Evaluation and Comparison of Open and High-Resolution LULC Datasets for Urban Blue Space Mapping

Blue spaces (or water bodies) have a positive impact on the built-up environment and human health. Various open and high-resolution land-use/land-cover (LULC) datasets may be used for mapping blue space, but they have rarely been quantitatively evaluated and compared. Moreover, few studies have investigated whether existing 10-m-resolution LULC datasets can identify water bodies with widths as narrow as 10 m. To fill these gaps, this study evaluates and compares four LULC datasets (ESRI, ESA, FROM-GLC10, OSM) for blue space mapping in Great Britain. First, a buffer approach is proposed for the extraction of water bodies of different widths from a reference dataset. This approach is applied to each LULC dataset, and the results are compared in terms of accuracy, precision, recall, and the F1-score. We find that a high median accuracy (i.e., >98%) is achieved with all four LULC datasets. The OSM dataset gives the best recall and Fl-score. Both the ESRI and ESA datasets produce better results than the FORM-GLC10 dataset. Additionally, the OSM dataset enables the identification of water bodies with widths of 10 m, whereas only water bodies with widths of 20 m or more can be identified in the other datasets. These findings may be beneficial for urban planners and designers in selecting an appropriate LULC dataset for blue space mapping.