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Environmental Science Studies with Remote Sensing Technologies: Exposure Assessment and Environmental Monitoring

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 4863

Special Issue Editor

Dr. Xiaoshuang Ma

E-Mail Website
Guest Editor
1. School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
2. Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
Interests: remote sensing image processing and interpretation; remote sensing of environment; synthetic aperture radar; target detection on remote sensing images; image denoising; deep learning; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Urbanization, dense population and the utilization of natural resources continually exert pressures on the Earth on which we live, resulting in increasingly prominent environmental problems. Mountains, rivers, forests, fields, lakes and grasses are the “life community” in which human beings share weal and woe. Monitoring and evaluating the environmental issues related to the above elements is crucial for scientific formulation of regional development strategies and is also a basic requirement for the concept of sustainable development. Remote sensing technology can obtain information on the Earth's surface (including near surface) and the atmosphere in a large area in time and has been widely used in environmental monitoring and assessment. The development of environmental remote sensing is changing quickly in terms of application areas and technical methods. Papers addressing these topics are invited for this Special Issue, especially those combining a high academic standard coupled with a practical focus on providing optimal exposure assessment and environmental monitoring solutions based on remote sensing technology.

Dr. Xiaoshuang Ma
Guest Editor

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. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly 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 2500 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

  • exposure assessment
  • environmental monitoring
  • environmental remote sensing
  • remote sensing of water quality
  • atmospheric remote sensing
  • vegetation remote sensing
  • soil and water conservation geological hazard monitoring
  • pollution of soil heavy metals
  • ocean and polar environment

Published Papers (3 papers)

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Research

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17 pages, 7871 KiB  
Article
Analysis of YOLOv5 and DeepLabv3+ Algorithms for Detecting Illegal Cultivation on Public Land: A Case Study of a Riverside in Korea
by Kyedong Lee, Biao Wang and Soungki Lee
Int. J. Environ. Res. Public Health 2023, 20(3), 1770; https://doi.org/10.3390/ijerph20031770 - 18 Jan 2023
Cited by 2 | Viewed by 1563
Abstract
Rivers are generally classified as either national or local rivers. Large-scale national rivers are maintained through systematic maintenance and management, whereas many difficulties can be encountered in the management of small-scale local rivers. Damage to embankments due to illegal farming along rivers has [...] Read more.
Rivers are generally classified as either national or local rivers. Large-scale national rivers are maintained through systematic maintenance and management, whereas many difficulties can be encountered in the management of small-scale local rivers. Damage to embankments due to illegal farming along rivers has resulted in collapses during torrential rainfall. Various fertilizers and pesticides are applied along embankments, resulting in pollution of water and ecological spaces. Controlling such activities along riversides is challenging given the inconvenience of checking sites individually, the difficulty in checking the ease of site access, and the need to check a wide area. Furthermore, considerable time and effort is required for site investigation. Addressing such problems would require rapidly obtaining precise land data to understand the field status. This study aimed to monitor time series data by applying artificial intelligence technology that can read the cultivation status using drone-based images. With these images, the cultivated area along the river was annotated, and data were trained using the YOLOv5 and DeepLabv3+ algorithms. The performance index mAP@0.5 was used, targeting >85%. Both algorithms satisfied the target, confirming that the status of cultivated land along a river can be read using drone-based time series images. Full article
(This article belongs to the Special Issue Environmental Science Studies with Remote Sensing Technologies: Exposure Assessment and Environmental Monitoring)
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11 pages, 3959 KiB  
Article
Marine Oil Spill Detection from SAR Images Based on Attention U-Net Model Using Polarimetric and Wind Speed Information
by Yan Chen and Zhilong Wang
Int. J. Environ. Res. Public Health 2022, 19(19), 12315; https://doi.org/10.3390/ijerph191912315 - 28 Sep 2022
Cited by 6 | Viewed by 1520
Abstract
With the rapid development of marine trade, marine oil pollution is becoming increasingly severe, which can exert damage to the health of the marine environment. Therefore, detection of marine oil spills is important for effectively starting the oil-spill cleaning process and the protection [...] Read more.
With the rapid development of marine trade, marine oil pollution is becoming increasingly severe, which can exert damage to the health of the marine environment. Therefore, detection of marine oil spills is important for effectively starting the oil-spill cleaning process and the protection of the marine environment. The polarimetric synthetic aperture radar (PolSAR) technique has been applied to the detection of marine oil spills in recent years. However, most current studies still focus on using the simple intensity or amplitude information of SAR data and the detection results are not reliable enough. This paper presents a deep-learning-based method to detect oil spills on the marine surface from Sentinel-1 PolSAR satellite images. Specifically, attention gates are added to the U-Net network architecture, which ensures that the model focuses more on feature extraction. In the training process of the model, sufficient Sentinel-1 PolSAR images are selected as sample data. The polarimetric information from the PolSAR dataset and the wind-speed information of the marine surface are both taken into account when training the model and detecting oil spills. The experimental results show that the proposed method achieves better performance than the traditional methods, and taking into account both the polarimetric and wind-speed information, can indeed improve the oil-spill detection results. In addition, the model shows pleasing performance in capturing the fine details of the boundaries of the oil-spill patches. Full article
(This article belongs to the Special Issue Environmental Science Studies with Remote Sensing Technologies: Exposure Assessment and Environmental Monitoring)
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Review

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31 pages, 21022 KiB  
Review
Developmental Features, Influencing Factors, and Formation Mechanism of Underground Mining–Induced Ground Fissure Disasters in China: A Review
by Yu Li, Hui Liu, Lijuan Su, Sidi Chen, Xiaojun Zhu and Pengfei Zhang
Int. J. Environ. Res. Public Health 2023, 20(4), 3511; https://doi.org/10.3390/ijerph20043511 - 16 Feb 2023
Cited by 1 | Viewed by 1400
Abstract
Mining–induced ground fissures are one of the major geological disasters affecting coal mines. In recent years, many effective monitoring methods have been developed to explore the developmental characteristics and nature of mining–induced ground fissures for being treated scientifically. This paper is mainly on [...] Read more.
Mining–induced ground fissures are one of the major geological disasters affecting coal mines. In recent years, many effective monitoring methods have been developed to explore the developmental characteristics and nature of mining–induced ground fissures for being treated scientifically. This paper is mainly on the development law and mechanism of mining ground fissure research results which have been comprehensively combed, highlighting the development trend, including the formation condition, development features, influencing factors, and mechanical mechanism of mining–induced ground fissures. Outstanding issues are discussed and future research hot spots and trends are pointed out. The major conclusions include: (1) under the shallow coal mining condition, because the rock layer fault zone directly reaches the surface, the ground fissure usually develops seriously; (2) mining–induced ground fissures are generally divided into four types: tensile fissures, compression fissures, collapsed fissures, and sliding fissures; (3) mining–induced ground fissures are affected by the coupling effect of underground mining and surface topography. The main factors are geological mining conditions, surface deformation, and surface topography, including rock and soil structure, rock and soil mechanical properties, surface horizontal deformation, surface slope, and so on; and (4) to ensure the safety of underground mining, temporary ground fissures formed during the process of coal mining must be treated when ground fissures and rock ground fissures are connected. The results of this article make up for the deficiencies of the relevant research, provide the basis and direction for future research, and have universal applicability and scientific guiding significance. Full article
(This article belongs to the Special Issue Environmental Science Studies with Remote Sensing Technologies: Exposure Assessment and Environmental Monitoring)
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