248 research outputs found

    Cityscape, poverty and crime: a quantitative assessment using VHR imagery

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    [EN] The first part of this work reviews the potential applications of satellite remote sensing to regional science research in urban settings. The availability of satellite remote sensing data has increased significantly in the last two decades. The increasing spatial resolution of commercial satellite imagery has influenced the emergence of new research and applications of regional science in urban settlements because it is now possible to identify individual objects of the urban fabric. The most common applications found in the literature are the detection of urban deprivation hot spots, quality of life index assessment, urban growth analysis, house value estimation, urban population estimation, urban social vulnerability assessment, and the variability of intra-urban crime rates. The satellite remote sensing imagery used in these applications has medium, high or very high spatial resolution (Landsat MSS, Landsat TM and ETM+, SPOT, ASTER, IRS, Ikonos and QuickBird). Consistent relationships between socio-economic variables derived from censuses and field surveys and proxy variables of vegetation coverage measured from satellite remote sensing data have been found in several cities in the US. Different approaches and techniques have been applied successfully around the world, but local research is always needed to account for the unique elements of each place. Spectral mixture analysis, object-oriented classifications and image texture measures are some of the techniques of image processing that have been implemented with good results. This work contributes empirical evidence about the usefulness of remote sensing imagery to quantify the degree of poverty at the intra-urban scale. This concept is based on two premises: first, that the physical appearance of an urban settlement is a reflection of the society; and second, that the people who reside in urban areas with similar physical housing conditions have similar social and demo- graphic characteristics. We evaluate the potential of the image-derived urban fabric descriptors to explain a measure of poverty known as the Slum Index. We found that these variables explain up to 59% of the variability in the Slum Index. Similar approaches could be used to lower the cost of socioeconomic surveys by developing an econometric model from a sample and applying that model to the rest of the city and to perform intercensal or intersurvey estimates of intra-urban Slum Index maps. The last part of this work analyzes the relation between the urban layout and crime. The link between place and crime is at the base of social ecology theories of crime that focus in the relationship of the characteristics of geographical areas and crime rates. The broken windows theory states that visible cues of physical and social disorder in a neighborhood can lead to an increase in more serious crime. Based on the premise that a settlement's appearance is a reflection of the society, we ask whether a neighbor- hood's design has a quantifiable imprint when seen from space using urban fabric descriptors computed from VHR imagery. The percentage of impervious surfaces other than clay roofs, the fraction of clay roofs to impervious surfaces, two structure descriptors related to the homogeneity of the urban layout, and the uniformity texture descriptor were all statistically significant. Areas with higher homicide rates tended to have higher local variation and less general homogeneity; that is, the urban layouts were more crowded and cluttered, with small dwellings with different roofing materials located in close proximity to one another, and these regions often lacked other homogeneous surfaces such as open green spaces, wide roads, or large facilities. These results seem to be in agreement with the broken windows theory and CPTED in the sense that more heterogeneous and disordered urban layouts are associated with higher homicide rates.[ES] La primera parte aporta una revisión de las aplicaciones de la teledetección satelital en la investigación de ciencia regional en entornos urbanos. La disponibilidad de imágenes satelitales se ha incrementado significativamente en las dos últimas décadas, al tiempo que la resolución espacial ha venido aumentando, lo que ha influenciado el surgimiento de investigaciones y aplicaciones de ciencia regional en zonas urbanas. Las aplicaciones más comunes son la detección de hot spots de pobreza urbana, la evaluación de índices de calidad de vida, el análisis del crecimiento urbano, la estimación de valores de vivienda, la estimación de población urbana, la evaluación de la vulnerabilidad social y las variaciones intra-urbanas en tasas de crimen. Las imágenes satelitales usadas tienen resolución espacial media, alta o muy alta (Landsat MSS, Landsat TM y ETM+, SPOT, ASTER, IRS, Ikonos y Quickbird). Se han encontrado relaciones consistentes entre variables socio-económicas obtenidas de censos y encuestas y variables de la cobertura de vegetación en varias ciudades de Estados Unidos. Algunas de las técnicas que se han implementado y obtenido buenos resultados son el análisis de mezcla espectral, las clasificaciones orientadas a objetos y las medidas de textura de la imagen. Se aporta evidencia empírica acerca de la utilidad de las imágenes satelitales para cuantificar el grado de pobreza a escala intra-urbana. Se basa en dos premisas: primero, que la apariencia física de un asentamiento urbano es un reflejo de la sociedad que lo habita; y segundo, que la población de áreas urbanas con condiciones físicas de vivienda parecidas tiene características sociales y demográficas similares. Evaluamos el potencial de los descriptores del tejido urbano extraídos de la imagen para explicar una medida de pobreza conocida como el índice Slum. Encontramos que esas variables explican hasta un 59% de la variabilidad en el índice Slum. Aproximaciones