[JOSS Review] Paper

[nmstreethran]

@AlexanderJuestel here are some initial comments on the paper. I have to do a quick check again so I'll comment if I have any further feedback.

openjournals/joss-reviews#6275

General comments

I'm curious how much lower the 100 m x 100 m resolution is compared to that of a building, since the paper states the following:

Evaluating the heat demand (usually in MWh = Mega Watt Hours) on a national or regional scale, including space and water heating for each apartment or each
building for every day of a year separately is from a perspective of resolution (spatial and temporal scale) and computing power
not feasible. Therefore, heat demand maps summarize the heat demand on a lower spatial resolution (e.g. 100 m x 100 m
raster) cumulated for one year (lower temporal resolution) for different sectors such as the residential and tertiary
sectors.

MWh was also defined here but it has already been used in the summary twice. I suggest moving the definition to the first instance where MWh is used. You can perhaps define it in the form of a footnote.

The acronym "HD" is used but is not defined anywhere in the paper.

According to my checklist, the statement of need must include the target audience of PyHeatDemand. The target audience should also be included in the documentation.

Formatting

I found some minor formatting issues in the PDF article and docs which I've listed below.

The blank lines in the following code are breaking the sentence, so they should be removed.

pyheatdemand/docs/source/about.rst

Lines 6 to 8 in 73f41fd

	**PyHeatDemand** is an open-source Python package for processing and harmonizing multi-scale-multi-type heat demand input data for
	constructing local to transnational harmonized heat demand maps (rasters). Knowledge about the heat demand (MWh/area/year) of a respective building,

pyheatdemand/joss/paper.md

Lines 26 to 28 in 73f41fd

	**PyHeatDemand** is an open-source Python package for processing and harmonizing multi-scale-multi-type heat demand input data for
	constructing local to transnational harmonized heat demand maps (rasters). Knowledge about the heat demand (MWh/area/year) of a respective building,

pyheatdemand/joss/paper.md

Lines 35 to 37 in 73f41fd

	(points or polygons), with building footprints (polygons), with street segments (lines), or with addresses directly provided in
	MWh but also as gas usage, district heating usage, or sources of heat. It is also possible to calculate the heat demand

The table isn't rendered properly. I think you need to remove all of these dashes, except for the one below the header row, to fix it. Also, you have referenced the table as Tab. 1. Since the table doesn't have a caption, you can either add a caption, or remove the reference to Tab. 1 and just refer to it as the "table below".

pyheatdemand/joss/paper.md

Lines 93 to 101 in 73f41fd

	|---------------|----------------------------------------------------------------------------------------------------------------------------------|
	| 2 | HD data provided as building footprints or street segments |
	|---------------|----------------------------------------------------------------------------------------------------------------------------------|
	| 3 | HD data provided as a point or polygon layer, which contains the sum of the HD for regions of official administrative units |
	|---------------|----------------------------------------------------------------------------------------------------------------------------------|
	| 4 | HD data provided in other data formats such as HD data associated with addresses |
	|---------------|----------------------------------------------------------------------------------------------------------------------------------|
	| 5 | No HD data available for the region |
	|---------------|----------------------------------------------------------------------------------------------------------------------------------|

Paper structure

I think the State of the field, PyHeatDemand Outlook, and PyHeatDemand Resources sections could possibly be merged with the previous sections as they are short. The outlook could go in the Summary. The state of the field should probably be in the statement of need. You can remove the GitHub repository and documentation link as the PDF of the paper already has a link to the repo. The DGE Rollout Webviewer and a reference to Herbst, 2021 could go in the summary as well, where you mention in the final sentence that the package was developed during the DGE Rollout project. You can also move Jüstel et al., 2023 here as an application of the package.

References

There are no citations provided in the summary and statement of need. I suggest adding citations to the following:

• Summary
  • the purpose of heat demand quantification and mapping
• Statement of need:
  • energy consumption, primary energy, and thermal energy statistics
  • EU energy efficiency directive and emission reduction target
  • example of heat demand input values for the residential and commercial sectors that are easily accessible and assessable

Bibliography

The DOI for Jüstel et al., 2023 is missing in the PDF. Change note= to doi= to fix this:

pyheatdemand/joss/paper.bib

Line 220 in 73f41fd

note={10.3390/en17020481},

Herbst, 2021 seems like it's missing several authors?

Some of the titles are not capitalised properly in the PDF output of the paper. These words/titles (emphasised in bold) should be enclosed in braces in the bib file to preserve the capitalisation:

• Herbst, K., E. (2021). A heat demand map of north-west europe
• Esmukov, K., & others. (2023). GeoPy: Geocoding library for python
• Gillies, S., & others. (2013). Rasterio: Geospatial raster i/o for Python programmers.
• Meha, D., Novosel, T., & Duić, N. (2020). Bottom-up and top-down heat demand mapping methods for small municipalities, case gllogoc

[AlexanderJuestel]

General Comments

The General comments were addressed in dc65f8f

In densely populated areas, many houses could be within a 100 m x 100 m square. It is also a way to cumulate values for a city/region to identify heat demand hot spots. The quadtree refinement using a variable size of squares demonstrates that even better.

• Definition of MWh: I tried to refine it a little or eliminate the abbreviations in the summary, respectively.
• Definition of HD: This was added to the Statement of Need. I did not add it to the summary to not use abbreviations.

The target audience is included in the Statement of Need: Combining the functionality of well-known geospatial Python libraries, the open-source package PyHeatDemand provides tools for public entities, researchers, or students for processing heat demand input data. Would that be sufficient?

[AlexanderJuestel]

Formatting

The formatting issues were addressed in becfecb

All line breaks were removed in the paper and the about section. The Table was fixed.

[AlexanderJuestel]

Paper Structure

The paper structure was addressed in 6e4b83d

The State of the field was moved to the statement of need section. The outlook was split. The first part went into the summary and the second part was merged with the Resources. This is the only of the three sections that remains now.

[AlexanderJuestel]

Bibliography

The bibliography issues were addressed in f9e661b

There were indeed some brackets missing.

[AlexanderJuestel]

References

The references issues were addressed in e9a4c5e

I would refrain from adding a reference to the summary as I see it as an abstract and would not add a reference there either.
Two references were added in the statement of need and an example of where to download heat demand input data for the state of North Rhine-Westphalia was addded to "Processing Heat Demand Input Data" Section

[AlexanderJuestel]

@nmstreethran with that, I should have addressed your comments and remarks on this issue. Feel free to have a look and thanks again for your great comments!

[nmstreethran]

The target audience is included in the Statement of Need: Combining the functionality of well-known geospatial Python libraries, the open-source package PyHeatDemand provides tools for public entities, researchers, or students for processing heat demand input data. Would that be sufficient?

Yes, that's sufficient. I'm happy with all the other changes too.