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Record W7025197095

Toward the Development of LADM-based Marine Cadastres: Is LADM Applicable to Marine Cadastres?

2016· article· en· W7025197095 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Repository (Delft University of Technology) · 2016
Typearticle
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCadastreRelation (database)HydrographyExtension (predicate logic)Domain (mathematical analysis)Relevance (law)Function (biology)
DOInot available

Abstract

fetched live from OpenAlex

Hoogsteden and Robertson (1998; 1999) were among very few early publications that supported the idea that consideration is to be given to the extension of “on-land” cadastral system into the offshore. It was circa 2001 that the terms “marine cadastre” or “marine cadastral” were first explicitly used in scholarly media and at professional conferences (Fowler and Tremi 2001; Collier, Leahy and Williamson 2001; Hirst and Robertson 2001; Ng'ang'a et al, 2001; Sutherland, Nichols and Monahan 2001; Todd 2001). Most publications, since then, that addressed the marine concept cadastre concept, acknowledged the obvious 3- dimensional (3D) marine spaces and support the need for marine cadastres to multipurpose in function (Ng’ang’a, Sutherland and Nichols 2002; Binns and Williamson 2003; Binns et al, 2004; Ng'ang'a et al, 2004; Fulmer 2007). From a literature review by the authors of this paper, no publication sufficiently addressed any ascription to an appropriately applicable data standard for marine cadastres. The Land Administration Domain Model (ISO 19152: 2012) (LADM) conceptual standard has been referenced in scholarly and professional works to have explicit relevance to 3D cadastres in exposed land- and built environments. These sources, however, only cursorily make reference to LADM’s applicability to marine cadastres (Lemmen et al, 2005; Lemmen and van Oosterom 2011; Lemmen 2012; de Almeida, Ellul and Rodrigues-de-Carvalho 2013; Tjia 2014; Eftychia 2015). Canadian Hydrographic Service & Geoscience Australia (2016) presents the most comprehensive modelling, to date, that refers to LADM in relation to marine cadastres. The authors propose an extension of the S- 100 IHO Universal Hydrographic Data Model into the development of the S-121 IHO standard, to handle maritime limits and boundaries. However, the proposed S-121 standard is not a pure LADM-based data model but seeks to build some components that would conform to ISO 19152. This paper attempts to the question “How applicable is LADM, as a published cadastral data standard, to marine cadastres?” The given answers are based on a list of reasonable criteria, developed from relevant literature reviews, and used to assess the LADM standard. It is concluded that LADM is indeed applicable, as published and as a whole, to marine cadastres. This can be good news to those jurisdictions who are seeking to develop marine cadastres in that they can reasonably trust the LADM as an applicable data standard.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0020.006
Scholarly communication0.0110.014
Open science0.0040.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.005

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 head0.028
GPT teacher head0.248
Teacher spread0.219 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations4
Published2016
Admission routes1
Has abstractyes

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