Spatio-temporal soil moisture estimation using neural network with wavelet preprocessing

Ajla Kulaglic, B. Berk Ustundag

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

Soil moisture is an important indicator that defines the land surface-atmosphere interactions by contributing precisely to the surface energy and water balance. In this study, we examine the utility of the Neural Network (NN) model using Discrete Wavelet Transform (DWT) as preprocessing mechanism for soil moisture estimation. The decomposed wavelet sub-time series data was used as input to the 3-layered NN. Recognition of, as well as understanding the changes and spatial distributions of soil moisture are crucial in order to determine water usage, droughts, floods and surface runoffs. This study aims to use remote sensing data together with ground-based agro-meteorological data. The soil moisture data from sites were composed of the 15- A nd 45-cm, measured at intervals of 8 days during the period of crop growth season (October to June) between 2014 and 2015. Simultaneously, soil moisture data were selected as remotely sensed images were acquired. Utilizing remotely sensed data (Landsat 7 and Landsat 8) Vegetation Indices (VI): Landsat Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Modified Soil Adjusted Vegetation Index (MSAVI) were obtained. Temperature Vegetation Dryness Index (TVDI) was computed with respect to LST. The results of this study showed that the proposed model, using ground-based and remotely sensed data, should serve as an enhanced method to obtain highly reliable soil moisture values.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2017 6th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2017
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781538638842
DOI'lar
Yayın durumuYayınlandı - 19 Eyl 2017
Etkinlik6th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2017 - Fairfax, United States
Süre: 7 Ağu 201710 Ağu 2017

Yayın serisi

Adı2017 6th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2017

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???6th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2017
Ülke/BölgeUnited States
ŞehirFairfax
Periyot7/08/1710/08/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Finansman

Authors would like to thank to Istanbul Technical University-Agricultural and Environmental Informatics and Applied Research Center TARBIL for providing the field data and Republic of Turkey Ministry of Food and Agriculture and Livestock for support of the project.

FinansörlerFinansör numarası
Istanbul Technical University-Agricultural and Environmental Informatics and Applied Research Center

    Parmak izi

    Spatio-temporal soil moisture estimation using neural network with wavelet preprocessing' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

    Alıntı Yap