Special Issue "Remote Sensing and Geoscience Information Systems in Applied Sciences"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental and Sustainable Science and Technology".

Deadline for manuscript submissions: 20 June 2020.

Special Issue Editors

Guest Editor
Prof. Dr. Hyung-Sup Jung Website E-Mail
The University of Seoul, 90 Jeonnong-dong, Dongdaemun-gu, Seoul 130-743, the Republic of Korea
Interests: Remote Sensing; Geoinformatics; Satellite Data Processing; Environmental Sensing
Guest Editor
Prof. Dr. Saro Lee E-Mail
1. Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124, Gwahak-ro Yuseong-gu, Daejeon 34132, Korea
2. Department of Geophysical Exploration, Korea University of Science and Technology, 217 Gajeong-ro Yuseong-gu, Daejeon 34113, Korea
Phone: 821053538179
Interests: GIS application in Geological Hazard and Geological Resources
Guest Editor
Prof. Dr. Kyung-Soo Han E-Mail
Department of Spatial Information Engineering, Punkyong National University,45, Yongso-ro, Nam-Gu, Busan 48513, Republic of Korea
Interests: Remote sensing for meteorology and land surface, Eco-climatological monitoring
Guest Editor
Prof. Dr. No-Wook Park Website E-Mail
Department of Geoinformatic Engineering, Inha University, Incheon 22212, Republic of Korea
Interests: Remote Sensing Data Classification; Geostatistics; Machine Learning; Environmental Modeling

Special Issue Information

Dear Colleagues,

Remote sensing and geoscience information systems in applied sciences, which cover all aspects of applied biology, applied chemistry, applied physics, and applied engineering, have become more essential in measuring, analyzing, understanding and applying the physical, ecological, geological, hydrological, and environmental characteristics of Earth surfaces. Original research articles and literature review papers addressing the advanced technologies of remote sensing and geoscience information systems in applied sciences will be considered for the publication in this Special Issue. The objectives of this Special Issue are to create a multidisciplinary forum of discussion on recent advances in the fields of remote sensing and geoscience information system for applied sciences and to find new applications to applied geology, applied biology, applied ecology, applied hydrology, applied environmentology, and so on.

Potential topics include but are not limited to the following:

  • Sensor design and platforms development;
  • Multisensor system design and onboard processing;
  • Advances in sensors for applications of remote sensing and geoscience information systems;
  • Multisensor integration in applied sciences;
  • Geospatial data models in applied sciences;
  • Spatial big data analysis in applied sciences;
  • Position and localization systems, algorithms, and techniques;
  • Innovative of remote sensor techniques;
  • Hyperspectral remote sensing in applied sciences;
  • Laser scanning sensors in applied sciences;
  • Image processing algorithm and systems;
  • Spatiotemporal analysis in remote sensing and geoscience information systems.

Prof. Dr. Hyung-Sup Jung
Prof. Dr. Saro Lee
Prof. Dr. Kyung-Soo Han
Prof. Dr. No-Wook Park
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 papers will be 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. Applied Sciences 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 1500 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

  • Remote sensing
  • Geoscience information system (GIS)
  • Global positioning system (GPS)
  • Satellite application
  • Image processing
  • Machine learning

Published Papers (5 papers)

