基于高分一号卫星影像的柽柳地上生物量遥感估算研究——以昌邑柽柳国家海洋特别保护区为例

AGB of Tamarix remote sensing estimation research based on GF-1 image -take Changyi Tamarix national special marine reserves as an example

  • 摘要: 柽柳是滨海湿地植被中的典型物种,多生长在潮间带和潮上带,在保护海岸、改良滩涂等方面发挥着巨大的作用。国民经济与社会发展"十三五"规划明确提出实施"南红北柳"湿地修复工程,凸显了柽柳在滨海湿地保护中的核心作用,应用遥感技术估算大范围柽柳的生物量对柽柳保护具有重要意义。本文以昌邑柽柳国家海洋特别保护区为例,应用国产GF-1卫星遥感数据和地面生物量实测数据,构建了柽柳地上生物量估算模型,选取了最优模型并开展了应用试验。结果表明:(1)5个植被指数中,比值植被指数RVI与柽柳地上生物量(AGB)相关性最高,为0.686;(2)RVI对应的三次多项式生物量估算模型决定系数最高,为0.81,且平均相对误差MRE和均方根误差RMSE最小,分别为4.7%和0.05 kg/m2;(3)应用2014年9月4日获取的昌邑柽柳国家海洋特别保护区GF-1卫星遥感影像,利用RVI三次多项式估算模型进行生物量遥感估算,得到研究区柽柳林地上平均生物量为0.75 kg/m2,总生物量为15020 t。

     

    Abstract: As a typical specie in coastal wetland, Tamarix grows in intertidal and supratidal zone and is very important for protection of the coast and the improvement of the shoal. The "NAN HONG BEI LIU" wetland restoration project have been put forward clearly under the "13th Five-Year" plan of national economic and social development, which show that Tamarix plays a key role in coast protection. So, it is of great significance for Tamarix protection to estimate widespreadly the biomass by using remote sensing technology. In this paper, Taking Changyi Tamarix national special marine reserves as an example, GF-1 data which is developed by ourselves and in stiu measured data is used to establish Tamarix above-ground biomass (AGB) estimation model and choose optimal model, the model is applied in study area. The results show:(1) As one of five vegetation index, the correlation coefficient of RVI and Tamarix AGB is the highest, that is 0.686; (2) The determination coefficient of cubic polynomial model with RVI is the highest, it is 0.81. MRE and RMSE of model is the smallest, which is 4.7% and 0.05 kg/m2 separately. (3) Combined with GF-1 image which is received in September 5, 2014 in the national special marine reserves, the model of cubic polynomial model with RVI is used to estimate AGB of Tamarix, the average AGB Tamarisk is 0.75 kg/m2 and the total biomass of 15020 t in study area.

     

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