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[Display omitted] • A mixed-methods approach links uneven waste exposure in Jakarta's slum and neoliberal waste governance. • The circular economy model has strengthened the informal sector with high-tech measures and global finance. • Strengthening of the informal sector has been unevenly articulated, creating two flows of neoliberal waste activities. • The informal sector focuses on recyclable materials, accumulating non-recyclable waste in their dumpsites. • Public services in capital-intensive areas transport collected waste to the unregulated dumpsites in slums. Urban slums in the Global South have a formidable challenge of mismanaged waste. Behind this challenge lies urban politics, creating disproportionate exposure to waste in marginalized settlements. This paper articulates an urban political ecology of uneven waste accumulation in slums with a case study of Jakarta, Indonesia. I apply a mixed-methods approach, by integrating a spatial regression model with a critical qualitative analysis, to draw the connection between the slums' waste crisis and neoliberal waste infrastructure. Since the mid-2010s, Jakarta's waste governance has shifted from a conventional collect-transport-dispose model to a circular economy model operating under a technocratic and neoliberal economy. Under the shifted governance, the informal sector has been strengthened through the integration of high-tech infrastructure to reduce waste and extract new profits from materials. However, the sector has been unevenly strengthened across the city, creating two flows of waste accumulation activities. First, the strengthening has been accelerated in low-income residential areas by introducing financial incentives for the informal sector to make up the shortfall created by public services. Consequently, the informal sector in slums—with its limited focus on recyclable materials—has led to the accumulation of mismanaged non-recyclable waste in unregulated dumpsites of slums. On the other hand, public services are relatively prevalent in capital-intensive areas to promote the economic growth. However, due to its compact land-uses in those areas, the services utilize the unregulated dumpsites in slums as semi-permanent landfills for storing the collected waste. [ABSTRACT FROM AUTHOR]

This study investigates the spatial strategies of home-based enterprises (HBE) in rental apartments in Jakarta. The provision of affordable housing in the city has been outpaced by rapid population growth, leading to a growing shortage of housing. As a result, high-density slum settlements have become a plausible housing solution, forcing the government to build rental apartments on public land to cope with the growing shortage. Although these apartments have been built to meet the technical requirements of homes, some residents appropriate their housing units to operate HBE in order to improve their livelihoods. These enterprises generate an interweaving of social, economic and domestic activities requiring the enactment of certain spatial strategies. Based on a case study of Jatinegara rental apartments, this research explored the spatial strategies of HBE and the relationship between these strategies and resident demographics. Multiple spatial strategies varying in time and space were found, which relate to different numbers and types of home-based enterprise. The results complement existing home-based enterprise research, and the spatial strategies found can contribute to the improved design of rental apartments for the underprivileged. [ABSTRACT FROM AUTHOR]

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification. [ABSTRACT FROM AUTHOR]