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Research

Open AccessArticle
A New Method for Positional Accuracy Control for Non-Normal Errors Applied to Airborne Laser Scanner Data
Appl. Sci. 2019, 9(18), 3887; https://doi.org/10.3390/app9183887 (registering DOI) - 16 Sep 2019
Abstract
A new statistical method for the quality control of the positional accuracy, useful in a wide range of data sets, is proposed and its use is illustrated through its application to airborne laser scanner (ALS) data. The quality control method is based on [...] Read more.
A new statistical method for the quality control of the positional accuracy, useful in a wide range of data sets, is proposed and its use is illustrated through its application to airborne laser scanner (ALS) data. The quality control method is based on the use of a multinomial distribution that categorizes cases of errors according to metric tolerances. The use of the multinomial distribution is a very novel and powerful approach to the problem of evaluating positional accuracy, since it allows for eliminating the need for a parametric model for positional errors. Three different study cases based on ALS data (infrastructure, urban, and natural cases) that contain non-normal errors were used. Three positional accuracy controls with different tolerances were developed. In two of the control cases, the tolerances were defined by a Gaussian model, and in the third control case, the tolerances were defined from the quantiles of the observed error distribution. The analysis of the test results based on the type I and type II errors show that the method is able to control the positional accuracy of freely distributed data. Full article
(This article belongs to the Special Issue Remote Sensing and Geoscience Information Systems in Applied Sciences)
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Open AccessArticle
Synthetic Aperture Radar Interferometry (InSAR) Ionospheric Correction Based on Faraday Rotation: Two Case Studies
Appl. Sci. 2019, 9(18), 3871; https://doi.org/10.3390/app9183871 - 15 Sep 2019
Abstract
Spaceborne synthetic aperture radar (SAR) imagery is affected by the ionosphere, resulting in distortions of the SAR intensity, phase, and polarization. Although several methods have been proposed to mitigate the ionospheric phase delay of SAR interferometry, the application of them with full-polarimetric SAR [...] Read more.
Spaceborne synthetic aperture radar (SAR) imagery is affected by the ionosphere, resulting in distortions of the SAR intensity, phase, and polarization. Although several methods have been proposed to mitigate the ionospheric phase delay of SAR interferometry, the application of them with full-polarimetric SAR interferometry is limited. Based on this background, Faraday rotation (FR)-based methods are used in this study to mitigate the ionospheric phase errors on full-polarimetric SAR interferometry. For a performance test of the selected method, L-band Advanced Land Observation Satellite (ALOS) Phase Array L-band SAR (PALSAR) full-polarimetric SAR images over high-latitude and low-latitude regions are processed. The result shows that most long-wavelength ionospheric phase errors are removed from the original phase after using the FR-based method, where standard deviations of the corrected result have decreased by almost a factor of eight times for the high-latitude region and 28 times for low-latitude region, compared to those of the original phase, demonstrating the efficiency of the method. This result proves that the FR-based method not only can mitigate the ionospheric effect on SAR interferometry, but also can map the high-spatial-resolution vertical total electronic content (VTEC) distribution. Full article
(This article belongs to the Special Issue Remote Sensing and Geoscience Information Systems in Applied Sciences)
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Open AccessArticle
Detection and 3D Visualization of Deformations for High-Rise Buildings in Shenzhen, China from High-Resolution TerraSAR-X Datasets
Appl. Sci. 2019, 9(18), 3818; https://doi.org/10.3390/app9183818 - 11 Sep 2019
Abstract
Shenzhen, a coastal city, has changed from a small village to a supercity since the late 1980s. With the rapid development of its population and economy, ground disasters also occur frequently. These disasters bring great harm to human life and surface architecture. However, [...] Read more.
Shenzhen, a coastal city, has changed from a small village to a supercity since the late 1980s. With the rapid development of its population and economy, ground disasters also occur frequently. These disasters bring great harm to human life and surface architecture. However, there is a lack of regular ground measurement data in this area. Permanent scatterer interferometry (PSI) technology can detect millimeter deformation of urban surface. In this paper, the building height and deformation from 2008 to 2010 in the Futian District of Shenzhen are obtained by using this technique alongside high-resolution TerraSAR-X data. For a visual expression of the result, we export the permanent scatterer (PS) points on buildings to Google Earth for 3D visualization after ortho-rectification of the PS height. Based on the Google Earth 3D model, the temporal and spatial characteristics of the building deformation became obvious. The InSAR measurements show that during the study period, the deformation rates of the Futian area are between –10 and 10 mm/year, and deformation is mainly distributed in a few buildings. These unstable activities can be attributed to human activities and the natural climate, which provides a reference for the local government to carry out a survey of surface deformation, as well as the monitoring and management of urban buildings, in the future. Full article
