Сравнение методов

	Георадар	Индекс нормализованного различия (NDVI)	Сейсмическая инверсия полных волновых форм
Область	Геофизика	Геофизика	Геофизика
Семейство	Process / pipeline	Process / pipeline	Process / pipeline
Год появления	1989	1973	1984
Автор метода	James Davis and Anthony Annan	Rouse, Haas, Schell, and Deering	Albert Tarantola
Тип	Shallow subsurface electromagnetic pulse detection	Spectral index for vegetation assessment	Seismic imaging and model parameterization technique
Основополагающий источник	Davis, J. L., & Annan, A. P. (1989). Ground-penetrating radar for high-resolution mapping of soil and rock stratigraphy. Geophysical Prospecting, 37(5), 531-551.	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.	Tarantola, A. (1984). Inversion of seismic reflection data in the acoustic approximation. Geophysics, 49(8), 1259-1266.
Другие названия	GPR	NDVI	FWI
Связанные	3	3	3
Сводка	Ground-Penetrating Radar (GPR) is a near-surface geophysical method that uses high-frequency electromagnetic pulses (typically 10 MHz to 2.5 GHz) to image shallow subsurface structures with exceptional spatial resolution. Pioneered by Davis and Annan in 1989, GPR is widely used in archaeology, civil engineering, environmental assessment, and shallow mineral exploration due to its ability to resolve features at decimeter to centimeter scales.	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.	Seismic Full-Waveform Inversion (FWI) is a computational technique that reconstructs detailed subsurface velocity and impedance models by iteratively fitting synthetic seismic waveforms to observed data. Introduced by Albert Tarantola in 1984, FWI has become the leading method for high-resolution imaging in exploration geophysics, engineering seismology, and subsurface characterization.