Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a 'black-box' solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise into deep learning, and use it as an implicit general model to tackle unprecedented large-scale influential challenges, such as climate change and urbanization.Comment: Accepted for publication IEEE Geoscience and Remote Sensing Magazin

Weak nodes detection in urban transport systems: Planning for resilience in Singapore

The availability of massive data-sets describing human mobility offers the possibility to design simulation tools to monitor and improve the resilience of transport systems in response to traumatic events such as natural and man-made disasters (e.g. floods terroristic attacks, etc...). In this perspective, we propose ACHILLES, an application to model people's movements in a given transport system mode through a multiplex network representation based on mobility data. ACHILLES is a web-based application which provides an easy-to-use interface to explore the mobility fluxes and the connectivity of every urban zone in a city, as well as to visualize changes in the transport system resulting from the addition or removal of transport modes, urban zones, and single stops. Notably, our application allows the user to assess the overall resilience of the transport network by identifying its weakest node, i.e. Urban Achilles Heel, with reference to the ancient Greek mythology. To demonstrate the impact of ACHILLES for humanitarian aid we consider its application to a real-world scenario by exploring human mobility in Singapore in response to flood prevention.Comment: 9 pages, 6 figures, IEEE Data Science and Advanced Analytic

Urban heritage endangerment at the interface of future cities and past heritage: A spatial vulnerability assessment

Uncontrolled urban growth has been an increasing concern in many regions throughout the world. Generated by a natural tendency of population growth in relation to unsustainable land use, city sprawl has led to complex spatial developments that are creating both benefits to, and challenges for decision makers. A major problem inherent in the uncontrolled growth of cities is the threat to the fragile cultural and ecological heritage, which may escalate to permanent and irreversible damage as a result of factors such as environmental depletion and landscape decay. Using modern geosciences and spatial information technologies as predictive tools to analyse and forecast urban growth, a regional spatial decision system may be useful in order to provide seemly and timely information on the risk of overburdening the carrying capacity regarding the historico-cultural heritage at local and regional levels.The present paper develops a predictive toolkit for urban heritage in relation to urban cultural endangerment. This common problem is shared through many regions of the world and is increasingly jeopardizing fragile archaeological landscape due to urban pressure. In this sense, and to forecast an example of this common pressure, the Algarve is exemplified as a laboratory for testing this novel methodology, relying on a combined analysis of urban growth potential and threats to the abundant presence of archaeological heritage in the area. Our appro ach supports the paradigm of city growth in the context of a common agenda emerging from the Valetta Treaty, in which preserving the archaeological heritage is recognized as a key element for sustainable development. The study provides novel empirical results from the above mentioned modelling approach, with important lessons for the developing world. This paper proposes as such, an integrative spatial analysis methodology on the issue of historico-cultural endangerment, which is a new approach to comparative spatial analysis for decision making on urban heritage endangerment at the regional scale. Later, the discussion extends to a more conceptual level of urban planning by considering the questions: Is urban sprawl influencing the way we perceive cities? If so, are there positive advantages in the paradigm of urban growth and urban sprawl which might help us to protect past heritage while ensuring sustainable and modern cities? © 2011 Elsevier Ltd

Sustainable Spatial Planning based on Ecosystem Services, Green Infrastructure and Nature-Based Solutions

Theoretical and methodological contributions as well as critical discussions on policy implementation characterize this Special Issue, with special reference to the following themes and research questions: 1) Integration of ecosystem services within spatial plans and strategic environmental assessment: “What function do ecosystem services play, or could play, within plan-making processes and strategic environmental assessments?”; “What are the most important challenges in putting integration into practice, and/or the most significant obstacles to achieving integration?”; and “What roles do scientific and technical expertise vs. community values and local knowledge play in integrating ecosystem services within spatial plans and environmental assessments?”; 2) Consideration and use of green infrastructure within spatial plans: “What function do green infrastructure play within plan-making processes?”; “What kinds of spatial plans are most suited for, or most effective in, designing and implementing green infrastructure?”; and “Does scale (local, regional, etc.) make a difference in the way green infrastructure are implemented within spatial plans?”; 3) Relationship between nature-based solutions and spatial plans: “Since nature-based solutions are increasingly promoted at the very strategic level, i.e., that of broad policies, and implemented at the very detailed level, i.e., that of projects, what is the role of nature-based solutions within spatial plans?” and “What tools are at planners’ disposal to effectively integrate nature-based solutions in planning processes and promote their use, especially in urban contexts?”

