Special Issue "Teaching and Learning in Remote Sensing"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editors

Dr. Marion Pause
E-Mail Website
Guest Editor
Institute of Photogrammetry and Remote Sensing, Faculty of Environmental Science, Technical University of Dresden, 01062 Dresden, Germany
Interests: multi-sensor remote sensing; soil moisture remote sensing; environmental monitoring; in-situ/remote sensing integration; remote sensing higher education
Special Issues and Collections in MDPI journals
Privat. Doz. Dr. habil. Angela Lausch
E-Mail Website
Guest Editor
Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research (UFZ), Permoserstr.15, D-04318 Leipzig, Germany
Interests: Remote sensing; scaling approaches; linked open data; semantic web; data science approaches; spectral abiotic and biotic traits; spectral trait and trait variation concepts; spatial-temporal process-pattern interactions; vegetation; biodiversity ecosystem health; land-use intensity using RS approaches; essential biodiversity variables (EBV)
Special Issues and Collections in MDPI journals
Dr. habil. András Jung
E-Mail Website
Guest Editor
Department of Geoinformatics and Remote Sensing, Leipzig University (LU), D-04103 Leipzig, Germany;
Technical Department, Szent István University, (SZIU), H-1118 Budapest, Hungary
Interests: hyperspectral remote sensing; field spectroscopy; mobile and snapshot imaging spectroscopy; precision farming; agriculture

Special Issue Information

Dear Colleagues,

Satellite and airborne remote sensing of the Earth’s environment is a comparatively young science characterized by technological innovations in short temporal intervals. For the successful, sustainable, and timely utilization of new and upcoming remote sensing data, individuals require methodological expertise and new skills (e.g., handling hyperspectral observations and full polarimetric SAR data).

Training people in these competences is essential to ensure high quality in the field. Therefore, attention has to be turned to teaching and learning remote sensing in higher education (and even earlier) as an ongoing and scholarly process to address the academic and industrial market requirements. Aside from its fast development, a further didactic challenge is the interdisciplinary character of remote sensing, including, for example, competences from electrical engineering, earth sciences, physics, or biology. While various innovative didactic concepts promoting learning, such as the flipped classroom approach or problem-based learning, have been successfully demonstrated in different fields of engineering education, practice reports in teaching and learning remote sensing are widely missing.

The goal of this Special Issue is to foster and disseminate experiences and findings about what improves the learning and teaching of remote sensing in higher education and in the interdisciplinary context of environmental sciences. The publications within this Special Issue shall support and inspire other educators in the field to successfully design their courses and train the next generation.

Contributions presenting teaching concepts, case studies, and reviews related to remote sensing education are our priority, and may include:

  • Practice reports including reflection and student feedback;
  • E-learning concepts including reflection and student feedback;
  • Scholarship of Teaching and Learning (SoTL) studies; and
  • Educational theories and practices related to remote sensing teaching and learning.

Dr. Marion Pause
Privat. Doz. Dr. habil. Angela Lausch
Dr. habil. András Jung
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. 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 2000 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.

Published Papers (4 papers)

