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Dev #195

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Adding gross carbon emissions titiler endpoint

danscales and others added 7 commits March 6, 2025 07:10
This is using the colors/symbology from the existing GFW raster tile
cache.

It includes one filter which is tree cover density, using
umd_tree_cover_density_2010/v1.6. This actually needs to be the 2000
version, I will change that before checkin, after I generate the proper
COGs.

I added an option in reader.py to specify the default_band, since it's
possible that the default band is not called default.tif.

All rendering is true_color (not encoded), so there is no render_type
parameter.
For emissions, I should be using the umd_tree_cover_density_2000 as the
tcd filter. And I originally created COG from the Mg_CO2e_ha-1__tcd_30
raster of gfw_forest_carbon_gross_emissions, but I really wanted the
default asset Mg_CO2e_ha-1, from which I created a default.tif COG.
this will be faster for clients as we pregenerate the emissions layer with the filter baked in
GTC-3144 Create carbon emissions titiler endpoint
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codecov-commenter commented Mar 14, 2025

⚠️ Please install the 'codecov app svg image' to ensure uploads and comments are reliably processed by Codecov.

Codecov Report

Attention: Patch coverage is 61.33333% with 29 lines in your changes missing coverage. Please review.

Project coverage is 79.20%. Comparing base (3fbdc60) to head (ae32228).

Files with missing lines Patch % Lines
...outes/titiler/algorithms/carbon_gross_emissions.py 47.36% 20 Missing ⚠️
...outes/titiler/gfw_forest_carbon_gross_emissions.py 70.00% 9 Missing ⚠️

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Additional details and impacted files
@@             Coverage Diff             @@
##           staging     #195      +/-   ##
===========================================
- Coverage    79.86%   79.20%   -0.67%     
===========================================
  Files           61       63       +2     
  Lines         2051     2125      +74     
===========================================
+ Hits          1638     1683      +45     
- Misses         413      442      +29     
Flag Coverage Δ
unittests 79.20% <61.33%> (-0.67%) ⬇️

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3 participants