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Sustainability of the Environment: Monitoring and Analysis of Water Resources Using State-of-the-Art Technologies

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 2672

Special Issue Editors


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Guest Editor
Department of Geomatics Engineering, Gebze Technical University, Gebze, Kocaeli 41400, Turkiye
Interests: machine learning; climate change; deep learning; remote sensing; water-quality assessment; susceptibility assessment of natural disasters; monitoring environmental changes; ocean color observations
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Marine Environment, Institute of Marine Sciences and Management, Istanbul University, Istanbul 34134, Turkiye
Interests: oceanography; remote sensing; emission

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Guest Editor
Department of Geomatics Engineering, Gebze Technical University, Gebze, Kocaeli 41400, Turkiye
Interests: optical and laser unmanned air vehicle; airborne laser scanning; SAR interferometry and radargrammetry; space-borne optical imaging; digital photogrammetry; virtual reality integration

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Guest Editor
Department of Geomatics Engineering, Gebze Technical University, Gebze, Kocaeli 41400, Turkiye
Interests: remote sensing and applications; image classification; machine learning

Special Issue Information

Dear Colleagues,

Water is essential not only to human life but also to the ecosystems that the whole world is built upon. As the world suffers from the disruptive effects of global climate change, stress on the hydrological cycle and water resources has intensified in the last decades. On the other hand, the overexploitation of water resources coupled with global population growth results in water scarcity, increasing the demand for clean water. This Special Issue is devoted to the latest studies using advanced technologies for monitoring and assessment of environmental pollution, mainly caused by industrial and agricultural activities, that occurred on water bodies including oceans, seas and coastal and inland waters. Water bodies are exposed to a wide range of pollutants, including pathogenic microorganisms, organic waste, fertilizers, pesticides, toxic chemicals and petroleum (oil). Due to the increase in the amount of pollution in both oceans and inland waters, we have been witnessing more environmental disasters, particularly in coastal zones, rivers and lakes. Harmful algal bloom, marine mucilage and oil seepage severely threaten healthy water ecosystems and monitoring of these events is particularly important for sustainable water management and protecting the water ecosystem. Remote sensing technologies offer great advantages for monitoring and analysis of water quality. Data acquired by these systems integrated with in situ measurements can be used to track disastrous events on a temporal basis. In addition, recent state-of-the-art nano-technologies have been applied for water and wastewater treatment, remediation and conservation. Studies covering the above-mentioned issues are all welcome.

Prof. Dr. Taskin Kavzoglu
Prof. Dr. Cem Gazioglu
Prof. Dr. Umut Gunes Sefercik
Dr. Ismail Colkesen
Guest Editors

Manuscript Submission Information

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Keywords

  • environmental pollution
  • climate change
  • water pollution
  • remote sensing
  • ocean color products
  • marine ecosystems
  • fresh water
  • eutrophic water bodies

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Published Papers (1 paper)

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Research

23 pages, 6492 KiB  
Article
Extraction of Water Bodies from High-Resolution Aerial and Satellite Images Using Visual Foundation Models
by Samed Ozdemir, Zeynep Akbulut, Fevzi Karsli and Taskin Kavzoglu
Sustainability 2024, 16(7), 2995; https://doi.org/10.3390/su16072995 - 3 Apr 2024
Cited by 2 | Viewed by 2136
Abstract
Water, indispensable for life and central to ecosystems, human activities, and climate dynamics, requires rapid and accurate monitoring. This is vital for sustaining ecosystems, enhancing human welfare, and effectively managing land, water, and biodiversity on both the local and global level. In the [...] Read more.
Water, indispensable for life and central to ecosystems, human activities, and climate dynamics, requires rapid and accurate monitoring. This is vital for sustaining ecosystems, enhancing human welfare, and effectively managing land, water, and biodiversity on both the local and global level. In the rapidly evolving domain of remote sensing and deep learning, this study focuses on water body extraction and classification through the use of recent deep learning models of visual foundation models (VFMs). Specifically, the Segment Anything Model (SAM) and Contrastive Language-Image Pre-training (CLIP) models have shown promise in semantic segmentation, dataset creation, change detection, and instance segmentation tasks. A novel two-step approach involving segmenting images via the Automatic Mask Generator method of the SAM and the zero-shot classification of segments using CLIP is proposed, and its effectiveness is tested on water body extraction problems. The proposed methodology was applied to both remote sensing imagery acquired from LANDSAT 8 OLI and very high-resolution aerial imagery. Results revealed that the proposed methodology accurately delineated water bodies across complex environmental conditions, achieving a mean intersection over union (IoU) of 94.41% and an F1 score of 96.97% for satellite imagery. Similarly, for the aerial imagery dataset, the proposed methodology achieved a mean IoU of 90.83% and an F1 score exceeding 94.56%. The high accuracy achieved in selecting segments predominantly classified as water highlights the effectiveness of the proposed model in intricate environmental image analysis. Full article
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