (PLSR) و ماشین بردار پشتیبان (SVR) مورد مقایسه قرار گرفت. نتایج نشان داد مدل SVR دقت کلی برآورد بالاتری نسبت به مدل PLSR در برآورد گچ خاک داشته است و همچنین در مدل SVR، روش حذف پیوستار در گروه واسنجی بهترین عملکرد (71/3= RPDCAL و 47/2 = RMSECAL ،93/0 =CAL R2) و طیف اصلی ضعیف‌ترین عملکرد (59/1= RPDCAL و 32/6 = RMSECAL ،76/0 =CAL R2) را در برآورد گچ خاک نشان داده‌اند. قابل‌ذکر است که در گروه اعتبارسنجی نیز، روش حذف پیوستار (49/2= RPDVAL و 58/3 = RMSEVAL ،88/0 =VAL R2) و طیف اصلی (12/1= RPDVAL و 81/7 = RMSEVAL ،52/0 =VAL R2) به ترتیب بهترین و ضعیف‌ترین عملکرد را نشان دادند. در این پژوهش، محدوده طول موج‌های 1450، 1550، 1700، 2100، ،2200 و 2400 نانومتر که بیش‌ترین همبستگی را با گچ خاک داشتند، به عنوان طول موج کلیدی گچ خاک در مناطق مستعد تولید گرد و غبار اهواز به دست آمد.

کلیدواژه‌ها

عنوان مقاله [English]

Application of hyperspectral images in Quantification of soil gypsum in center areas of Khuzestan province prone to dust generation

نویسندگان [English]

  • Mansour Chatrenor 1
  • ahmad landi 2
  • ahmad farrokhian firouzi 3
  • Aliakbar Noroozi 4
  • Hossein Ali Bahrami 5

1 Department of Soil Science and Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Department of soil science, Faculty of agriculture, Shahid Chamran university, Iran

3 shahid chamran university of Ahvaz

4 Soil Conservation and Watershed Management Research Institute, Tehran, Iran

5 soil science department of TMU

چکیده [English]

Considering that Khuzestan province has a large area of land susceptible to dust generation, novel approaches such as Hyperspectral images could be used in the determination of soil characteristics. One of the main challenges in using hyperspectral images for evaluation of soil properties in these areas is the presence of some compounds such as gypsum which may lead to some errors in estimating other soil properties. This research has mainly been conducted to determine the soil-gypsum key wavelength in the dust center of Khuzestan province. To achieve this goal, at first the original soil spectrum was preprocessed using FieldSpec3 setup via five methods including the Savitzky-Golay filter, the first derivative with the Savitzky-Golay filter (FD-SG), the second derivative with the Savitzky-Golay filter (SD-SG), the Standard Normal Variant (SNV) and the Continuum Removal method (CR). Two Multivariate regression models including Partial Least Squares Regression (PLSR) and Support Vector Machine (SVR) were used and compared in the estimation performance of soil gypsum. The results showed that the SVR model had better performance rather than the PLSR model in estimating soil gypsum. Also, in the SVR model, the continuum removal method (R2cal=0.93, RMSEcal=2.47, RPDcal=3.71) and the main spectra (R2cal=0.76, RMSEcal=6.32, RPDcal=1.59) had the best and weakest performance in estimating soil gypsum, respectively. It is noteworthy that the continuum removal method (R2val=0.88, RMSEval=3.57, RPDval=2.49) and the original spectrum (R2val=0.52, RMSEval=7.81, RPDval=1.12) in the validation group showed the best and the weakest performance, respectively. In the present study, wavelength ranges around 1450, 1550, 1700, 2100, 2200, 2400 nm which had the highest level of correlation with soil-gypsum content, was obtained as the key wavelengths of the soil in sensitive areas to dust production.

کلیدواژه‌ها [English]

  • key wavelength
  • Savitzky-Golay filter
  • second derivative method
  • Continuum removal method
  • SVR model
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