Assessments of multisensor vegetation index dependencies with hyperspectral and tower flux data

Alfredo R. Huete, Tomoaki Miura, Youngwook Kim, Kamel Didan, Jeffrey Privette

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Long term data records require the effective integration of new sensor technologies and improved algorithms to better characterize global and climate change impacts on ecosystems, while preserving the fundamental attributes of the existing data record. In this study, we investigated key determinants in the spectral translation and extension of MODIS Vegetation Index products across current sensor systems and to the NPOESS (VIIRS) era. We used simulated sensorspecific data sets derived from hyperspectral data using field spectroroadiometers and Hyperion sensors to investigate inter-sensor translation and continuity issues of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We also investigated the use of data fusion of satellite VI time series with in-situ flux tower time series measurements of photosynthesis, and the use of data fusion with tower-based continuous measures of broadband/hemispherical VI's as possible reference data sets for the inter-calibration of satellite VI time series from different sensor systems. Preliminary comparisons are presented with actual satellite VI measurements from SPOT-VEGETATION, Terra- and Aqua-MODIS, and AVHRR sensors. We found that with a consistent atmosphere correction scheme and a generalized compositing procedure, translation of multi-sensor datasets can be achieved with certain limitations.

Original languageEnglish (US)
Title of host publicationRemote Sensing and Modeling of Ecosystems for Sustainability III
DOIs
StatePublished - Nov 30 2006
EventRemote Sensing and Modeling of Ecosystems for Sustainability III - San Diego, CA, United States
Duration: Aug 14 2006Aug 16 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6298
ISSN (Print)0277-786X

Other

OtherRemote Sensing and Modeling of Ecosystems for Sustainability III
CountryUnited States
CitySan Diego, CA
Period8/14/068/16/06

Keywords

  • EVI
  • Flux tower
  • GPP
  • MODIS
  • NDVI
  • VIIRS
  • Vegetation indices

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Huete, A. R., Miura, T., Kim, Y., Didan, K., & Privette, J. (2006). Assessments of multisensor vegetation index dependencies with hyperspectral and tower flux data. In Remote Sensing and Modeling of Ecosystems for Sustainability III [629814] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6298). https://doi.org/10.1117/12.681382