Finally, it is worth mentioning the integration of LSP products into habitat
assessment; including both the evaluation of plant species habitat with a time
series of deca-resolution imagery (Evangelista et al. 2009) to animal species using
kilo-resolution LSP products (Herfindal et al. 2006). The use of LSP products in
habitat modeling can provide spatial predictions of species habitat at higher levels
of ecological complexity, including the consideration of functional groups and
species assemblages (Guisan and Thuiller 2005).
This section has described some of the foundational work in LSP research and
some potential future directions. With the various challenges and opportunities
related to this research, it is exciting to consider future research directions for LSP.
As we head into the future there will be an ever-longer time series of satellite data
from which to extract phenology metrics and look for trends across multiple
decades. The expanding size, coordination, and communication among the groundbased phenological networks will offer opportunities for the validation of LSP
products as well as a larger community of users who can use and understand LSP
products. Finally, with the extended time series and a stronger connection to
ground-based observations, it is likely that LSP can provide substantial input to
improve carbon, climate, and ecological models.
References
Ahl DE, Gower ST, Burrows SN, Shabanov NV, Myneni RB, Knyazikhin Y (2006) Monitoring
spring canopy phenology of a deciduous broadleaf forest using MODIS. Remote Sens Environ
104:88–95. doi:10.1016/j.rse.2006.05.003
Anderson BT, Strahler A (2008) Visualizing weather and climate. Wiley, New York
Baldocchi DD, Black TA, Curtis PS, Falge E, Fuentes JD, Granier A, Gu L, Knohl A, Pilegaard
K, Schmid HP, Valentini R, Wilson K, Wofsy S, Xu L, Yamamoto S (2005) Predicting the
onset of net carbon uptake by deciduous forests with soil temperature and climate data: a
synthesis of FLUXNET data. Int J Biometeorol 49:377–387. doi:10.1007/s00484-005-0256-4
Beck PSA, Atzberger C, Høgda KA, Johansen B, Skidmore AK (2006) Improved monitoring of
vegetation dynamics at very high latitudes: a new method using MODIS NDVI. Remote Sens
Environ 100:321–334. doi:10.1016/j.rse.2005.10.021
Bradley BA, Jacob RW, Hermance JF, Mustard JF (2007) A curve fitting procedure to derive
inter-annual phenologies from time series of noisy satellite NDVI data. Remote Sens Environ
106:137–145. doi:10.1016/j.rse.2006.08.002
Burrows S, Gower S, Clayton M, Mackay D, Ahl D, Norman JM & Diak G (2002) Application of
geostatistics to characterize leaf area index (LAI) from flux tower to landscape scales using a
cyclic sampling design. Ecosystems, 5:667–679
Cao C, Xiong X, Wu A, Wu X (2008) Assessing the consistency of AVHRR and MODIS L1B
reflectance for generating fundamental climate data records. J Geophys Res Atmos
113:D09114. doi:10.1029/2007JD009363
Castro KL, Sanchez-Azofeifa GA (2008) Changes in spectral properties, chlorophyll content and
internal mesophyll structure of senescing Populus balsamifera and Populus tremuloides
leaves. Sensors 8:51–69
Clark RN, Swayze GA, Wise R, Livo KE, Hoefen TM, Kokaly RF, Sutley SJ (2007) USGS
digital spectral library splib06a. U.S. Geological Survey, Data series 231
4 Land Surface Phenology
119
assessment; including both the evaluation of plant species habitat with a time
series of deca-resolution imagery (Evangelista et al. 2009) to animal species using
kilo-resolution LSP products (Herfindal et al. 2006). The use of LSP products in
habitat modeling can provide spatial predictions of species habitat at higher levels
of ecological complexity, including the consideration of functional groups and
species assemblages (Guisan and Thuiller 2005).
This section has described some of the foundational work in LSP research and
some potential future directions. With the various challenges and opportunities
related to this research, it is exciting to consider future research directions for LSP.
As we head into the future there will be an ever-longer time series of satellite data
from which to extract phenology metrics and look for trends across multiple
decades. The expanding size, coordination, and communication among the groundbased phenological networks will offer opportunities for the validation of LSP
products as well as a larger community of users who can use and understand LSP
products. Finally, with the extended time series and a stronger connection to
ground-based observations, it is likely that LSP can provide substantial input to
improve carbon, climate, and ecological models.
References
Ahl DE, Gower ST, Burrows SN, Shabanov NV, Myneni RB, Knyazikhin Y (2006) Monitoring
spring canopy phenology of a deciduous broadleaf forest using MODIS. Remote Sens Environ
104:88–95. doi:10.1016/j.rse.2006.05.003
Anderson BT, Strahler A (2008) Visualizing weather and climate. Wiley, New York
Baldocchi DD, Black TA, Curtis PS, Falge E, Fuentes JD, Granier A, Gu L, Knohl A, Pilegaard
K, Schmid HP, Valentini R, Wilson K, Wofsy S, Xu L, Yamamoto S (2005) Predicting the
onset of net carbon uptake by deciduous forests with soil temperature and climate data: a
synthesis of FLUXNET data. Int J Biometeorol 49:377–387. doi:10.1007/s00484-005-0256-4
Beck PSA, Atzberger C, Høgda KA, Johansen B, Skidmore AK (2006) Improved monitoring of
vegetation dynamics at very high latitudes: a new method using MODIS NDVI. Remote Sens
Environ 100:321–334. doi:10.1016/j.rse.2005.10.021
Bradley BA, Jacob RW, Hermance JF, Mustard JF (2007) A curve fitting procedure to derive
inter-annual phenologies from time series of noisy satellite NDVI data. Remote Sens Environ
106:137–145. doi:10.1016/j.rse.2006.08.002
Burrows S, Gower S, Clayton M, Mackay D, Ahl D, Norman JM & Diak G (2002) Application of
geostatistics to characterize leaf area index (LAI) from flux tower to landscape scales using a
cyclic sampling design. Ecosystems, 5:667–679
Cao C, Xiong X, Wu A, Wu X (2008) Assessing the consistency of AVHRR and MODIS L1B
reflectance for generating fundamental climate data records. J Geophys Res Atmos
113:D09114. doi:10.1029/2007JD009363
Castro KL, Sanchez-Azofeifa GA (2008) Changes in spectral properties, chlorophyll content and
internal mesophyll structure of senescing Populus balsamifera and Populus tremuloides
leaves. Sensors 8:51–69
Clark RN, Swayze GA, Wise R, Livo KE, Hoefen TM, Kokaly RF, Sutley SJ (2007) USGS
digital spectral library splib06a. U.S. Geological Survey, Data series 231
4 Land Surface Phenology
119