Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile
المؤلفون المشاركون
Ben-Dor, Eyal
Goldshleger, Naftali
Chudnovsky, Alexandra
المصدر
Applied and Environmental Soil Science
العدد
المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2012-08-22
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
We explored the effect of raindrop energy on both water infiltration into soil and the soil's NIR-SWIR spectral reflectance (1200–2400 nm).
Seven soils with different physical and morphological properties from Israel and the US were subjected to an artificial rainstorm.
The spectral properties of the crust formed on the soil surface were analyzed using an artificial neural network (ANN).
Results were compared to a study with the same population in which partial least-squares (PLS) regression was applied.
It was concluded that both models (PLS regression and ANN) are generic as they are based on properties that correlate with the physical crust, such as clay content, water content and organic matter.
Nonetheless, better results for the connection between infiltration rate and spectral properties were achieved with the non-linear ANN technique in terms of statistical values (RMSE of 17.3% for PLS regression and 10% for ANN).
Furthermore, although both models were run at the selected wavelengths and their accuracy was assessed with an independent external group of samples, no pre-processing procedure was applied to the reflectance data when using ANN.
As the relationship between infiltration rate and soil reflectance is not linear, ANN methods have the advantage for examining this relationship when many soils are being analyzed.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Goldshleger, Naftali& Chudnovsky, Alexandra& Ben-Dor, Eyal. 2012. Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile. Applied and Environmental Soil Science،Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-472466
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Goldshleger, Naftali…[et al.]. Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile. Applied and Environmental Soil Science No. 2012 (2012), pp.1-9.
https://search.emarefa.net/detail/BIM-472466
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Goldshleger, Naftali& Chudnovsky, Alexandra& Ben-Dor, Eyal. Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile. Applied and Environmental Soil Science. 2012. Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-472466
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-472466
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر