Earth Observation for the Implementation of Sustainable Development Goal 11 Indicators at Local Scale: Monitoring of the Migrant Population Distribution

Abstract

This study focused on implementation of the Sustainable Development Goal (SDG) 11 indicators, at local scale, useful in monitoring urban social resilience. For this purpose, the study focused on updating the distribution map of the migrant population regularly residing in Bari and a neighboring town in Southern Italy. The area is exposed to increasing migration fluxes. The method implemented was based on the integration of Sentinel-2 imagery and updated census information dated 1 January 2019. The study explored a vector-based variant of the dasymetric mapping approach previously used by the Joint Research Center (JRC) within the Data for Integration initiative (D4I). The dasymetric variant implemented can disaggregate data from census areas into a uniform spatial grid by preserving the information complexity of each output grid cell and ensure lower computational costs. The spatial distribution map of regular migrant population obtained, along with other updated ancillary data, were used to quantify, at local level, SDG 11 indicators. In particular, the map of regular migrant population living in inadequate housing (SDG 11.1.1) and the ratio of land consumption rate to regular migrant population growth rate (SDG 11.3.1) were implemented as specific categories of SDG 11 in 2018. At the local level, the regular migrant population density map and the SDG 11 indicator values were provided for each 100 × 100 m cell of an output grid. Obtained for 2018, the spatial distribution map revealed in Bari a high increase of regular migrant population in the same two zones of the city already evidenced in 2011. These zones are located in central parts of the city characterized by urban decay and abandoned buildings. In all remaining city zones, only a slight generalized increase was evidenced. Thus, these findings stress the need for adequate policies to reduce the ongoing process of residential urban segregation. The total of disaggregated values of migrant population evidenced an increase of 44.5% in regular migrant population. The indicators obtained could support urban planners and decision makers not only in the increasing migration pressure management, but also in the local level monitoring of Agenda 2030 progress related to SDG 11.

Development after Displacement: Evaluating the Utility of OpenStreetMap Data for Monitoring Sustainable Development Goal Progress in Refugee Settlements

“…Moreover, the consistency and stability of satellite data collection means that SDG-relevant data can be immediately compared over geographic space (i.e., between settlements) and over time. The use of satellite remote sensing data for monitoring SDG 6 [77], SDG 8 [78], and SDG 11 [79][80][81], in particular, offer a complementary landscape-based perspective to OSM's feature-based perspective. While the application of satellite imagery for monitoring landscape changes at or surrounding refugee settlements is relatively recent, e.g., References [82][83][84], an SDG monitoring effort that fuses OSM and satellite remote sensing data would offer a scalable, near-real-time, persistent approach, well-suited for refugee settlement-level SDG monitoring.…”

Earth Observation for Sustainable Infrastructure: A Review

“…First, the available indicators are confirmed data that can support SID and most of the case studies in literature about EOSI have been performed for this type of indicators. For instance, for SDG 11.1 that the access to living space and services should be ensured [6], all infrastructure have direct influence on the target and Earth observation based indicators have been available in the official database [60,61], where the data have been assessed in recent case studies [173,174]. In addition, the summary indicates that the Earth observation for indirect influenced targets of infrastructure is the predominant one for all five categories of infrastructure.…”

Digital sustainability: how information and communication technologies (ICTs) support sustainable development goals (SDGs) assessment in municipalities

“…On the other hand, considering the technology-driven orientation of Smart Cities, studies that address the use of technology for achieving the SDGs involve a specific stakeholder and look at one SDG at a time (Aquilino et al, 2020;Akuraju et al, 2020). They do not relate different goals nor explore the potential consequences of actions to other SDGs.…”