This is a catalog record. The data is held outside UD Dataverse. Original dataset: https://doi.org/10.5281/zenodo.7604104. Please cite the original dataset rather than this record.
"This dataset provides a high resolution (1-m) land cover map for Philadelphia, Pennsylvania in the United States of America during the summer of 2017. This dataset was created to differentiate two types of green space in Philadelphia: tree and grass cover. The dataset includes four numerically coded land cover classes. This classification is derived from National Agriculture Imagery Program (NAIP) 1-m aerial imagery captured in the State of Pennsylvania during June of 2017. To improve classification accuracy, NAIP data was stacked with Sentinel-2 level 1C 10-m and 20-m data using the .addBands() function in Google Earth Engine. Two files are available for download: (1) Philadelphia_classification_points.zip: Contains a shapefile of the 8,961 reference points used to train and test the classifier. (2) Philadelphia_Landcover_2017.zip: Contains a GEOTIFF of the classified image over Philadelphia, Pennsylvania for the summer of 2017."
Time period: summer 2017
Location: city of Philadelphia, PA
Formats: .shp, geotiff
Access (per the DSI catalog): Public (Dataset is or could be made publicly available to all without restrictions)
Project: Social media analysis reveals environmental injustices in Philadelphia urban parks. The United Nations Sustainable Development Goal (SDG) target 11.7 calls for access to safe and inclusive green spaces for all communities. Yet, historical residential segregation in the USA has resulted in poor quality urban parks near neighborhoods with primarily disadvantaged socioeconomic status groups, and an extensive park system that addresses the needs of primarily White middle-class residents. Here we center the voices of historically marginalized urban residents by using Natural Language Processing and Geographic Information Science to analyze a large dataset (n = 143,913) of Google Map reviews from 2011 to 2022 across 285 parks in the City of Philadelphia, USA. We find that parks in neighborhoods with a high number of residents from historically disadvantaged demographic groups are likely to receive lower scores on Google Maps. Physical characteristics of these parks based on aerial and satellite images and ancillary data corroborate the public perception of park quality. Topic modeling of park reviews reveal that the diverse environmental justice needs of historically marginalized communities must be met to reduce the uneven park quality—a goal in line with achieving SDG 11 by 2030. Funding: NASA Delaware Space Grant College and Fellowship Program (80NSSC20M0045).
Source: UD Dataset Catalog, UD Data Science Institute: https://research.dsi.udel.edu/dataset/metadata.html#High-Resolution-Greenspace-Land-Cover-in-Philadelphia-Pennsylvania
