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Publisher: SAGE Publications
Date: 16-05-2013
Abstract: China’s dramatic urban expansion has encompassed many peri-urban villages and turned them into so-called urban villages that provide a niche housing market for rural migrants for whom the formal housing market is unaffordable. Yet urban villages are very distinct from informal settlements elsewhere, because they are being developed by the original village community on collectively owned land. As these communities cannot sell their land and only build housing units for low-paid workers, the only way to make a higher return from their land is to increase its built intensity. This paper tests the hypothesis that the driving factors of this built intensity are analogous to factors that drive land prices in the formal city. Results of multivariate regression models of the built intensity of urban villages across the city of Shenzhen show a remarkable resemblance to hedonic models of land prices elsewhere. Location matters and access to employment, along with development constraints, are the most important determinants for the development of Shenzhen’s urban villages.
Publisher: Informa UK Limited
Date: 25-12-2020
Publisher: Copernicus GmbH
Date: 06-06-2016
DOI: 10.5194/ISPRS-ANNALS-III-3-317-2016
Abstract: Abstract. Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.
Publisher: MDPI AG
Date: 29-08-2013
DOI: 10.3390/RS5094209
Publisher: MDPI AG
Date: 15-04-2020
DOI: 10.20944/PREPRINTS201910.0242.V3
Abstract: Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying & slum households& in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This erse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 04-2018
Publisher: Elsevier BV
Date: 04-2016
Publisher: International Information and Engineering Technology Association
Date: 31-12-2016
Publisher: MDPI AG
Date: 21-10-2019
DOI: 10.20944/PREPRINTS201910.0242.V1
Abstract: Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying & slum households& in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This erse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.
Publisher: IEEE
Date: 11-07-2021
Publisher: MDPI AG
Date: 24-10-2019
DOI: 10.20944/PREPRINTS201910.0242.V2
Abstract: Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely silo-ed, and each fall short of producing accurate, timely, comparable maps that reflect local contexts. The first approach, classifying & slum households& in census and survey data and aggregating to administrative areas, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human interpretation and machine classification of satellite, aerial, or drone imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of basic public services. The latter, machine classification of imagery, can be automated and extended to incorporate new and multiple sources of data. This erse collection of authors represent experts from these four approaches to neighborhood deprivation mapping. We summarize common areas of understanding, and present a set of requirements to produce maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making.
Publisher: Elsevier BV
Date: 12-2020
Publisher: IEEE
Date: 03-2017
Publisher: Elsevier BV
Date: 03-2010
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 10-2012
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 03-2012
Publisher: Wiley
Date: 30-09-2022
Publisher: Elsevier BV
Date: 10-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2018
Publisher: Elsevier BV
Date: 03-2011
Publisher: Elsevier BV
Date: 07-2022
Publisher: WIT Press
Date: 07-2015
DOI: 10.2495/RAV150231
Publisher: SAGE Publications
Date: 18-08-2016
Abstract: Processes of globalization and neoliberal reforms of local governance in Indian cities have created distinct patterns by reshaping the physical and social landscapes of India’s cities, triggering contestations between the privileged and the dispossessed. This paper addresses the consequences for poor households of mega-urban renewal and infrastructure projects and the processes of displacement and resettlement in Ahmedabad, India. The findings indicate that the displaced poor households have been further impoverished in the course of current practices as a result of limited attention to the risk of impoverishment both in policy and in local government practices. Contrary to the state’s rhetoric of inclusive governance, the urban poor are completely excluded from planning for infrastructure development and resettlement processes, leading to a lack of understanding of their needs by the state and their subsequent impoverishment after resettlement.
