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

Dados Bibliográficos

ID22034332
AutoresMaciej Smaczyński (0000-0002-8569-6013, Adam Mickiewicz University in Poznań, autor correspondente), Beata Medyńska-Gulij (0000-0001-6969-4088, Adam Mickiewicz University in Poznań), Łukasz Halik (0000-0002-2537-0468, Adam Mickiewicz University in Poznań)
Ano2020
Volume9
Fascículo12
Páginas754
Data de publicação2020-12-16
Open AccessSim
TipoARTICLE
PeriódicoISPRS International Journal of Geo-Information (JOURNAL)
Identificadores do periódicoISSN: 2220-9964 • E-ISSN: 2220-9964
EditoraMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi9120754
OpenAlexW3113116065
IdiomaEN
Citações recebidas5
Referências citadas32

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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