CM Customized heat and gross floor area density maps

Table of Contents

Introduction

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).

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Inputs and outputs

Inputs

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):

  • hotmaps_ID: provide a unique, integer ID for each feature (polygon)
  • Type: Building type: set to 1 for service sector; other values are considered as residential (optional: can be left empty)
  • Year_Construction: Year of construction (optional: can be left empty)
  • Address: Address of the building (optional: can be left empty)
  • GFA: Gross floor area in m2
  • Footprint: footprint of the building in m2 (required if values for GFA are not provided)
  • NrFloor: number of floors (required if values for GFA are not provided)
  • spec_demand: Specific heat demand of each feature (polygon) in kWh
  • demand: Heat demand of each feature (polygon) in kWh
  • X_3035: The X-Coordinate of the center of the feature (polygon) in EPSG 3035 projection (Mandatory for the CSV file: can be left empty)
  • Y_3035: The Y-Coordinate of the center of the feature (polygon) in EPSG 3035 projection (Mandatory for the CSV file: can be left empty)

Important Note: The headers should be written as stated above. Otherwise, the code will break and returns an error.

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Outputs

As output, two raster files are generated:

  1. Gross floor area density map with pixel values in m2 per hectare
  2. Heat demand density map with pixel values in MWh per hectare

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Method

To visualize an own raster file in the Hotmaps toolbox, it should respect the rules defined by the toolbox. Generally, a raster should:

  1. have the CRS of ETRS89-extended / LAEA Europe - EPSG:3035,
  2. The coordinate of the raster origin (top-left corner of the raster) should be a multiplicand of 100, e.g. (4334900, 3019700).
  3. The resolution of the raster map should 100x100m
  4. The raster should refer to a location in Europe.

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.

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GitHub repository of this calculation module

Here you get the bleeding-edge development for this calculation module.

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How to cite

Mostafa Fallahnejad, in Hotmaps-Wiki, CM-District-heating-potentials (April 2019)

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Authors and reviewers

This page was written by Mostafa Fallahnejad (EEG - TU Wien).

☑ This page was reviewed by Marcul Hummel (e-think).

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License

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

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Acknowledgement

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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View in another language:

German*

* machine translated