Compara mètodes

	NDVI	Model Acoblat Oceà-Atmosfera	Índex de Precipitació Estandarditzada
Camp	Geofísica	Geofísica	Geofísica
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	1973	1975	1993
Autor original	Rouse, Haas, Schell, and Deering	Syukuro Manabe, Kirk Bryan, and others	Thomas McKee, Neil Doesken, and John Kleist
Tipus	Spectral index for vegetation assessment	Coupled atmosphere-ocean climate system simulation	Probabilistic drought indicator
Font seminal	Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. Third Earth Resources Technology Satellite Symposium Proceedings, 1, 309-317.	Manabe, S., Bryan, K., & Spelman, M. J. (1975). A global ocean-atmosphere climate model with seasonal variation for future studies of climate sensitivity. Journal of Physical Oceanography, 5(1), 3-29.	McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the Eighth Conference on Applied Climatology, 179-184.
Àlies	NDVI	AOGCM	SPI
Relacionats	3	3	3
Resum	The Normalized Difference Vegetation Index (NDVI) is a spectral index computed from satellite or aerial multispectral imagery that quantifies vegetation greenness and vigor. Introduced by Rouse and colleagues in 1973 using Landsat data, NDVI has become the most widely used remote sensing metric for vegetation monitoring, drought assessment, crop productivity forecasting, and land cover change detection.	An Ocean-Atmosphere Coupled Model (AOGCM) is a comprehensive climate simulation that couples dynamic general circulation models of the atmosphere and ocean with explicit exchange of heat, momentum, and moisture at the interface. Developed by Manabe, Bryan, and colleagues in the 1970s, coupled models are essential for simulating climate change, ocean circulation changes, and climate-ocean interactions over decadal to centennial timescales.	The Standardized Precipitation Index (SPI) is a climate index that quantifies precipitation anomalies relative to historical norms, standardized to account for differences in precipitation climatology across regions. Introduced by McKee, Doesken, and Kleist in 1993, SPI has become a primary tool for drought detection and characterization, adopted by meteorological agencies worldwide for operational drought monitoring and early warning systems.