Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology

This chapter surveys 12 different spatio-temporal statistical methods to determine the start and end of the growing season using a time series of satellite images. In the first section of the chapter, we divided the methods into four categories: thresholds, derivatives, smoothing functions, and fitted models. The general use, advantages, and potential limitations of each method are discussed. In the second section of the chapter, a case study is presented to highlight one method from each category. The four study areas range from the Northwest Territories in Canada to the winter wheat areas in south-central Kansas. We concluded the case study with a discussion of the differences in results for the four methods. The chapter is finished with a synopsis discussing the use of nomenclature, the problems with a lack of statistical error structure from most methods, and the perennial issue of oversmoothing.

[1]  D. Legates,et al.  Crop identification using harmonic analysis of time-series AVHRR NDVI data , 2002 .

[2]  Geoffrey M. Henebry,et al.  Land surface phenology and temperature variation in the International Geosphere–Biosphere Program high‐latitude transects , 2005 .

[3]  de Beurs,et al.  A statistical framework for the analysis of long image time series , 2005 .

[4]  Ramakrishna R. Nemani,et al.  Real-time monitoring and short-term forecasting of land surface phenology , 2006 .

[5]  J. Mustard,et al.  Cross-scalar satellite phenology from ground, Landsat, and MODIS data , 2007 .

[6]  S. Running,et al.  A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .

[7]  D. Roberts,et al.  Spectral shape-based temporal compositing algorithms for MODIS surface reflectance data , 2007 .

[8]  Jesslyn F. Brown,et al.  Measuring phenological variability from satellite imagery , 1994 .

[9]  C. Chatfield,et al.  Fourier Analysis of Time Series: An Introduction , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  John F. Mustard,et al.  A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data , 2007 .

[11]  Ranga B. Myneni,et al.  Analysis of interannual changes in northern vegetation activity observed in AVHRR data from 1981 to 1994 , 2002, IEEE Trans. Geosci. Remote. Sens..

[12]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[13]  K. Beurs,et al.  Evaluation of multi-sensor semi-arid crop season parameters based on NDVI and rainfall , 2008 .

[14]  Aaron Moody,et al.  Land-Surface Phenologies from AVHRR Using the Discrete Fourier Transform , 2001 .

[15]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[16]  Jürgen Symanzik,et al.  On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models , 2007 .

[17]  P. Rich,et al.  Phenology of mixed woody-herbaceous ecosystems following extreme events: net and differential responses. , 2008, Ecology.

[18]  Stein Rune Karlsen,et al.  Satellite‐based mapping of the growing season and bioclimatic zones in Fennoscandia , 2006 .

[19]  R. Tateishi,et al.  Analysis of phenological change patterns using 1982–2000 Advanced Very High Resolution Radiometer (AVHRR) data , 2004 .

[20]  D. Lloyd,et al.  A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery , 1990 .

[21]  Robert E. Wolfe,et al.  An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series , 2008, IEEE Geoscience and Remote Sensing Letters.

[22]  R. Ahas,et al.  Onset of spring starting earlier across the Northern Hemisphere , 2006 .

[23]  Jan Verbesselt,et al.  Evaluating satellite and climate data-derived indices as fire risk indicators in savanna ecosystems , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[24]  A. Fischer A model for the seasonal variations of vegetation indices in coarse resolution data and its inversion to extract crop parameters , 1994 .

[25]  G. Badhwar,et al.  Use of LANDSAT-derived profile features for spring small-grains classification , 1984 .

[26]  John Townshend,et al.  Multitemporal Dimensionality of Images of Normalized Difference Vegetation Index at Continental Scales , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[27]  John F. Hermance,et al.  Stabilizing high‐order, non‐classical harmonic analysis of NDVI data for average annual models by damping model roughness , 2007 .

[28]  Nadège Martiny,et al.  Characterization of the Interannual and Intraseasonal Variability of West African Vegetation between 1982 and 2002 by Means of NOAA AVHRR NDVI Data , 2007 .

[29]  C. Samimi,et al.  Assessing spatio‐temporal variations in plant phenology using Fourier analysis on NDVI time series: results from a dry savannah environment in Namibia , 2006 .

