基于通量塔净生态系统碳交换数据的植被物候遥感识别方法评价

选择北美洲72座通量塔观测的净生态系统碳交换(NEE)数据来计算植被物候,并以此作为参考数据,从可行性和准确性两方面对阈值法、移动平均法和函数拟合法三大类常用的植被物候遥感识别方法进行了综合评价.结果表明:基于局部中值的阈值法对植被物候识别的可行性和准确性均最优;其次为Logistic函数拟合法中的一阶导数方法;移动平均法对植被物候识别的可行性和准确性与移动窗口的大小有关,对于16 d合成的归一化差值植被指数(NDVI)时间序列数据来说,移动窗口大小为15时能获得较优的结果;而全局阈值法对植被物候识别的可行性和准确性均最差;Logistic函数拟合法中的曲率变化率方法在识别植被物候时虽然与基于NEE数据得到的植被物候在数值上存在较大偏差,但二者之间具有较高的相关性,说明基于曲率变化率方法识别出的植被物候能较真实地反映植被物候在时空上的变化趋势.

Evaluation of remote sensing extraction methods for vegetation phenology based on flux tower net ecosystem carbon exchange data

Taking the vegetation phenological metrics derived from the net ecosystem carbon exchange (NEE) data of 72 flux towers in North America as the references, a comprehensive evaluation was conducted on the three typical classes of remote sensing extraction methods (threshold method, moving average method, and function fitting method) for vegetation phenology from the aspects of feasibility and accuracy. The results showed that the local midpoint threshold method had the highest feasibility and accuracy for extracting vegetation phenology, followed by the first derivative method based on fitted Logistic function. The feasibility and accuracy of moving average method were determined by the moving window size. As for the MODJS 16 d composited time-series normalized difference vegetation index (NDVI), the moving average method had preferable performance when the window size was set as 15. The global threshold method performed quite poor in the feasibility and accuracy. Though the values of the phenological metrics extracted by the curvature change rate method based on fitted Logistic function and the corresponding ones derived from NEE data had greater differences, there existed a strong correlation between them, indicating that the vegetation phenological metrics extracted by the curvature change rate method could reflect the real temporal and spatial variations of vegetation phenology.