In the midst of a climate crisis like the one the world is facing right now, it is essential to try to find new tools that allow better decision-making both to mitigate climate change and to adapt to it. To this day, data science has yet to develop the necessary knowledge to tackle climate change, even though there are large databases with climate data available. With the technological revolution that society is experiencing, and the large amounts of data generated every moment, it is inevitable to think that the necessary responses will inevitably require greater collection and use of data, along with the tools, knowledge, and infrastructure needed. Cities, as great centers of knowledge, population density and innovation, must take the lead to promote data science and Big Data and incorporate them into building urban resilience. For the combination to be productive, both concepts must also be understood in a holistic and complemented way, resilience and Big Data. Both dynamic and relatively new concepts must find the point of union and scientists investigating adaptation must reach out to data scientists to find the skills necessary to clean the data as well as organize, analyze and manage it. Pairing Big Data insights with a well-established and localized urban resilience context can reveal deeper understanding of climate vulnerability, leading to the adaptation of better early-warning systems, more rigorous monitoring and evaluation and ultimately more robust adaptation response based on more accurately defined problems. This study analyzes both concepts, fully understanding what Big Data is, and studying urban climate resilience in a specific setting: the city of Madrid. In this way, the results of this study allow the clear identification of the varied applications of Big Data for a given environment of climate change threats, such as heatwaves, loss of biodiversity and flooding, describing their main data sources, methods, and standing criteria. In addition, the major characteristics of the Big Data use process are explained in the decision-making mechanism, describing the barriers and key drivers of data access, assessment, and application. Such considerations include the correct integration of the different stakeholders in the data collection, cleaning and application processes, ethical considerations of privacy, use and ownership, as well as good governance issues such as fostering citizen participation, encouraging innovation and urging the creation of a solid and robust management infrastructure that promotes the proper operation of the data conditions. The use of Big Data can be a fundamental tool for the development of more robust, flexible and reflexive resilience strategies, which keep climate threats projections updated, allowing adaptation measures to be more relevant and suited for a system’s shocks and stresses. This study broadens the knowledge on which are the correct data sources, the relevance of these data on their application in urban climate resilience and specific Big Data considerations for the city of Madrid.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-286117 |
| Date | January 2020 |
| Creators | Rojo, Juan |
| Publisher | KTH, Urbana och regionala studier |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-ABE-MBT ; 20751 |
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