Estimation of soil moisture profile using Wavelet Neural Networks

Ajla Kulaglic*, Burak Berk Ustundag

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The main purpose of the presented study is to examine the usability of a Wavelet Neural Network (WNN) model for soil moisture estimation. In this study, the wavelet transformations and neural networks have been employed to estimate the daily soil moisture. Collected data have been decomposed into wavelet sub-time series using Discrete Wavelet Transformation (DWT) with Haar mother wavelets. The sub-time series have been selected as the inputs of neural network for estimation performance. Decomposition is done on different type of data. At the same time, those decomposed sub-time series data are used like inputs to the Time-Delay Neural Network (TDNN). The selection of sub-time series has effect on the output data also. Soil moisture values at different depths are estimated using inverse discrete wavelet transformation (IDWT). DWT and IDWT are applied with the quadrature mirror filters of decomposition and synthesis filters. Also, it is shown that selection of sub-time series has impact on the neural network model's performance. Consequently, the most appropriate wavelet-NN configuration is determined for each station which means of selecting the appropriate mother wavelet, number of scales and the neural network type. The main point, in WNN type configuration is the wavelet decomposition and usage of sub-time series as inputs of neural network. The results have been provided with the error metrics of the Root Mean Square Error (RMSE) and Coefficient of Efficiency (CE) by comparing the real and estimated values.

Original languageEnglish
Title of host publication2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479941575
DOIs
Publication statusPublished - 25 Sept 2014
Event2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 - Beijing, China
Duration: 11 Aug 201414 Aug 2014

Publication series

Name2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014

Conference

Conference2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014
Country/TerritoryChina
CityBeijing
Period11/08/1414/08/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • data fusion
  • fractional vegetation cover
  • LANDSAT8
  • NDVI
  • soil mositure estimation
  • synthetic NDVI
  • TARBIL
  • time-delay neural network

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