Speaker
Dr
Linda Corucci
(MetaSensing)
Description
Floodplain vegetation classification is an important issue in the Netherlands since the country is highly vulnerable to flooding. The resistance force exerted by vegetation on water flowing over or through it alters the water flow velocity, thus, it is important to classify and monitor the vegetation in such sensitive areas. Currently, this is done by means of aerial photography interpretation with field control. However, such method results to be very time consuming. Moreover, it does not allow for the discrimination of the vegetation underneath canopy.
In order to answer the need for an efficient means of classifying and monitoring the vegetation present in the Dutch floodplains, MetaSensing performed test flights with their airborne fully polarimetric L and X band SAR systems over selected areas in the Netherlands. In addition, ground truth surveys have been conducted to validate the outcome of the classification.
The L band polarimetric SAR data allowed for distinguishing between most of the vegetation classes of interest. This was achieved by means of a classification algorithm based on an eigenvalue/eigenvector decomposition of the coherency matrix. However, by comparing the results of the classification with the ground truth, it was found that some misclassification happened in areas covered by vegetation types of different heights (such as tall shrubs and forest).
The use of a different frequency band, specifically X-band, was attempted and a fully polarimetric X-band SAR system was flown over the same areas. However, the analysis of the X band data did not add useful information to the L band classified data.
Since the main responsible for the misclassification resulted to be the missing information about the height of the vegetation, an additional flight with an X-band interferometric SAR system was performed, in order to obtain a Digital Surface Model (DSM) of the areas of interest.
By fusing the L-band classification with DSM it was possible to distinguish the vegetation types basing on their height, thus, it was possible to correctly label those classes which were previously misclassified.
Primary author
Dr
Linda Corucci
(MetaSensing)
Co-authors
Dr
Adriano Meta
(MetaSensing)
Mr
Alex Coccia
(MetaSensing)
Mr
Luca Marotti
(Sarmore)