Publisher: MDPI AG
Date: 14-07-2022
DOI: 10.3390/IJGI11070403
Abstract: Gridded population datasets model the population at a relatively high spatial and temporal granularity by reallocating official population data from irregular administrative units to regular grids (e.g., 1 km grid cells). Such population data are vital for understanding human–environmental relationships and responding to many socioeconomic and environmental problems. We analyzed one very broadly used gridded population layer (GHS-POP) to assess its capacity to capture the distribution of population counts in several urban areas, spread across the major world regions. This analysis was performed to assess its suitability for global population modelling. We acquired the most detailed local population data available for several cities and compared this with the GHS-POP layer. Results showed erse error rates and degrees depending on the geographic context. In general, cities in High-Income (HIC) and Upper-Middle-Income Countries (UMIC) had fewer model errors as compared to cities in Low- and Middle-Income Countries (LMIC). On a global average, 75% of all urban spaces were wrongly estimated. Generally, in central mixed or non-residential areas, the population was overestimated, while in high-density residential areas (e.g., informal areas and high-rise areas), the population was underestimated. Moreover, high model uncertainties were found in low-density or sparsely populated outskirts of cities. These geographic patterns of errors should be well understood when using population models as an input for urban growth models, as they introduce geographic biases.
Publisher: MDPI AG
Date: 13-05-2020
Abstract: Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low- and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas.
Publisher: Elsevier BV
Date: 02-2022
Publisher: Wiley
Date: 16-03-2022
Abstract: Wildfire affecting urban areas at the wildland urban interface (WUI) is a growing global concern, where management is important for urban residents as well as wildland vegetation. We used a socio‐ecological system perspective to investigate the interactions of urban land with a fire‐dependent wildland in South Africa’s City of Cape Town (CoCT). We examined changes in population growth, land cover change and related WUI footprint, occurrence of large fires, and related policies over time. We used Landsat data to track changes over the period 1990–2019 in the formal and informal urban and wildland footprint, census data to track changes in population, and difference normalised burn ratio and MODIS burned area product to track large fires. The urban footprint has expanded greatly and through consolidation has led to the reduction of the WUI. Furthermore, evidence points to an increase in fire suppression, even though national policies ask for wildfires to run their course where possible and appropriate. As a result of pressure from urban residents, local managers prefer short term fire suppression to long term risk reduction for urban areas and ecological management of wildland. Framing the problem as a socio‐ecological system enabled us to highlight how WUI management is a product of interaction between urban development, wildland type and policies. Our findings emphasise the point that wildland management is driven by urban residents and local municipalities, with national fire and disaster management policies not fully implemented.
Publisher: IEEE
Date: 05-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2018
Publisher: Elsevier BV
Date: 11-2016
Publisher: Optica Publishing Group
Date: 09-09-2020
DOI: 10.1364/OE.396925
Abstract: The overdetermination of the mathematical problem underlying ptychography is reduced by a host of experimentally more desirable settings. Furthermore, reconstruction of the s le-induced phase shift is typically limited by uncertainty in the experimental parameters and finite s le thicknesses. Presented is a conjugate gradient descent algorithm, regularized optimization for ptychography (ROP), that recovers the partially known experimental parameters along with the phase shift, improves resolution by incorporating the multislice formalism to treat finite s le thicknesses, and includes regularization in the optimization process, thus achieving reliable results from noisy data with severely reduced and underdetermined information.
Publisher: Springer Science and Business Media LLC
Date: 09-1989
DOI: 10.1007/BF02995839
Publisher: Elsevier BV
Date: 11-2014
Publisher: BMJ
Date: 04-2019
DOI: 10.1136/BMJGH-2018-001267
Abstract: Despite an estimated one billion people around the world living in slums, most surveys of health and well-being do not distinguish between slum and non-slum urban residents. Identifying people who live in slums is important for research purposes and also to enable policymakers, programme managers, donors and non-governmental organisations to better target investments and services to areas of greatest deprivation. However, there is no consensus on what a slum is let alone how slums can be distinguished from non-slum urban precincts. Nor has attention been given to a more fine-grained classification of urban spaces that might go beyond a simple slum/non-slum dichotomy. The purpose of this paper is to provide a conceptual framework to help tackle the related issues of slum definition and classification of the urban landscape. We discuss: The concept of space as an epidemiological variable that results in ‘neighbourhood effects’. The problems of slum area definition when there is no ‘gold standard’. A long-list of variables from which a selection must be made in defining or classifying urban slum spaces. Methods to combine any set of identified variables in an operational slum area definition. Two basic approaches to spatial slum area definitions—top-down (starting with a predefined area which is then classified according to features present in that area) and bottom-up (defining the areal unit based on its features). Different requirements of a slum area definition according to its intended use. Implications for research and future development.
