Journal ArticleDOI
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Michael A. White,Kirsten M. de Beurs,Kamel Didan,David W. Inouye,Andrew D. Richardson,Olaf P. Jensen,John O'Keefe,G. Zhang,Ramakrishna R. Nemani,Willem J. D. van Leeuwen,Jesslyn F. Brown,Allard de Wit,Michael E. Schaepman,Xioamao Lin,Michael D. Dettinger,Amey S. Bailey,John S. Kimball,Mark D. Schwartz,Dennis D. Baldocchi,J. T. Lee,William K. Lauenroth +20 more
TLDR
In this paper, the authors assess 10 start-of-spring (SOS) methods for North America between 1982 and 2006 and find that SOS estimates were more related to the first leaf and first flowers expanding phenological stages.Abstract:
Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by � 60 days and in standard deviation by � 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOSread more
Citations
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Effects of data temporal resolution on phenology extractions from the alpine grasslands of the Tibetan Plateau
TL;DR: In this article, the authors applied several commonly utilized vegetation phenology extraction methods on two different temporal resolution MODIS NDVI data and compared their performances on the Tibetan Plateau (TP).
Journal ArticleDOI
Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.
TL;DR: This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.
Journal ArticleDOI
Spatio-temporal differentiation of spring phenology in China driven by temperatures and photoperiod from 1979 to 2018
TL;DR: Wang et al. as discussed by the authors proposed coclustering-based methods and a temperatures-photoperiod driven phenological model to explore spatio-temporal differentiation in long-term spring phenology in China.
Journal ArticleDOI
Mapping Periodic Patterns of Global Vegetation Based on Spectral Analysis of NDVI Time Series
Laura Recuero,Javier Litago,Jorge E. Pinzon,Margarita Huesca,Maria C. Moyano,Alicia Palacios-Orueta +5 more
TL;DR: This work describes vegetation oscillations by a novel quantitative approach based on the spectral analysis of Normalized Difference Vegetation Index (NDVI) time series to identify different seasonal patterns regarding the intra-annual cycles (the number, amplitude, and stability).
Journal ArticleDOI
Predictive power of remote sensing versus temperature‐derived variables in modelling phenology of herbivorous insects
Juha Pöyry,Kristin Böttcher,Stefan Fronzek,Nadine Gobron,Reima Leinonen,Sari Metsämäki,Raimo Virkkala +6 more
TL;DR: In this article, the authors compared the predictive power of remote sensing versus temperature-derived variables in modelling peak flight periods of herbivorous insects, as exemplified by nocturnal moths.
References
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Journal ArticleDOI
FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities
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North american regional reanalysis
Fedor Mesinger,Geoff DiMego,Eugenia Kalnay,Kenneth E. Mitchell,Perry Shafran,Wesley Ebisuzaki,Dusan Jovic,John S. Woollen,Eric Rogers,Ernesto Hugo Berbery,Michael Ek,Yun Fan,Robert Grumbine,Wayne Higgins,Hong Li,Ying Lin,Geoff Manikin,David F. Parrish,Wei Shi +18 more
TL;DR: The North American Regional Reanalysis (NARR) project as mentioned in this paper uses the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output) to capture regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.
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