Data and code for: "Climate adaptation plans in the context of coastal settlements: the case of Portugal"

Dataset

Description

This repository contains python code in the form of Jupyter notebooks and geospatial data used in the Climate adaptation plans in the context of coastal settlements: the case of Portugal research paper.

Geospatial data represent the morphological structure of 30 seashore streets along the Portuguese coast. The data were analyzed using computational Jupyter notebooks to determine their morphometric profile, morphological classification and assess the risk of flooding due to the extreme weather events caused by climate change.

Building layers were manually digitized and, where available, enriched by OpenStreetMap data. Street network layer was extracted from OpenStreetMap. Other layers were generated using Jupyter notebooks.

Python code is stored within Jupyter notebooks. For the accessibility purposes, contents of notebooks were also exported into executable scripts and PDF.

Data structure:

GeoPackages containing geospatial data are divided according to geographical locations.
Date made available14 Oct 2020
PublisherUniversity of Strathclyde
Date of data production27 Mar 2020
Geographical coveragePortugal

Research Output

Climate adaptation plans in the context of coastal settlements: the case of Portugal

Dal Cin, F., Fleischmann, M., Romice, O. & Costa, J. P., 16 Oct 2020, In : Sustainability. 12, 20, 19 p., 8559.

Research output: Contribution to journalArticle

Open Access
File
  • Cite this

    Fleischmann, M. (Creator), Romice, O. (Supervisor), Dal Cin, F. (Creator) (14 Oct 2020). Data and code for: "Climate adaptation plans in the context of coastal settlements: the case of Portugal". University of Strathclyde. environment(.yml), pdf(.zip), python(.zip), README(.md), 01_Retrieve_network_data(ipynb), 02_Measure_morphometric_characters(ipynb), 03_Calculate_contextual_characters(ipynb), data(.zip), 05_Flood_risk_model(ipynb), 04_Hierarchical_clustering(ipynb), 06_Orientation_towards_wind(ipynb), 07_Plot(ipynb). 10.15129/1b52083a-7e9b-4cca-8d2b-44823a241c53