(This article belongs to the Special Issue Remote Sensing and Geoscience Information Systems in Applied Sciences)
Open AccessArticle
A Novel in Situ Stress Monitoring Technique for Fracture Rock Mass and Its Application in Deep Coal Mines
Appl. Sci. 2019, 9(18), 3742; https://doi.org/10.3390/app9183742 - 07 Sep 2019
Abstract
A novel in situ stress monitoring method, based on rheological stress recovery (RSR) theory, was proposed to monitor the stress of rock mass in deep underground engineering. The RSR theory indicates that the tiny hole in the rock can close gradually after it [...] Read more.
A novel in situ stress monitoring method, based on rheological stress recovery (RSR) theory, was proposed to monitor the stress of rock mass in deep underground engineering. The RSR theory indicates that the tiny hole in the rock can close gradually after it was drilled due to the rheology characteristic, during which process the stress that existed in the rock can be monitored in real-time. Then, a three-dimensional stress monitoring sensor, based on the vibrating wire technique, was developed for in field measurement. Furthermore, the in-field monitoring procedures for the proposed technique are introduced, including hole drilling, sensor installation, grouting, and data acquisition. Finally, two in situ tests were carried out on deep roadways at the Pingdingshan (PDS) No. 1 and No. 11 coal mines to verify the feasibility and reliability of the proposed technique. The relationship between the recovery stress and the time for the six sensor faces are discussed and the final stable values are calculated. The in situ stress components of rock masses under geodetic coordinates were calculated via the coordinate transformation equation and the results are consistent with the in situ stress data by different methods, which verified the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Remote Sensing and Geoscience Information Systems in Applied Sciences)
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Open AccessArticle
A Comprehensive and Automated Fusion Method: The Enhanced Flexible Spatiotemporal DAta Fusion Model for Monitoring Dynamic Changes of Land Surface
Appl. Sci. 2019, 9(18), 3693; https://doi.org/10.3390/app9183693 - 05 Sep 2019
Abstract
Spatiotemporal fusion methods provide an effective way to generate both high temporal and high spatial resolution data for monitoring dynamic changes of land surface. But existing fusion methods face two main challenges of monitoring the abrupt change events and accurately preserving the spatial [...] Read more.
Spatiotemporal fusion methods provide an effective way to generate both high temporal and high spatial resolution data for monitoring dynamic changes of land surface. But existing fusion methods face two main challenges of monitoring the abrupt change events and accurately preserving the spatial details of objects. The Flexible Spatiotemporal DAta Fusion method (FSDAF) was proposed, which can monitor the abrupt change events, but its predicted images lacked intra-class variability and spatial details. To overcome the above limitations, this study proposed a comprehensive and automated fusion method, the Enhanced FSDAF (EFSDAF) method and tested it for Landsat–MODIS image fusion. Compared with FSDAF, the EFSDAF has the following strengths: (1) it considers the mixed pixels phenomenon of a Landsat image, and the predicted images by EFSDAF have more intra-class variability and spatial details; (2) it adjusts the differences between Landsat images and MODIS images; and (3) it improves the fusion accuracy in the abrupt change area by introducing a new residual index (RI). Vegetation phenology and flood events were selected to evaluate the performance of EFSDAF. Its performance was compared with the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), the Spatial and Temporal Reflectance Unmixing Model (STRUM), and FSDAF. Results show that EFSDAF can monitor the changes of vegetation (gradual change) and flood (abrupt change), and the fusion images by EFSDAF are the best from both visual and quantitative evaluations. More importantly, EFSDAF can accurately generate the spatial details of the object and has strong robustness. Due to the above advantages of EFSDAF, it has great potential to monitor long-term dynamic changes of land surface. Full article
(This article belongs to the Special Issue Remote Sensing and Geoscience Information Systems in Applied Sciences)
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