Lifelong training program on QGIS tools for earth observation sciences in south-east Europe

Abstract

Earth Observation (EO) data are an indispensable source of useful geospatial information, which can be efficiently combined with other data within the latest released open-source QGIS software. This paper aims: i) to present a general overview of the QGIS EO plugins; ii) to promote the Lifelong Learning (LLL) courses for open-source QGIS software tools provided by the Geo-SEE Institute from Skopje; iii) to appreciate the advantages of open-source QGIS for developing and improving EO applications. The training objectives are to enhance the research, development tools and technologies of QGIS and stimulate the obtaining and disseminating knowledge to utilize the open-source GIS software. Furthermore, there is a growing need to increase the number of well-educated professionals on issues related to the EO sciences in South-East Europe (SEE), who are better prepared for the labor market in today's digital revolution by using QGIS tools and plugins combined with other related GIS software platforms provided by the OSGeo family.

Designing Online Workshops for Teacher Trainees: Heritage Mapping with Web GIS Story Maps

“…The participants were able to master its basic features after just a one-hour lesson, thereby crucially understanding that GIS is a methodological tool and not the primary object of study. In fact, there are studies that show that the use of GIS for terrestrial exploration is effective for lifelong learning (Idrizi et al, 2021), implying that it can be valid as a didactic resource for inexperienced students. The accessible and interactive interface of current web GIS (West & Horswell, 2018;Kerski, 2021) and the inclusion in our workshop of an initial lecture on web GIS were expected to contribute to success (Martínez-Hernández et al, 2022).…”

“…Nevertheless, group work could be considered in the design, perhaps on some specific tasks, if cooperative learning and social skills are included (Le et al, 2018) and individual learning is not compromised. Group work has already been shown to be effective in GIS-based learning (Carver et al, 2004;Idrizi et al, 2021).…”