基于GF-1 WFV的黄河口湿地植被碳储量估算研究

Estimation of Vegetation Carbon Storage in the Yellow River Estuary Wetland Based on GF-1 WFV Satellite Image

为掌握黄河口湿地植被地上生长部分碳储量的空间分布情况,基于GF-1WFV卫星数据,对黄河口湿地植被地上生长部分碳储量开展了遥感估算模型研究,并根据研究区植被类型空间分布特点,对不同植被类型地上生长部分碳储量的特征开展了分析,结果表明:6种植被碳储量估算模型中,基于NDVI建立的指数模型为单位面积碳储量估算最佳模型,其决定系数(R2)最大,值为0.76,均方根误差(RMSE)最小,值为19.1g/m2;在不同植被类型分布区,地上植被单位面积碳储量平均值大小顺序为互花米草>芦苇草甸>柽柳林>潮滩芦苇>盐地碱蓬,其中各区域平均值最大为78.1g/m2,最小为46.7g/m2。研究结果为提高黄河口湿地植被的碳储量提供了有效措施,即合理优化植被类型的空间分布、恢复裸滩上盐地碱蓬的生长和提高植被类型盖度。

In order to understand the spatial distribution of vegetation carbon storage in the Yellow River estuary, carbon storage of above-ground vegetation was estimated from China's GF-1 WFV satellite image. Based on the spatial distribution of vegetation types in the study area, the characteristics of the carbon stocks by different types of above-ground vegetation were analyzed. NDVI-based model was the best with a maximum coefficient of determination (0.76) and a minimum root mean square error (19.1 g/m^2). For different vegetation types, the sorting of above-ground vegetation carbon storage per unit area was spartina > phragmites meadow > tamarix chinesis shrub > tidal flat phragmites > suaeda, with the maximum (minimum) of 78.1 g/m^2 (46.7 g/m^2). The results indicate the effective measure to improve the carbon storage in the Yellow River estuary wetland, e.g. optimizing the spatial distribution of vegetation types, restoring the growth of suaeda on the bare beach, and increasing vegetation cover.