PHASE: A geostatistical model for the Kriging-based spatial prediction of crop phenology using public phenological and climatological observations
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Daniel Doktor | Cornelia Gläßer | Markus Möller | Henning Gerstmann | M. Möller | D. Doktor | C. Gläßer | H. Gerstmann
[1] J. Porter,et al. Effects of elevated CO2 and drought on wheat: testing crop simulation models for different experimental and climatic conditions , 2002 .
[2] Anton Vrieling,et al. Variability of African farming systems from phenological analysis of NDVI time series , 2011 .
[3] Annette Menzel,et al. Trends and temperature response in the phenology of crops in Germany , 2007 .
[4] L. F. Curtis,et al. Introduction to Environmental Remote Sensing. , 1978 .
[5] Gerrit Hoogenboom,et al. Relationship of base temperature to development of winter wheat , 2013 .
[6] J. Mustard,et al. Characterizing the landscape dynamics of an invasive plant and risk of invasion using remote sensing. , 2006, Ecological applications : a publication of the Ecological Society of America.
[7] Stefan Siebert,et al. Spatio-temporal patterns of phenological development in Germany in relation to temperature and day length , 2012 .
[8] Jennifer N. Hird,et al. Noise reduction of NDVI time series: An empirical comparison of selected techniques , 2009 .
[9] Jörg Kaduk,et al. Assessing the climate sensitivity of the global terrestrial carbon cycle model SILVAN , 1996 .
[10] Matthias Müller-Hannemann,et al. Parallelization strategies to deal with non-localities in the calculation of regional land-surface parameters , 2012, Comput. Geosci..
[11] Edzer J. Pebesma,et al. Real-time automatic interpolation of ambient gamma dose rates from the Dutch radioactivity monitoring network , 2009, Comput. Geosci..
[12] Roger Bivand,et al. Bindings for the Geospatial Data Abstraction Library , 2015 .
[13] Volker C. Radeloff,et al. The effect of Landsat ETM/ETM + image acquisition dates on the detection of agricultural land abandonment in Eastern Europe , 2012 .
[14] T. Pinto-Correia,et al. Mapping Soil Erosion Prevention Using an Ecosystem Service Modeling Framework for Integrated Land Management and Policy , 2014, Ecosystems.
[15] Jong-Sen Lee,et al. Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Weiwei Xiao,et al. Evaluating MODIS phenology product for rotating croplands through ground observations , 2013 .
[17] R. Lark,et al. Geostatistics for Environmental Scientists , 2001 .
[18] R. Lunetta,et al. Land-cover change detection using multi-temporal MODIS NDVI data , 2006 .
[19] R. Solantie,et al. Daytime temperature sum — a new thermal variable describing growing season characteristics and explaining evapotranspiration , 2004 .
[20] Peter Wick,et al. How to consider engineered nanomaterials in major accident regulations? , 2014, Environmental Sciences Europe.
[21] A. Roth,et al. The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar , 2003 .
[22] Heikki Hänninen,et al. A framework for modelling the annual cycle of trees in boreal and temperate regions , 2007 .
[23] O. Sonnentag,et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system , 2013 .
[24] Tim R. McVicar,et al. Determining temporal windows for crop discrimination with remote sensing: a case study in south-eastern Australia , 2004 .
[25] Jörg Schaber,et al. Physiology-based phenology models for forest tree species in Germany , 2003, International journal of biometeorology.
[26] Gregory Asner,et al. Applications of Remote Sensing to Alien Invasive Plant Studies , 2009, Sensors.
[27] P. Levelt,et al. ESA's sentinel missions in support of Earth system science , 2012 .
[28] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[29] Saskia Foerster,et al. Crop type mapping using spectral-temporal profiles and phenological information , 2012 .
[30] Miriam J. Metzger,et al. The credibility of volunteered geographic information , 2008 .
[31] F. Wielgolaski,et al. Starting dates and basic temperatures in phenological observations of plants , 1999 .
[32] José A. Sobrino,et al. Phenology Estimation From Meteosat Second Generation Data , 2013, IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens..
[33] Gustavo A. Slafer,et al. Base and optimum temperatures vary with genotype and stage of development in wheat , 1995 .
[34] Frank Ewert,et al. Effects of data aggregation on simulations of crop phenology , 2011 .
[35] Mark D. Schwartz,et al. Phenology: An Integrative Environmental Science , 2013, Springer Netherlands.
[36] Ray D. Jackson,et al. Extending the "degree day" concept of plant phenological development to include water stress effects , 1978 .
[37] Gregory S. McMaster,et al. Phenological responses of wheat and barley to water and temperature: improving simulation models , 2003, The Journal of Agricultural Science.
[38] Heikki Hänninen,et al. Plant Development Models , 2013 .
