Datasets:

boettiger-lab
/

pad-us-3

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Cannot get the split names for the config 'default' of the dataset.

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 154, in compute
                  compute_split_names_from_info_response(
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 126, in compute_split_names_from_info_response
                  config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 566, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              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 62, 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 3687, in read_schema
                  file = ParquetFile(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 341, in __init__
                  self.reader.open(
                File "pyarrow/_parquet.pyx", line 1250, 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 72, 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.

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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

PADUS3 contains files extracted from the orginal zip archive and associated geodatabase distributed by the USGS.
pad-us3-combined.parquet contains a geoparquet version of the geodatabase protected areas layer
pad-us3-combined.fgb contains 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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