## 4 Discussion
### Future Upgrades of CET Tool  
In future research, we are planning to integrate data obtained by UAVs infrared thermography (IRT) and in situ sensors, measuring sea surface temperatures (SST), into the newly developed CET tool. Applications of IRT in measuring water temperature are diverse and have been employed in a wide variety of fluvial environments [80]. In the context of the coastline detection issue, [81] used Landsat 8 Operational Land Imager (OLI)/Thermal  
Figure 15: Overestimation of the extracted coastline caused by spectral disinformation affected by small fishing boats within Veli Iz (**A**) and Vela Rava (**B**) harbors. Infrared Sensor (TIRS) in extracting accurate demarcation line. However, we would focus on integrating very high-resolution thermal models. Namely, it is generally known that the amount of radiation emitted by an object increases with temperature. Compared to land, water surfaces on thermal-IR imagery in the daytime usually have very dark to medium tones, while in the nighttime, they have moderately light tones. If there is no significant water pollution, this can enable a clear localization of water surfaces [82]. Figure 16A-D shows land and sea surface temperature (LST and SST) models of different spatial resolutions (from 30 m up to 5 cm) that can be potentially integrated into the CET tool. In Figure 16A, the surface temperature models of the Zadar County wider area with a spatial resolution of 30 m is shown. An isotherm of specific value was extracted from the SST model, and a clear demarcation line between the sea and the land can be seen (e.g., Pag, Dugi otok, Ugljan, Pasman). The optimal isotherm value, in this case, was determined by overlapping the derived LST with a high-resolution (0.5 m) digital orthophoto-DOP (0.5 m). However, in future research, the value of the isotherm can be determined based on several adequately distributed in situ measurements (thermometer) of sea surface temperature. Figure 16B-D shows surface temperature models with higher spatial resolutions ranging from 35 cm to 5 cm. These models were made from thermal images (RPJEG format) that contained temperature information in each pixel and were collected by the _UAV system Matrice 210 RTK V2 + Zemnuse XT2_ at various flying altitudes. This thermal camera has a declared absolute accuracy of 10 \({}^{\circ}\)C [83], but for observing land-sea temperature differences, relative accuracy is more important, which, in this case, is proved as satisfactory. Figure 16C demonstrates a possible solution to the CET tool limitations previously listed in Section 4.2. Namely, the presence of artificial objects (e.g., fishing boats) close to the coast can lead to the overestimation of the extracted coastline (Figure 15). Although these values are not large, this drawback needs to be addressed. However, if very high (<10 cm) resolution surface temperature models are generated, this problem can be solved. This is best seen in the example of Sali Bay (Figure 16C). On this thermal model, the extracted isotherm perfectly delimits the boundary between the coast and the land. All fishing boats in Sali bay are not recognized as land, i.e., the boundary of the coastline is not oversized. Figure 16D shows the isotherm derived for the narrow coastal area of the Santis gully from the most detailed (5 cm) surface temperature model generated. This wider coastal area is rich in coastal submerged freshwater springs that continuously flow through underground canals from the distant karst hinterland. These freshwater springs can also be felt physically in the sea due to the temperature, which is significantly lower than the surrounding sea. However, these environmental conditions did not negatively affect the derivation of a specific isotherm that would delaminate the land-sea surface. Therefore, the CET can ultimately use multispectral, thermal, and RGB imagery of various spatial resolutions.