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add area & area_percent statistics #169

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add area & area_percent statistics #169

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73260a3
add area & area_percent statistics
diversoft Jul 22, 2018
cfa3bdb
count is not necessary for area and area_percent
diversoft Jul 22, 2018
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20 changes: 19 additions & 1 deletion src/rasterstats/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -213,8 +213,26 @@ def gen_zonal_stats(
feature_stats['max'] = float(masked.max())
if 'mean' in stats:
feature_stats['mean'] = float(masked.mean())

stats_count = int(masked.count())
if 'count' in stats:
feature_stats['count'] = int(masked.count())
feature_stats['count'] = stats_count

if 'area' in stats:
if rast.src is not None:
cellsize = rast.src.res[0] * rast.src.res[1]
else:
cellsize = rast.affine.a * rast.affine.a
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@perrygeo perrygeo Jan 15, 2023

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Suggested change
cellsize = rast.affine.a * rast.affine.a
cellsize = rast.affine.a * rast.affine.e

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@perrygeo perrygeo Jan 15, 2023

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The cells size shouldn't be assumed to be square. It's very rare in practice to see rasters where a != e but it could happen

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@groutr groutr Jan 18, 2023

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I think you need the absolute value here: abs(rast.affine.a * rast.affine.e)

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@ericboucher ericboucher Jun 28, 2023

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To be safe, I would recommend reprojecting to be sure. I implemented a utility function for this use-case here - https://github.com/WFP-VAM/prism-app/pull/893/files#diff-0e7a305eb2d7da6652444269a99141f2a18d2fb8ea0ddbc045cd6c5a16e2ee9bR104

feature_stats['area'] = stats_count * cellsize

if 'area_percent' in stats:
if rast.src is not None:
cellsize = rast.src.res[0] * rast.src.res[1]
else:
cellsize = rast.affine.a * rast.affine.a
feature_stats['area_percent'] = stats_count * cellsize / geom.area


# optional
if 'sum' in stats:
feature_stats['sum'] = float(masked.sum())
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2 changes: 1 addition & 1 deletion src/rasterstats/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@

DEFAULT_STATS = ['count', 'min', 'max', 'mean']
VALID_STATS = DEFAULT_STATS + \
['sum', 'std', 'median', 'majority', 'minority', 'unique', 'range', 'nodata', 'nan']
['sum', 'std', 'median', 'majority', 'minority', 'unique', 'range', 'nodata', 'nan', 'area', 'area_percent']
# also percentile_{q} but that is handled as special case


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