# Google Earth Engine for Monitoring Marine Mucilage: Izmit Bay in Spring Bay in Spring 2021
## 3 Methodology
### Spectral Water-Related Indices  
In remote sensing, many water-related indices (e.g., ABDI, ANDWI, AWE, FAI, MNDWI, NDAVI, NDCI, NDTI, SWI, WI) have been proposed and applied by researchers for the extraction of different characteristics of water. While some of them focus on the detection of algal blooms, some others focus on the clarity or turbidity of the water. Considering the research question in this study, separation of mucilage, particularly low-density mucilage, from the clear water surface and algal types is a difficult task due to the spectral similarity, revisit frequency, and spatial resolution of the sensors. It should be also mentioned that mucilage is commonly observed in thin and long lines or tracks on the water surface.  
Attempts have been made by researchers to analyze the color of the oceans and extract information about the objects on the top layer of the water. Since researchers usually study the colors of open oceans, indices were mainly developed for lower spatial resolution imagery, particularly for MODIS imagery. To the best of the author's knowledge, the spectral index solely developed for detecting mucilage formation in the literature was the Mucilage Index (MI) proposed by [44] who successfully applied the index to the MODIS images of the Adriatic Sea to map mucilage events occurring in the summer of 2004. The numerator of the formula enhances the decrease of reflectance typical of mucilaginous material in the channel 3 compared to the average values of the channels 2 and 4. The low reflectance in the band 3 (459-479 nm) and the highest reflectance in band 4 (545-565 nm) are confirmed by measurements in situ with radiometers made in previous studies. The channel 6 in the formula is at the denominator because it usually has a very high value in case of the clouds and very low in case of mucilage [7]. It was reported by [44] that MI values ranging from 0 to 5 correspond to the occurrence of mucilage. However, Ref. [7] determined the optimal MI range as between 0.05 and 0.45 applying to the ARPA Campania dataset. At this point, it should be mentioned that the MI index and Floating Algae Index (FAI) [45] were originally developed for MODIS data. However, they can be easily adapted to Sentinel-2 imagery by considering the bandwidths of the corresponding bands. An improved version of FAI called adjusted FAI (AFAI) proposed by Ref. [46] was also employed in this study. The formulation is different to FAI, where the center wavelength is ignored since algae floating on the water surface have higher reflectance in the NIR than in other bands. On the other hand, recent indices including Normalized Difference Water Index (NDWI) and Normalized Difference Turbidity Index (NDTI) were developed and applied to higher resolution imagery. Green and NIR bands are employed in the estimation of NDWI with similar formulation to NDVI. Green and NIR wavelengths were selected to: (1) maximize the typical reflectance of water features by using green light wavelengths; (2) minimize the low reflectance of NIR by water features; and (3) take advantage of the high reflectance of NIR by terrestrial vegetation and soil features [47]. Although the NDWI may not distinguish between suspended sediments and chlorophyll a, it can provide information about the overall turbidity. On the other hand, clear water has a distinct reflectance of weak response in the green, very small in the red and almost zero response in the near infrared wavelength. Green and red wavelengths were used in the NDTI formulation to estimate different degrees of turbidity.  
In this study, surface mucilage aggregates were mapped using the above-mentioned spectral indices. The formulations of these indices with corresponding references are given in Table 2. It should be mentioned that two versions of NDWI proposed by [47; 48] were employed in this research. Quantitative and qualitative assessments were performed on the thematic maps produced by applying index equations to the selected Sentinel-2 images.