The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements
Abstract
In the last two decades the availability of global remote sensing data sets has provided a new means of studying global patterns and dynamics in vegetation. The vast majority of previous work in this domain has used data from the Advanced Very High Resolution Radiometer, which until recently was the primary source of global land remote sensing data. In recent years, however, a number of new remote sensing data sources have become available that have significantly improved the capability of remote sensing to monitor global ecosystem dynamics. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer to study global vegetation phenology. Using a novel new method based on fitting piecewise logistic models to time series data from MODIS, key transition dates in the annual cycle(s) of vegetation growth can be estimated in an ecologically realistic fashion. Using this method we have produced global maps of seven phenological metrics at 1‐km spatial resolution for all ecosystems exhibiting identifiable annual phenologies. These metrics include the date of year for (1) the onset of greenness increase (greenup), (2) the onset of greenness maximum (maturity), (3) the onset of greenness decrease (senescence), and (4) the onset of greenness minimum (dormancy). The three remaining metrics are the growing season minimum, maximum, and summation of the enhanced vegetation index derived from MODIS. Comparison of vegetation phenology retrieved from MODIS with in situ measurements shows that these metrics provide realistic estimates of the four transition dates identified above. More generally, the spatial distribution of phenological metrics estimated from MODIS data is qualitatively realistic, and exhibits strong correspondence with temperature patterns in mid‐ and high‐latitude climates, with rainfall seasonality in seasonally dry climates, and with cropping patterns in agricultural areas.
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Citations
Cites
A globally coherent fingerprint of climate change impacts across natural systems
Parmesan, C., & Yohe, G. (2003) · Nature · doi:10.1038/nature01286 · Cited by 11,265
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00096-2 · Cited by 9,869
Global land cover mapping from MODIS: algorithms and early results
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A., et al. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00078-0 · Cited by 2,676
Self-citationMonitoring vegetation phenology using MODIS
Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., Hodges, J. C. F., Gao, F., Reed, B. C., & Huete, A. (2003) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00135-9 · Cited by 2,567
Self-citationFirst operational BRDF, albedo nadir reflectance products from MODIS
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., Strugnell, N. C., Zhang, X., Jin, Y., Muller, J.-P., et al. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00091-3 · Cited by 2,451
Self-citationGlobal land cover classification at 1 km spatial resolution using a classification tree approach
Hansen, M. C., Defries, R. S., Townshend, J. R. G., & Sohlberg, R. (2000) · International Journal of Remote Sensing · doi:10.1080/014311600210209 · Cited by 2,280
Canopy reflectance, photosynthesis and transpiration
SELLERS, P. J. (1985) · International Journal of Remote Sensing · doi:10.1080/01431168508948283 · Cited by 2,278
A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation
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Improvements of the MODIS terrestrial gross and net primary production global data set
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Cited by
Crop planting dates: an analysis of global patterns
Sacks, W. J., Deryng, D., Foley, J. A., & Ramankutty, N. (2010) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2010.00551.x · Cited by 957
Influence of spring and autumn phenological transitions on forest ecosystem productivity
Richardson, A. D., Andy Black, T., Ciais, P., Delbart, N., Friedl, M. A., Gobron, N., Hollinger, D. Y., Kutsch, W. L., Longdoz, B., Luyssaert, S., et al. (2010) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2010.0102 · Cited by 936
Self-citationZeng, L., Wardlow, B. D., Xiang, D., Hu, S., & Li, D. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111511 · Cited by 867
Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics
Bolton, D. K., & Friedl, M. A. (2013) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2013.01.007 · Cited by 785
Self-citationToward a synthetic understanding of the role of phenology in ecology and evolution
Forrest, J., & Miller-Rushing, A. J. (2010) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2010.0145 · Cited by 744
Metadata
- Authors
- Zhang, X., Friedl, M. A., & Schaaf, C. B.
- Venue
- Journal of Geophysical Research: Biogeosciences
- Publisher
- American Geophysical Union (AGU)
- Published
- 2006-12
- Volume
- 111
- Issue
- G4
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W2124564759
- Cited by
- 517
- References
- 46
- FWCI
- 5.50
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, X., Friedl, M. A., & Schaaf, C. B. (2006). Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements. Journal of Geophysical Research: Biogeosciences. https://doi.org/10.1029/2006jg000217
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