Suitability of hyperspectral data for monitoring nitrogen and phosphorus content in constructed wetlands |
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Authors: | Wei Li Zhiguo Dou Rumiao Wang Zhijiang Zhao Shifeng Cui |
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Institution: | 1. Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China;2. Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;3. Beijing Hanshiqiao National Wetland Ecosystem Research Station, Beijing, China https://orcid.org/0000-0002-2133-9287;4. Beijing Hanshiqiao National Wetland Ecosystem Research Station, Beijing, China https://orcid.org/0000-0001-8031-4330;5. Beijing Hanshiqiao National Wetland Ecosystem Research Station, Beijing, China;6. Beijing Shunyi District Hanshiqiao Wetland Nature Reserve Management Office, Beijing, China |
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Abstract: | ABSTRACTThe nitrogen and phosphorus content in water and sediment is an important index for evaluating the nutritional status of wetland ecosystems. This study used an inversion model to assess the total nitrogen (TN) and total phosphorus (TP) content of constructed wetland using the canopy spectral reflectance data of four wetland plants. And then determine their relative suitability as a remotely sensed environmental monitoring tool. For water, the coefficient of determination (R2) of floating plants (up to 0.92) was higher than that of emergent plants (up to 0.82). For sediment, the R2 of TN inversion for S. natans was 0.59 and that of TP inversion for L. minor was 0.52, suggesting that floating plant canopy spectral reflectance data are more useful for assessing water directly, while indicators for the sedimentary environment can be assessed using emergent plants. Overall, the results clearly show that it is feasible to estimate water and sediment TN and TP content using plant canopy spectral reflectance data, providing the basis for widespread, rapid, and reliable monitoring of wetland ecosystem health via hyperspectral remote sensing. This study provides a reference for the timely development of further wetland restoration and protection measures. |
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