[39] J. F. Power,et al. Growth Analysis Based on Degree Days , 1984 .
[40] I. Leinonen,et al. The importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean forests ecosystems: an overview , 2000, International journal of biometeorology.
[41] Lars Eklundh,et al. Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology , 2010 .
[42] LeeJong-Sen. Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980 .
[43] Cornelia Gläßer,et al. Optimization of spectral indices and long-term separability analysis for classification of cereal crops using multi-spectral RapidEye imagery , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[44] Enli Wang,et al. Simulation of phenological development of wheat crops , 1998 .
[45] Albert Weiss,et al. Understanding and modeling the effect of temperature and daylength on soybean phenology under high-yield conditions , 2007 .
[46] R. Zurita-Milla,et al. Developing a Workflow to Identify Inconsistencies in Volunteered Geographic Information: A Phenological Case Study , 2015, PloS one.
[47] Antje Müller,et al. Climate changes and trends in phenology of fruit trees and field crops in Germany, 1961-2000 , 2004 .
[48] Hong Jiang,et al. Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach. , 2011, Ecology letters.
[49] W. Wilhelm,et al. Growing degree-days: one equation, two interpretations , 1997 .
[50] Tomislav Hengl,et al. A practical guide to geostatistical mapping of environmental variables , 2007 .
[51] Meifang Zhao,et al. Plant phenological modeling and its application in global climate change research: overview and future challenges , 2013 .
[52] Kevin P. Price,et al. Remote Sensing of Cropland Agriculture , 2009 .
[53] W. J. Thompson,et al. An analysis of primordium initiation in Avalon winter wheat crops with different sowing dates and at nine sites in England and Scotland , 1987, The Journal of Agricultural Science.
[54] Roger Woodard,et al. Interpolation of Spatial Data: Some Theory for Kriging , 1999, Technometrics.
[55] Winfried Schröder,et al. Modelling and mapping of plant phenological stages as bio-meteorological indicators for climate change , 2014, Environmental Sciences Europe.
[56] Victor F. Rodriguez-Galiano,et al. Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data , 2015, Remote. Sens..
[57] D. Krige. A statistical approach to some basic mine valuation problems on the Witwatersrand, by D.G. Krige, published in the Journal, December 1951 : introduction by the author , 1951 .
[58] A. Strahler,et al. Monitoring vegetation phenology using MODIS , 2003 .
[59] Edzer J. Pebesma,et al. Multivariable geostatistics in S: the gstat package , 2004, Comput. Geosci..
[60] Stefano Tasselli,et al. Effects of Carbon Nanotube Environmental Dispersion on an Aquatic Invertebrate, Hirudo medicinalis , 2015, PloS one.
[61] Senshan Yang,et al. Mathematical formulae for calculating the base temperature for growing degree days , 1995 .
[62] J. Porter,et al. A comparison of the models AFRCWHEAT2, CERES-Wheat, Sirius, SUCROS2 and SWHEAT with measurements from wheat grown under drought , 1998 .
[63] I. C. Prentice,et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .
[64] Thuy Le Toan,et al. Bud‐burst modelling in Siberia and its impact on quantifying the carbon budget , 2005, Global change biology.
[65] Sönke Müller,et al. Phenological structuring of multi-temporal rapideye imagergy , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.
[66] Gerard B. M. Heuvelink,et al. About regression-kriging: From equations to case studies , 2007, Comput. Geosci..
[67] G. Slafer,et al. Developmental Base Temperature in Different Phenological Phases of Wheat (Triticum aestivum) , 1991 .
[68] Max Kuhn,et al. Applied Predictive Modeling , 2013 .
[69] Patrick J. Guertin,et al. Organizing phenological data resources to inform natural resource conservation , 2014 .
[70] M. Fladeland,et al. Remote sensing for biodiversity science and conservation , 2003 .
[71] L. D. Bailey,et al. Fertility management in canola production , 1993 .
[72] Jeffrey W. White,et al. Simulating Crop Phenological Responses to Water Deficits , 2015 .
[73] G. Farquhar,et al. Foliar stage in wheat correlates better to photothermal time than to thermal time , 1989 .
[74] Wenping Yuan,et al. Comparison of Phenology Models for Predicting the Onset of Growing Season over the Northern Hemisphere , 2014, PloS one.
[75] Ralf Seppelt,et al. Simulation of forest tree species’ bud burst dates for different climate scenarios: chilling requirements and photo-period may limit bud burst advancement , 2016, International Journal of Biometeorology.
[76] Matthias Drusch,et al. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .
[77] Eike Luedeling,et al. Validation of winter chill models using historic records of walnut phenology , 2009 .
[78] Feng Gao,et al. Coupling of phenological information and synthetically generated time-series for crop types as indicator for vegetation coverage information , 2015, 2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp).