## 4 Discussion
### Chl Map  
The VI that best explained the variation in CC at the ESU level, the Landsat 8 NDVI green, was used to create the Chl maps. [PERSON] _et al._[69] developed the NDVI green for MODIS and, unlike its predecessor, the NDVI that uses the red band (650-690 nm), the NDVI green incorporates the green band (530-570 nm) in its formulation and is sensitive to a wider range of CC [69,84]. Similar to MODIS, the Landsat 8 green band ranges between 530 and 590 nm, this region of the electromagnetic spectrum is located above the \"green edge\" between two regions of strong pigment absorption: blue (460-480 nm) and red (650-690 nm) [69]. It has been observed that the green edge has behavior similar to the red edge in the sense that both edges tend to shift towards longer wavelengths at high CC [41]. Therefore, as CC increases and the red spectral band reaches minimum reflectance the green band still remains sensitive; this may explain why Landsat 8 NDVI green was best correlated to CC at ESU level. To our knowledge, this is the first time that Landsat 8 has been used to map the CC of mangrove forest at landscape scale in Mexico. The importance of the relationship between Landsat 8 VIs and CC stems from the potential of Chl to be used as a proxy of GPP, as has been suggested in precision agriculture studies [85, 86]. Although the Chl maps depict a reasonable spatial and temporal pattern in CC, there is uncertainty associated to them as they were constructed under some limitations and assumptions. The main limitation of this study is that LAI measurements were not collected during the field campaign. LAI is a major component of canopy Chl content [87, 88], this latter is defined as the product of CC and LAI [44, 84]. Therefore, in this study it was not possible to derive canopy Chl content to plot against Landsat 8 NDVI green. Instead of canopy Chl content, we used leaf CC averaged at the ESU level. In addition, differences in plant structure, changes in soil reflectance, and changes in soil moisture and leaf moisture might affect the relationship between Landsat 8 VIs and CC at ESU level [43] particularly at LAI \(<3\)[89]. Although this assumption requires further investigation, there are reasons to believe that LAI does not vary much temporally. In an evergreen tropical forest [PERSON] _et al._[90] reported seasonal variations in EVI and litter fall, but the authors did not find a seasonal pattern in LAI. Similarly, in a mangrove forest in the Mexican Pacific, Flores-de-Santiago, [PERSON] and Flores-Verdugo [22] found no significant difference in LAI between dry and rainy seasons for _R. mangle_ and _A. germinans_, irrespective of their condition; the authors only found significant difference in LAI in _L. racemosa_. In summary, one major assumption in the present study was that Landsat 8 NDVI green responded to variation in CC at the ESU level rather than to variation in LAI, canopy closure, and background reflectance, suggesting that further research is needed to account for the potential contribution from LAI in CC estimation. Another assumption was that the trees sampled were representative of a Landsat 8 pixel of 30 m \(\times\) 30 m. Pixels that cover more than one species are a source of uncertainty [68]. According to our results, mangrove species contribute in different proportions to the total CC at ESU level. Although only four species of mangrove dominate the landscape in the study area, species composition and density vary spatially [91]. It is also important to note that the association between CC and VIs was based on the January image (close to maximum canopy development) with average CC ranging between 40 and 70 \(\mu\)g cm\({}^{-2}\) thus particularly the low CC values (e.g., those estimated in April/May 2013) are affected by a degree of uncertainty.