Brandt, M., Mbow, C., Diouf, A. A., Verger, A., Samimi, C., and Fensholt, R.:
Ground- and satellite-based evidence of the biophysical mechanisms behind
the greening Sahel, Press, 2015.
Brown, M. E., Pinzon, J. E., Didan, K., Morisette, J. T., and Tucker, C. J.:
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, 1787–1793, 2006.
Brown, M. E., de Beurs, K. M., and Marshall, M.: Global phenological response
to climate change in crop areas using satellite remote sensing of
vegetation, humidity and temperature over 26 years, Remote Sens. Environ.,
126, 174–183, 2012.
Cihlar, J., Ly, H., Li, Z., Chen, J., Pokrant, H., and Huang, F.:
Multitemporal, multichannel AVHRR data sets for land biosphere
studies – Artifacts and corrections, Remote Sens. Environ., 60, 35–57,
1997.
De Jong, R., de Bruin, S., de Wit, A., Schaepman, M. E., and Dent, D. L.:
Analysis of monotonic greening and browning trends from global NDVI
time-series, Remote Sens. Environ., 115, 692–702, 2011.
De Jong, R., Verbesselt, J., Schaepman, M. E., and de Bruin, S.: Trend
changes in global greening and browning: contribution of short-term trends
to longer-term change, Glob. Change Biol., 18, 642–655, 2012.
Didan, K.: Multi-Satellite Earth Science Data Record for Studying Global
Vegetation Trends and changes, The University of Arizona, Tucson, AZ, 2014.
Eastman, R., Sangermano, F., Ghimire, B., Zhu, H., Chen, H., Neeti, N., Cai,
Y., Machado, E. A., and Crema, S. C.: Seasonal trend analysis of image time
series, Int. J. Remote Sens., 30, 2721–2726, 2009.
El Saleous, N. Z., Vermote, E. F., Justice, C. O., Townshend, J. R. G.,
Tucker, C. J., and Goward, S. N.: Improvements in the global biospheric
record from the Advanced Very High Resolution Radiometer (AVHRR), Int. J.
Remote Sens., 21, 1251–1277, 2000.
Fensholt, R., Sandholt, I., and Stisen, S.: Evaluating MODIS, MERIS, and
vegetation indices using in situ measurements in a semiarid environment,
IEEE Trans. Geosci. Remote Sens., 44, 1774–1786, 2006.
Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the
land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data,
validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901–919,
2008.
Friedl, M. A., Davis, F. W., Michaelsen, J., and Moritz, M. A.: Scaling and
uncertainty in the relationship between the NDVI and land surface
biophysical variables: An analysis using a scene simulation model and data
from FIFE, Remote Sens. Environ., 5, 233–246, 1995.
Gao, X., Huete, A. R., Ni, W., and Miura, T.: Optical–Biophysical
Relationships of Vegetation Spectra without Background Contamination, Remote
Sens. Environ., 74, 609–620, 2000.
Giannini, A., Salack, S., Lodoun, T., Ali, A., Gaye, A. T., and Ndiaye, O.: A
unifying view of climate change in the Sahel linking intra-seasonal,
interannual and longer time scales, Environ. Res. Lett., 8, 024010–024018, https://doi.org/10.1088/1748-9326/8/2/024010, 2013.
Gilbert, R. O.: Statistical Methods for Environmental Pollution Monitoring,
John Wiley & Sons, New York, NY, 1987.
Glenn, E. P., Huete, A. R., Nagler, P. L., and Nelson, S. G.: Relationship
Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant
Physiological Processes: What Vegetation Indices Can and Cannot Tell Us
About the Landscape, Sensors, 8, 2136–2160, 2008.
Goetz, S. J., Bunn, A. G., Fiske, G. J., and Houghton, R. A.:
Satellite-observed photosynthetic trends across boreal North America
associated with climate and fire disturbance, P. Natl. Acad. Sci. USA., 102, 13521–13525, 2005.