Towards an integrated vulnerability-based approach for evaluating, managing and mitigating earthquake risk in urban areas

Tese de doutoramento em Civil EngineeringSismos de grande intensidade, como aqueles que ocorreram na Turquía-Síria (2023) ou México (2017) deviam chamar a atenção para o projeto e implementação de ações proativas que conduzam à identificação de bens vulneráveis. A presente tese propõe um fluxo de trabalho relativamente simples para efetuar avaliações da vulnerabilidade sísmica à escala urbana mediante ferramentas digitais. Um modelo de vulnerabilidade baseado em parâmetros é adotado devido à afinidade que possui com o Catálogo Nacional de Monumentos Históricos mexicano. Uma primeira implementação do método (a grande escala) foi efetuada na cidade histórica de Atlixco (Puebla, México), demonstrando a sua aplicabilidade e algumas limitações, o que permitiu o desenvolvimento de uma estratégia para quantificar e considerar as incertezas epistémicas encontradas nos processos de aquisição de dados. Devido ao volume de dados tratado, foi preciso desenvolver meios robustos para obter, armazenar e gerir informações. O uso de Sistemas de Informação Geográfica, com programas à medida baseados em linguagem Python e a distribuição de ficheiros na ”nuvem”, facilitou a criação de bases de dados de escala urbana para facilitar a aquisição de dados em campo, os cálculos de vulnerabilidade e dano e, finalmente, a representação dos resultados. Este desenvolvimento foi a base para um segundo conjunto de trabalhos em municípios do estado de Morelos (México). A caracterização da vulnerabilidade sísmica de mais de 160 construções permitiu a avaliação da representatividade do método paramétrico pela comparação entre os níveis de dano teórico e os danos observados depois do terramoto de Puebla-Morelos (2017). Esta comparação foi a base para efetuar processos de calibração e ajuste assistidos por algoritmos de aprendizagem de máquina (Machine Learning), fornecendo bases para o desenvolvimento de modelos de vulnerabilidade à medida (mediante o uso de Inteligência Artificial), apoiados nas evidências de eventos sísmicos prévios.Strong seismic events like the ones of Türkiye-Syria (2023) or Mexico (2017) should guide our attention to the design and implementation of proactive actions aimed to identify vulnerable assets. This work is aimed to propose a suitable and easy-to-implement workflow for performing large-scale seismic vulnerability assessments in historic environments by means of digital tools. A vulnerability-oriented model based on parameters is adopted given its affinity with the Mexican Catalogue of Historical Monuments. A first large-scale implementation of this method in the historical city of Atlixco (Puebla, Mexico) demonstrated its suitability and some limitations, which lead to develop a strategy for quantifying and involving the epistemic uncertainties found during the data acquisition process. Given the volume of data that these analyses involve, it was necessary to develop robust data acquisition, storing and management strategies. The use of Geographical Information System environments together with customised Python-based programs and cloud-based distribution permitted to assemble urban databases for facilitating field data acquisition, performing vulnerability and damage calculations, and representing outcomes. This development was the base for performing a second large-scale assessment in selected municipalities of the state of Morelos (Mexico). The characterisation of the seismic vulnerability of more than 160 buildings permitted to assess the representativeness of the parametric vulnerability approach by comparing the theoretical damage estimations against the damages observed after the Puebla-Morelos 2017 Earthquakes. Such comparison is the base for performing a Machine Learning assisted process of calibration and adjustment, representing a feasible strategy for calibrating these vulnerability models by using Machine-Learning algorithms and the empirical evidence of damage in post-seismic scenarios.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), reference UIDB/04029/2020. This research had financial support provided by the Portuguese Foundation of Science and Technology (FCT) through the Analysis and Mitigation of Risks in Infrastructures (InfraRisk) program under the PhD grant PD/BD/150385/2019

Monitoring and modeling urban sprinkling: a new perspective of land take

According to the studies done until now on the recent urban transformation dynamics, namely urban sprinkling, this thesis aims to investigate the phenomenon from different points of view to bring out its unsustainable character. The urban dispersion phenomena, specific characteristic of low-density territories, will be examined through the sprinkling index by including new components in addition to the traditional settlement system components. It allows to evaluate the shape of the anthropic settlements and the distance between them which often results in fragmentation of the urban settlements which in turn generate landscape fragmentation. Nowadays, both in the proximity of large cities and in more external areas such as rural areas, there are often evidences of strong fragmentation of the anthropic settlements in which, even if the amount of occupied surface (land take) may not seem worrying, its configuration determines a general decrease in ecological connectivity, landscape quality and general degradation of soil functions. The general hypothesis is that fragmentation (of urban, landscape and habitat) can become an indicator of land take. In fact, it is not enough to consider only the loss of natural or agricultural areas, but also the distribution of buildings in the landscape matrix, i.e., its spatial component. An emblematic case is that of Basilicata region whose dynamics of transformation from the 50s to the present day will be investigated in this thesis. According to the latest report of the Italian Institute for Environmental Protection and Research (ISPRA 2020), the Basilicata region has only 3.15% of land consumption compared to the entire regional surface. This indicator is in contrast with the shape of the anthropic settlements which results fragmented and dispersed. It is essential that the effects of fragmentation as well as ecosystem disaggregation take on a "measurable" character, joining the list of indicators of urban and territorial quality such as land take and land consumption that European Union addresses to national communities currently consider essential and decisive to highlighting the efficiency/inefficiency of environmental and landscape management. It is crucial to understand and investigate what have been and will be in the future the most influential drivers on these dynamics that contribute intrinsically to land consumption and to define the addresses or the thresholds to contain this pulverized and disordered dissemination of anthropic settlements