Evaluation and characterization of vegetation indices with error/uncertainty analysis for EOS-MODIS

Persistent Link:
http://hdl.handle.net/10150/284157
Title:
Evaluation and characterization of vegetation indices with error/uncertainty analysis for EOS-MODIS
Author:
Miura, Tomoaki
Issue Date:
2000
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
A set of error/uncertainty analyses were performed on several "improved" vegetation indices (VIs) planned for operational use in the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products onboard the Terra (EOS AM-1) and Aqua (EOS PM-1) satellite platforms. The objective was to investigate the performance and accuracy of the satellite-derived VI products under improved sensor characteristics and algorithms. These include the "atmospheric resistant" VIs that incorporate the "blue" band for normalization of aerosol effects and the most widely-used, normalized difference vegetation index (NDVI). The analyses were conducted to evaluate specifically: (1) the impact of sensor calibration uncertainties on VI accuracies, (2) the capabilities of the atmospheric resistant VIs and various middle-infrared (MIR) derived VIs to minimize smoke aerosol contamination, and (3) the performances of the atmospheric resistant VIs under "residual" aerosol effects resulting from the assumptions in the MODIS aerosol correction algorithm. The results of these studies showed both the advantages and disadvantages of using the atmospheric resistant VIs for operational vegetation monitoring. The atmospheric resistant VIs successfully minimized optically thin aerosol smoke contamination (aerosol optical thickness (AOT) at 0.67 μm < 1.0) but not optically thick smoke (AOT at 0.67 μm > 1.0). On the other hand, their resistances to "residual" aerosol effects were greater when the effects resulted from the correction of optically-thick aerosol atmosphere. The atmospheric resistant VIs did not successfully minimize the residual aerosol effects from optically-thin aerosol atmosphere (AOT at 0.67 μm ≤ ∼0.15), which was caused mainly by the possible wrong choice of aerosol model used for the AOT estimation and correction. The resultant uncertainties of the atmospheric resistant Vls associated with calibration, which were twice as large as that of the NDVI, increased with increasing AOT. These results suggest that the atmospheric resistant VIs be computed from partially (Rayleigh/O₃) corrected reflectances under normal atmospheric conditions (e.g., visibility > 10 km). Aerosol corrections should only be performed when biomass burning, urban/industrial pollution, and dust storms (larger AOT) are detected.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Physical Geography.; Environmental Sciences.; Remote Sensing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Soil, Water and Environmental Science
Degree Grantor:
University of Arizona
Advisor:
Huete, Alfredo R.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleEvaluation and characterization of vegetation indices with error/uncertainty analysis for EOS-MODISen_US
dc.creatorMiura, Tomoakien_US
dc.contributor.authorMiura, Tomoakien_US
dc.date.issued2000en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractA set of error/uncertainty analyses were performed on several "improved" vegetation indices (VIs) planned for operational use in the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products onboard the Terra (EOS AM-1) and Aqua (EOS PM-1) satellite platforms. The objective was to investigate the performance and accuracy of the satellite-derived VI products under improved sensor characteristics and algorithms. These include the "atmospheric resistant" VIs that incorporate the "blue" band for normalization of aerosol effects and the most widely-used, normalized difference vegetation index (NDVI). The analyses were conducted to evaluate specifically: (1) the impact of sensor calibration uncertainties on VI accuracies, (2) the capabilities of the atmospheric resistant VIs and various middle-infrared (MIR) derived VIs to minimize smoke aerosol contamination, and (3) the performances of the atmospheric resistant VIs under "residual" aerosol effects resulting from the assumptions in the MODIS aerosol correction algorithm. The results of these studies showed both the advantages and disadvantages of using the atmospheric resistant VIs for operational vegetation monitoring. The atmospheric resistant VIs successfully minimized optically thin aerosol smoke contamination (aerosol optical thickness (AOT) at 0.67 μm < 1.0) but not optically thick smoke (AOT at 0.67 μm > 1.0). On the other hand, their resistances to "residual" aerosol effects were greater when the effects resulted from the correction of optically-thick aerosol atmosphere. The atmospheric resistant VIs did not successfully minimize the residual aerosol effects from optically-thin aerosol atmosphere (AOT at 0.67 μm ≤ ∼0.15), which was caused mainly by the possible wrong choice of aerosol model used for the AOT estimation and correction. The resultant uncertainties of the atmospheric resistant Vls associated with calibration, which were twice as large as that of the NDVI, increased with increasing AOT. These results suggest that the atmospheric resistant VIs be computed from partially (Rayleigh/O₃) corrected reflectances under normal atmospheric conditions (e.g., visibility > 10 km). Aerosol corrections should only be performed when biomass burning, urban/industrial pollution, and dust storms (larger AOT) are detected.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPhysical Geography.en_US
dc.subjectEnvironmental Sciences.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSoil, Water and Environmental Scienceen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHuete, Alfredo R.en_US
dc.identifier.proquest9972100en_US
dc.identifier.bibrecord.b40639605en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.