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Urban slum structure: integrating socioeconomic and land cover data to model slum evolution in Salvador, Brazil

机译:城市贫民窟结构:整合社会经济和土地覆盖数据以模拟巴西萨尔瓦多的贫民窟演变

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Background The expansion of urban slums is a key challenge for public and social policy in the 21st century. The heterogeneous and dynamic nature of slum communities limits the use of rigid slum definitions. A systematic and flexible approach to characterize, delineate and model urban slum structure at an operational resolution is essential to plan, deploy, and monitor interventions at the local and national level. Methods We modeled the multi-dimensional structure of urban slums in the city of Salvador, a city of 3 million inhabitants in Brazil, by integrating census-derived socioeconomic variables and remotely-sensed land cover variables. We assessed the correlation between the two sets of variables using canonical correlation analysis, identified land cover proxies for the socioeconomic variables, and produced an integrated map of deprivation in Salvador at 30 m × 30 m resolution. Results The canonical analysis identified three significant ordination axes that described the structure of Salvador census tracts according to land cover and socioeconomic features. The first canonical axis captured a gradient from crowded, low-income communities with corrugated roof housing to higher-income communities. The second canonical axis discriminated among socioeconomic variables characterizing the most marginalized census tracts, those without access to sanitation or piped water. The third canonical axis accounted for the least amount of variation, but discriminated between high-income areas with white-painted or tiled roofs from lower-income areas. Conclusions Our approach captures the socioeconomic and land cover heterogeneity within and between slum settlements and identifies the most marginalized communities in a large, complex urban setting. These findings indicate that changes in the canonical scores for slum areas can be used to track their evolution and to monitor the impact of development programs such as slum upgrading.
机译:背景信息城市贫民窟的扩大是21世纪公共和社会政策面临的主要挑战。贫民窟社区的异质性和动态性限制了刚性贫民窟定义的使用。在运营分辨率下,系统地,灵活地表征,描述和建模城市贫民窟的结构对于在地方和国家层面计划,部署和监控干预措施至关重要。方法我们通过整合人口普查衍生的社会经济变量和遥感土地覆盖变量,对萨尔瓦多市(巴西300万居民)的城市贫民窟的多维结构进行了建模。我们使用典范的相关性分析评估了两组变量之间的相关性,确定了社会经济变量的土地覆盖代理,并以30 m×30 m的分辨率绘制了萨尔瓦多的贫困综合图。结果规范分析确定了三个重要的排序轴,这些轴根据土地覆被和社会经济特征描述了萨尔瓦多人口普查区的结构。第一个规范轴捕获了从拥挤的瓦楞屋顶房屋的低收入社区到高收入社区的梯度。第二个规范轴在社会经济变量之间进行了区分,这些变量表征了最边缘化的人口普查区,即那些无法获得卫生设施或自来水的人口。第三个规范轴的变化量最少,但是区分了高收入区域和屋顶白色油漆或平铺的低收入区域。结论我们的方法反映了贫民窟定居点之内和之间的社会经济和土地覆盖异质性,并确定了在大型复杂城市环境中边缘化程度最高的社区。这些发现表明,贫民窟地区的规范分数的变化可用于追踪其演变并监测诸如贫民窟升级之类的发展计划的影响。

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