Integrating microwave and optical data for monitoring soil moisture

R. S. Morgan, M. Abd El-Hady, I. S. Rahim, Joel Silva, A. Berg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In arid regions, such as Egypt, irrigation is the main source of water consumption and freshwater resources are getting scarcer. Therefore, the development of an appropriate irrigation water practices becomes a necessity. Soil moisture, in particular, plays a key role in any efficient water use strategy for agriculture. This study aims at suggesting a protocol for processing microwave data (Sentinel-1) supported by optical data (Landsat 8) with and without ancillary data and utilizing Artificial Neural Network (ANN) to provide repeatable, reliable and accurate estimation of soil moisture content and at a practical interval. The results of this study suggested two approaches for soil moisture predictions using Sentienl-1 data. The first approach depended totally on remote sensing data with a correlation of 0.76. The second approach is more suitable when accurate detailed field survey of soil field capacity is available and reached a correlation of about 0.98.

Original languageEnglish
Title of host publicationProceedings of Living Planet Symposium 2016
EditorsL. Ouwehand
PublisherEuropean Space Agency
ISBN (Electronic)9789292213053
Publication statusPublished - 1 Aug 2016
EventLiving Planet Symposium 2016 - Prague, Czech Republic
Duration: 9 May 201613 May 2016

Publication series

NameEuropean Space Agency, (Special Publication) ESA SP
VolumeSP-740
ISSN (Print)0379-6566

Conference

ConferenceLiving Planet Symposium 2016
CountryCzech Republic
CityPrague
Period9/05/1613/05/16

Keywords

  • Landsat 8
  • Neural Network
  • Sentinel-1
  • Soil moisture content
  • Water resource management

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