Guay, K. C., Beck, P. S. A., Berner, L. T., Goetz, S. J., Baccini, A., and
Buermann, W.: Vegetation productivity patterns at high northern latitudes: a
multi-sensor satellite data assessment, Glob. Change Biol., 20,
3147–3158, 2014.
Gutman, G. and Ignatov, A.: The derivation of the green vegetation fraction
from NOAA/AVHRR data for use in numerical weather prediction models, Int. J.
Remote Sens., 19, 1533–1543, 1998.
Hall, F., Masek, J. G., and Collatz, G. J.: Evaluation of ISLSCP Initiative
II FASIR and GIMMS NDVI products and implications for carbon cycle science,
J. Geophys. Res.-Atmos., 111, D22S08, https://doi.org/10.1029/2006JD007438, 2006.
Hall, F. G., Huemmrich, K. F., Goetz, S. J., Sellers, P. J., and Nickeson, J.
E.: Satellite remote sensing of surface energy balance: Success, failures,
and unresolved issues in FIFE, J. Geophys. Res.-Atmos., 97,
19061–19089, 1992.
Holben, B. N.: Characteristics of maximum-value composite images from
temporal AVHRR data, Int. J. Remote Sens., 7, 1417–1434, 1986.
Huete, A.: A soil-adjusted vegetation index (SAVI), Remote Sens. Environ.,
25, 295–309, 1988.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L.
G.: Overview of the radiometric and biophysical performance of the MODIS
vegetation indices, Remote Sens. Environ., 83, 195–213, 2002.
Huete, A., Kim, H.-J., and Miura, T.: Scaling dependencies and uncertainties
in vegetation index – biophysical retrievals in heterogeneous environments,
in Geoscience and Remote Sensing Symposium, 2005, IGARSS '05, Proceedings
2005 IEEE International, 7, 5029–5032, 2005.
Huete, A., Didan, K., Leeuwen, W. van, Miura, T., and Glenn, E.: MODIS
Vegetation Indices, in: Land Remote Sensing and Global Environmental Change,
edited by: Ramachandran, B., Justice, C. O., and Abrams, M. J., 579–602,
Springer New York, 2010.
Jiang, L., Kogan, F. N., Guo, W., Tarpley, J. D., Mitchell, K. E., Ek, M.
B., Tian, Y., Zheng, W., Zou, C.-Z., and Ramsay, B. H.: Real-time weekly
global green vegetation fraction derived from advanced very high resolution
radiometer-based NOAA operational global vegetation index (GVI) system, J. Geophys. Res.-Atmos., 115, D11114, https://doi.org/10.1111/j.1365-2486.2011.02397.x, 2010.
Jiang, Z., Huete, A. R., Chen, J., Chen, Y., Li, J., Yan, G., and Zhang, X.:
Analysis of NDVI and scaled difference vegetation index retrievals of
vegetation fraction, Remote Sens. Environ., 101, 366–378, 2006.
Jiang, Z., Huete, A. R., Didan, K., and Miura, T.: Development of a two-band
enhanced vegetation index without a blue band, Remote Sens. Environ.,
112, 3833–3845, 2008.
Kandasamy, S., Baret, F., Verger, A., Neveux, P., and Weiss, M.: A comparison of methods for smoothing and gap
filling time series of remote sensing observations – application to MODIS LAI products, Biogeosciences, 10, 4055–4071, https://doi.org/10.5194/bg-10-4055-2013,
2013.
Kang, Y., Ozdogan, M., Zipper, S. C., Roman, M. O., Walker, J., Youn Hong,
S., Marshall, M., Magliulo, V., Moreno, J., Alonso, L., Miyata, A., Kimbal,
B., and Loheide, S. P.: How Universal is the Relationship between Remotely
Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment,
Remote Sens. Environ. Press, 2015.
