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Tidal datum conversion grids for the Eastern Shore of Virginia and surrounding waters (2013)

2018· dataset· en· W6939682699 sur OpenAlexaboutno aff

Notice bibliographique

RevueEnvironmental Data Initiative · 2018
Typedataset
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeodetic datumShoreElevation (ballistics)Sea levelTidal ModelNorth American Datum of 1927Baseline (sea)Interpolation (computer graphics)

Résumé

récupéré en direct d'OpenAlex

Data consists of conversion factors that can be used to convert between numerous vertical tidal datums and the North American Vertical Datum of 1988 (NAVD88). The data cover the Eastern Shore of Virginia and parts of southeastern Maryland along with the surrounding coastal waters and are represented as approximately 100m (100.584m) resolution grids. The six included tidal datums are local mean sea level (LMSL), mean tidal level (MTL), mean low water (MLW), mean lower low water (MLLW), mean high water (MHW), and mean higher high water (MHHW). All vertical units are in meters. By combining multiple conversions to and from NAVD88, conversion between the various tidal datums is possible. Two versions of the conversion factor grids are provided for each NAVD88-to-tidal-datum pairing: one that only contains data for areas not masked as nodata by the NOAA VDatum program (original source data) and one that contains both the original and interpolated data (see below for details). Naming conventions used were "cfactor_DDD" for the original VDatum-detrived dataset where "DDD" is the local tidal datum and "cf_nd_DDD" for the dataset that includes interpolated values within the nodata masks (IDW interpolation across masked areas, typically upland regions but also shallow seaside bays and creeks for which no adequate tidal benchmarks were available). By definition, the baseline elevation (sea level or 0.0m elevation) for NAVD88 is referenced to the fixed International Great Lakes Datum of 1985 local mean sea level height value, at Rimouski, Quebec, Canada. Additional tidal bench mark elevations were not used to calculate NAVD88 due to the demonstrated variations in sea surface topography, i.e., the fact that mean sea level is not the same equipotential surface at all tidal benchmarks. The magnitude of the difference between local mean sea level (LMSL) at the tidal benchmarks of the Eastern Shore of Virginia and the NAVD88 defined sea-level varies from 0.039 to 0.149 meters BELOW zero NAVD88. Tidal prisms also vary at each tidal benchmark (in part due to differences in basin configuration and tidal interactions) causing the conversion factors for the other tidal datums to also vary spatially in similar but not identical patterns. The VDatum 3.2 software program from NOAA (http://vdatum.noaa.gov/) was used to convert the x,y,z center points of the 100m gridded data wherein all Z elevations were set equal to zero (0) from NAVD88 to each of the six local tidal datums (the X,Y horizontal WGS84 UTM 18N coordinates remained unchanged). The resulting conversion factors represent the new elevation at which the NAVD88 zero level would lie in reference to the new datum; thus, to convert from NAVD88 and the new tidal datum, one would add this conversion factor to the NAVD88 elevations to get elevations relative to the chosen tidal datum. To convert to NAVD88 from a given tidal datum, one would subtract the conversion factor from the tidal elevation. Data were turned back into gridded data with the same resolution and horizontal extent as the original data grid. The internal data grids used by the VDatum program mask as nodata most land areas (including marshes) plus many of the seaside shallow bays, either in part or in full, for which reliable tidal benchmark data is/was not available. As a result, the program cannot be used in these nodata areas, even if immediately adjacent to data areas. So as to make conversion factors available for these coastal bays and marshes and seaside watersheds of interest to the VCRLTER, conversion factors for gridded regions within the NOAA nodata masks were interpolated from neighboring data values using the inverse distance weighting (IDW) techniques employed by ESRI's ArcGIS 10.1 software. IDW interpolation resulted in conversion factors that varied gradually spatially when adjacent to the NOAA VDatum data grids but that often showed relatively sharp transitions when equidistant between different far-apart basins (such as mid-peninsula between the Chesapeake Bay and Atlantic Ocean, or within South Bay bounded by data constructed from tidal datums for the Atlantic Ocean (east), Ship Shoal Inlet (south), Sand Shoal Inlet (north), and Magothy Channel (west)). It is suggested that the appropriate use of this data is to convert elevation datasets referenced to a tidal datum to NAVD88 if integrating multiple datasets together over large areas, such as across the full Eastern Shore or across multiple watersheds or coastal bays, so as to not introduce artificial IDW-related transitions into otherwise vertically-consistent upland elevations or basin-scale bathymetric surveys. When converting elevations of fringing upland marshes, the conversion factors (including interpolated values) can likely be used directly on a cell-by-cell level to adjust the tidal elevations to NAVD88 or to another tidal datum without the involvement of any IDW-related transitions. Likewise for many of the back-barrier seaside marshes and bays of Accomack County in the northern portion of the data coverage where no channel tidal datums intervene between the Atlantic coastline and the Chesapeake Bay. However, when converting bathymetric survey data for individual bays or basins with significant nodata-masked areas that exhibit sharp IDW-related transitions, it is suggested that it would be more appropriate to use a single area-averaged conversion factor calculated across the whole basin (or across the whole basin minus any portion where the conversion factor is closer [more-related] to a channel on the other side of an upland barrier without connecting flow paths). Likewise when converting to tidal datums full upland mainland watersheds. This again should prevent introducing sharp transitions and steps into the bathymetry survey data, which it is assumed is otherwise internally consistent.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,119
Score d'incertitude au seuil0,237

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0270,026

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,054
Tête enseignante GPT0,284
Écart entre enseignants0,230 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2018
Routes d'admission1
Résumé présentoui

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