{"title":"A dataset of major urban park of Wuhan in 2021","authors":"Yiming Liao, ShuZhu Wang, K. Chang, Chang Qin, Zhuoying Deng, Zheng Lv, Qi Zhou","doi":"10.11922/11-6035.noda.2022.0005.zh","DOIUrl":null,"url":null,"abstract":"Urban park data have been widely applied to urban planning and management. The availability of urban park has also been viewed as one of the evaluation indicators of the UN’s sustainable development goals. However, currently there is still a lack of urban park datasets that are open to the public. To fill this gap, this study aims to produce a dataset of major urban parks of Wuhan in 2021. This dataset was produced based on multi-source data, including OpenStreetMap, POI and Google Earth image, with the official Statistical Table of Major Urban Parks of Wuhan in 2021 as a reference. This dataset is in the format of ESRI shapefile, covering the name, area, latitude and longitude coordinates and address of the city parks in the year of 2021. We found that the correlation coefficient between the areas of urban parks for our dataset and the official statistic results is up to 0.96, which confirms the reliability and accuracy of our dataset. The approach of using multi-source data for acquiring urban park data boasts the advantage in reducing time-consuming and labor-intensive manual work; more importantly, it may also be used as a reference in acquiring urban park data of other cities.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Scientific Data","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.11922/11-6035.noda.2022.0005.zh","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Urban park data have been widely applied to urban planning and management. The availability of urban park has also been viewed as one of the evaluation indicators of the UN’s sustainable development goals. However, currently there is still a lack of urban park datasets that are open to the public. To fill this gap, this study aims to produce a dataset of major urban parks of Wuhan in 2021. This dataset was produced based on multi-source data, including OpenStreetMap, POI and Google Earth image, with the official Statistical Table of Major Urban Parks of Wuhan in 2021 as a reference. This dataset is in the format of ESRI shapefile, covering the name, area, latitude and longitude coordinates and address of the city parks in the year of 2021. We found that the correlation coefficient between the areas of urban parks for our dataset and the official statistic results is up to 0.96, which confirms the reliability and accuracy of our dataset. The approach of using multi-source data for acquiring urban park data boasts the advantage in reducing time-consuming and labor-intensive manual work; more importantly, it may also be used as a reference in acquiring urban park data of other cities.