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International Symposium on Remote Sensing (ISRS2024)

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

Deadline for manuscript submissions: 28 February 2025 | Viewed by 1769

Special Issue Editors


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Guest Editor
Department of Civil Engineering, National Chung Hsing University, 250 Kuokuang Rd., Taichung 402, Taiwan
Interests: remote sensing; image processing; AI; UAVs; environmental monitoring; disaster damage assessment
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Civil Engineering, National Chung Hsing University, Taichung, Taiwan
Interests: remote sensing; GIS; UAV photogrammetry; image processing; water vapor
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Civil Engineering, National Chung Hsing University, Taichung, Taiwan
Interests: geodesy; GNSS

Special Issue Information

Dear Colleagues,

The 2024 International Symposium on Remote Sensing (ISRS2024) is scheduled to be held in Taichung, Taiwan, from April 24th to 26th, 2024 (https://sites.google.com/view/2024isrs). The symposium aims to delve into various contemporary topics, such as AI, IoT, sensor platforms, unmanned vehicles, GIS, and GNSS, with the primary goal of showcasing the recent advancements in Remote Sensing technology. The convergence of cutting-edge sensing technologies with innovative artificial intelligence (AI) integrated into information and communication technology (ICT) presents a remarkable opportunity to address real-world challenges.

The ISRS2024 is positioned as both a scientific forum and an effective platform for participants to exchange and share their experiences regarding state-of-the-art techniques and the latest developments in remote sensing and spatial information sciences.

A Special Issue of Remote Sensing is planned in collaboration with the ISRS2024, incorporating peer-reviewed feature papers presented at the symposium. Authors intending to publish in this Special Issue must significantly revise their ISRS2024 conference papers, providing a more detailed presentation of the research, including a methodology, results, and discussions. Additionally, submissions should include extra data sets and comparisons to meet the criteria for publication in Remote Sensing. Authors must provide the corresponding ISRS2024 abstract number when submitting their manuscripts; failure to do so will result in the submission not being considered for this Special Issue.

Prof. Dr. Ming-Der Yang
Dr. Huiping Tsai
Dr. Yen-Ru Lai
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

  • remote sensing
  • spatial information sciences
  • global navigation satellite systems
  • photogrammetry
  • geoinformatics
  • artificial intelligence

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Published Papers (1 paper)

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Research

17 pages, 5317 KiB  
Article
Seamless Weather Data Integration in Trajectory-Based Operations Utilizing Geospatial Information
by Sang-Il Kim, Donghyun Jin, Jiyeon Kim, Do-Seob Ahn and Kyung-Soo Han
Remote Sens. 2024, 16(19), 3573; https://doi.org/10.3390/rs16193573 - 25 Sep 2024
Viewed by 715
Abstract
In this study, a 4D trajectory weather (4DT-Wx) prototype system was developed and evaluated for effective weather information integration in trajectory-based operation (TBO) environments. The system has two key distinguishing features: multi-model-based trajectory services and buffer zone information provision. We constructed a distributed [...] Read more.
In this study, a 4D trajectory weather (4DT-Wx) prototype system was developed and evaluated for effective weather information integration in trajectory-based operation (TBO) environments. The system has two key distinguishing features: multi-model-based trajectory services and buffer zone information provision. We constructed a distributed processing system using Apache Spark, enabling the efficient processing of large-scale weather data. The performance evaluation demonstrated excellent scalability and efficiency in processing large-scale data. An analysis of the buffer configurations highlighted that buffer zone information is valuable in decision-making processes and has the potential to enhance the system performance. The system’s practical applicability is presented through visualizations of the extracted weather information. This system is expected to enhance aviation safety and operational efficiency, providing a foundation for addressing increasingly complex weather conditions and flight scenarios in the future. The approach presented in this study marks a significant step toward effective TBO implementation and the advancement of future air traffic management. The evaluation of the 4DT-Wx system analyzed the accuracy of weather data processing and the performance of distributed processing, finding that the temperature (T) estimation had the highest accuracy, and that the parallel processing using Apache Spark was most effectively modeled by Ahmed et al.’s model. The findings suggest the potential for further optimization in integrating various weather models and developing algorithms to enhance their utilization. Full article
(This article belongs to the Special Issue International Symposium on Remote Sensing (ISRS2024))
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