Comparison of Remote Sensing Time-Series Smoothing Methods for Grassland Spring Phenology Extraction on the Qinghai–Tibetan Plateau

作者：Nan Li, Pei Zhan, Yaozhong Pan, Xiufang Zhu, Muyi Li, Dujuan Zhang · 发表于：Remote Sensing · 年份：2020 · DOI：10.3390/rs12203383 · 被引用次数：48 · 研究领域：Remote Sensing in Agriculture、Plant Water Relations and Carbon Dynamics、Urban Heat Island Mitigation

Accurate evaluation of start of season (SOS) changes is essential to assess the ecosystem’s response to climate change. Smoothing method is an understudied factor that can lead to great uncertainties in SOS extraction, and the applicable situation for different smoothing methods and the impact of smoothing parameters on SOS extraction accuracy are of critical importance to be clarified. In this paper, we use MOD13Q1 normalized difference vegetation index (NDVI) data and SOS observations from eight agrometeorological stations on the Qinghai–Tibetan Plateau (QTP) during 2001–2011 to compare the SOS extraction accuracies of six popular smoothing methods (Changing Weight (CW), Savitzky-Golay (SG), Asymmetric Gaussian (AG), Double-logistic (DL), Whittaker Smoother (WS) and Harmonic Analysis of NDVI Time-Series (HANTS)) for two types of different SOS extraction methods (dynamic threshold (DT) with 9 different thresholds and double logistic (Zhang)). Furthermore, a parameter sensitivity analysis for each smoothing method is performed to quantify the impacts of smoothing parameters on SOS extraction. Finally, the suggested smoothing methods and reference ranges for the parameters of different smoothing methods were given for grassland phenology extraction on the QTP. The main conclusions are as follows: (1) the smoothing methods and SOS extraction methods jointly determine the SOS extraction accuracy, and a bad denoising performance of smoothing method does not necessarily lead to a ...