GitLab

The aim of the analysis was to decide if data quality of OpenStreetMap (OSM) was sufficient to perform an analysis of effects of the Jakarta 2013 flood on the road network and the accessibility of health sites. Analysis done in R.

A wrapper for ChangesetMD, a tool to provide OpenStreetMap changeset metadata via a postgres database (https://github.com/ToeBee/ChangesetMD).

A wrapper for whodidit, an OSM user names database (https://github.com/Zverik/whosthat).

An analysis using the ohsome API: http://k1z.blog.uni-heidelberg.de/2020/11/23/exploring-localness-of-osm-data-an-analysis-using-the-oshdb-and-ohsome-api/

Comparison of OSM and ATKIS land use classes, intersections and symmetrical differences, possible grouping

Calculation of land use shares of green and blue land use classes of grid cells, summed up NDVI per grid cell, NDVI boxplots per land use class (ATKIS and OSM)

extracts data from an oshdb ignite cluster for a specified bounding box region and saves it into a H2 oshdb file

Express Server

Postgis db

Frontend

Random Forest classification over Sentinel-2 data using training labels from OSM landcover database