Publisher: MDPI AG
Date: 22-09-2018
DOI: 10.3390/RS10101522
Abstract: The survey-based slum mapping (SBSM) program conducted by the Indonesian government to reach the national target of “cities without slums” by 2019 shows mapping inconsistencies due to several reasons, e.g., the dependency on the surveyor’s experiences and the complexity of the slum indicators set. By relying on such inconsistent maps, it will be difficult to monitor the national slum upgrading program’s progress. Remote sensing imagery combined with machine learning algorithms could support the reduction of these inconsistencies. This study evaluates the performance of two machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF), for slum mapping in support of the slum mapping c aign in Bandung, Indonesia. Recognizing the complexity in differentiating slum and formal areas in Indonesia, the study used a combination of spectral, contextual, and morphological features. In addition, sequential feature selection (SFS) combined with the Hilbert–Schmidt independence criterion (HSIC) was used to select significant features for classifying slums. Overall, the highest accuracy (88.5%) was achieved by the SVM with SFS using contextual, morphological, and spectral features, which is higher than the estimated accuracy of the SBSM. To evaluate the potential of machine learning-based slum mapping (MLBSM) in support of slum upgrading programs, interviews were conducted with several local and national stakeholders. Results show that local acceptance for a remote sensing-based slum mapping approach varies among stakeholder groups. Therefore, a locally adapted framework is required to combine ground surveys with robust and consistent machine learning methods, for being able to deal with big data, and to allow the rapid extraction of consistent information on the dynamics of slums at a large scale.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 12-2007
Publisher: IEEE
Date: 07-2016
Publisher: SAGE Publications
Date: 2012
DOI: 10.1068/A44696
Abstract: China's dynamic urbanisation since 1978 has led to the proliferation of so-called ‘urban villages’ in many cities. Their development, via a self-help approach by indigenous villagers, delivers low-cost housing and various other social and economic activities. Consequently, urban villages are characterised by growing numbers of buildings and a mix of functions, including residential, industrial, commercial, and public services. These uses enable different activities in urban villages, assimilating migrants into the city by providing an alternative niche for working and living. Variations in land-use ersity in Shenzhen's 318 urban villages were analysed using 2009 data, for more than 333 000 buildings. Four statistical models, including three based on a spatial regimes analysis, are used to explain their land-use ersity. The results reveal that an urban village's land-use pattern is linked to its location in the urban fabric, its phase of development, and the development level of its environs. Different patterns are apparent inside and outside the Special Economic Zone of Shenzhen, suggesting that the current uniform redevelopment policy for urban villages may not be appropriate.
Publisher: MDPI AG
Date: 11-2018
DOI: 10.3390/IJGI7110428
Abstract: The continuous increase in deprived living conditions in many cities of the Global South contradicts efforts to make cities inclusive, safe, resilient, and sustainable places. Using ex les of Asian, African, and Latin American cities, this study shows the scope and limits of earth observation (EO)-based mapping of deprived living conditions in support of providing consistent global information for the SDG indicator 11.1.1 “proportion of urban population living in slums, informal settlements or inadequate housing”. At the technical level, we compare several EO-based methods and imagery for mapping deprived living conditions, discussing their ability to map such areas including differences in terms of accuracy and performance at the city scale. At the operational level, we compare available municipal maps showing identified deprived areas with the spatial extent of morphological mapped areas of deprived living conditions (using EO) at the city scale, discussing the reasons for inconsistencies between municipal and EO-based maps. We provide an outlook on how EO-based mapping of deprived living conditions could contribute to a global spatial information base to support targeting of deprived living conditions in support of the SDG Goal 11.1.1 indicator, when uncertainties and ethical considerations on data provision are well addressed.
