Jorge Eduardo Patiño Quinchía

We analyze the effects of greenspace exposure on academic performance, considering the differences between exposure at school and at home. We use granular administrative data from students in Medellín, Colombia, a developing-country city, to examine the relationship between greenspace exposure and academic achievement. The results show that exposure to green spaces has positive and significant effects on academic achievement when proximity and localization are greater around students’ residences than at school. These findings underscore the importance of integrating urban greenspaces into educational policy and urban planning to promote academic success.

The next few decades will bring rapid urbanization and climatic stress to African cities. Green spaces can increase the resilience of cities against heat waves, floods, landslides, and even coastal erosion, as well as improve sustainability by improving air quality, protecting biodiversity, and absorbing carbon. However, quantitative data on urban form, the availability of green spaces, and air pollution are very scarce and difficult to access for African cities. In this work, we use open geospatial data to quantitatively analyze the relationships between urban form, the presence of green spaces, and air quality. The results of this analysis indicate that the presence of green spaces is related to better air quality, but that they must be accompanied by other policies for their presence to be truly effective. Las próximas décadas serán de rápida urbanización y estrés climático en las ciudades africanas. Los espacios verdes pueden aumentar la resiliencia de las ciudades frente a las olas de calor, las inundaciones, los deslizamientos de tierra e incluso la erosión costera, además de mejorar la sostenibilidad al reparar la calidad del aire, proteger la biodiversidad y absorber carbono. Sin embargo, datos cuantitativos sobre la forma urbana, la disponibilidad de espacios verdes y la contaminación del aire son muy escasos y de difícil acceso para ciudades en África. En este trabajo usamos datos geoespaciales abiertos para analizar cuantitativamente las relaciones entre la forma urbana, la presencia de espacios verdes y la calidad del aire. Los resultados del análisis indican que la presencia de espacios verdes se relaciona con mejor calidad del aire, pero que deben estar acompañados de otras políticas para que su presencia sea realmente efectiva. As próximas décadas serão de rápida urbanização e estresse climático nas cidades africanas. Os espaços verdes podem aumentar a resiliência das cidades contra ondas de calor, inundações, deslizamentos de terra e até erosão costeira, além de melhorar a sustentabilidade ao melhorar a qualidade do ar, proteger a biodiversidade e sequestrar carbono. No entanto, os dados quantitativos sobre a forma urbana, a disponibilidade de espaços verdes e a poluição do ar são muito escassos e de difícil acesso para as cidades africanas. Neste trabalho utilizamos dados geoespaciais abertos para analisar quantitativamente as relações entre a forma urbana, a presença de espaços verdes e a qualidade do ar. Os resultados desta análise indicam que a presença de espaços verdes está relacionada com uma melhor qualidade do ar, mas que devem ser acompanhadas de outras políticas para que a sua presença seja verdadeiramente eficaz.

A large proportion of Africa’s infrastructure is yet to be built. Where and how these new buildings are constructed matters since today’s decisions will last for decades. The resulting morphology of cities has lasting implications for a city’s energy needs. Estimating and projecting these needs has always been challenging in Africa due to the lack of data. Yet, given the sweeping urbanization expected in Africa over the next three decades, this obstacle must be overcome to guide cities toward a trajectory of sustainability and resilience. Based on the location and surface of nearly 200 million buildings on the continent, we estimate the interbuilding distance of almost six thousand cities. Buildings’ footprint data enable the construction of urban form indicators to compare African cities’ elongation, sprawl, and emptiness. We establish the BASE model, where the mean distance between buildings is a functional relation to the number of Buildings and their average Area, as well as the Sprawl and the Elongation of its spatial arrangement. The mean distance between structures in cities—our proxy for its energy demands related to mobility—grows faster than the square root of its population, resulting from the combined impact of a sublinear growth in the number of buildings and a sublinear increase in building size and sprawl. We estimate that when a city doubles its population, it triples its energy demand from transport.

High-resolution population mapping is of high relevance for developing and implementing tailored actions in several fields: From decision making in crisis management to urban planning. Earth Observation has considerably contributed to the development of methods for disaggregating population figures with higher resolution data into fine-grained population maps. However, which method is most suitable on the basis of the available data, and how the spatial units and accuracy metrics affect the validation process is not fully known. We aim to provide recommendations to researches that attempt to produce high-resolution population maps using remote sensing and geospatial information in heterogeneous urban landscapes. For this purpose, we performed a comprehensive experimental research on population disaggregation methods with thirty-six different scenarios. We combined five different top-down methods (from basic to complex, i.e., binary and categorical dasymetric, statistical, and binary and categorical hybrid approaches) on different subsets of data with diverse resolutions and degrees of availability (poor, average and rich). Then, the resulting population maps were systematically validated with a two-fold approach using six accuracy metrics. We found that when only using remotely sensed data the combination of statistical and dasymetric methods provide better results, while highly-resolved data require simpler methods. Besides, the use of at least three relative accuracy metrics is highly encouraged since the validation depends on level and method. We also analysed the behaviour of relative errors and how they are affected by the heterogeneity of the urban landscape. We hope that our recommendations save additional efforts and time in future population mapping.

El cambio climático y el calentamiento global son provocados principalmente por las actividades antrópicas. Por esta razón, conocer las líneas de investigación que relacionen Series de Tiempo de Temperatura Superficial e Índices de Vegetación es de suma importancia, dada la amplitud de las diferentes áreas científicas abiertas sobre el calentamiento global. Se presenta a la comunidad académica, por tanto, el resultado de la presente clasificación, la cual divide los estudios en dos áreas principales representativas en el estudio del cambio climático: (1) Modelado y Análisis de Geodatos y (2) Teledetección. De este último se derivan dos tipos, unos construidos con Análisis de Regresión Lineal (RL) y otros con Análisis de Regresión No Lineal (RNL). En el Modelado y Análisis de Geodatos, los Modelos Climáticos Globales (GCM) no son la herramienta adecuada para estos análisis debido a su gruesa resolución espacial. Esto implica el desarrollo de modelos híbridos con teledetección, que están también limitados por las diferencias de resolución. Por el contrario, la teledetección es la herramienta de mayor difusión para este tipo de estudios. Finalmente, se abre una prometedora ventana para el desarrollo en las series de tiempo con análisis de Regresión No Lineal.

The availability of green spaces is an important issue for urban populations worldwide, given the benefits that the green spaces provide for health, well-being, and quality of life. But urban green spaces are not always distributed equally for different population groups within cities. Latin America is the second most urbanized region of the world, but there are few published studies analysing the green space availability for different urban population groups, and less so analysing the long-term trends. This work presents an analysis of long-term availability of urban green spaces by different socioeconomic status population groups in Medellin city, Colombia, using open geospatial data and open software tools. The results indicate that disparities between different groups have been decreasing in the last years, but there are still efforts to do. Showing this kind of analysis based on open data and tools is essential as it opens the possibility for replicating it in other cities with scarce budgets.