Monitoring earths surface dynamics with optical imagery
Resumen:
The increasing availability of high‐quality optical satellite images should allow, in principle, continuous monitoring of Earth's surface changes due to geologic processes, climate change, or anthropic activity. For instance, sequential optical images have been used to measure displacements at Earth's surface due to coseismic ground deformation [e.g., Van Puymbroeck et al., 2000], ice flow [Scambos et al., 1992; Berthier et al., 2005], sand dune migration [Crippen, 1992], and landslides [Kääb, 2002; Delacourt et al., 2004]. Surface changes related to agriculture, deforestation, urbanization, and erosion—which do not involve ground displacement—might also be monitored, provided that the images can be registered with sufficient accuracy. Although the approach is simple in principle, its use is still limited, mainly because of geometric distortion of the images induced by the imaging system, biased correlation techniques, and implementation difficulties.
2008 | |
Procesamiento de Señales | |
Inglés | |
Universidad de la República | |
COLIBRI | |
https://hdl.handle.net/20.500.12008/38615
https://doi.org/10.1029/2008EO010001 |
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Acceso abierto | |
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
Sumario: | The increasing availability of high‐quality optical satellite images should allow, in principle, continuous monitoring of Earth's surface changes due to geologic processes, climate change, or anthropic activity. For instance, sequential optical images have been used to measure displacements at Earth's surface due to coseismic ground deformation [e.g., Van Puymbroeck et al., 2000], ice flow [Scambos et al., 1992; Berthier et al., 2005], sand dune migration [Crippen, 1992], and landslides [Kääb, 2002; Delacourt et al., 2004]. Surface changes related to agriculture, deforestation, urbanization, and erosion—which do not involve ground displacement—might also be monitored, provided that the images can be registered with sufficient accuracy. Although the approach is simple in principle, its use is still limited, mainly because of geometric distortion of the images induced by the imaging system, biased correlation techniques, and implementation difficulties. |
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