Publisher: Informa UK Limited
Date: 03-07-2015
Publisher: IEEE
Date: 03-2017
Publisher: Springer Netherlands
Date: 2010
Publisher: MDPI AG
Date: 19-01-2020
Abstract: Urbanization is playing a key role in big cities of developing countries, which, in effect, is increasing the population. This study takes care of the mega infrastructure project (Orange Line Metro Train (OLMT)) to explore and identify the H& S (Health and Safety) factors that affect the local residents and the main key stakeholders working on the project. A Sequential Mixed-Method approach of the OLMT-project includes qualitative and quantitative methods were adopted. The data have been collected from the targeted population working on the OLMT-project through a questionnaire. The main key finding of the study indicates that poor planning and a lack of communication between the public and government led to frustration. The most significant factors that identified in the study were unsafe to work practice, project scope constraints, lack in technical and material support, unsafe/bad condition, health/environment degradation, declination and loss of resources and time, no proper emergency system, and negligence in adopting safety rules and laws. The study also revealed that the consensus should also be noticed between the key stakeholders (e.g., contractors, clients, safety officials, academia) in the second round of the Delphi survey of the project. The study findings will help the key stakeholders to prioritize their energies towards attaining zero levels of inadequate health and safety practices in infrastructure projects. The study outcomes can also be generalized for the other developing countries having a similar work scenario.
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 03-2008
Publisher: African Journals Online (AJOL)
Date: 28-07-2016
DOI: 10.4314/RJ.V1I1S.4D
Publisher: Elsevier BV
Date: 11-2022
Publisher: IEEE
Date: 03-2017
Publisher: SPIE
Date: 13-10-2009
DOI: 10.1117/12.838687
Publisher: MDPI AG
Date: 31-07-2019
DOI: 10.3390/IJGI8080341
Abstract: Better and more detailed analyses of global human exposure to hazards and associated disaster risk require improved geoinformation on population distribution and densities. In particular, issues of temporal and spatial resolution are important for determining the capacity for assessing changes in these distributions. We combine the best-available global population grids with latest data on volcanoes, to assess and characterize the worldwide distribution of population from 1975–2015 in relation to recent volcanism. Both Holocene volcanoes and those where there is evidence of significant eruptions are considered. A comparative analysis is conducted for the volcanic hot spots of Southeast Asia and Central America. Results indicate that more than 8% of the world’s 2015 population lived within 100 km of a volcano with at least one significant eruption, and more than 1 billion people (14.3%) lived within 100 km of a Holocene volcano, with human concentrations in this zone increasing since 1975 above the global population growth rate. While overall spatial patterns of population density have been relatively stable in time, their variation with distance is not monotonic, with a higher concentration of people between 10 and 20 km from volcanoes. We find that in last 40 years in Southeast Asia the highest population growth rates have occurred in close proximity to volcanoes (within 10 km), whereas in Central America these are observed farther away (beyond 50 km), especially after 1990 and for Holocene volcanoes.