Karnieli, A., Bayasgalan, M., Bayarjargal, Y., Agam, N., Khudulmur, S., and
Tucker, C. J.: Comments on the use of the Vegetation Health Index over
Mongolia, Int. J. Remote Sens., 27, 2017–2024, 2006.
Marshall, M. and Thenkabail, P.: Developing in situ Non-Destructive
Estimates of Crop Biomass to Address Issues of Scale in, Remote Sens., 7,
808–835,
2015.
Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G.,
Huemmrich, K. F., Gao, F., Kutler, J., and Lim, T.-K.: A Landsat surface
reflectance dataset for North America, 1990–2000, IEEE Geosci. Remote Sens.
Lett., 3, 68–72, 2006.
Mayaux, P., Pekel, J.-F., Desclée, B., Donnay, F., Lupi, A., Achard, F.,
Clerici, M., Bodart, C., Brink, A., Nasi, R., and Belward, A.: State and
evolution of the African rainforests between 1990 and 2010, Philos. Trans.
R. Soc. B, 368, 20120300, https://doi.org/10.1098/rstb.2012.0300 , 2013.
Monsi, M. and Saeki, T.: Über den Lichtfaktor in den
Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion, Jpn.
J. Bot., 14, 22–52, 1953.
Moulin, S., Kergoat, L., Viovy, N., and Dedieu, G.: Global-Scale Assessment
of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements, J. Clim.,
10, 1154–1170, 1997.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global
evapotranspiration algorithm based on MODIS and global meteorology data,
Remote Sens. Environ., 111, 519–536, 2007.
Myneni, R., Hoffman, S., Knyazikhin, Y., Privette, J., Glassy, J., Tian,
Y., Wang, Y., Song, X., Zhang, Y., Smith, G., Lotsch, A., Friedl, M.,
Morisette, J., Votava, P., Nemani, R., and Running, S.: Global products
of vegetation leaf area and fraction absorbed PAR from year one of MODIS
data, Remote Sens. Environ., 83, 214–231, 2002.
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C.,
Tucker, C. J., Myneni, R. B., and Running, S. W.: Climate-Driven Increases in
Global Terrestrial Net Primary Production from 1982 to 1999, Science,
300, 1560–1563, 2003.
Paruelo, J. M., Garbulsky, M. F., Guerschman, J. P., and Jobbágy, E. G.:
Two decades of Normalized Difference Vegetation Index changes in South
America: identifying the imprint of global change, Int. J. Remote Sens.,
25, 2793–2806, 2004.
Pedelty, J., Devadiga, S., Masuoka, E., Brown, M., Pinzon, J., Tucker, C.,
Roy, D., Ju, J., Vermote, E., Prince, S., Nagol, J., Justice, C., Schaaf,
C., Liu, J., Privette, J., and Pinheiro, A.: Generating a long-term land data
record from the AVHRR and MODIS Instruments, in Geoscience and Remote
Sensing Symposium, 2007, IGARSS 2007, IEEE International, 1021–1025,
2007.
Peischl, S., Walker, J. P., Rüdiger, C., Ye, N., Kerr, Y. H., Kim, E., Bandara, R., and Allahmoradi, M.: The AACES
field experiments: SMOS calibration and validation across the Murrumbidgee River catchment, Hydrol. Earth Syst. Sci., 16, 1697–1708, https://doi.org/10.5194/hess-16-1697-2012, 2012.
Quillet, A., Peng, C., and Garneau, M.: Toward dynamic global vegetation
models for simulating vegetation–climate interactions and feedbacks: recent
developments, limitations, and future challenges, Environ. Rev., 18,
333–353, 2010.
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the
planet: 1. Geographic distribution of global agricultural lands in the year
2000, Global Biogeochem. Cy., 22, GB1003, https://doi.org/10.1029/2007GB002952, 2008.
Rao, C. R. N. and Chen, J.: Inter-satellite calibration linkages for the
visible and near-infared channels of the Advanced Very High Resolution
Radiometer on the NOAA-7, -9, and -11 spacecraft, Int. J. Remote Sens.,
16, 1931–1942, 1995.
