Assessment and mapping of soil salinity using electromagnetic induction and Landsat 8 OLI remote sensing data in an irrigated olive orchard under semi-arid conditions

Author:

Gharsallah Mohamed Elhedi,Aichi Hamouda,Stambouli Talel,Ben Rabah Zouhair,Ben Hassine Habib

Abstract

Salinisation threatens the sustainability of irrigated olive orchards in Tunisia. Electromagnetic induction measurements and soil spectral index calculations could help to survey the soil salinity. This study aimed to map changes in the soil salinity spatial pattern using geostatistical techniques and soil spectral index regression. The study area is located in Sminja, Tunisia. It is a 665 ha olive orchard, landscaped in ridges and furrows and managed following a very high-density planting system (1.5 × 4 m<sup>2</sup>). Electromagnetic readings measured in situ with an electromagnetic device (EM38) that was fitted, in turn, to the electrical conductivity of the saturated paste of five soil depths namely: 0–20, 20–40, 40–60, 60–80 and 80–100 cm and to the average electrical conductivity of the saturated paste of the 0–100 cm soil depth. Both the ordinary kriging and universal kriging performed similarly and well in mapping the soil salinity. (R<sup>2</sup>= 0.86 and 0.89 for the 0–20 cm and the 0–100 cm depths, respectively). Our results prove that mapping the soil salinity based on electromagnetic induction and kriging methods is an effective approach, which allows one to monitor the soil salinity within permanent croplands in semi-arid conditions. Salinisation that reaches intolerable values by olive trees, is especially accumulated on the top of the ridges, where the drippers are installed. Furthermore, based on two Landsat 8 images acquired on April 30, 2019 and May 16, 2019, respectively, we calculated seven soil spectral indices. Nevertheless, multiple regression models between the electromagnetic readings and various combinations of soil spectral indices were poor. In the coming investigations, under permanent land cover, spectral index regression models should integrate not only the soil, but also vegetation indices.

Publisher

Czech Academy of Agricultural Sciences

Subject

Soil Science,Aquatic Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3