Salīdzināt metodes

	InSAR	NDVI	Seismiskā pilnvaiņu inversija
Nozare	Ģeofizika	Ģeofizika	Ģeofizika
Saime	Process / pipeline	Process / pipeline	Process / pipeline
Izcelsmes gads	1989	1973	1984
Autors	Gabriel, Goldstein, and Zebker	Rouse, Haas, Schell, and Deering	Albert Tarantola
Tips	Radar interferometry for millimeter-precision surface deformation	Spectral index for vegetation assessment	Seismic imaging and model parameterization technique
Pirmavots	Gabriel, A. K., Goldstein, R. M., & Zebker, H. A. (1989). Mapping small elevation changes over large areas: Differential radar interferometry. Journal of Geophysical Research, 94(B7), 9183-9191.	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.
Citi nosaukumi	InSAR	NDVI	FWI
Saistītās	3	3	3
Kopsavilkums	Interferometric Synthetic Aperture Radar (InSAR) is a radar remote sensing technique that measures millimeter-scale ground surface deformation by analyzing the phase difference between radar images acquired from slightly different orbital positions. Pioneered by Gabriel, Goldstein, and Zebker in 1989, InSAR has become essential for earthquake rupture characterization, volcanic monitoring, landslide detection, and subsidence quantification.	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.