High-Resolution Land Cover Mapping with Geographic Object-Based Image Analysis (GEOBIA) for Neighborhood-Level Understanding of Urban Environments

Land cover maps disseminate complex earth observation products by categorizing surface features into multipurpose reference maps. Neighborhood-level high resolution (HR) land cover maps give valuable information to cities, states, and governmental agencies (Szantoi et al., 2020). Analysis of HR urban land cover maps quantify fields, such as those bio-geophyical and social--economic, hazard mitigation, and change through time (Griffith & Hay, 2018; O’Neil-Dunne et al., 2014). Geographic Object-Based Image Analysis (GEOBIA) is a methodology of extracting information from remote sensing imagery. The process of GEOBIA applies segmentation algorithms to imagery by grouping similar pixels into objects. The homogenous objects store information about each pixel group, for example, spectral values (RGB, reflectance values), texture (contrast), spatial information (area, height), and contextual properties (length of shared border) (Hossain & Chen, 2019; Kucharczyk et al., 2020). GEOBIA was performed on high-resolution 0.5 feet, 8-bit, RGB-NIR, NAD83(2011) east-Illinois aerial imagery from 2021 for the Justice and Willow Springs neighborhoods of Cook County, Chicago, Illinois. These data were combined with lidar derivatives for a 3D understanding of the landscape. The segmentation was implemented with eCognition Developer 10.4 software. Preprocessing of imagery, lidar derivatives (DEM and nDSM), map schemes similar to National Land Cover Database (NLCD), and statistics analyses were prepared in ArcGIS Pro 3.3. Statistical analysis of accuracy will be completed (2/10/2025) with a comparison of land cover maps and imagery. This project can serve as an example of best practices for the development of high-resolution neighborhood scale land cover maps through GEOBIA. Future work could include the change through time of the Cook County urban environment.