(b) Continued validation of coarse-to-high resolution LAI/FPAR products with
available and future acquisitions of field measurements in enhancing the
accuracy of the satellite-derived products. Field measurements that provide
synoptic knowledge about biome-specific spectral characteristics, will be an
integral part of product assessment efforts that feed into algorithm refinement.
(c) Utilization of high-resolution LAI products for estimating above ground biomass and Net Primary Productivity (NPP) estimates. Current algorithms in
fusing Landsat derived LAI and canopy height estimates from the ICESat
GLAS instrument have shown significant potential in estimating biomass over
forested regions.
(d) Enhancing the MODIS experience to Landsat LAI/FPAR products to monitor
long-term changes and trends in land surface characteristics due to climatic
variability and human-induced changes.
References
Asrar G, Fuchs M, Kanemasu ET, Hatfield JL (1984) Estimating absorbed photosynthetic
radiation and leaf-area index from spectral reflectance in wheat. Agron J 76(2):300–306
Baret F, Weiss M, Lacaze R, Camacho F, Makhmara H, Pacholcyzk P, Smets B (2013) GEOV1:
LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over
existing products. Part1: principles of development and production. Remote Sens Environ
137:299–309
Baret F, Weiss M, Lacaze R, Camacho F, Pacholcyzk P, Smets B (2010) Consistent and accurate
LAI, FAPAR, and FCover global products: principles and evaluation of GEOV1 products. In:
Proceedings of 3rd RAQRS, 27th Sept.- 1st Oct., Torrent, pp 208–213
Baret F, Hagolle O, Geiger B, Bicheron P, Miras B, Huc M, Berthelot B et al (2007) LAI, fAPAR
and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of
the algorithm. Remote Sens Environ 110(3):275–286. http://www.sciencedirect.com/science/
article/B6V6V-4NKJ1K0-1/2/29e421e7954752424d9bfbf9b697ca68
Bonan GB, Levis S, Sitch S, Vertenstein M, Oleson KW (2003) A dynamic global vegetation
model for use with climate models: concepts and description of simulated vegetation
dynamics. Glob Change Biol 9(11):1543–1566. doi:10.1046/j.1529-8817.2003.00681.x
Brown L, Chen JM, Leblanc SG, Cihlar J (2000) A shortwave infrared modification to the simple
ratio for LAI retrieval in boreal forests an image and model analysis. Remote Sens Environ
71(1):16–25. doi:10.1016/S0034-4257(99)00035-8
Brown M, Pinzon JE, Didan K, Morisette JT, Tucker CJ (2006) Evaluation of the consistency of
long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and
Landsat ETM ? sensors. IEEE Trans Geosci Remote Sens 44(7):1787–1793. doi:10.1109/
TGRS.2005.860205
Camacho F, Baret F, Cernicharo J, Lacaze R, Weiss M (2012) Quality assessment of the first
version of Geoland-2 biophysical variables produced at global scale. In: Sobrino J. (Ed.),
Third international symposium on recent advances in quantitative remote sensing. Torrent
Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and
leaf area index. Remote Sens Environ 62(3):241–252
Chander G, Huang C, Yang L, Homer C, Larson C (2009) Developing consistent landsat data sets
for large area applications: the mrlc 2001 protocol. IEEE Geosci Remote Sens Lett
6(4):777–781. doi:10.1109/LGRS.2009.2025244
2 Green Leaf Area and Fraction of Photosynthetically
57
available and future acquisitions of field measurements in enhancing the
accuracy of the satellite-derived products. Field measurements that provide
synoptic knowledge about biome-specific spectral characteristics, will be an
integral part of product assessment efforts that feed into algorithm refinement.
(c) Utilization of high-resolution LAI products for estimating above ground biomass and Net Primary Productivity (NPP) estimates. Current algorithms in
fusing Landsat derived LAI and canopy height estimates from the ICESat
GLAS instrument have shown significant potential in estimating biomass over
forested regions.
(d) Enhancing the MODIS experience to Landsat LAI/FPAR products to monitor
long-term changes and trends in land surface characteristics due to climatic
variability and human-induced changes.
References
Asrar G, Fuchs M, Kanemasu ET, Hatfield JL (1984) Estimating absorbed photosynthetic
radiation and leaf-area index from spectral reflectance in wheat. Agron J 76(2):300–306
Baret F, Weiss M, Lacaze R, Camacho F, Makhmara H, Pacholcyzk P, Smets B (2013) GEOV1:
LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over
existing products. Part1: principles of development and production. Remote Sens Environ
137:299–309
Baret F, Weiss M, Lacaze R, Camacho F, Pacholcyzk P, Smets B (2010) Consistent and accurate
LAI, FAPAR, and FCover global products: principles and evaluation of GEOV1 products. In:
Proceedings of 3rd RAQRS, 27th Sept.- 1st Oct., Torrent, pp 208–213
Baret F, Hagolle O, Geiger B, Bicheron P, Miras B, Huc M, Berthelot B et al (2007) LAI, fAPAR
and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of
the algorithm. Remote Sens Environ 110(3):275–286. http://www.sciencedirect.com/science/
article/B6V6V-4NKJ1K0-1/2/29e421e7954752424d9bfbf9b697ca68
Bonan GB, Levis S, Sitch S, Vertenstein M, Oleson KW (2003) A dynamic global vegetation
model for use with climate models: concepts and description of simulated vegetation
dynamics. Glob Change Biol 9(11):1543–1566. doi:10.1046/j.1529-8817.2003.00681.x
Brown L, Chen JM, Leblanc SG, Cihlar J (2000) A shortwave infrared modification to the simple
ratio for LAI retrieval in boreal forests an image and model analysis. Remote Sens Environ
71(1):16–25. doi:10.1016/S0034-4257(99)00035-8
Brown M, Pinzon JE, Didan K, Morisette JT, Tucker CJ (2006) Evaluation of the consistency of
long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and
Landsat ETM ? sensors. IEEE Trans Geosci Remote Sens 44(7):1787–1793. doi:10.1109/
TGRS.2005.860205
Camacho F, Baret F, Cernicharo J, Lacaze R, Weiss M (2012) Quality assessment of the first
version of Geoland-2 biophysical variables produced at global scale. In: Sobrino J. (Ed.),
Third international symposium on recent advances in quantitative remote sensing. Torrent
Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and
leaf area index. Remote Sens Environ 62(3):241–252
Chander G, Huang C, Yang L, Homer C, Larson C (2009) Developing consistent landsat data sets
for large area applications: the mrlc 2001 protocol. IEEE Geosci Remote Sens Lett
6(4):777–781. doi:10.1109/LGRS.2009.2025244
2 Green Leaf Area and Fraction of Photosynthetically
57