Rao, C. R. N. and Chen, J.: Post-launch calibration of the visible and
near-infrared channels of the Advanced Very High Resolution Radiometer on
the NOAA-14 spacecraft, Int. J. Remote Sens., 17, 2743–2747, 1996.
Rocha, A. V. and Shaver, G. R.: Advantages of a two band EVI calculated from
solar and photosynthetically active radiation fluxes, Agric. For. Meteorol.,
149, 1560–1563, 2009.
Rouse, J. W.: Monitoring the vernal advancement and retrogradation (green
wave effect) of natural vegetation, available at:
http://ntrs.nasa.gov/search.jsp?R=19740022555 (last access: 6 April 2015),
1974.
Scheftic, W., Zeng, X., Broxton, P., and Brunke, M.: Intercomparison of Seven
NDVI Products over the United States and Mexico, Remote Sens., 6,
1057–1084, 2014.
Sellers, P. J.: Canopy reflectance, photosynthesis and transpiration, Int.
J. Remote Sens., 6, 1335–1372, 1985.
Tian, F., Fensholt, R., Verbesselt, J., Grogan, K., Horion, S., and Wang, Y.:
Evaluating temporal consistency of long-term global NDVI datasets for trend analysis, Remote Sens. Environ., 163, 326–340, 2015.
Tucker, C. J.: Red and photographic infrared linear combinations for
monitoring vegetation, Remote Sens. Environ., 8, 127–150, 1979.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W.,
Mahoney, R., Vermote, E. F., and El Saleous, N.: An extended AVHRR 8-km NDVI
dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote
Sens., 26, 4485–4498, 2005.
Van Leeuwen, W. J. D., Orr, B. J., Marsh, S. E., and Herrmann, S. M.:
Multi-sensor NDVI data continuity: Uncertainties and implications for
vegetation monitoring applications, Remote Sens. Environ., 100, 67–81,
2006.
Vermote, E., Saleous, N. E., Kaufman, Y. J., and Dutton, E.: Data
pre-processing: Stratospheric aerosol perturbing effect on the remote
sensing of vegetation: Correction method for the composite NDVI after the
Pinatubo eruption, Remote Sens. Rev., 15, 7–21, 1997.
Wang, X., Piao, S., Ciais, P., Li, J., Friedlingstein, P., Koven, C., and
Chen, A.: Spring temperature change and its implication in the change of
vegetation growth in North America from 1982 to 2006, P. Natl. Acad. Sci. USA, 108, 1240–1245, 2011.
Xiao, X., Braswell, B., Zhang, Q., Boles, S., Frolking, S., and Moore III,
B.: Sensitivity of vegetation indices to atmospheric aerosols:
continental-scale observations in Northern Asia, Remote Sens. Environ.,
84, 385–392, 2003.
Xin, Q., Gong, P., Yu, C., Yu, L., Broich, M., Suyker, A. E., and Myneni, R.
B.: A Production Efficiency Model-Based Method for Satellite Estimates of
Corn and Soybean Yields in the Midwestern US, Remote Sens., 5,
5926–5943, 2013.
Zeng, X., Dickinson, R. E., Walker, A., Shaikh, M., DeFries, R. S., and Qi,
J.: Derivation and Evaluation of Global 1-km Fractional Vegetation Cover
Data for Land Modeling, J. Appl. Meteorol., 39, 826–839, 2000.
Zhou, L., Tian, Y., Myneni, R. B., Ciais, P., Saatchi, S., Liu, Y. Y., Piao,
S., Chen, H., Vermote, E. F., Song, C., and Hwang, T.: Widespread decline of
Congo rainforest greenness in the past decade, Nature, 509, 86–90,
2014.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao,
S., Nemani, R. R., and Myneni, R. B.: Global Data Sets of Vegetation Leaf
Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation
(FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS)
Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011,
Remote Sens., 5, 927–948, 2013.