The dynamics of poor urban areas - analyzing morphologic transformations across the globe using Earth observation data

The urban environment is in constant motion, mostly through construction but also through destruction of urban elements. While formal development is a process with long planning periods and thus the built landscape appears static, informal or spontaneous settlements seem to be subject to high dynamics in their ever unfinished urban form. However, the dynamics and morphological characteristics of physical transformation in such settlements of urban poverty have been hardly empirically studied on a global scale or temporal consistent foundation. This paper aims at filling this gap by using Earth observation data to provide a temporal analysis of builtup transformation over a period of ~7 years in 16 documented manifestations of urban poverty. This work applies visual image interpretation using very high resolution optical satellite data in combination with in-situ and Google Street View images to derive 3D city models. We measure physical spatial structures through six spatial morphologic variables - number of buildings, size, height, orientation, heterogeneity and density. Our temporal assessment reveals inter- as well intra-urban differences and we find different, yet generally high morphologic dynamic across study sites. This is expressed in manifold ways: from demolished and reconstructed areas to such where changes appeared within the given structures. Geographically, we find advanced dynamics among our sample specifically in areas of the global south. At the same time, we observe a high spatial variability of morphological transformations within the studied areas. Despite partly high morphologic dynamics, spatial patterns of building alignments, streets and open spaces remain predominantly constant

The connection between slums and COVID-19 cases in Jakarta, Indonesia : a case study of Kapuk Urban Village

COVID-19 has spread world-wide, and with multiple health, social, and economic ramifications. These present a formidable challenge for those belonging to vulnerable communities, such as those living in slums. There is now a growing literature urging attention to this challenge. However, few studies have examined the actual lived realities within these areas using direct, observational research, notwithstanding commentary elsewhere that such close attention is necessary to ensure effective action. This study took this approach in relation to a particular case-study, Kapuk Urban Village, in Jakarta, Indonesia. Drawing on an existing schema involving three spatial scales of slum areas (environs, settlement, and object), the research confirms how different built and socio-economic features can exacerbate vulnerability, and COVID-19 transmission. We also add to the body of knowledge by contributing a dimension of ‘ground-level’ research engagement. We conclude by discussing related ideas around ensuring community resilience and effective policy implementation, and recommend an “urban acupuncture” approach to encourage government regulations and actions better tailored to such communities

Evaluating Strategies for Community-sourced Photography for Mapping Alcohol Adverts in the Urban Slums in Kampala, Uganda

The transient and temporary nature of urban slums throughout the world provide a challenge for collecting actionable data on indicators that can accurately predict factors that have both adverse and protective effects on health. By studying methods to identify hotspots of alcohol advertising more efficiently, there can be a better system for allocating resources or directing research teams to focus efforts on more in-depth studies. In this capstone, a pilot exercise performed in May 2019 explored utilizing locally sourced photographs of alcohol advertisements and then digitally mapping this data to identify and visualize areas of concern that contain a large volume of alcohol advertisements. The aim of this evaluation is to determine the feasibility of this digital mapping method to determine if it is a cost-effective tool that can accurately identify these areas of concern. In addition to the May 2019 pilot project, this paper evaluates other digital mapping projects to continue to improve accuracy, efficiency, and effectiveness

Advances in remote sensing applications for urban sustainability

Abstract: It is essential to monitor urban evolution at spatial and temporal scales to improve our understanding of the changes in cities and their impact on natural resources and environmental systems. Various aspects of remote sensing are routinely used to detect and map features and changes on land and sea surfaces, and in the atmosphere that affect urban sustainability. We provide a critical and comprehensive review of the characteristics of remote sensing systems, and in particular the trade-offs between various system parameters, as well as their use in two key research areas: (a) issues resulting from the expansion of urban environments, and (b) sustainable urban development. The analysis identifies three key trends in the existing literature: (a) the integration of heterogeneous remote sensing data, primarily for investigating or modelling urban environments as a complex system, (b) the development of new algorithms for effective extraction of urban features, and (c) the improvement in the accuracy of traditional spectral-based classification algorithms for addressing the spectral heterogeneity within urban areas. Growing interests in renewable energy have also resulted in the increased use of remote sensing—for planning, operation, and maintenance of energy infrastructures, in particular the ones with spatial variability, such as solar, wind, and geothermal energy. The proliferation of sustainability thinking in all facets of urban development and management also acts as a catalyst for the increased use of, and advances in, remote sensing for urban applications

"Last-Mile" preparation for a potential disaster

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of small-scale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socio-economic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BACKGROUND: The rapid and often uncontrolled rural-urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa's population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam. METHODS: Openly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2-10 years (PfPR2-10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2-10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population. RESULTS: The results suggest that the spatial distribution of PfPR2-10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2-10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values. CONCLUSIONS: The outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

abstract: This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics