IEEE Geoscience and Remote Sensing Magazine - June 2019 - 185

EDUCATION
TOBIAS SCHÜTTLER, SHIMRIT MAMAN, AND RAIMUND GIRWIDZ

Teaching Remote Sensing Techniques
With High-Quality, Low-Cost Sensors

s a versatile and multidisciplinary area of scientific
research with diverse applications for everyday
life, satellite remote sensing presents a particularly suitable context for science education. In this article, we give
a short overview of how self-acquired infrared remote
sensing data can be applied in individual remote sensing
projects conducted by high school students in their own
environments. We conducted a joint pilot project with
students from Beer-Sheva, Israel, and Munich, Germany.
The students were tasked with acquiring and analyzing remote sensing measurements in the field. The educational
program was evaluated through a questionnaire and by
observing the students. Our analysis of 32 student projects showed that the educational program fostered a variety of important science competencies, and the students
thought the program was interesting and meaningful.

REMOTE SENSING PROJECTS IN SCHOOLS
Remote sensing commonly refers to the acquisition of information about Earth's surface by studying reflected
and/or emitted electromagnetic radiation without any
physical contact with the sensor/s. By analyzing the reflectance of solar radiation from different surfaces on
Earth, researchers can classify these surfaces according to
their specific spectral fingerprints. Remote sensing is an
outstanding analytical technology that may be applied in
many geosciences applications, so it is not surprising that
space agencies, such as NASA and the European Space
Agency, have invested some effort to bring the study of
remote sensing, especially satellite remote sensing, into
school curricula. Teachers of such curricula are aided by
educational software, tutorials, and satellite data that can
be downloaded and analyzed in student projects.
As educators, we believe that the use of data pertaining to students' own particular regions will make such
Digital Object Identifier 10.1109/MGRS.2018.2878596
Date of publication: 18 June 2019

JUNE 2019

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

projects more meaningful and increase students' engagement. In addition, students can easily compare remote
sensing data with what they can see locally. It is widely
accepted that project- and context-based learning fosters
students' interest, self-efficacy, and cognitive skills and
addresses the problem of inert knowledge (e.g., [1]-[3],
[6], [7]). Furthermore, context-based learning provides
multi- and interdisciplinary approaches that make science learning more relevant to students [5]. Satellite
remote sensing is a particularly suitable technology for
context-based science learning: it is interdisciplinary,
combining physics, mathematics, geosciences, engineering, biology, and chemistry, and it offers a variety of applications not only in everyday life, including weather
forecasting and disaster monitoring and protection, but
also in agriculture and the study of Earth's surface.
This project is suitable for high school students
studying remote sensing. It is based on a simple and
cost-effective technology that offers students the opportunity not only to analyze remote sensing data available in online data bases but also to create their own remote sensing data bases. It can easily be replicated, and
schools can realize attractive projects related to their
home region. The project framework was developed at
the German Aerospace Center (DLR) and the Earth and
Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev, Israel. The program is designed to give
students a deeper insight into the physical and technical
backgrounds of remote sensing. During the project, students are required to plan and execute their own measurement campaigns; analyze and validate their data;
and present it in final form to their peers, teachers, and
scientists of the two facilities.
REMOTE SENSING OF VEGETATION
WITH CONVERTED DIGITAL CAMERAS
For the project, we chose the remote sensing of vegetation with converted digital cameras. (We discuss the
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IEEE Geoscience and Remote Sensing Magazine - June 2019

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