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.

We monitored the water quality and hydrological conditions of a horizontal subsurface constructed wetland (HSSF-CW) in Beijing, China, for two years. We simulated the area-based constant and the temperature coefficient with the first-order kinetic model. We examined the relationships between the nitrogen (N) removal rate, N load, seasonal variations in the N removal rate, and environmental factors—such as the area-based constant, temperature, and dissolved oxygen (DO). The effluent ammonia (NH₄⁺-N) and nitrate (NO₃⁻-N) concentrations were significantly lower than the influent concentrations (p < 0.01, n = 38). The NO₃⁻-N load was significantly correlated with the removal rate (R² = 0.96, p < 0.01), but the NH₄⁺-N load was not correlated with the removal rate (R² = 0.02, p > 0.01). The area-based constants of NO₃⁻-N and NH₄⁺-N at 20 °C were 27 ± 26 (mean ± SD) and 14 ± 10 m∙year⁻¹, respectively. The temperature coefficients for NO₃⁻-N and NH₄⁺-N were estimated at 1.004 and 0.960, respectively. The area-based constants for NO₃⁻-N and NH₄⁺-N were not correlated with temperature (p > 0.01). The NO₃⁻-N area-based constant was correlated with the corresponding load (R² = 0.96, p < 0.01). The NH₄⁺-N area rate was correlated with DO (R² = 0.69, p < 0.01), suggesting that the factors that influenced the N removal rate in this wetland met Liebig’s law of the minimum.