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Record W2036774528 · doi:10.5589/m10-066

Anisotropic reflectance effects on spectral indices for estimating ecophysiological parameters using a portable goniometer system

2010· article· en· W2036774528 on OpenAlexvenueaboutno aff
Craig A. Coburn, Eric Van Gaalen, Derek R. Peddle, Lawrence B. Flanagan

Bibliographic record

VenueCanadian Journal of Remote Sensing · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsBidirectional reflectance distribution functionGoniometerRemote sensingNormalized Difference Vegetation IndexEnvironmental scienceHyperspectral imagingMossAnisotropyPhotochemical Reflectance IndexReflectivityFluxNetAtmospheric sciencesLeaf area indexGeographyOpticsEddy covarianceEcosystemGeologyPhysicsEcology

Abstract

fetched live from OpenAlex

AbstractRemote sensing studies are affected by the inherently anisotropic nature of reflectance from natural surfaces. The objective of this study was to investigate the effect of anisotropic reflectance on the 970 nm water band index (WBI) for Pleurozium schreberi moss from the Fluxnet Canada Western Peatland site in northern Alberta. A series of hyperspectral bidirectional reflectance measurements from the University of Lethbridge Goniometer System (ULGS-I) were assessed for their effect on a variety of WBI and NDVI spectral indices. These indices are often used to estimate ecophysiological parameters such as plant water content, pigment content, and leaf area and subsequently have the potential to contribute to estimates of ecosystem CO2 flux across large regions. Estimates of the bidirectional reflectance distribution function (BRDF) from laboratory ULGS-I measurements of P. schreberi moss were made under controlled illumination conditions from which WBI and NDVI were computed to evaluate the variation in index magnitude by view direction. As view angle increased from nadir, WBI declined dramatically from 1.40 to 1.24, and NDVI values changed from 0.87 to 0.96. This finding increases our understanding of the effect of anisotropic reflectance on vegetation indices and enhances our ability to derive improved information from remote sensing data when these angular effects are prevalent for different surface targets.Les études de télédétection sont affectées par la nature anisotrope inhérente de la réflectance des surfaces naturelles. L'objectif de cette étude était d'étudier l'effet de la réflectance anisotrope sur l'indice WBI (« water band index ») à 970 nm de l'hypne de Schreber (Pleurozium schreberi) sur le site de la Station de flux des tourbières de l'ouest de Fluxnet-Canada située dans le nord de l'Alberta. Une série de mesures hyperspectrales de réflectance bidirectionnelle acquises à l'aide du système de goniomètre de l'Université de Lethbridge (ULGS-I) ont été évaluées pour leur effet sur divers indices spectraux WBI et NDVI. Ces indices sont souvent utilisés pour estimer les paramètres écophysiologiques tels que la teneur en eau des plantes, la teneur en pigments et la surface foliaire car ceux-ci peuvent ultimement contribuer aux estimations des flux de CO2 de l'écosystème à travers de vastes régions. Des estimations de la fonction de distribution de la réflectance bidirectionnelle (FDRB) à partir de mesures de ULGS-I en laboratoire de l'hypne de Schreber (P. schreberi) ont été réalisées dans des conditions contrôlées d'éclairement à partir desquelles les indices WBI et NDVI ont été calculés pour évaluer la variation de la magnitude de l'indice selon la direction de visée. À mesure que l'angle de visée augmentait à partir du nadir, le WBI diminuait dramatiquement de 1,40 à 1,24 et les valeurs de NDVI changeaient de 0,87 à 0,96. Cette découverte améliore notre connaissance de l'effet de la réflectance anisotrope sur les indices de végétation et accroìt notre capacité à dériver une meilleure information à partir des données de télédétection lorsque ces effets angulaires sont omniprésents pour différentes cibles de surface.[Traduit par la Rédaction]

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.747

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 integrity0.0000.001
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations21
Published2010
Admission routes2
Has abstractyes

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