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.
GeoPackages containing geospatial data are divided according to geographical locations.
|Date made available||14 Oct 2020|
|Publisher||University of Strathclyde|
|Date of data production||27 Mar 2020|