Chromaticity analysis of LANDSAT Multispectral Scanner and Thematic Mapper imagery of Chilko Lake, British Columbia, using a theoretical optical water quality model
Notice bibliographique
Résumé
Chromaticity analysis of LANDSAT Multispectral Scanner (MSS) imagery of Chilko Lake, B.C. reveals a. locus whose shape has not been previously reported. To investigate the cause of this and to come to a broader understanding of chromaticity analysis for MSS and Thematic Mapper (TM) data, an optical water quality model has been used. The model is composed of a four component reflectance model (R-model), an interface model and an atmospheric model. The R-model was calibrated for Chilko Lake by determining the specific absorption and backscattering spectra for suspended minerals (SM), chlorophyll-a uncorrected for phaeophytins (C) and yellow substance (YS). The fourth component is water. The model reproduces the observed locus shape and indicates that it is primarily a function of SM, with the unreported lower limb on MSS imagery caused by SM gradients with concentrations less than 1-2 mg/L. The effects of C, YS and SM cannot be separated on plots of chromaticity coordinates X and Y for either MSS or TM data. In addition, haze or wind gradients, if they occur over water with low levels of SM, would look similar to the lower limb on MSS XY plots. However, if brightness is used in combination with X, the model predicts that C and YS, though themselves inseparable, can be differentiated from SM at all but the lowest concentrations of SM. Furthermore, haze and wind gradients can be distinguished from the lower limb. Thus the addition of brightness to chromaticity analysis has the potential to significantly improve the technique. The model was tested by comparing simulated chromaticity results with results from actual images (one TM image and three MSS images) for which ground truth had been collected. Qualitative predictions regarding haze and water quality patchiness were confirmed. Correlation analysis with R² values from 0.81 to 0.95 also strongly confirmed predictions regarding SM, but showed that the model is systematically underestimating SM. Correlation tests for a combined C and YS factor (CYS) were inconclusive because of the systematic modeling error, but classification maps provide weak evidence that CYS is behaving qualitatively as predicted and that CYS can be differentiated from SM. The modeling error is thought to originate in atmospheric assumptions which are not met. The R-model which is fundamental to the study has been tested and is not a major source of error. The study concludes that the model is qualitatively correct and that the use of brightness improves chromaticity analysis by allowing separation of CYS and SM, though further work should be undertaken to verify these results. Maps of CYS and SM in Chilko Lake reveal that CYS tends to be higher along the western shore and where the hypolimnion is exposed. SM are highest near stream mouths. The distribution patterns are related to physical processes within the lake and provide a synoptic view of the connection between water quality parameters and circulation which would be difficult to achieve in any other way.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».