550
satellite imaging and remote sensing methodology. Remote sensing offers accurate
automated methods for detecting change in restored wetlands. Vegetation change
detection is a powerful indicator of restoration success. The restoration projects use
vegetative cover as an important indicator of restoration success. Our research,
which relies on several series of radar images captured especially during the growth
period, enables us to improve plant formation recognition by exploiting the temporal dynamics of the various plant classes of the restored areas of the delta. Temporal
analyses revealed that no single date allows satisfactory characterization of all the
vegetation classes. Thus, the temporal dimension, which is represented by seasonal
evolution, is an essential component if we intend to draw up a detailed inventory of
the restored vegetation classes in the delta.
The synergy of a time series of radar satellite observations with the optical data
and radar data can be exploited to improve monitoring and analyze the vegetation in
the restoration areas of the Danube Delta. Information from different sensors may
assist in the variable retrieval by limiting potential ambiguities. The temporal resolution of the optical sensor Sentinel-2 does not provide temporally frequent products of vegetation characteristics due to the cloud coverage. Application of a
multi-temporal radar, multi-sensor approach to a temporal sequence of data acquired
by different sensors can improve mapping and monitoring of vegetation state variables over time. By integrating the Sentinel-1 time series with optical images such
as those obtained by Sentinel-2, the quality of the habitat maps of the restoring areas
in the Danube Delta can be improved considerably (97.1%). Very good Kappa indices were obtained; for the time series radar, the Kappa index was 0.96, and for
multi-sensor data integration the Kappa index was 0.97. The reliable Producers
Accuracy and K coefficient results prove the complementarity of the two satellites
for the observation, analysis and spatial representation of the deltaic plant ecosystems. The Producers Accuracy analysis by class shows that the Sentinel-2 sensor
has its limits concerning the detection of similar plant classes, such as, for example,
the different classes of reed. Although this sensor detects these classes, the mapping
precision is not always high (on some occasions, it is approximately 55% for the
‘reed on compact plaur’ class). In contrast, the use of a Sentinel-1 time series reveals
an interesting C band radar time signature in the Danube Delta ecosystem. Moreover,
the combination with Sentinel-2 data resulted in considerable reduction of the
observed confusions for both Sentinel-1 and Sentinel-2 with, for instance, a
Producers Accuracy value of the ‘reed on compact plaur’ class of 90.46%, as well
as increased accuracy for other reed classes.
As revealed by the data collected by the satellites used in our research, the plant
cover of the restored areas appears to be normal and to consist of plant formations
similar to those found in the natural areas of the delta. Therefore, we could conclude
that plant ecosystem restoration in the Danube Delta has been successful.
Acknowledgment This work was supported by the CNES.
S. Niculescu et al.
satellite imaging and remote sensing methodology. Remote sensing offers accurate
automated methods for detecting change in restored wetlands. Vegetation change
detection is a powerful indicator of restoration success. The restoration projects use
vegetative cover as an important indicator of restoration success. Our research,
which relies on several series of radar images captured especially during the growth
period, enables us to improve plant formation recognition by exploiting the temporal dynamics of the various plant classes of the restored areas of the delta. Temporal
analyses revealed that no single date allows satisfactory characterization of all the
vegetation classes. Thus, the temporal dimension, which is represented by seasonal
evolution, is an essential component if we intend to draw up a detailed inventory of
the restored vegetation classes in the delta.
The synergy of a time series of radar satellite observations with the optical data
and radar data can be exploited to improve monitoring and analyze the vegetation in
the restoration areas of the Danube Delta. Information from different sensors may
assist in the variable retrieval by limiting potential ambiguities. The temporal resolution of the optical sensor Sentinel-2 does not provide temporally frequent products of vegetation characteristics due to the cloud coverage. Application of a
multi-temporal radar, multi-sensor approach to a temporal sequence of data acquired
by different sensors can improve mapping and monitoring of vegetation state variables over time. By integrating the Sentinel-1 time series with optical images such
as those obtained by Sentinel-2, the quality of the habitat maps of the restoring areas
in the Danube Delta can be improved considerably (97.1%). Very good Kappa indices were obtained; for the time series radar, the Kappa index was 0.96, and for
multi-sensor data integration the Kappa index was 0.97. The reliable Producers
Accuracy and K coefficient results prove the complementarity of the two satellites
for the observation, analysis and spatial representation of the deltaic plant ecosystems. The Producers Accuracy analysis by class shows that the Sentinel-2 sensor
has its limits concerning the detection of similar plant classes, such as, for example,
the different classes of reed. Although this sensor detects these classes, the mapping
precision is not always high (on some occasions, it is approximately 55% for the
‘reed on compact plaur’ class). In contrast, the use of a Sentinel-1 time series reveals
an interesting C band radar time signature in the Danube Delta ecosystem. Moreover,
the combination with Sentinel-2 data resulted in considerable reduction of the
observed confusions for both Sentinel-1 and Sentinel-2 with, for instance, a
Producers Accuracy value of the ‘reed on compact plaur’ class of 90.46%, as well
as increased accuracy for other reed classes.
As revealed by the data collected by the satellites used in our research, the plant
cover of the restored areas appears to be normal and to consist of plant formations
similar to those found in the natural areas of the delta. Therefore, we could conclude
that plant ecosystem restoration in the Danube Delta has been successful.
Acknowledgment This work was supported by the CNES.
S. Niculescu et al.