Multi-criteria evaluation of the suitability of growth functions for modeling remotely sensed phenology
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Mark A. Friedl | Nathan Phillips | M. Friedl | M. Verma | N. Phillips | A. Finzi | Adrien C. Finzi | M. Verma
[1] R. Oren,et al. Sensitivity of stand transpiration to wind velocity in a mixed broadleaved deciduous forest , 2014 .
[2] Charles W Cook,et al. Natural gas pipeline leaks across Washington, DC. , 2014, Environmental science & technology.
[3] N. Phillips,et al. Secondary stem lengthening in palms: response to commentary by Tomlinson and Quinn. , 2013, American journal of botany.
[4] O. Sonnentag,et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system , 2013 .
[5] P. Atkinson,et al. Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology , 2012 .
[6] Mark A. Friedl,et al. Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology , 2012 .
[7] Mark D. Schwartz,et al. Intercomparing multiple measures of the onset of spring in eastern North America , 2010 .
[8] Damien Sulla-Menashe,et al. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .
[9] M. Schaepman,et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006 , 2009 .
[10] Liang Liang,et al. Landscape phenology: an integrative approach to seasonal vegetation dynamics , 2009, Landscape Ecology.
[11] Jennifer N. Hird,et al. Noise reduction of NDVI time series: An empirical comparison of selected techniques , 2009 .
[12] Andrew D. Richardson,et al. Phenological Differences Between Understory and Overstory: A Case Study Using the Long-Term Harvard Forest Records , 2009 .
[13] Anne Tolvanen,et al. MODIS-NDVI-based mapping of the length of the growing season in northern Fennoscandia , 2008, Int. J. Appl. Earth Obs. Geoinformation.
[14] Erwin Ulrich,et al. Evaluation of the onset of green-up in temperate deciduous broadleaf forests derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data , 2008 .
[15] D. Baldocchi. ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems , 2008 .
[16] John F. Mustard,et al. Extracting Phenological Signals From Multiyear AVHRR NDVI Time Series: Framework for Applying High-Order Annual Splines With Roughness Damping , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[17] J. Mustard,et al. Cross-scalar satellite phenology from ground, Landsat, and MODIS data , 2007 .
[18] D. Hollinger,et al. Refining light-use efficiency calculations for a deciduous forest canopy using simultaneous tower-based carbon flux and radiometric measurements , 2007 .
[19] Inez Y. Fung,et al. The changing carbon cycle at Mauna Loa Observatory , 2007, Proceedings of the National Academy of Sciences.
[20] Jürgen Symanzik,et al. On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models , 2007 .
[21] P. Buchwald. A general bilinear model to describe growth or decline time profiles. , 2007, Mathematical biosciences.
[22] Mark A. Friedl,et al. Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements , 2006 .
[23] S. Katsanevakis. Modelling fish growth: model selection, multi-model inference and model selection uncertainty , 2006 .
[24] Ranga B. Myneni,et al. Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS , 2006 .
[25] J. O'keefe,et al. Phenology of a northern hardwood forest canopy , 2006 .
[26] P. Beck,et al. Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI , 2006 .
[27] J. Mustard,et al. Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .
[28] C J Tucker,et al. Drier summers cancel out the CO2 uptake enhancement induced by warmer springs. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[29] Pascal Yiou,et al. Historical phenology: Grape ripening as a past climate indicator , 2004, Nature.
[30] Markus Reichstein,et al. Similarities in ground- and satellite-based NDVI time series and their relationship to physiological activity of a Scots pine forest in Finland , 2004 .
[31] R. Fensholt,et al. Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements , 2004 .
[32] G. Henebry,et al. Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan , 2004 .
[33] Arnaud Carrara,et al. Net ecosystem CO2 exchange of mixed forest in Belgium over 5 years , 2003 .
[34] A. Strahler,et al. Monitoring vegetation phenology using MODIS , 2003 .
[35] G. Yohe,et al. A globally coherent fingerprint of climate change impacts across natural systems , 2003, Nature.
[36] Per Jönsson,et al. Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..
[37] N. C. Strugnell,et al. First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .
[38] Dennis D. Baldocchi,et al. Modeling CO2 and water vapor exchange of a temperate broadleaved forest across hourly to decadal time scales , 2001 .
[39] Aaron Moody,et al. Land-Surface Phenologies from AVHRR Using the Discrete Fourier Transform , 2001 .
[40] A. Menzel,et al. Trends in phenological phases in Europe between 1951 and 1996 , 2000, International journal of biometeorology.
[41] Nathan Phillips,et al. A comparison of daily representations of canopy conductance based on two conditional time- averaging methods and the dependence of daily conductance on environmental factors , 1998 .
[42] G. Dedieu,et al. Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements , 1997 .
[43] S. Running,et al. A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .
[44] S. Goward,et al. Global Primary Production: A Remote Sensing Approach , 1995 .
[45] Nadine Gobron,et al. Optical remote sensing of vegetation: Modeling, caveats, and algorithms , 1995 .
[46] L. Eklundh,et al. Fourier series for analysis of temporal sequences of satellite sensor imagery , 1994 .
[47] Jesslyn F. Brown,et al. Measuring phenological variability from satellite imagery , 1994 .
[48] R. Myneni,et al. On the relationship between FAPAR and NDVI , 1994 .
[49] Forrest G. Hall,et al. FIFE in 1992: Results, scientific gains, and future research directions , 1992 .
[50] W. Silk,et al. Use of a flexible logistic function to describe axial growth of plants , 1992 .
[51] F. J. Richards. A Flexible Growth Function for Empirical Use , 1959 .
[52] Benjamin Gompertz,et al. XXIV. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. In a letter to Francis Baily, Esq. F. R. S. &c , 1825, Philosophical Transactions of the Royal Society of London.
[53] Benjamin Gompertz,et al. On the Nature of the Function Expressive of the Law of Human Mortality , 1815 .