similares a esta podrían usarse para disminuir el costo de encuestas socioeconómicas por medio del desarrollo de un modelo econométrico usando una muestra y luego aplicando el modelo al resto de la ciudad, y para elaborar estimaciones inter-censales o inter-encuestas de mapas intra-urbanos del índice Slum. La última parte analiza la relación entre el trazado urbano y crimen. El enlace entre el lugar y el crimen está en la base de las teorías socio-ecológicas de crimen que se enfocan en la relación de las características de las áreas geográficas y las tasas de crimen. La teoría de las ventanas rotas afirma que las evidencias visibles de desorden físico y social en un barrio pueden llevar al incremento de crímenes más serios. Con base en la premisa de que la apariencia de un asentamiento es un reflejo de la sociedad, nos preguntamos si el diseño del barrio tiene un impacto cuantificable cuando se observa desde el espacio usando descriptores del tejido urbano obtenidos de imágenes de muy alta resolución. El porcentaje de superficies impermeables diferentes a los techos de arcilla, la fracción de techos de arcilla sobre las superficies impermeables, dos variables de estructura relacionadas con la homogeneidad del trazado urbano y la variable de textura uniformidad resultaron estadísticamente significativas. Las áreas con tasas de homicidio más altas tienden a tener mayor variación local y menor homogeneidad general; esto es, los trazados urbanos son más desordenados y hacinados, con pequeñas viviendas que tienen materiales diferentes en sus techos localizadas muy cerca unas de otras, y estas áreas carecen a menudo de otras superficies homogéneas tales como espacios verdes abiertos, vías amplias y grandes construcciones industriales o institucionales. Estos resultados parecen estar en acuerdo con la teoría de las ventanas rotas y CPTED en el sentido de que los trazados urbanos más desordenados y heterogéneos están asociados con tasas de homicid[CA] La primera part aporta una revisió de les potencials aplicacions de la teledetecció espacial a la investigació en ciència regional en entorns urbans. La disponibilitat de dades de percepció remota des de satèl·lits s'ha incrementat significativament a les dues últimes dècades. La resolució espacial de les imatges de satèl·lit comercials també han anat augmentant i això, ha influït en l'aparició de investigacions i aplicacions a la ciència regional en assentaments urbans. Les aplicacions més comunes trobades a la literatura són la detecció de punts calents de pobresa urbana, l'avaluació dels índex de qualitat de vida, les anàlisis de creixement urbà, l'avaluació de la vulnerabilitat social i les variacions intraurbanes de les taxes de crims. Les imatges de satèl·lit emprades tenen resolució espacial mitjana, alta o molt alta (Landsat MSS, Landsat TM i ETM+, SPOT, ASTER, IRS, Ikonos y Quickbird). S'han torbat relacions consistents entre variables socioeconòmiques obtingudes de censos i enquestes i variables de la cobertura de vegetació en varies ciutats del Estats Units. Algunes de les tècniques que s'han implementat i han donat bons resultats són l'anàlisi de mescla espectral, les classificacions orientades a objecte i les mesures de textura de les imatges. Es aporta evidència empírica sobre la utilitat de les imatges de satèl·lit per quantificar el grau de pobresa a escala intraurbana. Es bassa en dues premisses: primer, que l'aparença física d'un assentament urbà n'és un reflex de la societat que l'habita; i segon, que les persones que resideixen en àrees urbanes amb condicions físiques de vivenda paregudes tenen també característiques socials i demogràfiques similars. Avaluem el potencial dels descriptors del teixit urbà extrets de la imatge per explicar una mesura de pobresa coneguda com index Slum. Trobem que aquestes variables expliquen fins un 59% de la variabilitat de l'índex Slum. Aproximacions semblants a aquesta es podrien emprar per a disminuir el cost de les enquestes socioeconòmiques mitjançant el desenvolupament d'un model economètric utilitzant una mostra i després aplicant el model a la resta de la ciutat, i per elaborar estimacions inter-censals o inter-enquestes de mapes intraurbans de l'índex Slum. La darrera part analitza la relació entre el traçat urbà i el crim. L'enllaç entre el lloc i el crim està a la base de les teories socio-ecològiques del crim que es centren en la relació de les característiques de les àrees geogràfiques i les taxes de crims. La teoria de les finestres trencades afirma que les evidències visibles de desordre físic i social d'un barri pot portar a l'augment de crims més greus. Basant-se en la premissa de que l'aparença d'un assentament n'és el reflex de la societat, ens hi preguntem si el disseny del barri té un impacte quantificable quan s'observa des de el espai, utilitzant descriptors del teixit urbà obtinguts de imatges de molt alta resolució. Han resultat estadísticament significatius el percentatge de superfícies impermeables diferents a les teulades de argila, la fracció de teulades d'argila sobre les superfícies impermeables, dues variables d'estructura relacionades amb la homogeneïtat del traçat urbà i la variable de textura de uniformitat. Les àrees amb taxes d'homicidi més altes tendeixen a presentar una major variació local i una menor homogeneïtat general; és a dir, el traçats urbans són més desordenats i amuntonats, amb petites vivendes que tenen materials diferents a les seues teulades localitzades molt prop unes d'altres, i aquestes àrees manquen sovint d'altres superfícies homogènies, com ara espais verds oberts, vies amplies i grans construccions industrials o institucionals. Aquests resultats pareixen estar-hi d'acord amb la teoria de les finestres trencades i CPTED en el sentit de que els traçats urbans més desordenats i heterogenis estan associats amb taxes d'homicides mPatiño Quinchía, JE. (2015). Cityscape, poverty and crime: a quantitative assessment using VHR imagery [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59453TESI

