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Remote Sensing
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Recent Geospatial Methods and Techniques for Urban Water Management
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Recent Geospatial Methods and Techniques for Urban Water Management

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 6809

Special Issue Editors

Dr. Bakhtiar Feizizadeh

E-Mail Website
Guest Editor
Geoinformation Science Lab, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Interests: gis multicriteria decision analysis; sensitivity and uncertainty analysis; spatial data infrastructure; geospatial modelling; object-based image analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Ayyoob Sharifi

E-Mail Website
Guest Editor
The IDEC Institute & Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University, 1-5-1, Higashi-Hiroshima 739-8529, Japan
Interests: urban resilience; smart cities; climate change adapatation and mitigation; neighborhood planning; eco-urbanism
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vahid Nourani

E-Mail Website
Guest Editor
Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, 29 Bahman Ave., Tabriz 5166616471, Iran
Interests: artificial intelligence in hydrology; numerical methods in water sciences; geostatistics; stochastic hydrology; GIS and remote sensing applications in water science; climate change modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Freshwater resources are of critical importance for sustaining human life. From an environmental perspective, cities are widely recognized as major consumers of water resources. It is well understood that large amounts of surface and groundwater resources are needed to meet the increasing water demands of cities. In some parts of the world, this increasing water demand has altered natural hydrological regimes and has led to adverse environmental impacts on freshwater ecosystems and resources. Considering the significance of water resource management in the urban environment, this Special Issue aims to invite experts and researchers to share their research regarding urban water management using geospatial methods. Articles focused on urban water resource management, water scarcity, the spatiotemporal modeling of urban water consumption, climate change impacts on urban water recourse, scenario-based urban water modeling, applications of GIS and remote sensing in topics related to urban water, and similar topics highly sought after for submission.

Dr. Bakhtiar Feizizadeh
Dr. Ayyoob Sharifi
Prof. Dr. Vahid Nourani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban water resources
  • urban water management methods and techniques
  • geospatial techniques
  • spatiotemporal modelling
  • scenario-based urban water modelling
  • water scarcity modeling in urban environments
  • natural hazard and disaster impacts on sustainable urban water supply
  • risk mitigation in the domain of urban water
  • climate change impacts on urban water supply
  • climate-resilient urban water management

Published Papers (3 papers)

