The majority of urban inhabitants in low-and middle-income country (LMIC) cities live in deprived urban areas. However, policy efforts and the monitoring of global goals and agendas such as the United Nation's Sustainable Development Goals (SDGs) and UN-Habitat New Urban Agenda are hindered by the unavailability of statistical and spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, and presently, there is a strong focus within the existing literature on household-level (including individual) deprivation and less on area-level deprivation and this is problematic because deprivation at the area and household-level are known to interrelate and result in multiple challenges for individuals and communities. Within this scoping review, we build on existing literature that focuses on household-or area-level deprivation to arrive at a combined understanding of how urban deprivation is defined in relation to LMIC cities. The scoping review of existing literature was used in conjunction with local stakeholder workshops to produce a framework titled "Domains of Deprivation Framework". The Domains of Deprivation Framework conceptualizes urban deprivation at three different scales, including at the household scale, within the area scale and at the area connect scale. It includes nine domains, (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) City Governance (Area Connect scale). The Domains of Deprivation Framework is designed to support diverse urban, health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities from a holistic perspective, combining traditional data sources (e.g., surveys or census data) with new data sources (e.g., Earth Observation data).

El presente del ser humano es urbano. Si la pandemia de la COVID-19 no varía la tendencia actual, el futuro va a serlo en mayor medida. Esto convierte a las ciudades en el principal foco de recepción y emisión de materia y energía a escala global. Debido a esta repercusión, el reto medioambiental al que se enfrenta la sociedad del siglo XXI obliga a centrarse en la ciudad. Puede que transformando la ciudad sea posible avanzar hacia horizontes ambientales más favorables. Pero para convertir a la ciudad en el escenario principal donde afrontar este reto, es necesario transformar el modo de entender y de hacer ciudad. Para ello se debe revisar y comprender la forma en la que la ciudad se ha relacionado con la naturaleza. Este artículo analiza, desde una perspectiva ambiental, el discurso urbano español de las últimas décadas. Permite reconstruir el camino recorrido y descubre algunas directrices sobre cuál debería ser el camino correcto hacia el que deberían dirigirse los planteamientos urbanos futuros. La ciudad va a adquirir paulatinamente un mayor papel en la mejora ambiental del planeta y, en el caso de España, este horizonte se encuentra marcado por la Agenda Urbana Española 2019.

Urbanization processes are manifested by the change in the physical morphology of cities. Gaining knowledge about cities through their morphology is naturally linked to the capability of remote sensing (RS) that can monitor city forms with a synoptic view. Yet, our knowledge of the urban form does not linearly increase with the increase of image data. Thus, the role, challenges and potentials of RS in deriving knowledge about urban morphology are worth investigating. We argue that ongoing efforts of mapping urban elements in RS are only marginally contributing to the understanding of cities in terms of urban morphology. We further reason that magnifying the role of RS depends on a suggested workflow involving steps that are external to RS, mainly including characterizing urban morphology through meaningful measurements of mapped elements, and interpreting the measured physical forms as proxies of the socioeconomic status. To exemplify the major steps, we focus on urban poverty (deprivation), and examine its manifestation through the morphology of buildings. Our findings show that challenges appear as soon as the collection of building information from RS images starts. This is mainly caused by inconsistent, incomplete and inaccurate GIS based representation of buildings on images, as well as low quality predictions, hidden from accuracy metrics. Although the potential of deriving meaningful urban morphological patterns from building maps for explaining socioeconomic patterns still holds, several uncertainties remain unsolved, such as the way urban processes are manifested morphologically and how the morphology is captured with the influence of building map quality. Our main conclusion is that as RS imagebased morphological information propagates and fluctuates along the process of knowledge derivation, causing difficulties in quantifying the exact amount of urban knowledge derived. Nonetheless, useful knowledge could already be obtained even with suboptimal data sources and model performances, which opens the opportunity to facilitate transferable and reproducible urban morphology studies by using widely accessible data despite their suboptimal quality.

Many cities in low- and medium-income countries (LMICs) are facing rapid unplanned growth of built-up areas, while detailed information on these deprived urban areas (DUAs) is lacking. There exist visible differences in housing conditions and urban spaces, and these differences are linked to urban deprivation. However, the appropriate geospatial information for unravelling urban deprivation is typically not available for DUAs in LMICs, constituting an urgent knowledge gap. The objective of this study is to apply deep learning techniques and morphological analysis to identify degrees of deprivation in DUAs. To this end, we first generate a reference dataset of building footprints using a participatory community-based crowd-sourcing approach. Secondly, we adapt a deep learning model based on the U-Net architecture for the semantic segmentation of satellite imagery (WorldView 3) to generate building footprints. Lastly, we compute multi-level morphological features from building footprints for identifying the deprivation variation within DUAs. Our results show that deep learning techniques perform satisfactorily for predicting building footprints in DUAs, yielding an accuracy of F1 score = 0.84 and Jaccard Index = 0.73. The resulting building footprints (predicted buildings) are useful for the computation of morphology metrics at the grid cell level, as, in high-density areas, buildings cannot be detected individually but in clumps. Morphological features capture physical differences of deprivation within DUAs. Four indicators are used to define the morphology in DUAs, i.e., two related to building form (building size and inner irregularity) and two covering the form of open spaces (proximity and directionality). The degree of deprivation can be evaluated from the analysis of morphological features extracted from the predicted buildings, resulting in three categories: high, medium, and low deprivation. The outcome of this study contributes to the advancement of methods for producing up-to-date and disaggregated morphological spatial data on urban DUAs (often referred to as `slums¿) which are essential for understanding the physical dimensions of deprivation, and hence planning targeted interventions accordingly.

