# Observation Capability Evaluation Model for Flood-Observation-Oriented Satellite Sensor Selection
## 4 Discussion
### Superiority of Ocem
Additionally, the qualitative comparative results underscore the OCEM's effectiveness in supporting flood-water-monitoring-oriented sensor selection and planning due to its consideration of spatiotemporal characteristics in flood events. Figure 7. Comparison between DOCI and OCEM in quantifying the observation capability of optical sensors in the three experimental observation tasks. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & **Applicable** & \multirow{2}{*}{**Evaluation Mode**} & \multicolumn{2}{c}{**Spatiotemporal Processes**} & \multicolumn{2}{c}{**Environmental Impact**} & \multicolumn{2}{c}{**Main Content**} \\ \cline{3-6}  & **Scenario** & & & & & \\ \hline \multirow{2}{*}{OCEM} & \multirow{2}{*}{Flood} & \multirow{2}{*}{Quantitative} & \(\surd\) & \(\surd\) & \multicolumn{2}{c}{\(\surd\)} & Quantitatively evaluate the performance of satellite sensors in flood water observation tasks, considering the spatiotemporal characteristics of the flood event. This enables the optimum selection and planning of sensors \\ \hline \multirow{2}{*}{DOCI} & \multirow{2}{*}{General} & \multirow{2}{*}{Quantitative} & \(\times\) & \(\surd\) & Quantitatively evaluate the observation performance of satellite sensors in various scenarios to support their optimal selection and planning \\ \hline \multirow{2}{*}{SSCI} & \multirow{2}{*}{General} & \multirow{2}{*}{Quantitative} & \(\times\) & \(\times\) & Cluster satellite sensors based on the evaluation of their static observation capability, enabling the recommendation of multiple sensors for different observation scenarios \\ \hline \multirow{2}{*}{SOCA Ontology} & \multirow{2}{*}{General} & \multirow{2}{*}{Qualitative} & \(\times\) & \(\times\) & \multicolumn{2}{c}{Create a semantic web where each satellite sensor is semantically linked to its multidimensional observation capabilities (e.g., SensorA, hasObservationSpace, SpaceA), supporting the fast and semantic discovery of satellite sensors} \\ \hline \multirow{2}{*}{SOCO-Field} & \multirow{2}{*}{General} & \multirow{2}{*}{Qualitative} & \(\times\) & \(\surd\) & \multicolumn{2}{c}{Establish the linkage between geographical locations and sensor observation capabilities based on the GIS object field model. This enables location-based discovery and qualitative cognition of sensors} \\ \hline \multirow{2}{*}{SOCCEM} & \multirow{2}{*}{Astronomy} & \multirow{2}{*}{Quantitative} & \(\times\) & \(\surd\) & Evaluate the observation stability and accuracy of star sensors in hypersonic aerothermal conditions \\ \hline \multirow{2}{*}{EOPEM} & \multirow{2}{*}{General} & \multirow{2}{*}{Quantitative} & \(\times\) & \(\times\) & Assess the degree of satisfaction of Earth observation sensor capabilities in metering SGD demand, as well as its future potential \\ \hline \multirow{2}{*}{SBSM} & \multirow{2}{*}{Flood} & \multirow{2}{*}{Quantitative} & \(\times\) & \(\times\) & Use the Elimination and Choice Expressing Reality method to select the optimal bands of sensors for flood area detection and mapping \\ \hline \hline \end{tabular}  
Notes: \(\surd\) means supported, \(\times\) means unsupported.  
\end{table} 
Table 11: Comparison between the OCEM and other sensor observation capability evaluation and selection methods.