{"title":"A global perspective on the value of multi-level analysis as an enabler for achieving SDGs","authors":"Robert Ndugwa, Dennis Mwaniki","doi":"10.18778/1231-1952.30.2.03","DOIUrl":null,"url":null,"abstract":"With more than 50 percent of the global population living in urban areas, Sustainable Development Goal 11 on Sustainable Cities and Communities provides a critical lever for us to realise all other SDG goals. This calls for tracking urban spatial development at various levels to facilitate a better understanding of the role, amongst others, of remote sensing data in the field of sustainable urban development and services of general interest to be provided by authorities. Urbanisation patterns may thus be retraced, but also modelled in order to provide evidence for decision makers. Without proper planning, the spatial impacts of urbanisation and subsequent spatial inequalities are more likely to affect disadvantaged groups most. In the last decade of the SDGs, the use of data to inform policies is very critical, and such evidence needs to be anchored in multi-level analysis and ensure vertical and horizontal applications at all governance levels.","PeriodicalId":43719,"journal":{"name":"European Spatial Research and Policy","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Spatial Research and Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18778/1231-1952.30.2.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
With more than 50 percent of the global population living in urban areas, Sustainable Development Goal 11 on Sustainable Cities and Communities provides a critical lever for us to realise all other SDG goals. This calls for tracking urban spatial development at various levels to facilitate a better understanding of the role, amongst others, of remote sensing data in the field of sustainable urban development and services of general interest to be provided by authorities. Urbanisation patterns may thus be retraced, but also modelled in order to provide evidence for decision makers. Without proper planning, the spatial impacts of urbanisation and subsequent spatial inequalities are more likely to affect disadvantaged groups most. In the last decade of the SDGs, the use of data to inform policies is very critical, and such evidence needs to be anchored in multi-level analysis and ensure vertical and horizontal applications at all governance levels.