Land use/land cover changes impact on groundwater level and quality in the northern part of the United Arab Emirates

Samy Elmahdy, Mohamed Mohamed, Tarig Ali

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

This study aims to develop an integrated approach for mapping and monitoring land use/land cover (LULC) changes and to investigate the impacts of LULC changes and population growth on groundwater level and quality using Landsat images and hydrological information in a Geographic information system (GIS) environment. All Landsat images (1990, 2000, 2010, and 2018) were classified using a support vector machine (SVM) and spectral analysis mapper (SAM) classifiers. The result of validation metrics, including precision, recall, and F1, indicated that the SVM classier has a better performance than SAM. The obtained LULC maps have an overall accuracy of more than 90%. Each pair of enhanced LULC maps (1990-2000, 2000-2010, 2010-2018, and 1990-2018) were used as input data for an image difference algorithm to monitor LULC changes. Maps of change detection were then imported into a GIS environment and spatially correlated against the spatiotemporal maps of groundwater level and groundwater quality. The results also show that the approximate built-up area increased from 227.26 km2 (1.39%) to 869.77 km2 (7.41%), while vegetated areas (farmlands, parks and gardens) increased from about 76.70 km2 (0.65%) to 290.70 km2 (2.47%). The observed changes in LULC are highly linked to the depletion in groundwater level and quality across the study area from the Oman Mountains to the coastal areas.

Original languageEnglish
Article number1715
JournalRemote Sensing
Volume12
Issue number11
DOIs
Publication statusPublished - Jun 1 2020

Keywords

  • Change detection
  • Groundwater level
  • Groundwater quality
  • Land use/land cover
  • Landsat
  • Support vector machine
  • United Arab Emirates

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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