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Record W2242664426 · doi:10.11834/jrs.20143133

Retrieving forest background reflectance in northeast of China from MODIS BRDF data: Taking Jiagedaqi District as a case study

2014· article· en· W2242664426 on OpenAlexfundno aff
GU Chunming, 刘振波 LIU Zhenbo, Yunjian Ge

Bibliographic record

VenueNational Remote Sensing Bulletin · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaPriority Academic Program Development of Jiangsu Higher Education InstitutionsUniversity of TorontoNational Aeronautics and Space Administration
KeywordsBidirectional reflectance distribution functionReflectivityRemote sensingEnvironmental scienceChinaScale (ratio)GeographyCartographyArchaeology

Abstract

fetched live from OpenAlex

基于MODIS二向反射分布函数(BRDF)模型参数产品数据,利用4-scale模型建立查找表,ä»¥ä¸­å›½ä¸œåŒ—å¤§å ´å®‰å²­åŠ æ ¼è¾¾å¥‡åœ°åŒºä¸ºç ”ç©¶åŒº,反演森林背景反射率,å¹¶åˆ†æžä¸åŒæ£®æž—ç±»åž‹äºŒå‘åå°„ä¸ŽèƒŒæ™¯åå°„çŽ‡ç‰¹æ€§åŠå ¶å­£èŠ‚å˜åŒ–ã€‚ç ”ç©¶ç»“æžœè¡¨æ˜Ž:(1ï¼‰ç ”ç©¶åŒºé’ˆå¶æž—å’Œæ··äº¤æž—äºŒå‘åå°„ç‰¹å¾è¾ƒä¸ºç›¸ä¼¼,å¤å­£é˜”å¶æž—åœ¨çº¢å ‰æ³¢æ®µçš„äºŒå‘åå°„çŽ‡å€¼å‡ä½ŽäºŽé’ˆå¶æž—å’Œæ··äº¤æž—,而在近红外波段则相反;不同森林类型二向反射率均存在明显的季节变化,å ¶ä¸­é˜”å¶æž—äºŒå‘åå°„çŽ‡å­£èŠ‚å˜åŒ–æœ€ä¸ºæ˜Žæ˜¾;(2ï¼‰ç ”ç©¶åŒºå¤å­£æ£®æž—èƒŒæ™¯åå°„çŽ‡åœ¨çº¢å ‰æ³¢æ®µè¾ƒä½Ž,均在0.1以下,近红外波段背景反射率普遍高于0.3,且空间差异较大;(3)不同森林类型的背景反射率季节变化趋势大致相同,ä½†å˜åŒ–å¹ åº¦å­˜åœ¨å·®å¼‚:阔叶林的背景反射率值季节差异最大,å°¤å ¶åœ¨è¿‘çº¢å¤–æ³¢æ®µã€‚

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.258
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.032
GPT teacher head0.289
Teacher spread0.257 · 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 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
Published2014
Admission routes1
Has abstractyes

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