[30]  Benjamin W. Heumann,et al.  AVHRR Derived Phenological Change in the Sahel and Soudan, Africa, 1982 - 2005 , 2007 .

[31]  F. Kogan Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data , 1995 .

[32]  Mryka Hall-Beyer,et al.  Comparison of single-year and multiyear NDVI time series principal components in cold temperate biomes , 2003, IEEE Trans. Geosci. Remote. Sens..

[33]  Per Jönsson,et al.  Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..

[34]  Ranga B. Myneni,et al.  Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS , 2006 .

[35]  G. Henebry,et al.  Northern Annular Mode Effects on the Land Surface Phenologies of Northern Eurasia , 2008 .

[36]  Heiko Balzter,et al.  Coupling of Vegetation Growing Season Anomalies and Fire Activity with Hemispheric and Regional-Scale Climate Patterns in Central and East Siberia , 2007 .

[37]  Per Jönsson,et al.  TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..

[38]  J. Eastman,et al.  Long sequence time series evaluation using standardized principal components , 1993 .

[39]  Stein Rune Karlsen,et al.  Variability of the start of the growing season in Fennoscandia, 1982–2002 , 2007, International journal of biometeorology.

[40]  C. Tucker,et al.  Increased plant growth in the northern high latitudes from 1981 to 1991 , 1997, Nature.

[41]  G. Henebry Grasslands of the North American Great Plains , 2003 .

[42]  H. Fritz,et al.  Cover: On the nature of the South Tibetan Detachment Zone (STDZ), Kumaun Himalayas , 2006 .

[43]  David P. Roy,et al.  Generating a long-term land data record from the AVHRR and MODIS Instruments , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[44]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[45]  R. J. Scholes,et al.  Leaf green-up in a semi-arid African savanna –separating tree and grass responses to environmental cues , 2007 .

[46]  A. Strahler,et al.  Climate controls on vegetation phenological patterns in northern mid‐ and high latitudes inferred from MODIS data , 2004 .

[47]  P. Beck,et al.  Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI , 2006 .

[48]  M. D. Schwartz Phenology: An Integrative Environmental Science , 2003, Tasks for Vegetation Science.

[49]  Mark D. Schwartz,et al.  Changes in North American spring , 2000 .

[50]  J. Mustard,et al.  Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .

[51]  Geoffrey M. Henebry,et al.  Trend analysis of the Pathfinder AVHRR Land (PAL) NDVI data for the deserts of central Asia , 2004, IEEE Geoscience and Remote Sensing Letters.

[52]  P. Ciais,et al.  Variations in satellite‐derived phenology in China's temperate vegetation , 2006 .

[53]  Robert B. Mitchell,et al.  Predicting Forage Quality in Switchgrass and Big Bluestem , 2001 .

[54]  G. Henebry,et al.  Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan , 2004 .

[55]  C. Tucker,et al.  Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999 , 2001, International journal of biometeorology.

[56]  F. Csillag,et al.  A comparison of three approaches for predicting C4 species cover of northern mixed grass prairie , 2003 .

[57]  Ranga B. Myneni,et al.  Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999 , 2003 .

[58]  Alexander J. Smart,et al.  Predicting Leaf/Stem Ratio and Nutritive Value in Grazed and Nongrazed Big Bluestem , 2001 .

[59]  N. Delbart,et al.  Determination of phenological dates in boreal regions using normalized difference water index , 2005 .

[60]  G. Dedieu,et al.  Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements , 1997 .

[61]  S. Kalluri,et al.  The Pathfinder AVHRR land data set: An improved coarse resolution data set for terrestrial monitoring , 1994 .

[62]  F. Wielgolaski,et al.  Starting dates and basic temperatures in phenological observations of plants , 1999 .

[63]  Mark D. Schwartz,et al.  Assessing satellite‐derived start‐of‐season measures in the conterminous USA , 2002 .

[64]  Geoffrey M. Henebry Advantages of principal components analysis for land cover segmentation from SAR image series , 1997 .

[65]  G. Henebry,et al.  A technique for monitoring ecological disturbance in tallgrass prairie using seasonal NDVI trajectories and a discriminant function mixture model , 1997 .

[66]  Bradley C. Reed,et al.  Remote Sensing Phenology , 2009 .