USING UAV-BASED 3D IMAGES OF INDIVIDUAL TREE SPECIES IN DISTANCE EDUCATION IN FORESTRY
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences
; XLVI-4/W5-2021:533-537, 2021.
Article
in English
| ProQuest Central | ID: covidwho-1598843
ABSTRACT
Distance education has been offered for years, but the integration of technological developments and opportunities into education has recently increased its popularity and event it became an indispensable method during the Covid-19 pandemic period. In distance education, accessing all class materials such as lecture presentations, class notes, reading materials, videos, live chats or class hours, and archive records allow students (participants) to learn without being in the same environments with teachers or learners. Technology has made vast contributions to the field of education. For instance, 3D as a teaching tool for the class attracts students’ attention, makes the learning process more enjoyable, and increases participation. In particular, for the disciplines, such as forestry, earth, and environmental sciences, which require laboratory exercises, field observation, field trips, and in-situ measurements, 3D modeling has provided many benefits in distance education. It enables 3D demonstration of the individual tree species to develop a virtual field laboratory. This study focused on the data sources and techniques to generate a 3D model of the individual tree species that forestry students used for distance education. The capabilities of the method in the generation of 3D models were evaluated by using UAV-based SfM photogrammetry. The results indicated that implementing 3D images of individual tree species can be a promising method that may increase the interest, interaction and satisfaction of the students in distance education in forestry.
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences
Year:
2021
Document Type:
Article
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