Different pixel sizes of topographic data for prediction of soil salinity.
Modeling techniques can be powerful predictors of soil salinity across various scales, ranging from local landscapes to global territories. This study was aimed to examine the accuracy of soil salinity prediction model integrating ANNs (artificial neural networks) and topographic factors with differ...
Saved in:
Main Authors: | Shima Esmailpour, Ebrahim Mahmoudabadi, Mohammad Ghasemzadeh Ganjehie, Alireza Karimi |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2024-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0315807 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep learning detects entire multiple-size lunar craters driven by elevation data and topographic knowledge
by: Liyang Xiong, et al.
Published: (2025-01-01) -
Interaction between biochar particle size and soil salinity levels on soil properties and tomato yield
by: Zhuqing Wu, et al.
Published: (2025-02-01) -
Effect of topographical and soil complexity on potato yields in irrigated fields
by: Michael Kehoe, et al.
Published: (2025-02-01) -
Response of Plant Community Characteristics and Soil Factors to Topographic Variations in Alpine Grasslands
by: Qinyang Liang, et al.
Published: (2024-12-01) -
Data model for the cartographic representation of toponyms on topographic maps published by the MGI
by: Marković Viktor
Published: (2024-01-01)