 |
| Titel |
Assessing soil surface roughness using reflectance band indices obtained with an airborne multispectral sensor at very high spatial resolution |
| VerfasserIn |
Jesús Rodríguez González, José Alfonso Gómez, Pablo J. Zarco-Tejada |
| Konferenz |
EGU General Assembly 2011
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250052606
|
|
|
|
|
|
| Zusammenfassung |
| Surface processes like water and wind erosion, and water vapour and CO2 diffusion in natural
and agricultural soils are strongly influenced by soil surface roughness (SSR). SSR is often
measured using non-contact methods such as laser profilers or scanners, digital close range
stereo-photogrammetry and terrestrial laser scanning or LIDAR systems. These methods
however lack the potential to conveniently assess SSR over larger areas like the plot or field
scale size.
Numerous investigations on soil reflectance characteristics in the optical wavelength
region showed that the single most important factor influencing the observed bidirectional
soil reflectance anisotropy is soil surface roughness. Thus, in principle optical remote sensing
methods have the potential to provide useful quantitative information on SSR. The possibility
to assess SSR by means of correlating measured reflectance data at different wavelengths and
under different illumination and viewing angles has been successfully demonstrated at
extremely fine spatial scales (mm) using sieved soil materials and hyperspectral
data.
We present here results of a study aimed at investigating if a similar approach can be
applied to larger field or plot scales under operational conditions using very high spatial
resolution multispectral imagery (12.5cm) acquired at different sun angles. For this aim,
airborne imagery was acquired over two study sites with the narrow-band multispectral
ADC sensor (Tetracam Inc., USA) onboard an unmanned aerial vehicle (UAV)
platform at wavelengths 550, 670 and 800nm. The imagery was then corrected to
at-ground reflectance after geometric, radiometric calibrations and atmospheric
correction.
The first study site was an experimental field (100x40m) on which different roughness
levels were obtained by applying five conventional tillage methods on different subplots and
imagery acquired at four different times of the day. The second study site was a large olive
orchard with trees planted at 7.5x5.0m and bare soils between rows. Three tillage
treatments were applied on two separate blocks within the orchard. For this site, the
imagery was acquired only at two different times of the day due to the shadow
cast on the soil by the olive trees. A laser-scanning instrument was used to obtain
representative digital elevation models (DEMs) for each treatment with a grid resolution of
7.2x7.2mm over an area of 0.9x0.9m. Four roughness indices (standard deviation, the
tortuosity indices TA and TB, mean surface slope) were calculated for each DEM as
quantitative descriptors of SSR. For each DEM location, reflectance data was extracted
from the corrected reflectance imagery and a suite of several spectral band indices
calculated.
Simple linear regression and correlation analysis was used to investigate the relationship
between the spectral band indices and the quantitative roughness indices quantitative
roughness indices extracted from the field measured DEMs on both site. Meaningful
prediction models were obtained, suggesting the potential of this methodology for
obtaining quantitative estimates of soil surface roughness over larger field sites. |
|
|
|
|
|
|