The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 58, in _split_generators
self.info.features = datasets.Features.from_arrow_schema(pq.read_schema(f))
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 2325, in read_schema
file = ParquetFile(
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 318, in __init__
self.reader.open(
File "pyarrow/_parquet.pyx", line 1470, in pyarrow._parquet.ParquetReader.open
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
United States Protected Areas Database
U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2022, Protected Areas Database of the United States (PAD-US) 3.0: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q9LQ4B.
The PAD database classifications are complex and include overlapping and apparently duplicate polygons. For instance, national park boundaries can be found are listed in Proclamation feature class and also in Fee class (showing internal holes within boundaries). The processed PAD data layers here have been subset to the continental US (matching availability in MOBI data), and restricted to feature classes of "Fee" and "Easements", except for tribal boundaries which are taken from the "Proclamations." See ProtectedLands.net for a more detailed discussion of the data structure and classification involved in PAD. Code for reproducing this processing can be found at https://github.com/boettiger-lab/pad-us-3
USGS PAD-v3 is distributed as an ESRI Geodatabase. After subsetting the data and labelling according to the additional classification listed above based on manager type indicated in the data, core attributes are serialized into PMTiles and Geoparquet formats hosted on source.coop. PMTiles allows for rapid rendering of vector objects at the appropriate zoom level in an interactive map from remote servers. Geoparquet provides a high-performance serialization that can be efficiently queried directly from remote https addresses without download using software such as duckdb, widely available in python, R, and other languages.
Contents Overview
PADUS3contains files extracted from the orginal zip archive and associated geodatabase distributed by the USGS.pad-us3-combined.parquetcontains a geoparquet version of the geodatabase protected areas layerpad-us3-combined.fgbcontains a FlatGeobuff version of the geodatabase protected areas layer
PMTiles are computed with GDAL 3.8.4 up to max zoom 10 as follows:
ogr2ogr -dsco MAX_SIZE=90000000 -dsco MAX_FEATURES=50000000 -dsco MAXZOOM=10 public.pmtiles public_protected.fgb
Examples
Examples are generated with the map.py script.
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