Dear reviewer ,

Thank you very much for your constructive comments to manuscript. We are trying to consider all your comments.

Concerning your main comments:

1.- First, I found some parts in the methodology was not sufficiently detailed. For example, the 2.5 Data processing (should be named as Data Analyses at least) section has very limited information, inconsistent with the level of details in other subsections 2.1-2.4. It is unclear if the authors have conducted geometric corrections, radiometric corrections (and how), HCA and PCA analysis steps, etc. When I read Section 3 Results, I found it difficult to match with Section 2. Also, where is the results for the non-parametric K-S test?

• Regarding to the subtitle, we consider thar both meaning are relevant, because of that we decide use “Data processing and analyses”.
• Regarding data processing (the noise reduction process, and geometric correction process): A more detailed text has been added. the paragraph in this section would read as follows:

“Several steps were involved in processing the raw image data captured by the hyperspectral camera using the Spectronon Pro software. First, the raw data were processed to obtain reflectance (R(λ)), using the calibration file provided by Resonon and the downwelling irradiance data provided by Miniature Spectrometer (Flame Ocean Insight). In the following step, pixel cleaning by an adapted NDWI index was undertaken, masking those pixels that did not correspond to water and those saturated due to solar radiation angle incidence (Xie et al., 2014). The lack of reference points in the monitoring areas a no geometric correction was applied to hyperspectral data, because of that the data are used as data instead imagen in this study. In the next step, this data was normalize using min-max method, such that the new minimum and maximum values are 0 and 1. After that, the use of Savitzky-Golay method or digital smoothing polynomial filtering (DISPO), based on least squares polynomial smoothing fit and differentiation (Ruffin and King, 1999; Gallagher, 2020), was applied to reduce the signal of the noise and obtain a clean spectrum, with less distortion than moving average techniques, without altering its properties. Finally, reflectance raw data were averaged, obtaining a reflectance value at each band to emphasise the shape singularities of each spectrum.”

• The non-parametric K-S test data have been added at a supplementary table referred as Table S2 in the results texts (lines 276, 283-287, 290-2).

2.- Second, my main critique is about Section 3.1, which characterizes those sites but takes a few pages. While it is helpful to characterize those sites, it was done with lengthy statistical analyses and their visualizations that are not quite relevant to the main theme - hyperspectral analyses. It is unclear how it supports the main objective "the characterisation of the reflectance spectra of different phytoplankton assemblages, either harmful or non-harmful, dominated by a single species." However, if this subsection were removed, the results section would be so slim. 

• Although the description of environmental condition is a bit extensive and somewhat irrelevant for the main objective, we consider an important aspect in the text, especially to determine if these conditions indirectly affect the spectral signal. Indeed, an apparent relation between the spectral signals and localities condition, especially regarding to the chlorophyl.

3.- Third, because the authors focused on a pilot study in this article, it is reasonable to expect a comprehensive blueprint on the path forward. I found Section 4.2 was relatively underdeveloped. Challenges and opportunities are better to be organized around a few general themes for deeper insights.

• Regarding to this point, you can see in the discussion 4.2 section, changes at text expressing the principal challenges and advantages that our equipment have experienced during the monitoring. Thus, you will read in the manuscript:

“Other limitations that appeared frequently during the study were related to technical aspects such as the flight time limited by the battery’s life, the area coverage limited by network signal and again batteries durability, or the lack of reference points in a continuous body water (Kislik et al., 2018; Wu et al., 2019). The battery’s life was identified as a quite important aspect being the main factor that spatially limited the monitoring to coastal areas and also few stations barely separated during the study. Another aspect to consider is the camera size. Nowadays hyperspectral cameras are still new being not yet completely functional due to their big size and weight that force to acquire a bigger drone and therefore a more expensive one. Related to the camera one more aspect that can be a challenge is the high variability at cameras market, with different characteristics in spectral resolution, geometry acquisition and imaging systems. Although this can be considered at first as a positive point, we have to be cautious at the moment to acquire the camera because this is going to limit the possibility to compare data and apply algorithms in future.

Other important barriers which make it difficult to identify phytoplankton using reflectance data are the analysis of the vertical distribution of phytoplankton in the water column (~ 1-40 m) in both satellites and UAV systems, especially in the design of future algorithms. Therefore, not just the phytoplankton distribution in water column but also the presence of other particles, mainly non-biological ones, and their impact in solar radiation absorption/reflexion together with physical aspects as the water roughness.

Although recent works have been including hyperspectral data for the study of phytoplankton assemblages, these datasets are still limited to specific areas and unavailable, being the lack of a robust hyperspectral images’ library another important factor to consider.”

Regarding your minor comments

Lastly, the article suffers from the use of inaccurate phrases, grammatical errors, and labeling issues.

 - For example, at Line55, spatial-temporal resolution has contained the long revisit cycle. à  

• This text has been rephase and grammatical reviewed by a native British.

- At Line 82, it is unclear if geography (complex topography) would be a direct issue for phytoplankton.

• Although the reference to the complex topography (geography) was not related to phytoplankton, we have had changes to be clearer in the text.

- In the legend of Fig 11, the label for low and high Chlo(s) were not distinguishable.

• We have reviewed and corrected the Chl-a label at both in the legend of the figure 11 and inside the figure. Now the Chl-a labels are higher.

- Line 344:  the phrase 'a non-significant difference' sounds odd.  

• This has been reviewed and corrected.

- Line 350: what is "clusters together assemblage"?

• This expression refers that the HCA groups localities under same phytoplankton groups and genera dominance. The statement was reviewed and improved.

- Line 366: variability -> the variability.

• Reviewed and corrected.

Thank you very much for your time and contributions.