ALBERT

Description: Geospatial technologies play an important role in understanding and monitoring of land cover and land use change which is critical in achieving Sustainable Development Goal (SDG) 11 and related goals. In this study, we assessed SDG Indicator 11.3.1, Ratio of Land Consumption Rate to Population Growth Rate (LCRPGR) and other urban growth trends of four cities in South Africa using Landsat 5 TM and SPOT 2&5 satellite images and census data collected in 1996, 2001 and 2011. The 2011 built-up areas were mapped using South Africa’s SPOT 5 Global Human Settlements Layer (GHSL) system whereas the 1996 and 2001 built-up areas were extracted from Landsat 5 and SPOT 2 satellite imagery using a kNN object-based image analysis technique that uses textural and radiometric features. We used the built-up area layer to calculate the land consumption per capita and total urban change for each city, both of which have been identified as being important explanatory indicators for the ratio of LCRPGR. The assessment shows that the two major cities, Johannesburg and Tshwane, recorded a decline in the ratio of LCRPGR between the periods 1996–2001 and 2001–2011. In contrast, the LCRPGR ratios for secondary cities, Polokwane and Rustenburg increased during the same periods. The results further show that Tshwane recorded an increase in land consumption per capita between 1996 and 2001 followed by a decrease between 2001 and 2011. Over the same time, Johannesburg experienced a gradual decrease in land consumption per capita. On the other hand, Polokwane and Rustenburg recorded a unique growth trend, in which the overall increase in LCRPGR was accompanied by a decrease in land consumption per capita. In terms of land consumption, Tshwane experienced the highest urban growth rate between 1996 and 2001, whereas Johannesburg and Polokwane experienced the highest urban growth rates between 2001 and 2011. The information derived in this study shows the significance of Indicator 11.3.1 in understanding the urbanization trends in cities of different sizes in South Africa and creates a baseline for nationwide assessment of SDG 11.3.1.

Description: Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups.

Description: As we enter the decade of action on the SDGs, it is necessary to have quantifiable information on the relevant costs of achieving the Sustainable Development Goals (SDGs). Without this information, it will be difficult for decision-makers and stakeholders to effectively allocate existing and scarce resources as well as identify the resource gap that would need to be bridged through exploration and implementation of feasible alternate financing mechanisms. Several studies have estimated the global resource needs to achieve the SDGs, but none identify a clear way to estimate these costs for cities, which are expected to deliver on the SDG agenda for the anticipated 70% of the world's population by 2050. This is perhaps because resource needs vary significantly with city context. Acknowledging this need and to stimulate the dialogue on local costs of sustainability, this study proposes a novel method to determine the cost of achieving housing, transportation, public spaces and solid waste management dimensions (or hard costs) of Sustainable Development Goal 11 (SDG 11) as well as the cost of municipal governance and planning (soft costs) for cities in developing countries. The study also demonstrates the value proposition of using a systematic approach to model the costs of achieving SDG 11 by applying this method to four countries. Apart from sharing the proposed method, the study shares four key findings: (1) despite the inherent difficulty of quantifying and standardizing what comprehensive urban sustainability means for all cities, urban experts do agree on objective criteria of what a baseline level of urban performance should be for some of its dimensions; (2) pursuit of sustainable cities implies different things depending on the development status of the country; (3) cities of different sizes have differing needs and costing methods need to account for transitions from small- to medium-size and medium- to large-size over time; and (4) better understanding needs to be built of what achievement might look like in practice for the subjective targets of SDG 11 such as those pertaining to “heritage and conservation” and “disaster risk and resilience.”