**4. Results**

With the configuration used, a flight of about 10 minutes can collect usable hyperspectral images (i.e., excluding take-off, landing, and turning phases) over an area of about 2.6 × 104 m<sup>2</sup> (2.6 ha), with a resolution of 4.5 cm × 6 cm. The reflectance spectra obtained at each pixel are inherent signatures of the targeted surfaces, resulting from the presence, the shape, and the position/orientation of specific absorption features, such as pigments, which compose the surface. For identification and classification purposes, the spectrum of each class of targets has to be uniquely characterized by its general shape, combined with local absorption or reflectance peaks.

The quality of the results is assessed in two ways:

(i) Firstly, by comparing the spectra obtained from Hyper-DRELIO imagery with spectra, measured by the field spectrometer on the same types of substrates or sediment coverage.

(ii) Secondly, by comparing spectra from Hyper-DRELIO imagery acquired at two different times on a surface assumed to be stable over time—in this case, sand.

#### *4.1. Comparison to Field Spectrometer*

Hyper-DRELIO imagery and field spectrometer control measurements are not exactly synchronous (separated by a few minutes to an hour). In addition, since the field spectrometer measurements are performed from the fixed platform, they can be separated from the Hyper-DRELIO images by several tens of meters. Differences between the spectra may appear, depending on the type/concentration of the benthic biofilm, which is related to the tidal time or on local variations of the targeted materials (concentration, structure, spectral mixing, or surface orientation).

Figures 6 and 7 show the spectra obtained over the sediment surface covered by benthic biofilm and over the pioneer mangroves, respectively. For a given class of targets, the characteristics of the spectra are globally similar between the field spectrometer and Hyper-DRELIO imagery, with local minima and maxima being clearly identifiable, both for the benthic biofilm and the pioneer mangroves. Thus, Hyper-DRELIO imagery succeeds in spatially capturing the spectral specificities of each target class. However, Hyper-DRELIO data are noisier for wavelengths higher than 800 nm. To evaluate the degree of similarity between the Hyper-DRELIO reflectance spectra and the field spectrometer reflectance spectra, we used a correlation coefficient to compare the reflectance levels and the spectral angle mapper (SAM) method [58]. The SAM "distance" assesses the similarity between the shape of two spectra by calculating the angle between these spectra and is, therefore, less sensitive to multiplicative noise. The smaller the SAM distance, the higher the similarity (two exactly similar spectra would have a zero SAM distance). We compare the mean value of three spectra measured by the field spectrometer (Figures 6b and 7c) and the mean value of eight spectra extracted from Hyper-DRELIO images (Figures 6c and 7d) for the two biota. Above the benthic biofilm, a SAM distance of 0.039 and a correlation coefficient of 0.96 were found. Above the pioneer mangrove, the SAM distance was 0.159 and the correlation coefficient was 0.97.

With a small pixel size, the probability of capturing different class of targets in a pixel is limited. Nevertheless, a very high spatial resolution also captures some complexities that are not visible at lower resolutions, such as the structure of the foliage. Figures 6c and 7d show a disparity between the spectra extracted from Hyper-DRELIO imagery (mean standard deviation of 0.004 for the biofilm, and 0.061 for the mangrove, respectively). In the visible spectrum, the spectral signature is mainly influenced by pigment composition. In NIR (near infrared), the spectrum is rather influenced by the structure and water content of the target. That explains the higher disparity (particularly in NIR) obtained among mangrove spectra, extracted from Hyper-DRELIO imagery.

**Figure 6.** Spectra comparison above the benthic biofilm. (**a**) Biofilm patch on the Hyper-DRELIO image (in natural colours) where the spectra are pointed (red crosses). The image was acquired on 2018-09-12 at 13:15. (**b**) Biofilm spectra measured by GER1500 spectrometer. (**c**) Biofilm spectra extracted from Hyper-DRELIO imagery (mean standard deviation between the reflectance spectra: 0.004).

**Figure 7.** Spectra comparison above the pioneer mangroves. (**a**) Aerial oblique photograph of the pioneer mangroves. (**b**) Mangrove patch on the Hyper-DRELIO image (in natural colours) where the spectra are pointed (red crosses). The image was acquired on 12 September 2018 at 11:08. (**c**) Mangrove spectra measured by GER1500 spectrometer. (**d**) Mangrove spectra extracted from Hyper-DRELIO imagery (mean standard deviation between the reflectance spectra: 0.061).

#### *4.2. Relative Comparison over the Sandy Beach*

As the flights were conducted at different times of the day, one way of checking the effectiveness of the radiometric corrections is to compare the spectra acquired several hours apart over the same substrate. Since the surface texture of the mudflat may change during the tidal cycle because of biofilm development, desiccation, and/or bioturbation processes, the part of the study area assumed to change the least over time was the upper sandy beach.

Two sets of five spectra were extracted on the supra-tidal part of the beach for the flight on 12 September 2018 at 11:30 (Flight 1) and for the flight on 12 September 2018 at 13:30 (Flight 2). From these spectra (Figure 8), the intra-set variability (for the same flight) was evaluated from the standard deviation (averaged over all wavelengths). For the spectra of Flight 1 (respectively, Flight 2), the standard deviation was 0.024 (or 5.48%), respectively, 0.037 (or 8.81%) for Flight 2. The quality of the radiometric corrections was assessed by comparing the average spectra from the two data sets (Vol 1 and Vol 2). The average difference between these average spectra was 0.026 (or 5.64%). This deviation was considered satisfactory as it was of the same order of magnitude as the intra-set variability.

**Figure 8.** Spectra comparison above the supra-tidal sandy beach. (**a**,**b**) Sandy beach on the Hyper-DRELIO images (in natural colours) where the spectra are pointed (red crosses). The images were acquired on 12 September 2018 at 11:08 (Flight 1) (**a**) and on 12 September 2018 at 13:14 (Flight 2) (**b**). (**c**) Sand spectra extracted from Hyper-DRELIO imagery for Flight 1 (orange colour) and Flight 2 (green colour). The mean spectrum for each data set is depicted in bold.
