CM Scale heat and cool density maps

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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Introduction

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 generates a new raster by multiplying each cell 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 multiplication 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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Method

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

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Application

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 of 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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References

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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*.

* CREM

Centre de Recherches Energétiques et Municipales

Rue Marconi 19 - CP 256

CH-1920 Martigny

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License

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

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