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The Land Use Mapping Techniques (Including the Areas Used by Pedestrians) Based on Low-Level Aerial Imagery

Bibliographic Data

ID22034332
AuthorsMaciej Smaczyński (0000-0002-8569-6013, Adam Mickiewicz University in Poznań, corresponding author), Beata Medyńska-Gulij (0000-0001-6969-4088, Adam Mickiewicz University in Poznań), Łukasz Halik (0000-0002-2537-0468, Adam Mickiewicz University in Poznań)
Year2020
Volume9
Issue12
Pages754
Publication date2020-12-16
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi9120754
OpenAlexW3113116065
LanguageEN
Citations received5
References cited32

Traditionally, chorochromatic maps with a qualitative measurement level are used for land use presentations. Along with the use of UAV (Unmanned Aerial Vehicles), it became possible to register dynamic phenomena in a small space. We analyze the application of qualitative and quantitative mapping methods to visualize land use in a dynamic context thanks to cyclically obtained UAV imaging. The aim of the research is to produce thematic maps showing the actual land use of the small area urbanized by pedestrians. The research was based on low-level aerial imagery that recorded the movement of pedestrians in the research area. Additionally, based on the observation of pedestrian movement, researchers pointed out the areas of land that pedestrians used incorrectly. For this purpose, the author will present his own concept of the point-to-polygon transformation of pedestrians’ representation. The research was an opportunity to demonstrate suitable mapping techniques to effectively convey the information on land use by pedestrians. The results allowed the authors of this article to draw conclusions on the choice of suitable mapping techniques during the process of thematic land use map design and to specify further areas for research

Cartography · Civil engineering · Geography · Land use · Pedestrian · Remote sensing · Spatial contextual awareness · Thematic map · 3D Surveying and Cultural Heritage · Computer Science · Engineering · Remote Sensing and LiDAR Applications · Robotics and Sensor-Based Localization · Artificial Intelligence

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Citations per year1
Citation span2021 - 2023 (3)
Highly citedNo

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