Aerial data analysis for integration into a green cadastre - an example from Aarhus, Denmark

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing 2023-01, Vol.16, p.1-13
• Main Authors: Knopp, Julius M., Levin, Gregor, Banzhaf, Ellen
• Format: Article
• Language: English
• Subjects: Agricultural land; Cadastre; Climate adaptation; Climate change; Climate change adaptation; Data analysis; Data mining; Data models; digital orthophotos; digital orthophotos (DOP); Image processing; Information processing; Land cover; Land use; Laser radar; Lidar; Mapping; object-based image analysis; object-based image analysis (OBIA); Orthophotography; Resilience; Rural areas; Semantics; Social resilience; Spatial discrimination; Spatial resolution; structural biodiversity; Surface treatment; Urban areas; Urban environments; Urban planning; urban-rural fringe; Vegetation mapping
• ISSN: 1939-1404; 2151-1535
• DOI: 10.1109/JSTARS.2023.3289218

Fostering urban resilience and adaptation to climate change pose new demands on the knowledge of Land Use and Land Cover (LULC) in heterogeneous urban spaces. High-resolution urban mapping is a valuable tool, which serves to map detailed categories. Such semantic data is integrated in national and regional administration as public goods. In the light of many countries around the globe making their data publicly available, we present a method to (a) map urban areas based on multitemporal orthophotos and LiDAR derived digital surface model, and (b) extract information about vegetation in an automated processing chain. This approach is threshold-driven and relies on an automatic generation of spectral thresholds and existing real-world based classifications. We included cadastral data to add land-use information for specific categories, such as agricultural land use and to assess the product's accuracy. Adding this data creates a LULC product and makes a seamless integration into urban planning routines possible. The results of the study provide a detailed LULC map for the municipality of Aarhus in the year 2015 with a spatial resolution of 20 cm and ten thematic classes. Depending on the reference data, we achieved thematic overall accuracies of 34% and 64% using a polygon based approach. Our study has found that utilising both multitemporal orthophotos and elevation data can enhance the LC mapping of urban landscapes. The methodology could be transferred to other areas in Denmark or to countries providing similar datasets, and lends itself to a repeatable LULC mapping with minimal user interaction.