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Research

18 pages, 4265 KiB  
Article
Extracting Urban Water Bodies from Landsat Imagery Based on mNDWI and HSV Transformation
by Liwei Chang, Lei Cheng, Chang Huang, Shujing Qin, Chenhao Fu and Shiqiong Li
Remote Sens. 2022, 14(22), 5785; https://doi.org/10.3390/rs14225785 - 16 Nov 2022
Cited by 6 | Viewed by 1790
Abstract
Urban water bodies are critical for sustainable urban ecological and social development. However, the complex compositions of urban land cover and small water bodies pose considerable challenges to urban water surface delineation. Here, we propose a novel urban water extraction algorithm (UWEA) that [...] Read more.
Urban water bodies are critical for sustainable urban ecological and social development. However, the complex compositions of urban land cover and small water bodies pose considerable challenges to urban water surface delineation. Here, we propose a novel urban water extraction algorithm (UWEA) that is efficient in distinguishing water and other low-reflective objects by combining the modified normalized difference water index (mNDWI) and HSV transformation. The spectral properties of urban land covers were analyzed and the separability of objects in different color spaces was compared before applying the HSV transformation. The accuracy and robustness of the UWEA were validated in six highly urbanized subregions of Beijing, Tokyo, and New York, and compared with the mNDWI and HIS methods. The results show that the UWEA had the fewest total errors (sum of omission and commission errors) for all the validation sites, which was approximately 3% fewer errors than those of the mNDWI and 17% fewer errors than those of the HIS method. The UWEA performed best because it was good at identifying small water bodies and suppressing reflective surfaces. The UWEA is effective in urban water monitoring and its thresholds are also robust in various situations. The resulting highly accurate water map could support water-related analyses. This method is also useful for scientists, managers, and planners in water resource management, urban hydrological applications, and sustainable urban development. Full article
(This article belongs to the Special Issue Recent Geospatial Methods and Techniques for Urban Water Management)
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19 pages, 12517 KiB  
Article
Unsustainable Anthropogenic Activities: A Paired Watershed Approach of Lake Urmia (Iran) and Lake Van (Turkey)
by Sajad Khoshnood, Aynaz Lotfata and Ayyoob Sharifi
Remote Sens. 2022, 14(20), 5269; https://doi.org/10.3390/rs14205269 - 21 Oct 2022
Cited by 3 | Viewed by 1971
Abstract
Water availability in lakes must be studied in order to better manage ecosystems within lake basins and meet economic development needs. Despite being Iran’s largest lake, Lake Urmia’s water level and surface area have declined dramatically over the past two decades. During the [...] Read more.
Water availability in lakes must be studied in order to better manage ecosystems within lake basins and meet economic development needs. Despite being Iran’s largest lake, Lake Urmia’s water level and surface area have declined dramatically over the past two decades. During the same period, Lake Van in Turkey maintained a relatively stable water level and surface area. As a result, comparing factors related to water level and surface area in these lakes, which have similar geographical and climate conditions but different management policies, can be an appropriate way to identify the causes of water declines in Lake Urmia. Comparing these variables may help explain observed differences in lake behavior between 2000 and 2016. Hydrometric and climatic parameters, as well as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), were used to achieve this goal. Changes in precipitation, temperature, and evapotranspiration in both lakes show essentially identical trends, but this is not a convincing explanation for Lake Urmia’s water surface changes. The results revealed that dam construction and water diversion projects, the expansion of irrigated agriculture, and the lake’s shallow depth in most parts were the primary causes of Lake Urmia’s shrinkage compared to Lake Van. Full article
(This article belongs to the Special Issue Recent Geospatial Methods and Techniques for Urban Water Management)
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24 pages, 8394 KiB  
Article
A GIS-Based Spatiotemporal Impact Assessment of Droughts in the Hyper-Saline Urmia Lake Basin on the Hydro-Geochemical Quality of Nearby Aquifers
by Bakhtiar Feizizadeh, Zahra Abdollahi and Behzad Shokati
Remote Sens. 2022, 14(11), 2516; https://doi.org/10.3390/rs14112516 - 24 May 2022
Cited by 4 | Viewed by 2020
Abstract
Urmia Lake is a hyper-saline lake in northwestern Iran that has been drying up since 2005. The main objective of this study was to evaluate the water quality in aquifers that are the main source of fresh water for the eastern plains Urmia [...] Read more.
Urmia Lake is a hyper-saline lake in northwestern Iran that has been drying up since 2005. The main objective of this study was to evaluate the water quality in aquifers that are the main source of fresh water for the eastern plains Urmia Lake, which has been drying up due to intensive land use/cover changes and climate change. We evaluated hydro-geochemical data and factors contributing to aquifer pollution and quality variation for nine aquifers in the vicinity of Urmia Lake during the dry and wet seasons from 2000–2020. Our methodology was based on the analysis of 10 years of data from 356 deep and semi-deep wells using GIS spatial analysis, multivariate statistical analysis, and agglomerative hierarchical clustering. We developed a Water Quality Index (WQI) for spatiotemporal assessment of the status of the aquifers. In doing so, we highlighted the value of combining Principal Component Analysis (PCA), WQI, and GIS to determine the hydro-geochemical attributes of the aquifers. We found that the groundwater in central parts of the study area was unsuitable for potable supplies. Anthropogenic sources of contamination, such as chemical fertilizers, industrial waste, and untreated sewage water, might be the key factors causing excessive concentrations of contaminants affecting the water quality. The PCA results showed that over 80% of the total variance could be attributed to two principal factors for most aquifers and three principal factors for two of the aquifers. We employed GIS-based spatial analysis to map groundwater quality in the study area. Based on the WQI values, approximately 48% of groundwater samples were identified as poor to unsuitable for drinking purposes. Results of this study provide a better hydro-geochemical understanding of the multiple aquifers that require preventive action against groundwater damage. We conclude that the combined approach of using a multivariate statistical technique and spatial analysis is effective for determining the factors controlling groundwater quality. Full article
(This article belongs to the Special Issue Recent Geospatial Methods and Techniques for Urban Water Management)
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