Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS

Climate change is predicted to alter the canopy phenology of temperate and boreal forests, which will affect carbon, water, and energy budgets. Therefore, there is a great need to evaluate remotely sensed products for their potential to accurately capture canopy dynamics. The objective of this study was to compare several products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) to field measurements of fraction photosynthetically active radiation (FPAR) and plant area index (PAI) for a deciduous broadleaf forest in northern Wisconsin in 2002. MODIS products captured the general phenological development of the canopy although MODIS products overestimated the leaf area during the overstory leaf out period. Field data suggest that the period from budburst to canopy maturity, or maximum PAI, occurred in 10 to 12 days while MODIS products predicted onset of greenness and maturity from 1 to 21 days and 0 to 19 days earlier than that from field observations, respectively. Temporal compositing of MODIS data and understory development are likely key factors explaining differences with field data. Maximum PAI estimates differed only by 7% between field derived and MODIS-based estimates of LAI. Implications for ecosystem modeling of carbon and water exchange and future research needs are discussed.

[1]  C. Tucker,et al.  Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999 , 2001 .

[2]  F. Shahrokhi Remote sensing of earth resources , 1972 .

[3]  N. Carolina. EFFECTS OF GLOBAL WARMING ON , 2008 .

[4]  Ranga B. Myneni,et al.  Analysis and optimization of the MODIS leaf area index algorithm retrievals over broadleaf forests , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Y. Knyazikhin,et al.  Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions , 2003 .

[6]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

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

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

[9]  N. Tremblay,et al.  Seasonal Dynamics of Understory Vegetation in Four Eastern Canadian Forest Types , 2001, International Journal of Plant Sciences.

[10]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[11]  Jeremy K. Leggett,et al.  Global warming: The Greenpeace report , 1990 .

[12]  Ranga B. Myneni,et al.  Analysis of leaf area index and fraction of PAR absorbed by vegetation products from the terra MODIS sensor: 2000-2005 , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[13]  R. Gifford,et al.  The global carbon cycle: a viewpoint on the missing sink , 1994 .

[14]  John M. Norman,et al.  Application of Geostatistics to Characterize Leaf Area Index (LAI) from Flux Tower to Landscape Scales Using a Cyclic Sampling Design , 2002, Ecosystems.

[15]  Y. Knyazikhin,et al.  Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests , 2003 .

[16]  S. T. Gower,et al.  Direct and Indirect Estimation of Leaf Area Index, fAPAR, and Net Primary Production of Terrestrial Ecosystems , 1999 .

[17]  P. Reich,et al.  Trade-offs in seedling survival, growth, and physiology among hardwood species of contrasting successional status along a light-availability gradient , 2001 .

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

[19]  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..

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

[21]  C. Girard Estimation of phenological stages and physiological states of grasslands from remote sensing data , 1982, Vegetatio.

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

[23]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[24]  S. Running,et al.  Satellite Evidence of Phenological Differences Between Urbanized and Rural Areas of the Eastern United States Deciduous Broadleaf Forest , 2002, Ecosystems.

[25]  P. Reich,et al.  Acclimation of respiration to temperature and CO2 in seedlings of boreal tree species in relation to plant size and relative growth rate , 1999 .

[26]  K. Davis,et al.  Component and whole-system respiration fluxes in northern deciduous forests. , 2004, Tree physiology.

[27]  Ramakrishna R. Nemani,et al.  Canopy duration has little influence on annual carbon storage in the deciduous broad leaf forest , 2003 .

[28]  J. Rea,et al.  Phenological evaluations using Landsat—1 sensors , 1976 .

[29]  P. Reich,et al.  Leaf age and season influence the relationships between leaf nitrogen, leaf mass per area and photosynthesis in maple and oak trees , 1991 .

[30]  J. Morison,et al.  Seasonal changes in the photosynthetic capacity of canopy oak (Quercus robur) leaves: the impact of slow development on annual carbon uptake , 2003, International journal of biometeorology.

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

[32]  Rasmus Fensholt,et al.  MODIS leaf area index products: from validation to algorithm improvement , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[33]  C. Justice,et al.  Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation , 1997 .

[34]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[35]  P. Newton,et al.  Reduced water repellency of a grassland soil under elevated atmospheric CO2 , 2004 .

[36]  Christopher B. Field,et al.  Environmental control of leaf area production: Implications for vegetation and land‐surface modeling , 2003 .

[37]  B. Sigurdsson Elevated [CO2] and nutrient status modified leaf phenology and growth rhythm of young Populus trichocarpa trees in a 3-year field study , 2001, Trees.

[38]  S. N. Burrows,et al.  Spatial variability of aboveground net primary production for a forested landscape in northern Wisconsin , 2003 .

[39]  Steven W. Running,et al.  A regional phenology model for detecting onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index , 2003 .

[40]  S. Gower,et al.  Interrelationships among the edaphic and stand characteristics, leaf area index, and aboveground net primary production of upland forest ecosystems in north central Wisconsin , 1997 .