An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series

@article{Gao2008AnAT,
  title={An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series},
  author={Feng Gao and Jeffrey T. Morisette and Robert E. Wolfe and Gregory A. Ederer and Jeffrey A. Pedelty and Edward J. Masuoka and Ranga B. Myneni and Bin Tan and Joanne M. Nightingale},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2008},
  volume={5},
  pages={60-64}
}
Ecological and climate models require high-quality consistent biophysical parameters as inputs and validation sources. NASA's moderate resolution imaging spectroradiometer (MODIS) biophysical products provide such data and have been used to improve our understanding of climate and ecosystem changes. However, the MODIS time series contains occasional lower quality data, gaps from persistent clouds, cloud contamination, and other gaps. Many modeling efforts, such as those used in the North… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 14 references

TIMESAT - a program for analyzing time-series of satellite sensor data

Computers & Geosciences • 2004
View 6 Excerpts
Highly Influenced

Seasonality extraction by function fitting to time-series of satellite sensor data

IEEE Trans. Geoscience and Remote Sensing • 2002
View 5 Excerpts
Highly Influenced

Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI

P.S.A. Beck, C. Atzberger, K. A. Høgda
Remote Sens. Environ., vol. 100, no. 3, pp. 321–334, Feb. 2006. • 2006
View 2 Excerpts

MODIS leaf area index products: from validation to algorithm improvement

IEEE Transactions on Geoscience and Remote Sensing • 2006
View 4 Excerpts

Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland

Y. Wang, C. E. Woodcock, W. Buermann
Remote Sens. Environ., vol. 91, no. 1 pp. 114–127, May 2004. • 2004
View 1 Excerpt

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