Abstract

The chlorophyll content can indicate the general health of vegetation, and can be estimated from hyperspectral data. The aim of this study is to estimate the chlorophyll content of mangroves at different stages of restoration in a coastal wetland in Quanzhou, China, using proximal hyperspectral remote sensing techniques. We determine the hyperspectral reflectance of leaves from two mangrove species, Kandelia candel and Aegiceras corniculatum, from short-term and long-term restoration areas with a portable spectroradiometer. We also measure the leaf chlorophyll content (SPAD value). We use partial-least-squares stepwise regression to determine the relationships between the spectral reflectance and the chlorophyll content of the leaves, and establish two models, a full-wave-band spectrum model and a red-edge position regression model, to estimate the chlorophyll content of the mangroves. The coefficients of determination for the red-edge position model and the full-wave-band model exceed 0.72 and 0.82, respectively. The inverted chlorophyll contents are estimated more accurately for the long-term restoration mangroves than for the short-term restoration mangroves. Our results indicate that hyperspectral data can be used to estimate the chlorophyll content of mangroves at different stages of restoration, and could possibly be adapted to estimate biochemical constituents in leaves.

Highlights

  • Mangroves grow along the edges of harbors and beaches in tropical and subtropical areas

  • From the average and trend line of the chlorophyll content, we conclude that the chlorophyll content decreases in the order of the short-term restoration of: Kandelia candel > long-term restoration of Kandelia candel > short-term restoration of Aegiceras corniculatum > long-term restoration of Aegiceras corniculatum

  • When sampling the short-term restoration mangroves, we found that Kandelia candel was more likely to survive in areas frequently submerged by the tide than Aegiceras corniculatum

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Summary

Introduction

Mangroves grow along the edges of harbors and beaches in tropical and subtropical areas. China has implemented various projects to conserve and restore mangroves, and, with large-scale ecological restoration work under way, the area of mangrove forest is expected to reach 70,000 hm by 2020 [4]. The chlorophyll content is an indicator of vegetation stress and can be used as a basis for estimating other biochemical parameters [5] and should be measured when monitoring, restoring and managing coastal wetland ecosystems. As such, it would be useful if there were methods that resource managers could use to monitor the chlorophyll content of mangroves from hyperspectral data [6,7,8,9]

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