Research Article
Estimation of Soil Electrical Conductivity using Dual – Polarized SAR Sentinel -1 Imagery
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 176 - Issue 19 |
| Published: May 2020 |
| Authors: Tanvi Agarwal, Rajni Ranjan Singh Makwana, Laxmi Shrivastava |
10.5120/ijca2020920148
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Tanvi Agarwal, Rajni Ranjan Singh Makwana, Laxmi Shrivastava . Estimation of Soil Electrical Conductivity using Dual – Polarized SAR Sentinel -1 Imagery. International Journal of Computer Applications. 176, 19 (May 2020), 41-43. DOI=10.5120/ijca2020920148
@article{ 10.5120/ijca2020920148,
author = { Tanvi Agarwal,Rajni Ranjan Singh Makwana,Laxmi Shrivastava },
title = { Estimation of Soil Electrical Conductivity using Dual – Polarized SAR Sentinel -1 Imagery },
journal = { International Journal of Computer Applications },
year = { 2020 },
volume = { 176 },
number = { 19 },
pages = { 41-43 },
doi = { 10.5120/ijca2020920148 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2020
%A Tanvi Agarwal
%A Rajni Ranjan Singh Makwana
%A Laxmi Shrivastava
%T Estimation of Soil Electrical Conductivity using Dual – Polarized SAR Sentinel -1 Imagery%T
%J International Journal of Computer Applications
%V 176
%N 19
%P 41-43
%R 10.5120/ijca2020920148
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Soil to mankind is a basic natural resource. Soil is a blend of solid, liquid and gaseous substances, shapes the top most layer of the Earth’s crust. The saline soil are the ‘salt affected soils’ generally found in arid and semi – arid regions. These soils are generally found in ‘low precipitation area’ where precipitation and evaporation ratio is less than 10.75[5]. This paper manages soil electrical conductivity estimation utilizing Sentinel -1 SAR imagery.. The support vector regression (SVR) technique, with RBF kernel function, was utilized to relate illustrative factors to ground estimated saltiness. We additionally applied K-Fold method for upgrading the model..
References
- Mohammad Mahdi Taghadosi, Mahdi Hasanlou, Kamran Eftekhari, 2019, “Soil salinity mapping using dual – polarized SAR sentinel -1 imagery”, International Journal of Remote Sensing.
- Ashutosh Pandey, Shashi Ranjan Kumar, A.K. Shrivastava, 2018, “Review and analysis of Microwave Remote Sensing behavior of soil in India”, International Journal of Research in Advent Technology, vol. 6, No. 1.
- Agnieszka Szyplowska, Justyna Szerement, Arkadiusz Lewandowski, 2018, “Impact of soil salinity on the relation between soil moisture and dielectric permittivity”, IEEE.
- Hong Jiang, Yusufujiang Rusuli, Tureniguli Amuti & Qing He, 2018, “Quantitative assessment of soil salinity using multi – source remote sensing data based on the support vector machine and artificial neural network”, International Journal Of Remote Sensing.
- Singh, G., D.S. Bundela, M. Sethi, K. Lal and S.K. Kamra, 2010,“Remote Sensing and geographic information system for appraisal of salt – affected soils in India”, Journal Of Environmental Quality.
- Saha, S.K., 2011, “Microwave Remote Sensing in Soil Quality Assessment”, ISPRS – International Archives of the Photogrammetry, remote sensing and spatial information Sciences.
- [Wu, Y., and W.Wang, 2011, “Modelling the backscattering coefficient of salt affected soils using AIEM model”, In Earth Resources and environmental remote sensing/GIS application II, International society of optics and photonics.
- Li,Y.Y., K.Zhao, J.H. Ren, Y.L. Ding, and L.L. Wu.,2014, “Analysis of dielectric constant of saline – alkali soils and the effect on Radar backscattering coefficient: A case study of soda alkaline saline soils in western Jilin province using RADARSAT-2 data”, The Scientific World Journal.
- Vijayarekha, K., 2014, “Feature Extraction”, School of Electrical and Electronics Engineering.
- Xiangzheng Meng, Qi Zhou, Jiexiang Hu, Leshi Shu,Ping Jiang, 2017, “A Global Support Vector Regression based on sorted K – Fold Method”, IEEE International Conference on Industrial Engineering and Engineering Management.
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