    A methodology to produce geographical information for land planning using very-high resolution images

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    Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

    Global spatial and temporal analysis of human settlements from Optical Earth Observation: Concepts, procedures, and preliminary results

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    This report provides an overview on the concepts, processing procedures and examples used to quantify changes in built-up land from optical satellite imagery. This is part of the larger work of the Global Human Settlement (GHS) team from the Joint Research Centre (JRC) that aims to measure the spatial extent of global human settlements, to monitor its changes over time and characterize the morphology of settlements. This built-up change analysis addresses the quantification of urbanization including some socio-economic and physical processes associated with urbanization. This includes the quantification of the building stock for modeling physical exposure in disaster risk modeling, as background layer for emergency response when a disaster unfolds and as background building stock layer for normalizing physical loss data. Based on the application of three of the most used change detection methods, Principal Component Analysis, Image Differencing Comparison, and Post-Classification Comparison, we present and discuss preliminary results, and try to identify future research directions for developing an appropriate approach for GHSL result images. The case studies were carried on Alger and Dublin city areas.JRC.G.2-Global security and crisis managemen

    Rapid road inventory using high resolution satellite imagery

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    Master'sMASTER OF ENGINEERIN

    An integrative approach using remote sensing and social analysis to identify different settlement types and the specific living conditions of its inhabitants

