内蒙古羊草草原返青期遥感识别方法研究  

Optimal remote sensing method for estimating green-up date of Leymus chinensis steppe in Inner Mongolia

作　　者：范德芹[1,2] 朱文泉[2,3] 赵学胜[1] 郑周涛[2,3] 

机构地区：[1]中国矿业大学(北京)地球科学与测绘工程学院,北京100083 [2]北京师范大学资源学院,北京100875 [3]北京师范大学地表过程与资源生态国家重点实验室,北京100875

出　　处：《北京师范大学学报（自然科学版）》2016年第5期639-644,共6页Journal of Beijing Normal University(Natural Science)

基　　金：国家自然科学基金资助项目(41171306;41371389)

摘　　要：研究羊草返青期遥感识别方法对于模拟及预测内蒙古草原植被物候变化具有重要意义.为了有效识别内蒙古羊草草原的返青期,本研究基于250m分辨率的MODIS归一化差值植被指数(NDVI)时序数据,首先分别采用双高斯函数、多项式、S-G滤波3种拟合方法对原始NDVI时序数据进行重建,然后进一步分别采用最大斜率阈值法、动态阈值法及滑动平均法对重建的最优NDVI数据进行返青期识别,并利用33个样本点的返青期地面观测数据对遥感监测结果进行了地面验证.结果表明,"基于S-G滤波拟合的滑动平均法"是内蒙古羊草草原返青期的最佳遥感识别方法,可以此为基础开展内蒙古草原主要植被返青期的时空变化规律研究.Accurate detection of green-up dates for Leymus chinensis is important to simulate and predict vegetation phenology shifts under the influence of climate change in Inner Mongolia. To identify green-up date of Leymus chinensis steppe effectively, double-Gaussian, Savitzky-Golay, and polynomial functions were used to reconstruct normalized difference vegetation index （NDVI） time series. After evaluations by visual inspection and root mean square error, the most feasible reconstruction method was identified. The maximum slope threshold, dynamic threshold and moving average methods were then used to derive green-up dates from the best reconstructed NDVI time series. Performance of these three methods for green-up date identification was tested against green-up data from 33 ground observation samples and corresponding Moderate-resolution Imaging Spectroradiometer NDVI time-series data at 250-meter resolution. NDVI time series reconstructed with Savitzky-Golay method indicated that green-up dates identified with moving average method agreed well with actually observed ground phenology data.

关 键 词：羊草 草原 NDVI 返青期 遥感 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]