## 6 Discussion
### Advantages and Limitations of the Presented Lava Flow Mapping Approach  
Using the _dNDVI_ analysis (Section 4.2), an effective methodology was applied to detect vegetation changes with PlanetScope data. Similar to the results of [PERSON] et al. [18], ash and tephra deposits could be detected very well, which in turn is an important parameter for further analysis of possible secondary natural hazards, e.g., secondary lahars [25]. However, this methodology is applicable only in vegetated areas. The _dNDVI_ methodology is not suitable for detecting volcanic hazards in unvegetated areas as there are no temporal changes in the _NDVI_ signal [18; 23]. In addition, the detected vegetation change cannot be automatically assigned to a volcanic hazard. Natural vegetation changes triggered by fire, landslides, or seasonal changes also cause a reduction in the _NDVI_ signal [20; 23]. Explosive eruptions also often result in complete destruction of vegetation in the impact zone (Section 5.1, Figure 4). To identify these areas and not confuse them with ash or tephra deposition, a preliminary visual analysis with expert knowledge of the pre- and post-scene is necessary [18]. Ash deposits can be very easily eroded by wind or precipitation, which is why the selection of pre- and post-scenes that are close in time to the eruption is particularly important [18]. After deriving the _dNDVI_ layer, a threshold must be used to extract the area of change [60]. The definition of this threshold value proves to be difficult. The method used for manually finding a threshold based on local-specific factors and expert knowledge achieved good results in this regard [18; 21]. However, this introduces a degree of subjectivity into the classification. Alternatively, automatable adaptive methods of threshold finding exist (e.g., Otsu method [67]), which can speed up and potentially optimize the process [60]. The developed OBIA change analysis (Section 4.3) also allows, in contrast to the _dNDVI_ analysis, the classification of volcanic hazards in areas without vegetation. Due to the use of PlanetScope data in combination with modelling based on topographic data (DEM), the methodology offers decisive advantages over classical numerical modelling of volcanic hazards (e.g., MAGFLOW [68], LAHARZ [69]). These modelling efforts rely on strong parameterization of input variables and are used only to predict volcanic natural hazards [58; 70]. By linking such modelling with information from satellite imagery, post-eruption or near-real-time analyses can also be performed [14]. The developed OBIA methodology models the potential area of lava flows via a simple distance analysis to the drainage system. Using the PlanetScope data, spectral and textual information from the real world can then in turn be transferred to the model, which is not possible in the aforementioned numerical modelling. In addition, the full potential of the VHR PlanetScope data is exploited via the object-oriented approach. Thus, on the one hand, the reduction in spectral variability in the scene can contribute to an improved classification of lava flows [21]. On the other hand, contextual information about individual image objects can be obtained [63]. Regarding the scarcely existing spectral differences between lava flows and background [22; 24], this is crucial for the function of the methodology. In addition, the analysis of texture and brightness changes leads to homogeneous and continuous lava flow segments within the object-based approach. This would not be possible in a pixel-based classification [24]. However, there are some limitations and potential sources of error in the OBIA methodology. For the methodology to function, alteration or overprinting of pixels due to _dNDVI_ changes or NHI hotspots is essential. If this is not the case, potential outflows, via intersection with these areas of change, cannot be identified and lava flow modelling fails.