Investigating the effect of Wetness index and spectral data on the estimation of soil particles percentage using neuro-fuzzy, artificial neural network and regression tree models
Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Direct estimation of some soil characteristics is time consuming, costly and sometimes not possible. In recent years, indirect methods have been used to estimate these properties. In the present study, to predict the soil texture fractions, 115 profiles were identified based on the Hypercube technique, and the horizons were sampled and the percentage of sand, clay and silt of soil samples were measured. Environmental variables used in this study include the terrain attributes (derived from a digital elevation model), Landsat 8 image data (acquired in 2015), geomorphological map, and spectrometric data (laboratory data). Artificial neural network, regression tree and neuro-fuzzy models were used to make a correlation between soil data (clay, sand and silt) and environmental variables. The results of this study showed that the neuro-fuzzy model was more accurate in prediction of the three parameters of clay, sand and silt than artificial neural network and tree regression. The RMSE value in the neuro fuzzy model was compared to regression tree model. The neuro fuzzy model results were, for clay surface 1.43 %, for sand surface 1.98% and for silt surface 2.1% that reduced by 6.71%, 8.49% and 5.42% for clay, sand and silt respectively, compared to regression tree model. The results also showed that the most important auxiliary variables are spectrometric data followed by MrVBF and wetness index.

Language:
Persian
Published:
Irrigation & Water Engineering, Volume:10 Issue: 38, 2019
Pages:
104 to 123
magiran.com/p2081563  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 990,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
دسترسی سراسری کاربران دانشگاه پیام نور!
اعضای هیئت علمی و دانشجویان دانشگاه پیام نور در سراسر کشور، در صورت ثبت نام با ایمیل دانشگاهی، تا پایان فروردین ماه 1403 به مقالات سایت دسترسی خواهند داشت!
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 50 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!