Publisher: Elsevier BV
Date: 12-2003
Publisher: IEEE
Date: 03-2017
Publisher: IEEE
Date: 03-2015
Publisher: Wiley
Date: 15-07-2019
DOI: 10.1002/WCC.600
Abstract: Maps synthesizing climate, biophysical and socioeconomic data have become part of the standard tool‐kit for communicating the risks of climate change to society. Vulnerability maps are used to direct attention to geographic areas where impacts on society are expected to be greatest and that may therefore require adaptation interventions. Under the Green Climate Fund and other bilateral climate adaptation funding mechanisms, donors are investing billions of dollars of adaptation funds, often with guidance from modeling results, visualized and communicated through maps and spatial decision support tools. This paper presents the results of a systematic review of 84 studies that map social vulnerability to climate impacts. These assessments are compiled by interdisciplinary teams of researchers, span many regions, range in scale from local to global, and vary in terms of frameworks, data, methods, and thematic foci. The goal is to identify common approaches to mapping, evaluate their strengths and limitations, and offer recommendations and future directions for the field. The systematic review finds some convergence around common frameworks developed by the Intergovernmental Panel on Climate Change, frequent use of linear index aggregation, and common approaches to the selection and use of climate and socioeconomic data. Further, it identifies limitations such as a lack of future climate and socioeconomic projections in many studies, insufficient characterization of uncertainty, challenges in map validation, and insufficient engagement with policy audiences for those studies that purport to be policy relevant. Finally, it provides recommendations for addressing the identified shortcomings. This article is categorized under: Vulnerability and Adaptation to Climate Change Values‐Based Approach to Vulnerability and Adaptation
Publisher: SAGE Publications
Date: 16-02-2016
Abstract: In the past two decades, many Asian countries including India have mandated participatory local governance through national statutes. Emerging research on Asian cities shows that despite strong national mandates, the practice of participatory governance at local levels remains largely ineffective. Our research in Ahmedabad, India, shows that while the state government’s policy mandate for invited spaces for participation in local governance is weak compared with the national government’s policy mandate, the practice of participatory governance by the local government is even weaker, leading to ineffective or closed participatory spaces. In the absence of invited spaces, the middle class successfully uses the executive wing at the ward and zonal levels and e-governance and m-governance platforms to negotiate their needs, whereas the poor rely on the elected representatives, but with limited success, resonating the experience of many cities in Asia. While in other cities of India, the poor have successfully engaged with elected representatives through clientelism to negotiate their needs, in Ahmedabad, this platform is captured also by the elite middle class and offers little opportunity to the poor. In response to the denial of all invited spaces of engagement and the consequent implications on their lives, the poor mobilize to claim spaces for engagement with the state through judicial recourse. Although successful, claimed spaces of the poor are one-off mechanisms that close upon the end of the judicial process rather than culminate into permanent invited spaces for participation.
Publisher: CRC Press
Date: 03-09-2009
Publisher: Elsevier BV
Date: 11-2019
DOI: 10.1016/J.JENVMAN.2019.109482
Abstract: Policy making for complex Social-Ecological Systems (SESs) is a multi-factorial and multi-stakeholder decision making process. Therefore, proper policy simulation in a SES should consider both the complex behavior of the system and the multi-stakeholders' interventions into the system, which requires integrated methodological approaches. In this study, we simulate impacts of policy options on a farming community facing water scarcity in Rafsanjan, Iran, using an integrated modeling methodology combining an Agent Based Model (ABM) with Fuzzy Cognitive Mapping (FCM). First, the behavioral rules of farmers and the causal relations among environmental variables are captured with FCMs that are developed with both qualitative and quantitative data, i.e. farmers' knowledge and empirical data from studies. Then, an ABM is developed to model decisions and actions of farmers and simulate their impacts on overall groundwater use and emigration of farmers in this case study. Finally, the impacts of different policy options are simulated and compared with a baseline scenario. The results suggest that a policy of facilitating farmers' participation in management and control of their groundwater use leads to the highest reduction of groundwater use and would help to secure farmers' activities in Rafsanjan. Our approach covers four main aspects that are crucial for policy simulation in SESs: 1) causal relationships, 2) feedback mechanisms, 3) social-spatial heterogeneity and 4) temporal dynamics. This approach is particularly useful for ex-ante policy options analysis.
