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Record W2362163233

Estimating Status and Potential Degree of Desertification in Gan su Province Based on RS and GIS

2003· article· en· W2362163233 on OpenAlexaff
Anqing Ma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsDesertificationAridChinaPhysical geographyField surveyGeographyEnvironmental scienceScale (ratio)Remote sensingCartographyGeologyEcology
DOInot available

Abstract

fetched live from OpenAlex

Evaluating status and possibility of desertification is an important field in arid and semi-arid zone. For Gansu province is located in inner northwestern China, fragile environment and irrational human activity have made it a relatively serious area of desertification in northern China, and a main source of dust storm happening in China every year as well as. The paper acquires data of variety of land use and desertification on Gansu province from 1986 to 2000, by interpreting TM images of the two periods with GIS software ARC/INFO. Then, on the basis of the data, the study uses index of desertification extent to analyze spatial pattern of desertification on the province. The result indicates that on desertification scale, the Hexi corridor exceeds the other areas, in contrast to it that desertification extent of the Hexi corridor is less than it of the other areas. Based on the above results, with support of integration of ARC/INFO, statistic software SPSS and office software EXCEL, the study uses means of principal component analysis (PCA) to evaluate potential extent of every county on possibility of desertification. The result shows that the possibility of desertification of the Hexi corridor and the Gannan region exceed it of other areas, which is in accord with present spatial pattern of desertification scale on Gansu province.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.214
Teacher spread0.193 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2003
Admission routes1
Has abstractyes

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