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Although geographical information systems (GIS) and remote sensing play an increasing role for monitoring of land degradation und soil erosion at regional and even global scale, the potential of large-scale aerial photography for the documentation and comprehension of geomorphological forms has as yet been little exploited. An important reason for this research deficiency is the lack of adequate image scales and resolutions. Highly dynamic processes of erosion and gully development cannot be mapped in detail from standard aerial photography or satellite imagery because neither spatial nor temporal resolution of this imagery corresponds to the process magnitudes and dynamics of gullies which require high resolution and flexible repeat rates. At the MoGul study sites, gully systems are monitored with aerial photography taken from unmanned platforms with remote controlled cameras. Both remote sensing systems were developed together with the staff of the technical workshop at the Faculty of Geosciences and Geography: |
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Aerial photographic survey with kite |
Kite system |
Barranco Rojo near Botorrita, Province of Zaragoza (Spain); aerial photograph taken from blimp |
Hot-air blimp of the Department of Physical Geography |
Hot-air blimp
Remote controlled hot-air blimps have been employed by the research group since 1995 (see EPRODESERT project) and can be used at wind velocities up to approx. 3 Beaufort. They combine an open hot-air system as known from montgolfières with the streamline form of a blimp or zeppelin. The camera system comprises two SLR cameras which can be rotated by remote control for optimal alignment of the oblong image format. It is suspended from a damped cardan joint which together with the blimp's inertia warrants sharp vertical photographs. The blimp is guided and positioned with 500 m tether ropes; burner and camera system are remote controlled. Depending on altitude and focal lengths, the photographs vary in scale between approx. 1:250 und 1:10 000, yielding ground resolutions of 3 mm - 12 cm when digitized.
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