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Record W4393764486 · doi:10.5281/zenodo.5830967

USGS National Map 3DEP 1 Arc-second Digital Elevation Models (DEMs): Full Coverage for U.S. Interstate Highway System

2022· dataset· en· W4393764486 on OpenAlexaboutno aff
U.S. Geological Survey, Leah Brooks

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDigital elevation modelElevation (ballistics)Arc (geometry)GeologyGeographyGeodesyRemote sensingEngineering

Abstract

fetched live from OpenAlex

This is an archive of the USGS National Map 3DEP 1 Arc-second Digital Elevation Models (DEMs). While it should be reasonably complete (provided via DVD by USGS), coverage has only been verified to provide full coverage for the U.S. Interstate Highway System (see notes below). Original description: This is a tiled collection of the 3D Elevation Program (3DEP) and is 1 arc-second (approximately 30 m) resolution.The elevations in this Digital Elevation Model (DEM) represent the topographic bare-earth surface. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. [...] The seamless 1 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The seamless 1 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and much of Alaska and Canada. The seamless 1 arc-second DEM is available as pre-staged products tiled in 1 degree blocks in Erdas .img, ESRI arc-grid, and grid float formats. The seamless 1 arc-second DEM layer is updated continually as new data become available. The archived data here were acquired from two sources: DVD purchased from USGS on (DATE), as per process described in README.pdf The list of files stemming from the DVD are listed in "manifest_USGS_DVD.txt" manual download of missing grid cells from https://apps.nationalmap.gov/downloader/ on (DATE), as per procedure described in README.pdf, files are listed in "manifest_missingrasters.txt"

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1220.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.217
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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