Abstract
There is a need to develop indicators of mangrove condition using remotely sensed data. However, remote estimation of leaf and canopy biochemical properties and vegetation condition remains challenging. In this paper, we (i) tested the performance of selected hyperspectral and broad band indices to predict chlorophyll concentration (CC) on mangrove leaves and (ii) showed the potential of Landsat 8 for estimation of mangrove CC at the landscape level. Relative leaf CC and leaf spectral response were measured at 12 Elementary Sampling Units (ESU) distributed along the northwest coast of the Yucatan Peninsula, Mexico. Linear regression models and coefficients of determination were computed to measure the association between CC and spectral response. At leaf level, the narrow band indices with the largest correlation with CC were Vogelmann indices and the MTCI (R2 > 0.5). Indices with spectral bands around the red edge (705–753 nm) were more sensitive to mangrove leaf CC. At the ESU level Landsat 8 NDVI green, which uses the green band in its formulation explained most of the variation in CC (R2 > 0.8). Accuracy assessment between estimated CC and observed CC using the leave-one-out cross-validation (LOOCV) method yielded a root mean squared error (RMSE) = 15 mg·cm−2, and R2 = 0.703. CC maps showing the spatiotemporal variation of CC at landscape scale were created using the linear model. Our results indicate that Landsat 8 NDVI green can be employed to estimate CC in large mangrove areas where ground networks cannot be applied, and mapping techniques based on satellite data, are necessary. Furthermore, using upcoming technologies that will include two bands around the red edge such as Sentinel 2 will improve mangrove monitoring at higher spatial and temporal resolutions.
Highlights
Mangrove forests cover approximately 13.7 million ha of tropical and subtropical shorelines across118 countries [1]
Our results indicate that Landsat 8 NDVI green can be employed to estimate CC in large mangrove areas where ground networks cannot be applied, and mapping techniques based on satellite data, are necessary
The results presented in this work add to our understanding of the relationship between vegetation indices and the biochemical composition of mangrove by showing which multispectral and hyperspectral indices best explain the variation in chlorophyll concentration at the leaf and canopy level
Summary
Mangrove forests cover approximately 13.7 million ha of tropical and subtropical shorelines across118 countries [1]. Mexico ranks fourth in terms of mangrove coverage (742,000 ha), with. Mangrove forests provide a wealth of direct and indirect ecosystem services such as natural protection barriers and nursery habitat for marine organisms [2,3,4,5]. C removal from the atmosphere has been estimated at around 1,170 ± 127 g·C·m−2·year−1 [13] These figures acquire relevance in the context of climate change mitigation as C sequestration is emerging as a major strategy to reduce atmospheric C. In spite of the array of ecosystem services provided by mangroves, their high productivity, and their role played in C dynamics at the land–ocean interface [14], large areal losses are presently occurring due to deforestation and land use conversion due to both human and natural drivers [15,16]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
