Spatial prediction of saline and sodic soils in rice‒shrimp farming land by using integrated artificial neural network/regression model and kriging. Issue 3 (23rd February 2018)
- Record Type:
- Journal Article
- Title:
- Spatial prediction of saline and sodic soils in rice‒shrimp farming land by using integrated artificial neural network/regression model and kriging. Issue 3 (23rd February 2018)
- Main Title:
- Spatial prediction of saline and sodic soils in rice‒shrimp farming land by using integrated artificial neural network/regression model and kriging
- Authors:
- Dinh, Quang Toan
Liang, Dongli
Thi Anh Thu, Tran
Le, Trong Dieu Hien
Dinh Vuong, Nguyen
Pham, Van Tat - Abstract:
- ABSTRACT: In the context of widespread saline and sodic soil, mapping and monitoring spatial distribution of soil salinity and sodicity are important for utilization and management in agriculture lands. In this study, two-stage assessment was proposed to predict spatial distribution of saline and sodic soils. First, artificial neural network (ANN) and multiple linear regressions (MLR) model were used to predict sodium adsorption ratio (SAR) and exchangeable sodium percentage (ESP) based on soil electrical conductivity (EC) and pH. Then, the Kriging interpolation method combined with overlay mapping technique was used to perform saline spatial predictions in the study area. The model accuracy level is evaluated based on coefficient of determination (R 2 ) and root mean square error (RMSE). In the first stage, the values of R 2 and RMSE of SAR and ESP were 0.94, 0.17 and 0.94, 0.24 for ANN, and 0.35, 0.52 and 0.34, 0.76 for MLR, respectively. Similarly, in the second stage, the RMSE of ANN-Kriging were much closer to 0 and relatively lower than MLR-Kriging and Kriging. The results show that ANN-Kriging can be used to improve the accuracy of mapping and monitoring spatial distribution of saline and sodic soil in areas that develop the rice-shrimp cultivation model.
- Is Part Of:
- Archives of agronomy and soil science. Volume 64:Issue 3(2018)
- Journal:
- Archives of agronomy and soil science
- Issue:
- Volume 64:Issue 3(2018)
- Issue Display:
- Volume 64, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 64
- Issue:
- 3
- Issue Sort Value:
- 2018-0064-0003-0000
- Page Start:
- 371
- Page End:
- 383
- Publication Date:
- 2018-02-23
- Subjects:
- Exchangeable sodium percentage -- sodium absorption ratio -- salt-affected soils -- spatial analysis prediction -- rice–shrimp cultivation
Horticulture -- Periodicals
Soils -- Periodicals
630.5 - Journal URLs:
- http://www.tandf.co.uk/journals/titles/03650340.asp ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/03650340.2017.1352088 ↗
- Languages:
- English
- ISSNs:
- 0365-0340
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1630.923000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 5686.xml