A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects DOI Creative Commons
Farhad Samadzadegan, Ahmad Toosi, Farzaneh Dadrass Javan

et al.

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 76

Published: Dec. 11, 2024

Numerous remote sensing (RS) systems currently collect data about Earth and its environments. However, each system provides limited in terms of spatial resolution, spectral information, other parameters. Given technological constraints, combining from diverse sources can effectively enhance RS solutions through enrichment. Many studies have investigated the fusion acquired different sensors platforms. This paper a comprehensive review research on multi-platform -sensor fusion, encompassing visible-light images, multi/hyper-spectral RADAR LiDAR point clouds, thermal spectrometry samples, geophysical data. An analysis over 950 papers revealed that feature-level multi-sensor was most commonly employed technique, surpassing pixel- decision-level approaches. Moreover, satellite more prevalent than manned unmanned aerial vehicles. The integration initially gained traction applications such as precision agriculture before expanding to land use cover mapping. addresses previously overlooked issues presents framework facilitate seamless Guidelines for this include ensuring same acquisition time, co-registration, true orthorectification, consistent resolution or information content, radiometric consistency, wavelength band coverage.

Language: Английский

A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects DOI Creative Commons
Farhad Samadzadegan, Ahmad Toosi, Farzaneh Dadrass Javan

et al.

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 76

Published: Dec. 11, 2024

Numerous remote sensing (RS) systems currently collect data about Earth and its environments. However, each system provides limited in terms of spatial resolution, spectral information, other parameters. Given technological constraints, combining from diverse sources can effectively enhance RS solutions through enrichment. Many studies have investigated the fusion acquired different sensors platforms. This paper a comprehensive review research on multi-platform -sensor fusion, encompassing visible-light images, multi/hyper-spectral RADAR LiDAR point clouds, thermal spectrometry samples, geophysical data. An analysis over 950 papers revealed that feature-level multi-sensor was most commonly employed technique, surpassing pixel- decision-level approaches. Moreover, satellite more prevalent than manned unmanned aerial vehicles. The integration initially gained traction applications such as precision agriculture before expanding to land use cover mapping. addresses previously overlooked issues presents framework facilitate seamless Guidelines for this include ensuring same acquisition time, co-registration, true orthorectification, consistent resolution or information content, radiometric consistency, wavelength band coverage.

Language: Английский

Citations

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