Publisher: IEEE
Date: 06-2012
Publisher: MDPI AG
Date: 27-05-2016
DOI: 10.3390/RS8060455
Publisher: Elsevier BV
Date: 04-2011
Publisher: Springer Science and Business Media LLC
Date: 07-06-2018
Publisher: MDPI AG
Date: 19-11-2020
DOI: 10.3390/RS12223799
Abstract: Since 2005, Egypt has a new land-use development policy to control unplanned human settlement growth and prevent outlying growth. This study assesses the impact of this policy shift on settlement growth in Assiut Governorate, Egypt, between 1999 and 2020. With symbolic machine learning, we extract built-up areas from Landsat images of 2005, 2010, 2015, and 2020 and a Landscape Expansion Index with a new QGIS plugin tool (Growth Classifier) developed to classify settlement growth types. The base year, 1999, was produced by the national remote sensing agency. After extracting the built-up areas from the Landsat images, eight settlement growth types (infill, expansion, edge-ribbon, linear branch, isolated cluster, proximate cluster, isolated scattered, and proximate scattered) were identified for four periods (1999:2005, 2005:2010, 2010:2015, and 2015:2020). The results show that prior to the policy shift of 2005, the growth rate for 1999–2005 was 11% p.a. In all subsequent periods, the growth rate exceeded the target rate of 1% p.a., though by varying amounts. The observed settlement growth rates were 5% (2005:2010), 7.4% (2010:2015), and 5.3% (2015:2020). Although the settlements in Assiut grew primarily through expansion and infill, with the latter growing in importance during the last two later periods, outlying growth is also evident. Using four class metrics (number of patches, patch density, mean patch area, and largest patch index) for the eight growth types, all types showed a fluctuated trend between all periods, except for expansion, which always tends to increase. To date, the policy to control human settlement expansion and outlying growth has been unsuccessful.
Publisher: Informa UK Limited
Date: 05-05-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2016
Publisher: Springer Science and Business Media LLC
Date: 24-04-2011
DOI: 10.1038/NMETH.1600
Publisher: MDPI AG
Date: 28-02-2020
DOI: 10.3390/IJGI9030141
Abstract: Peripheral urban sprawl configures new, extensive conurbations that transcend current administrative boundaries. Land use planning, supported by the analysis of future scenarios, is a guide to achieve sustainability in large metropolitan areas. To understand how urban sprawl is consuming natural and agricultural land, this paper analyzes land use changes in the metropolis of Quito, considering a combination of urban planning, natural conservation and risk areas. Using the Dyna-CLUE model we simulate spatial demands for future land uses by 2050, based on two growth scenarios: the trend scenario (unrestricted growth) and the regulated scenario, which considers two parameters—a government proposal for urban expansion areas and laws that protect natural areas. Both scenarios show how urban expansion consumes agricultural and natural areas. This expansion is backed by urban policies which do not sufficiently account for conservation areas nor for risk areas. Therefore, these simulations suggest that planning should follow a more holistic approach that explicitly considers urban growth beyond current administrative limits, in what we refer to as the New Metropolitan Area of Quito.
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.SCITOTENV.2018.09.324
Abstract: Heat exposure has become a global threat to human health and life with increasing temperatures and frequency of extreme heat events. Considering risk as a function of both heat vulnerability and hazard intensity, this study examines whether poor urban dwellers residing in slums are exposed to higher temperature, adding to their vulnerable demographic and health conditions. Instead of being restricted by s ling size of pixels or other land surface zones, this study follows the intrinsic latent patterns of the heat phenomenon to examine the association between small clusters of slums and heat patterns. Remotely sensed land surface temperature (LST) datasets of moderate resolution are employed to derive the morphological features of the temperature patterns in the city of Ahmedabad, India at the local scale. The optimal representations of temperature pattern morphology are learnt automatically from temporally adjacent images without manually choosing model hyper-parameters. The morphological features are then evaluated to identify the local scale temperature pattern at slum locations. Results show that in particular locations with slums are exposed to a locally high temperature. More specifically, larger slums tend to be exposed to a more intense locally high temperature compared to smaller slums. Due to the small size of slums in Ahmedabad, it is hard to conclude whether slums are impacting the locally high temperature, or slums are more likely to be located in poorly built places already with a locally high temperature. This study complements the missing dimension of hazard investigation to heat-related risk analysis of slums. The study developed a workflow of exploring the temperature patterns at the local scale and examination of heat exposure of slums. It extends the conventional city scale urban temperature analysis into local scales and introduces morphological measurements as new parameters to quantify temperature patterns at a more detailed level.
