CM Scale heat and cool density maps

Table of Contents

In a glance

This module scales the default layer with a given factor. The aim is to provide a distribution of heat and cold demand, if only the total amount of heat and cold demand is available.

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The aim of the calculation module is to quickly obtain a new raster by scaling a raster density map by a user-chosen factor. It generate a new raster by multiplying each cells of the input raster by the given factor.

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Inputs and outputs

The input parameters and layers as well as output layers and parameters are as follows.

Input layers and parameters are:

  • Multiplication factor [-]: a real value between 0 and 1000
    • if the multiplication factor is > 1, the output raster is greater than the input.
    • if the multiplicatino factor is < 1, the output raster is smaller than the input.
  • The layer to be scaled :
    • Heat or Cool density map in raster format (*.tif)

Output layers and parameters are:

  • An output raster (*.tif), corresponding to the input scaled by the multiplication factor.

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Each cell's value of the input raster is multiply by the multiplication factor.

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If we know the total consumption of an area, and the indicator Total head demand does not correspond this value, it is possible to scale the heat demand by the ratio (Total_real / Total_default). The following figure gives the example for a multiplication factor value of 0.5.

Fig. 1-0

GitHub repository of this calculation module

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

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How to cite

Thiery Bernhard, in Hotmaps-Wiki, en-CM-Scale-heat-and-cool-density-maps (April 2019)

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Authors and reviewers

This page is written by Thierry Bernhard*.

This page was reviewed by Lesly Houndole and Albain Dufils*.


Centre de Recherches Energétiques et Municipales

Rue Marconi 19 - CP 256

CH-1920 Martigny

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Copyright © 2016-2019: CREM

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


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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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* machine translated