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  • This dataset contains the areas affected by landslides triggered by Typhoon Parma in the area of Itogon (Benguet, Philippines) between the 2nd and 5th October 2009. The polygons were mapped using Google Earth imagery dated 31 December 2003 for pre-event and images and 31 December 2009 for post-event images. The area has an extension of 150 km2. Full details about this dataset can be found at https://doi.org/10.5285/2e15dbd2-71c3-4e86-aa90-6029d37bd417

  • This dataset includes synthetically produced data from 10 different cities (Istanbul, Nablus, Chattogram, Cox’s Bazaar, Nairobi, Nakuru, Quito, Kokhana, Rapti and Darussalam) for a future urban context. The data includes physical elements in a city such as buildings, roads, and power networks, as well as social elements such as households and individuals. The dataset contains a maximum of 9 different data types, described below. For some cities power and road network data were not considered due to context specific priorities. landuse: The land use plan data depicting how the land will be zoned and used in the next fifty years within the area or interest. The attributes include the land use type, areal coverage in hectares, maximum population density and existing population. building: Data representing the building footprints that will emerge as a result of the future exposure generation procedure. It includes the attributes of the building such as its identifier number, construction type, number of floors, footprint area, occupation type and construction code level. road nodes: Data representing the points where road segments (edges) are connected to each other, including the identifier number for each node. road edges: Data representing the road segments, including the ID numbers of the starting and ending point (node). power nodes: Data representing the points where power lines (edges) are connected to each other, including the identifier number for each node. power edges: Data representing the power segments, including the including the ID numbers of the starting and ending point (node). household: Data that contains social attributes of a household living in a building. The attributes include number of individuals, income level and commonly used facility ID (such as hospital). individual: Data that contains the attributes of the individuals that are a part of a household. The attributes are age, gender, school ID (if relevant), workplace ID (if relevant) and last attained education level. Distribution table: The future projections for each city that identifies the socio-demographic changes and expected physical development in the next 50 years. The data can be used in geospatial platforms. The nomenclature for the data is as follows: “CitynameFutureExposureDataset/Cityname_CommunityCode_DataType”. This dataset was created as case studies for the Tomorrows Cities: Tomorrowville virtual testbed. It is supported by NERC as part of the GCRF Urban Disaster Risk Hub (NE/S009000/1). Full details about this dataset can be found at https://doi.org/10.5285/cdfea06f-d47c-4967-99d4-cc71bddea45d

  • This dataset contains information about predicted future erosion hazards to electricity transmission towers at a site in the Mersey River valley. River channel change and floodplain erosion rates were simulated under 6 hypothetical flow scenarios, covering the years 2018 to 2050. These scenarios include: “baseline” where we assumed the 32 years of flow from 2018 to 2050 matched the preceding 32-year period; and “plus 10, 20, 30, 40 & 50%” where we assumed daily averaged flow magnitudes increased by 10, 20, 30, 40 or 50%, depending on the scenario. Simulations were run using the CAESAR-Lisflood landscape evolution model. Input files that were used to drive the simulations include a 15-metre resolution DEM covering a ~4.5 km long reach of river valley, and daily-averaged flow inputs (m3 s-1). Landscape changes over time were extracted at the locations of each electricity transmission tower, with the severity of erosion used to judge the relative risks of each tower from future climate change. The work was supported by the Natural Environment Research Council (Grant NE/S01697X/1) as part of the project: ‘Erosion Hazards in River Catchments: Making Critical Infrastructure More Climate Resilient’. Full details about this dataset can be found at https://doi.org/10.5285/78bc21a9-39e0-4efc-992c-5587439fe6be

  • This dataset contains the areas affected by landslides triggered by Typhoon Mangkhut in the area of Itogon (Benguet, Philippines) between the 13th and 15th of September 2018. The polygons were mapped using very high-resolution satellite imagery from before and after the typhoon. The pre-typhoon images were captured on 18/02/2018 and the post-typhoon images were captured on 02/03/2019 using the World-View 2 satellite. Google Earth imagery was also used as a supplementary source. The study area covers 570 km2. Full details about this dataset can be found at https://doi.org/10.5285/32765a61-8510-4dfc-b7c7-58bad12f8497

  • This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111