Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States
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Bing Zhang | Liangyun Liu | Dailiang Peng | Shezhou Luo | Alfredo Huete | Xinjie Liu | Wenjiang Huang | Helin Zhang | Xiao Zhang | Xiaoyang Zhang | A. Huete | Xiaoyang Zhang | Wenjiang Huang | Bing Zhang | Liangyun Liu | D. Peng | Helin Zhang | Shezhou Luo | Xinjie Liu | Xiao Zhang | Siyuan Wang | Siyuan Wang
[1] A. Huete,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .
[2] H. Kerdiles,et al. NOAA-AVHRR NDVI decomposition and subpixel classification using linear mixing in the Argentinean Pampa , 1995 .
[3] H. L. Miller,et al. Climate Change 2007: The Physical Science Basis , 2007 .
[4] Per Jönsson,et al. TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..
[5] K. Gerst,et al. Species-specific phenological responses to winter temperature and precipitation in a water-limited ecosystem , 2015 .
[6] Mark A. Friedl,et al. Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology , 2012 .
[7] Alfredo Huete,et al. Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect , 2013 .
[8] Andrew D. Richardson,et al. Phenological Differences Between Understory and Overstory: A Case Study Using the Long-Term Harvard Forest Records , 2009 .
[9] C. Tucker,et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999 , 2001 .
[10] Jean-Pierre Wigneron,et al. Monitoring elevation variations in leaf phenology of deciduous broadleaf forests from SPOT/VEGETATION time-series , 2011 .
[11] S. Vavrus,et al. Spring plant phenology and false springs in the conterminous US during the 21st century , 2015 .
[12] Qinchuan Xin,et al. A risk-benefit model to simulate vegetation spring onset in response to multi-decadal climate variability: Theoretical basis and applications from the field to the Northern Hemisphere , 2016 .
[13] Dan Tarpley,et al. Diverse responses of vegetation phenology to a warming climate , 2007 .
[14] A. Strahler,et al. Monitoring vegetation phenology using MODIS , 2003 .
[15] C. Tucker,et al. Satellite remote sensing of primary production , 1986 .
[16] Joel A. Granados,et al. Using phenocams to monitor our changing Earth: toward a global phenocam network , 2016 .
[17] P. Gong,et al. Modeling grassland spring onset across the Western United States using climate variables and MODIS-derived phenology metrics , 2015 .
[18] Philippe Ciais,et al. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades , 2007 .
[19] C. Parmesan. Ecological and Evolutionary Responses to Recent Climate Change , 2006 .
[20] A. Huete,et al. Development of a two-band enhanced vegetation index without a blue band , 2008 .
[21] S. Bruin,et al. Analysis of monotonic greening and browning trends from global NDVI time-series , 2011 .
[22] Chaoyang Wu,et al. Intercomparison and evaluation of spring phenology products using National Phenology Network and AmeriFlux observations in the contiguous United States , 2017 .
[23] R. Zurita-Milla,et al. Trends and Natural Variability of Spring Onset in the Coterminous United States as Evaluated by a New Gridded Dataset of Spring Indices , 2015 .
[24] Andrew D Richardson,et al. Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States , 2016, Global change biology.
[25] Mark A. Friedl,et al. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery , 2014 .
[26] P. Ciais,et al. Variations in satellite‐derived phenology in China's temperate vegetation , 2006 .
[27] N. Delbart,et al. Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004) , 2006 .
[28] J. Schaber,et al. Responses of spring phenology to climate change , 2004 .
[29] C. Tucker,et al. Increased plant growth in the northern high latitudes from 1981 to 1991 , 1997, Nature.
[30] N. Delbart,et al. Comparing land surface phenology with leafing and flowering observations from the PlantWatch citizen network , 2015 .
[31] Michele Meroni,et al. Combining medium and coarse spatial resolution satellite data to improve the estimation of sub-pixel NDVI time series , 2008 .
[32] Damien Sulla-Menashe,et al. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .
[33] D. Dragoni,et al. Trends in fall phenology across the deciduous forests of the Eastern USA , 2012 .
[34] Lingling Liu,et al. Comparisons of global land surface seasonality and phenology derived from AVHRR, MODIS, and VIIRS data , 2017 .
[35] Andrew D Richardson,et al. Near-surface remote sensing of spatial and temporal variation in canopy phenology. , 2009, Ecological applications : a publication of the Ecological Society of America.
[36] Yanhong Tang,et al. Can EVI-derived land-surface phenology be used as a surrogate for phenology of canopy photosynthesis? , 2014 .
[37] G. Henebry,et al. Exploration of scaling effects on coarse resolution land surface phenology , 2017 .
[38] Carl F. Salk,et al. Light gains and physiological capacity of understorey woody plants during phenological avoidance of canopy shade , 2005 .
[39] M. Schaepman,et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006 , 2009 .
[40] D. Lobell,et al. Cropland distributions from temporal unmixing of MODIS data , 2004 .
[41] M. Friedl,et al. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product , 2010 .
[42] Mitchell D. Goldberg,et al. Monitoring fall foliage coloration dynamics using time-series satellite data , 2011 .
[43] Robert G. Bailey,et al. DISTINGUISHING BETWEEN WATERSHEDS AND ECOREGIONS 1 , 1997 .
[44] Patrick J. Guertin,et al. Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications , 2014, International Journal of Biometeorology.
[45] Chaoyang Wu,et al. Land surface phenology of China's temperate ecosystems over 1999–2013: Spatial–temporal patterns, interaction effects, covariation with climate and implications for productivity , 2016 .
[46] J. Mustard,et al. Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .
[47] R. Bailey. Identifying Ecoregion Boundaries , 2004, Environmental management.
[48] Ana Domínguez,et al. Estimating effective landscape distances and movement corridors: Comparison of habitat and genetic data , 2015 .
[49] C. Tucker,et al. North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer , 1985, Vegetatio.
[50] T. Swetnam,et al. Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.
[51] Alan H. Strahler,et al. The IGBP DISCover confidence sites and the system for terrestrial ecosystem parameterization: tools , 1999 .
[52] José A. Sobrino,et al. Global land surface phenology trends from GIMMS database , 2009 .
[53] Peter M. Atkinson,et al. The use of MERIS Terrestrial Chlorophyll Index to study spatio-temporal variation in vegetation phenology over India , 2010 .
[54] Deng Xiangzheng,et al. Landscape change detection in Yulin prefecture , 2004 .
[55] P. Ciais,et al. Leaf onset in the northern hemisphere triggered by daytime temperature , 2015, Nature Communications.