El Plan de Accesibilidad de Jerez de los Caballeros se ha planteado como una herramienta de gestión municipal, que tiene como objetivo servir de guía en las intervenciones que se lleven a cabo en vías y edificios públicos, con el fin de garantizar la calidad y la accesibilidad universal de los espacios públicos. El Plan pauta dichas intervenciones, cuantificándolas y describiéndolas de forma innovadora para su posterior puesta en marcha, en un ámbito que se ciñe a la delimitación de la muralla y un periodo de desarrollo previsto de 4 años (2018-2022). Ha sido impulsado por la Junta de Extremadura y el Ayuntamiento de Jerez de los Caballeros, teniendo en consideración una importante participación ciudadana. Tras su aprobación y presentación en enero de 2019, consiguió el premio OTAEX 2019.

In the past two decades, Earth observation (EO) data have been utilized for studying the spatial patterns of urban deprivation. Given the scope of many existing studies, it is still unclear how very-high-resolution EO data can help to improve our understanding of the multidimensionality of deprivation within settlements on a city-wide scale. In this work, we assumed that multiple facets of deprivation are reflected by varying morphological structures within deprived urban areas and can be captured by EO information. We set out by staying on the scale of an entire city, while zooming into each of the deprived areas to investigate deprivation through land cover (LC) variations. To test the generalizability of our workflow, we assembled multiple WorldView-3 datasets (multispectral and shortwave infrared) with varying numbers of bands and image features, allowing us to explore computational efficiency, complexity, and scalability while keeping the model architecture consistent. Our workflow was implemented in the city of Nairobi, Kenya, where more than sixty percent of the city population lives in deprived areas. Our results indicate that detailed LC information that characterizes deprivation can be mapped with an accuracy of over seventy percent by only using RGB-based image features. Including the near-infrared (NIR) band appears to bring significant improvements in the accuracy of all classes. Equally important, we were able to categorize deprived areas into varying profiles manifested through LC variability using a gridded mapping approach. The types of deprivation profiles varied significantly both within and between deprived areas. The results could be informative for practical interventions such as land-use planning policies for urban upgrading programs.

Routine and accurate data on deprivation are needed for urban planning and decision support at various scales (i.e., from community to international). However, analyzing information requirements of diverse users on urban deprivation, we found that data are often not available or inaccessible. To bridge this data gap, Earth Observation (EO) data can support access to frequently updated spatial information. However, a user-centered approach is urgently required for the production of EO-based mapping products. Combining an online survey and several forms of user interactions, we defined five system specifications (derived from user requirements) for designing an open-access spatial information system for deprived urban areas. First, gridded maps represent the optimal spatial granularity to deal with high uncertainties of boundaries of deprived areas and to protect privacy. Second, a high temporal granularity of 1-2 years is important to respond to the high spatial dynamics of urban areas. Third, detailed local-scale information should be part of a city-to-global information system. Fourth, both aspects, community assets and risks, need to be part of an information system, and such data need to be combined with local community-based information. Fifth, in particular, civil society and government users should have fair access to data that bridges the digital barriers. A data ecosystem on urban deprivation meeting these requirements will be able to support community-level action for improving living conditions in deprived areas, local science-based policymaking, and tracking progress towards global targets such as the SDGs.

Some of the great cities on our planet have been proposing their transformation in search of a more humane and sustainable city that allows them to face, unequivocally, the new challenges of society, overcoming the current urban paradigm where private vehicle plays an essential role. To this situation will inevitably be added the consequences that COVID-19 will have in the conception of our society and with it, in our cities. Among the most innovative and interesting proposals present in the urban debate in recent years is the idea of chrono-urbanism and the 15 minutes-city that Anne Hidalgo, current mayor of Paris, included in the program with which she has been re-elected.

The study on the incidence of sectorial reports in preparation of General Plans in Spainis completed with this article. In the previous issue of this magazine, we studied the way in which urban planning legislation of each Autonomous Community regulates the City Councils requests to the Sectorial Administration for the reports on General Plans, the mechanisms that they establish for the coordination of this set of reports, and its integration with those required in the strategic environmental assessment. This second part presents a comparative study about the reports that, both through urban planning and sectorial legislation, are provided in each Community, about the moment when they are requested and about the determining, binding or merely mandatory nature of the different reports. The analysis of the way in which this aspect, and its impact on the elaboration and procedure of planning is regulated in each Community, allows to identify a range of measures that try to solve the inconveniences that the sectorial vision of the different reports can present and at the same time that seek to facilitate their integration into the General Plan while remaining comprehensive with the tasks of planning.

The aplication of the urban theory in the city of Huesca and the change of the urban design movement from the 70s to 80s.

Starting in 1945, Pedro Bidagor, the National Chief of Urban Planning in Spain, attempted to replicate the British regional urban model based on Abercrombie's proposals of the County of London Plan and the Greater London Plan. The Greater Valencia Administrative Corporation, with its supramunicipal approach, was the principal representative of this urbanistic transposition. This article analyses the transmission of British planning ideas and practices in the years following the Spanish post-war period, and the important role that the architect Pedro Muguruza - key figure in early Francoism - played in it. The study also demonstrates the influence that the contemporary British urban models based on neighbourhood units had for the satellite town centres projected in Valencia (Burjasot and Manises, 1952).