Publisher: African Journals Online (AJOL)
Date: 28-07-2017
DOI: 10.4314/RJ.V1I1S.7D
Publisher: Springer Science and Business Media LLC
Date: 17-03-2023
DOI: 10.1007/S11069-023-05897-Z
Abstract: Deprived settlements, usually referred to as slums, are often located in hazardous areas. However, there have been very few studies to examine this notion. In this study, we leverage the advancements in open geospatial data, earth observation (EO), and machine learning to create a multi-hazard susceptibility index and a transferrable disaster risk approach to be adapted in low- and middle-income country (LMIC) cities, with low-cost methods. Specifically, we identify multi-hazards in Nairobi's selected case study area and construct a susceptibility index. Then, we test the predictability of deprived settlements using the multi-hazard susceptibility index in comparison with EO texture-based methods. Lastly, we survey 100 households in two deprived settlements (typical and atypical slums) in Nairobi and use the survey outcomes to validate the multi-hazard susceptibility index. To test the assumption that deprived areas are dominantly located in areas with higher susceptibility to multiple hazards, we contrast morphologically identified deprived settlements with non-deprived settlements. We find that deprived settlements are generally more exposed to hazards. However, there are variations between central and peripheral settlements. In testing the predictability of deprivation using multi-hazards, the multi-hazard-based model performs better for deprived settlements than for other classes. In contrast, the texture-based model is better at classifying all types of morphological settlements. Lastly, by contrasting the survey outcomes to the household interviews, we conclude that proxies used for the multi-hazard susceptibility index adequately capture the hazards. However, more localized proxies can be used to improve the index performance.
Publisher: Elsevier BV
Date: 2022
Publisher: Informa UK Limited
Date: 25-02-2020
Publisher: Elsevier BV
Date: 04-2015
Publisher: Copernicus GmbH
Date: 06-06-2016
DOI: 10.5194/ISPRSANNALS-III-3-317-2016
Abstract: Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.
Publisher: Elsevier BV
Date: 07-2017
DOI: 10.1016/J.JENVMAN.2017.04.017
Abstract: In this study we demonstrate how to support policy option analysis for a problematic Social-Ecological System (SES) with the help of stakeholder participation. SES sustainability problems 1) are highly complex, 2) may lack reliable data, 3) encompass conflicting interests and 4) may require contradictory management interventions. Our approach uses a structured participatory method combining the Driver-Pressure-State-Impact-Response (DPSIR) model together with Fuzzy Cognitive Mapping (FCM) to capture the complexity of the system and simplify its representation for simulation and policy option analysis. Using this novel mixed-method was useful in dealing with above-mentioned characteristics of the complex SES problems. The method was applied in a case study of water scarcity in Rafsanjan, Iran. FCMs were produced for 60 in idual farmers and 40 in idual researchers and policy makers. Our mixed-method analysis reveals similarities and differences of stakeholder knowledge and problem perception, and simulates the impacts of alternative policy options according to each group's perception. The final result of our case study indicates that farmers in Rafsanjan strongly believe in the impact of economic ersification on reducing water shortage, but they have a low level of trust in the ability of the government to regulate and control water usage, whereas the policy makers and researchers still believe in the role of government control and monitoring policies to deal with water scarcity in Rafsanjan.
