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This module generates both a heat density and a floor area density map in the form of raster files. The input to the module a CSV file with certain column headers. For example, X-coordinate and Y-coordinate of the centre of buildings in EPSG:3035 coordinate reference system or their corresponding gross floor area and annual heat demand should be included in the CSV file. The generated raster files follow required projection and resolution by the Hotmaps toolbox and therefore, can be easily uploaded to the user accounts.
This module will only be available as a stand-alone module; it will not be integrated into the toolbox. The users of this CM should be familiar with python programming and have installed required libraries (e.g. Numpy, Pandas, GeoPandas and GDAL).
The module accepts a CSV file as input. The following headers are expected in case of any of the input file types (should be available in the header of the CSV file):
Important Note: The headers should be written as stated above. Otherwise, the code will break and returns an error.
As output, two raster files are generated:
To visualize an own raster file in the Hotmaps toolbox, it should respect the rules defined by the toolbox. Generally, a raster should:
Based on the above criteria and coordinates given in the input CSV file, each input coordinate is allocated to a certain pixel. Entries allocated to one single pixel are aggregated. The bottom-left pixel and top-right pixel determine the extent of the pixel. The resolution of the map is 100x100m. Accordingly, a heat density map and gross floor area map is generated.
Here you get the bleeding-edge development for this calculation module.
Mostafa Fallahnejad, in Hotmaps-Wiki, CM-District-heating-potentials (April 2019)
This page was written by Mostafa Fallahnejad (EEG - TU Wien).
☑ This page was reviewed by Marcul Hummel (e-think).
Copyright © 2016-2020: Mostafa Fallahnejad
Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons CC BY 4.0 International License.
SPDX-License-Identifier: CC-BY-4.0
License-Text: https://spdx.org/licenses/CC-BY-4.0.html
We would like to convey our deepest appreciation to the Horizon 2020 Hotmaps Project (Grant Agreement number 723677), which provided the funding to carry out the present investigation.
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Last edited by fallahnejad, 2021-01-13 09:48:53