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Open AccessArticle
Bringing Earth Observation to Schools with Digital Integrated Learning Environments
Remote Sens. 2020, 12(3), 345; https://doi.org/10.3390/rs12030345 - 21 Jan 2020
Abstract
The digital integrated learning environments (ILEs) for earth observation described in this article are bringing the complex topic of earth observation into classrooms. They are intended to give pupils with no prior experience in remote sensing the opportunity to solve tasks with earth [...] Read more.
The digital integrated learning environments (ILEs) for earth observation described in this article are bringing the complex topic of earth observation into classrooms. They are intended to give pupils with no prior experience in remote sensing the opportunity to solve tasks with earth observation data by using the same means that professionals have at hand. These learning environments integrate remote sensing tools and background knowledge in a comprehensive e-learning environment. They are tailored for use in schools, whereby the curriculum typically does not include earth observation, teachers are generally not familiar with its concepts, and the technical infrastructure is still not quite ready for digital teaching resources. To make the learning environments applicable, the special demands and obstacles presented by a school environment have to be considered. These obstacles are used to derive the requirements for the use of satellite data in school classes and create classroom resources in terms of technology, didactics, and e-learning. The concept itself was developed ten years ago, and since, then multiple applications have been created and used in classes. Data from an online questionnaire focuses on the specific qualities of the learning modules, enabling us to assess whether the concept works, and where there is need for improvement. The results show that the learning environments are being used, and that they continue to open the minds of pupils and teachers alike to a new perspective on the earth. Full article
(This article belongs to the Special Issue Teaching and Learning in Remote Sensing)
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Open AccessArticle
An Innovative Virtual Simulation Teaching Platform on Digital Mapping with Unmanned Aerial Vehicle for Remote Sensing Education
Remote Sens. 2019, 11(24), 2993; https://doi.org/10.3390/rs11242993 - 12 Dec 2019
Abstract
This work mainly discusses an innovative teaching platform on Unmanned Aerial Vehicle digital mapping for Remote Sensing (RS) education at Wuhan University, underlining the fast development of RS technology. Firstly, we introduce and discuss the future development of the Virtual Simulation Experiment Teaching [...] Read more.
This work mainly discusses an innovative teaching platform on Unmanned Aerial Vehicle digital mapping for Remote Sensing (RS) education at Wuhan University, underlining the fast development of RS technology. Firstly, we introduce and discuss the future development of the Virtual Simulation Experiment Teaching Platform for Unmanned Aerial Vehicle (VSETP-UAV). It includes specific topics such as the Systems and function Design, teaching and learning strategies, and experimental methods. This study shows that VSETP-UAV expands the usual content and training methods related to RS education, and creates a good synergy between teaching and research. The results also show that the VSETP-UAV platform is of high teaching quality producing excellent engineers, with high international standards and innovative skills in the RS field. In particular, it develops students’ practical skills with technical manipulations of dedicated hardware and software equipment (e.g., UAV) in order to assimilate quickly this particular topic. Therefore, students report that this platform is more accessible from an educational point-of-view than theoretical programs, with a quick way of learning basic concepts of RS. Finally, the proposed VSETP-UAV platform achieves a high social influence, expanding the practical content and training methods of UAV based experiments, and providing a platform for producing high-quality national talents with internationally recognized topics related to emerging engineering education. Full article
(This article belongs to the Special Issue Teaching and Learning in Remote Sensing)
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Open AccessArticle
Project-Based Learning Applied to Unmanned Aerial Systems and Remote Sensing
Remote Sens. 2019, 11(20), 2413; https://doi.org/10.3390/rs11202413 - 17 Oct 2019
Cited by 1
Abstract
The development of unmanned aerial vehicle (UAV) technology and the miniaturization of sensors have changed the way remote sensing (RS) is used, popularizing this geoscientific discipline in other fields, such as precision agriculture. This makes it necessary to implement the use of these [...] Read more.
The development of unmanned aerial vehicle (UAV) technology and the miniaturization of sensors have changed the way remote sensing (RS) is used, popularizing this geoscientific discipline in other fields, such as precision agriculture. This makes it necessary to implement the use of these technologies in teaching RS alongside the classical platforms (satellite and manned aircraft). This manuscript describes how The Higher Technical School of Agricultural Engineering at the University of Córdoba (Spain) has introduced UAV RS into the academic program by way of project-based learning (PBL). It also presents the basic characteristics of PBL, the design of the subject, the description of the teacher-guided and self-directed activities, as well as the degree of student satisfaction. The teaching and learning objectives of the subject are to learn how to determine the vigor, temperature, and water stress of a crop through the use of RGB, multispectral, and thermographic sensors onboard a UAV platform. From the onset, students are motivated, actively participate in the tasks related to the realization of UAV flights, and subsequent processing and analysis of the registered images. Students report that PBL is more engaging and allows them to develop a better understanding of RS. Full article
(This article belongs to the Special Issue Teaching and Learning in Remote Sensing)
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Open AccessLetter
Advancing Learning Assignments in Remote Sensing of the Environment Through Simulation Games
Remote Sens. 2020, 12(4), 735; https://doi.org/10.3390/rs12040735 - 22 Feb 2020
Abstract
Environmental remote sensing has faced increasing satellite data availability, advanced algorithms for thematic analysis, and novel concepts of ground truth. For that reason, contents and concepts of learning and teaching remote sensing are constantly evolving. This eventually leads to the intuition of methodologically [...] Read more.
Environmental remote sensing has faced increasing satellite data availability, advanced algorithms for thematic analysis, and novel concepts of ground truth. For that reason, contents and concepts of learning and teaching remote sensing are constantly evolving. This eventually leads to the intuition of methodologically linking academic learning assignments with case-related scopes of application. In order to render case-related learning possible, smart teaching and interactive learning contexts are appreciated and required for remote sensing. That is due to the fact that those contexts are considered promising to trigger and gradually foster students’ comprehensive interdisciplinary thinking. To this end, the following contribution introduces the case-related concept of applying simulation games as a promising didactic format in teaching/learning assignments of remote sensing. As to methodology, participating students have been invited to take on individual roles bound to technology-related profiles (e.g., satellite-mission planning, irrigation, etc.) Based on the scenario, stakeholder teams have been requested to elaborate, analyze and negotiate viable solutions for soil moisture monitoring in a defined context. Collaboration has been encouraged by providing the protected, specifically designed remoSSoil-incubator environment. This letter-type paper aims to introduce the simulation game technique in the context of remote sensing as a type of scholarly teaching; it evaluates learning outcomes by adopting certain techniques of scholarship of teaching and learning (SoTL); and it provides food for thought of replicating, adapting and enhancing simulation games as an innovative, disruptive next-generation learning environment in remote sensing. Full article
(This article belongs to the Special Issue Teaching and Learning in Remote Sensing)
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