Publisher: Elsevier BV
Date: 10-2010
Publisher: MDPI AG
Date: 25-02-2019
DOI: 10.3390/RISKS7010024
Abstract: Risk management is a comparatively new field and there is no core system of risk management in the construction industries of developing countries. In Pakistan, construction is an extremely risk-seeking industry lacking a good reputation for handling risk. However, it is gradually giving it more importance as a result of increased competition and construction activities. For this purpose, a survey-based study has been conducted which aims to investigate the risk management practices used in construction projects in Pakistan. To achieve the objective, data was collected from 22 contractor firms working on 100 erse projects. The analysis indicates that risk management has been implemented at a low level in the local environment. The results also disclose that there is a higher degree of correlation between effective risk management and project success. The findings reveal the importance of risk management techniques, their usage, implication, and the effect of these techniques on the success of construction projects from the contractor’s perspective, thus convincing the key participants of projects about the use of risk management.
Publisher: IEEE
Date: 06-2011
Publisher: Elsevier BV
Date: 12-2003
Publisher: Wiley
Date: 10-01-2020
DOI: 10.1002/EET.1881
Publisher: Elsevier BV
Date: 10-2010
Publisher: MDPI AG
Date: 19-04-2017
DOI: 10.3390/RS9040384
Publisher: Informa UK Limited
Date: 23-12-2018
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 04-2019
Publisher: Springer International Publishing
Date: 2023
Publisher: MDPI AG
Date: 07-2020
DOI: 10.3390/LAND9070212
Abstract: In many cities and urban areas in Africa, land acquisition for urban redevelopment, land readjustment, and resettlement of affected urban residents are currently framed as innovative approaches to eradicating informal settlements, improving the living environments, and supporting the implementation of newly adopted city Master Plans. Nevertheless, it is not yet known how the responses of institutions and affected people shape these processes. Based on research conducted in Kigali, Rwanda, this article discusses affected residents’ responses to land expropriation and resettlement necessary for urban redevelopments. Our findings show that affected informal settlement dwellers voiced their concerns over the deviations from the Expropriation Law, compensation decision-making made behind closed doors, lack of transparency in property valuation, and compensation packages that they perceive to be unfair. Some of the consequences of these concerns are strong feelings of unfairness, exclusion, and marginalisation distrust and increased perceptions of impoverishment risks, all of which fuel contestation and resistance attitudes among the affected landowners. The affected landowners agitate to assert their rights and stake their claims through contestations, community mobilisation, and legal recourse. We conclude that such contestations constitute claimed spaces and interactions in which affected landowners are laying claim to fair processes against the ‘’exceptionality’’ and the “decide-defend” decision-making approaches, while local authorities assert legitimacy of their decisions. Critically, informal households affected by urban redevelopments see opportunities for participation in their resettlement decision-making as fundamental to securing their future.
Publisher: MDPI AG
Date: 10-03-2018
DOI: 10.3390/IJGI7030091
Abstract: Unmanned Aerial Vehicles (UAVs), or drones, have been gaining enormous popularity for many applications including informal settlement upgrading. Although UAVs can be used to efficiently collect highly detailed geospatial information, there are concerns regarding the ethical implications of its usage and the potential misuse of data. The aim of this study is therefore to evaluate the societal impacts of using UAVs for informal settlement mapping through two case studies in Eastern Africa. We discuss how the geospatial information they provide is beneficial from a technical perspective and analyze how the use of UAVs can be aligned with the values of: participation, empowerment, accountability, transparency, and equity. The local concept of privacy is investigated by asking citizens of the informal settlements to identify objects appearing in UAV images which they consider to be sensitive or private. As such, our research is an explicit ex le of how to increase citizen participation in the discussion of geospatial data security and privacy issues over urban areas and provides a framework of strategies illustrating how such issues can be addressed.
Publisher: Wiley
Date: 16-02-2013
Location: Netherlands
No related grants have been discovered for Richard Sliuzas.