Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

Sven Lautenbach,Robert Hecht,Christina Ludwig,Martin Schorcht,Alexander Zipf

doi:10.3390/ijgi10040251

Abstract

Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its spatial resolution of 10 m fails to capture fine-grained urban structures, while in OSM green spaces are not mapped consistently and with the same level of completeness everywhere. To address these limitations, we propose to fuse these data sets under explicit consideration of their uncertainties. The Sentinel-2 derived Normalized Difference Vegetation Index was fused with OSM data using the Dempster–Shafer theory to enhance the detection of small vegetated areas. The distinction between public and private green spaces was achieved using a Bayesian hierarchical model and OSM data. The analysis was performed based on land use parcels derived from OSM data and tested for the city of Dresden, Germany. The overall accuracy of the final map of public urban green spaces was 95% and was mainly influenced by the uncertainty of the public accessibility model.

Highlights

IntroductionPublic urban green spaces, defined as vegetated spaces within cities that are accessible to the general public (e.g., municipal parks, public playgrounds), are an important factor for the urban quality of life by providing various ecosystem services [1]
Public urban green spaces, defined as vegetated spaces within cities that are accessible to the general public, are an important factor for the urban quality of life by providing various ecosystem services [1]
Recent studies even suggest that sufficient accessibility to nearby public green spaces is beneficial to the well-being and mental health of citizens [6,7,8,9] and urban nature is seen as resilient infrastructure in times of crisis, such as the COVID-19 pandemic [10]

Summary

Introduction

Public urban green spaces, defined as vegetated spaces within cities that are accessible to the general public (e.g., municipal parks, public playgrounds), are an important factor for the urban quality of life by providing various ecosystem services [1]. The Urban Atlas [17] for the EU or the Trust for Public Land’s ParkServe data set [18] for the US contains land use information at a higher resolution but only for selected cities Due to these issues, there is a need for data fusion methods to create comprehensive urban green space data sets that enable analyses across multiple cities [14]

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Discussion

Conclusion