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    Someday in 2007, the world population reached a historical landmark: for the first time in human history, more than half of the world´s population was urban. A stagnation of this urbanization process is not in sight, so that by 2050, already 70 percent of humankind is projected to live in urban settlements. Over the last few decades, enormous migrations from rural hinterlands to steadily growing cities could be witnessed coming along with a dramatic growth of the world’s urban population. The speed and the scale of this growth, particularly in the so called less developed regions, are posing tremendous challenges to the countries concerned as well as to the world community. Within mega cities the strongest trends and the most extreme dimensions of the urbanization process can be observed. Their rapid growth results in uncontrolled processes of fragmentation which is often associated with pronounced poverty, social inequality, socio-spatial and political fragmentation, environmental degradation as well as population demands that outstrip environmental service capacity. For the majority of the mega cities a tremendous increase of informal structures and processes has to be observed. Consequentially informal settlements are growing, which represent those characteristic municipal areas being subject to particularly high population density, dynamics as well as marginalization. They have quickly become the most visible expression of urban poverty in developing world cities. Due to the extreme dynamics, the high complexity and huge spatial dimension of mega cities, urban administrations often only have an obsolete or not even existing data basis available to be at all informed about developments, trends and dimensions of urban growth and change. The knowledge about the living conditions of the residents is correspondingly very limited, incomplete and not up to date. Traditional methods such as statistical and regional analyses or fieldwork are no longer capable to capture such urban process. New data sources and monitoring methodologies are required in order to provide an up to date information basis as well as planning strate¬gies to enable sustainable developments and to simplify planning processes in complex urban structures. This research shall seize the described problem and aims to make a contribution to the requirements of monitoring fast developing mega cities. Against this background a methodology is developed to compensate the lack of socio-economic data and to deduce meaningful information on the living conditions of the inhabitants of mega cities. Neither social science methods alone nor the exclusive analysis of remote sensing data can solve the problem of the poor quality and outdated data base. Conventional social science methods cannot cope with the enormous developments and the tremendous growth as they are too labor-, as well as too time- and too cost-intensive. On the other hand, the physical discipline of remote sensing does not allow for direct conclusions on social parameters out of remote sensing images. The prime objective of this research is therefore the development of an integrative approach − bridging remote sensing and social analysis – in order to derive useful information about the living conditions in this specific case of the mega city Delhi and its inhabitants. Hence, this work is established in the overlapping range of the research topics remote sensing, urban areas and social science. Delhi, as India’s fast growing capital, meanwhile with almost 25 million residents the second largest city of the world, represents a prime example of a mega city. Since the second half of the 20th century, Delhi has been transformed from a modest town with mainly administrative and trade-related functions to a complex metropolis with a steep socio-economic gradient. The quality and amount of administrative and socio-economic data are poor and the knowledge about the circumstances of Delhi’s residents is correspondingly insufficient and outdated. Delhi represents therefore a perfectly suited study area for this research. In order to gather information about the living conditions within the different settlement types a methodology was developed and conducted to analyze the urban environment of the mega city Delhi. To identify different settlement types within the urban area, regarding the complex and heterogeneous appearance of the Delhi area, a semi-automated, object-oriented classification approach, based on segmentation derived image objects, was implemented. As the complete conceptual framework of this research, the classification methodology was developed based on a smaller representative training area at first and applied to larger test sites within Delhi afterwards. The object-oriented classification of VHR satellite imagery of the QuickBird sensor allowed for the identification of five different urban land cover classes within the municipal area of Delhi. In the focus of the image analysis is yet the identification of different settlement types and amongst these of informal settlements in particular. The results presented within this study demonstrate, that, based on density classes, the developed methodology is suitable to identify different settlement types and to detect informal settlements which are mega urban risk areas and thus potential residential zones of vulnerable population groups. The remote sensing derived land cover maps form the foundation for the integrative analysis concept and deliver there¬fore the general basis for the derivation of social attributes out of remote sensing data. For this purpose settlement characteristics (e.g., area of the settlement, average building size, and number of houses) are estimated from the classified QuickBird data and used to derive spatial information about the population distribution. In a next step, the derived information is combined with in-situ information on socio-economic conditions (e.g., family size, mean water consumption per capita/family) extracted from georeferenced questionnaires conducted during two field trips in Delhi. This combined data is used to characterize a given settlement type in terms of specific population and water related variables (e.g., population density, total water consumption). With this integrative methodology a catalogue can be compiled, comprising the living conditions of Delhi’s inhabitants living in specific settlement structures – and this in a quick, large-scaled, cost effective, by random or regularly repeatable way with a relatively small required data basis.The combined application of remotely sensed imagery and socio-economic data allows for the mapping, capturing and characterizing the socio-economic structures and dynamics within the mega city of Delhi, as well as it establishes a basis for the monitoring of the mega city of Delhi or certain areas within the city respectively by remote sensing. The opportunity to capture the condition of a mega city and to monitor its development in general enables the persons in charge to identify unbeneficial trends and to intervene accordingly from an urban planning perspective and to countersteer against a non-adequate supply of the inhabitants of different urban districts, primarily of those of informal settlements. This study is understood to be a first step to the development of methods which will help to identify and understand the different forms, actors and processes of urbanization in mega cities. It could support a more proactive and sustainable urban planning and land management – which in turn will increase the importance of urban remote sensing techniques. In this regard, the most obvious and direct beneficiaries are on the one hand the governmental agencies and urban planners and on the other hand, and which is possibly the most important goal, the inhabitants of the affected areas, whose living conditions can be monitored and improved as required. Only if the urban monitoring is quickly, inexpensively and easily available, it will be accepted and applied by the authorities, which in turn enables for the poorest to get the support they need. All in all, the listed benefits are very convincing and corroborate the combined use of remotely sensed and socio-economic data in mega city research

    Mapping and modeling the urban landscape in Bangkok, Thailand: physical-spectral-spatial relations of population–environmental interactions

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    This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants’ settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants’ spatial clustering in urban space is associated with the source village and a number of sociodemographic variables. In addition, the migrants’ neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent
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