Spatial prediction and modeling of soil salinity using simple cokriging, artificial neural networks, and support vector machines in El Outaya plain, Biskra, southeastern Algeria-Reference-Cited by-同舟云学术

Spatial prediction and modeling of soil salinity using simple cokriging, artificial neural networks, and support vector machines in El Outaya plain, Biskra, southeastern Algeria

Published:2021-01-07 Issue:3 Volume:40 Page:390-408
ISSN:2096-0956
Container-title:Acta Geochimica
language:en
Short-container-title:Acta Geochim

Author:

Boudibi Samir^ORCID,Sakaa Bachir,Benguega Zineeddine,Fadlaoui Haroun,Othman Tarek,Bouzidi Narimen

Publisher

Springer Science and Business Media LLC

Subject

Geochemistry and Petrology

Link

https://link.springer.com/content/pdf/10.1007/s11631-020-00444-0.pdf

Reference44 articles.

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2. Abuelgasim A, Ammad R (2018) Mapping soil salinity in arid and semi-arid regions using landsat 8 OLI satellite data. Remote Sens Appl Soc Environ 13:415–425. https://doi.org/10.1016/j.rsase.2018.12.010

3. Achieng KO (2019) Computers and geosciences modelling of soil moisture retention curve using machine learning techniques: artificial and deep neural networks vs support vector regression models. Comput Geosci 133:104320. https://doi.org/10.1016/j.cageo.2019.104320

4. Avdan U, Jovanovska G (2016) Algorithm for automated mapping of land surface temperature using LANDSAT 8 Satellite Data. J Sensors 8

5. Benchetrit M (1956) Les sols d’Algérie. Rev géographie Alp 44:749–761. https://doi.org/10.3406/rga.1956.1790

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