Método simple para identificación de zonas homogéneas de NDVI y temperatura de superficie en la Península Ibérica

Referencias bibliográficas

• BARTHOLOMÉ, E. & BELWARD, A.S. 2005. GLC2000: a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing. 26(9): 1959–1977.
• COOPS, N., WULDER, M., DURO, D., HAN, T. & BERRY, S. 2008. The development of a Canadian dynamic habitat index using multitemporal satellite estimates of canopy light absorbance. Ecological indicators. 8: 754 – 766.
• CULLUM, J.K. & WILLOUGHBY, R.A. 1985. Lanczos Algorithm for large symmetric eigenvalue computations. Vol. 1 -7. Boston. USA.
• EVA, H., BELWARD, A., DE MIRANDA, E., DI BELLA, C., GOND, V., HUBER, O., JONES, S., SGRENZAROLI, M. & FRITZ, S. (2004). A land cover map of South America. Global Change Biology. 10: 731-744.
• FOVELL, R. 1997, Consensus clustering of US temperature and precipitation data. Journal of Climate. 10: 1405 – 1427.
• FOVELL, R. & FOVELL, M.Y. 1994. Climate zones of the Conterminous United States defined using cluster Analysis. Journal of Climate. 6: 2103 – 2135.
• HEROLD, M., WOODCOCK, C., DI GREGORIO, A., MAYAUX, P., BELWARD, A., LATHAM, J. & SCHMULLIUS, C.C. 2006. A joint initiative for harmonization and validations of land cover datasets. IEEE Trans. Geosci. Remote Sens. 4(7): 1719 – 1727.
• HOLBEN, B. N. 1986. Characteristics o maximumvalue composite image from temporal AVHRR data. International Journal of Remote Sensing. 7: 1417 – 1464.
• HUANG, CH., LI, X., LU, L. 2008. Retrieving soil temperature profile by assimilation MODIS LST products with ensemble Kalman filter. Remote Sensing of Environment. 112: 1320 – 1336.
• HUETE, A., DIDAN, K., MIURA, T., RODRÍGUEZ, E.P., GAO, X. & FERREIRA, L.G. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment. 83: 195 – 213.
• JULIEN, Y., SOBRINO, J. A. & VERHOEF, W. 2006. Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999, Remote Sensing of Environment. 103: 43–55.
• JULIEN, Y. 2008. Vegetation monitoring through retrieval of NDVI and LST time series from historical databases. PhD. Thesis. University of Valencia. 288 pp.
• JULIEN, Y. & SOBRINO, J. A. 2008a. The Yearly Land Cover Dynamics (YLCD) method: an analysis of global vegetation from NDVI and LST parameters, Remote Sensing of Environment (in press).
• JULIEN, Y. & SOBRINO, J.A. 2008b. Global land surface phenology trends from GIMMS database. International Journal of Remote Sensing (in press).
• KARLSEN, S.R. & CO-AUTHORS. 2007. MODIS-NDVI-based mapping of the length of the growing season in northern Fennoscandia. International Journal of Applied Earth Observation and Geoinformation (in press).
• KOTTEK, M., GRIESER, J., BECK, C., RUDOLF, B. & RUBEL, F. 2006. World Map of Köppen-Geiger Climate Classification updated. Meteorol Z. 15: 259 – 263.
• LETTS, P.A. 1978. Unsupervised classification in the Aries Image Analysis system. Proc. 5th Canadian Symposium on Remote Sensing, 61- 71.
• LOBO, A., LEGENDRE, P., REBOLLAR, J.L.G., CARRERAS, J., MINOT, J.M. & 2004. Land cover classification at a regional scale in Iberia: separability in a multi-temporal and multi-spectral data set of satellite images. International Journal of Remote Sensing. 25(1): 205 – 213.
• NEMANI, R. R. & RUNNING, S.W. 1997. Land cover characterization using multitemporal re, near-IR and thermal-IR data from NOAA/AVHRR. Ecological Applications. 7(1): 79 – 90.
• NEUMANN, K., HEROLD, M., HARTLEY, A. & SCHMULLIUS, C. 2007. comparative assessment of CORINE2000 and GLC2000: Spatial analysis of land cover data for Europe. International Journal of Applied Earth Observation and Geoinformation. 9: 425 – 437.
• PEEL, M.C., FINLAYSON, B.L. & MCMAHON, T.A. 2007. Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Science. 11: 1633 – 1644.
• PÉREZ, C. 2004. Técnicas de Análisis Multivariante de Datos. Editorial Pearson and Prentice May, Madrid, España, 646 pp.
• PRICE, J.C. 1991. Using spatial context in satellite data to infer regional scale evapotranspiration, IEEE Transanction in Geoscience and Remote Sensing. 28: 940 – 948.
• PRIVETE, J. L., FOWLER, C., BALDWIN, D., WICK. G. A. & EMERY, W. J. 1995. Effects of orbital drift on advanced very high resolu- tion radiometer (AVHRR) products: normalized difference vegetation index (NDVI) and sea surface temperature (SST). Remote Sensing of Environment. 53: 164 – 171.
• RHEE, J., IM, J., CARBONE, B. & JENSEN, J. 2008. Delineation of climate regions using in-situ and remotely-sensed data for the Carolinas. Remote Sensing of Environment.112: 3099 – 3111. RICHARDS, J.A. & JIA, X. 1999. Remote sensing digital image analysis : an introduction. Springer, Berlin, 363 pp.
• SOBRINO, J.A., EL-KHARRAZ, J. & LI, Z. 2003. Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote Sensing. 24(24): 5161 – 5182.
• STRAHLER, A.H., MUCHONEY, D., BORAK, J., FRIEDL, M., GOPAL, S., LAMBIN, E. & MODDY, A. 1999. Modis Landcover Product: Algorithm Theoretical Basis Document. V 5.0
• THORNTHWAITE, C. W.1948. An approach toward a rational classification of climate. Geographical Review. 38: 55 – 94.
• VIÑA, A., BEARER, S., ZHANG, H., OUYANG, Z. & LIU, J. 2008. Evaluating MODIS data for mapping wildlife habitat distribution. Remote Sensing of Environment. 112: 2160 – 2169.
• WAN, Z. 2006. MODIS land surface temperature product user’s guide. Institute of Computational Earth System Science. University of California, Santa Barbara, CA. WAN, Z., ZHANG, Y., ZHANG, Q., & LI, Z. -L. 2002. Validation of the land surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment. 83: 163 − 180.
• WAN, Z., ZHANG, Y., ZHANG, Q., & LI, Z. -L. 2004. Quality assessment and validation of the MODIS global land-surface temperature. International Journal of Remote Sensing. 25: 261 − 274.
• ZHANG, X., FRIEDL, M., SCHAAF, C. & STRAHLER, A. 2004. Climate controls on vegetation phenological patterns in northern midand high latitudes inferred from MODIS data. Global Change Biology. 10:1133 – 1145.
• ZHANG, X., FRIEDL, M. & SCHAAF, C. 2006. Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements. Journal of Geophysical Research, 111: G04017.