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Urban Cooling: valuation with building footprints #89
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The methods are as follows:
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Ahhh, monthly runs, cool! Thanks for the data sources! |
After discussing, we've decided that the very first step for displaying results can just include reporting the estimated air temp differences across scenarios, just modeling the daytime mean air temperature for the month of August. There is a valuation method, including calculating heating & cooling degree-days, just with a single-month model. We can implement that later on, not for the immediate milestone. It involves a linear regression-based estimate of degree-days for the month that was modeled. |
On hold for now, though it does seem likely we want to go down the path of valuation described above. |
#120 includes the valuation methods |
On hold for a decision about #126 |
I have extracted the building footprint data from Microsoft's data store. https://planetarycomputer.microsoft.com/dataset/ms-buildings#Example-Notebook For the valuation, we also need energy-consumption parameters. Chris and I discussed this on Slack and he shared a table with those parameters, keyed by I still need to figure out the appropriate way to use the building footprint data in the context of this valuation workflow. And the building data also includes a mean-height field, so really we have footprints and heights of all(?) buildings. |
Why aren't we using the valuation component built-in to the invest urban cooling model? Chris's custom valuation method calculates cooling-degree-days, and then applies the energy consumption & cost parameters. That is more sophisticated than the invest method, which does not consider degree-days and might require some different parameters than we have. |
…is not used in that module. lucode is used instead. natcap#89
It's not clear to me if/how to incorporate building footprint data into this valuation. The valuation parameter How can building footprint/height data influence the energy cost parameters? Should |
I'm looking at the spreadsheet of invest_model_results.csv (see #80 ) and at https://github.com/chrisnootenboom/urban-workflow/blob/master/naturban/valuation/ucm.py
And the valuation seems to hinge on counting heating & cooling degree-days. Though I can't quite figure out how those could be calculated when the model does not return a timeseries of temperature.
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