黑河流域遥感物候产品验证与分析

发布时间：2018-01-25 09:14

本文关键词： 遥感物候产品生长起点生长终点验证黑河流域　出处：《遥感学报》2017年03期 　论文类型：期刊论文

【摘要】：植被物候遥感产品对全球变化响应、农业生产管理、生态学的应用等多领域研究具有重要意义。但现有植被物候遥感产品还有较多问题,主要包括一方面使用不同参数的时间序列数据以及不同提取算法导致的产品结果差异较大,另一方面在地面验证中地面观测数据与遥感反演数据的物理含义不一致导致的验证方法的系统性误差。本文以黑河流域为研究区,对比验证基于EVI(Enhanced Vegetation Index)时间序列数据提取的MLCD(MODIS global land cover dynamics product)植被遥感物候产品和基于LAI(Leaf Area Index)时间序列数据提取的UMPM(product by universal multi-life-cycle phenology monitoring method)植被遥感物候产品的有效性及精度等。同时,通过验证分析进一步评估基于EVI和LAI时间序列提取的物候特征的差异及特点,探讨由于地面观测植被物候与遥感提取植被物候的物理意义的不一致问题导致的直接验证结果偏差。结果表明:UMPM产品有效性整体高于MLCD产品,但在以草地和灌木为主的稀疏植被区,由于LAI取值精度的原因,UMPM产品存在较多缺失数据,且时空稳定性较低;基于玉米地面观测数据表明,EVI对植被开始生长的信号比LAI更加敏感,更适合提取生长起点,但植被指数易饱和,峰值起点普遍提前,基于LAI提取的峰值起点更加合理。由于地面观测的物候期在后期更加关注果实生长,遥感观测仅关注叶片的生长,遥感定义的峰值终点和生长终点与玉米的乳熟期和成熟期差异较大。
[Abstract]:Vegetation phenological remote sensing products are of great significance in response to global change, agricultural production management, application of ecology and other fields, but there are still many problems in existing vegetation phenological remote sensing products. It mainly includes on the one hand using different parameters of time series data and different extraction algorithms led to greater differences in product results. On the other hand, the systematic error of the verification method caused by the discrepancy between the physical meaning of the ground observation data and the remote sensing inversion data in the ground validation. This paper takes the Heihe River Basin as the study area. Compare and verify MLCD-based time series data extraction based on EVI(Enhanced Vegetation Index. MODIS global land cover dynamics product) vegetation remote sensing phenological products and based on Lai (. UMPM (UMPM) for extracting time Series data from Leaf Area Index. Product by universal multi-life-cycle phenology monitoring method. The validity and precision of vegetation remote sensing phenological products. The differences and characteristics of phenological features extracted based on EVI and LAI time series were further evaluated by validation analysis. This paper discusses the deviation of direct verification result caused by the discrepancy between the physical meaning of ground observation vegetation phenology and remote sensing extraction of vegetation phenology. The result shows that the validity of MLCD product is higher than that of MLCD product. However, in the sparse vegetation area with grassland and shrubs, there are many missing data and low spatiotemporal stability due to the accuracy of LAI values. Based on the ground observation data of maize, it shows that EVI is more sensitive to the signal of vegetation growth than LAI, and is more suitable for extracting the growth starting point, but the vegetation index is easy to saturation, and the peak value is generally ahead of time. The peak value based on LAI extraction is more reasonable. Since the phenological period of surface observation is more concerned with fruit growth in the later period, remote sensing observation only focuses on the growth of leaves. The peak end point and growth end point of remote sensing definition are different from the milking stage and mature stage of maize.
【作者单位】：中国科学院遥感与数字地球研究所遥感科学国家重点实验室;中国科学院大学;
【基金】：国家自然科学基金(编号:41271366) 国家重点基础研究发展计划(973计划)(编号:2013CB733401)~~
【分类号】：S127;TP79
【正文快照】： 引用格式:王聪,李静,柳钦火,柏军华,徐保东,赵静,曾也鲁.2017.黑河流域遥感物候产品验证与分析.遥感学报,21(3):442 457Wang C,Li J,Liu Q H,Bai J H,Xu B D,Zhao J and Zeng Y L.2017.Validation and analysis of remote sensingphenology products in the Heihe River Basi

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