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孙莉昕，朱文泉，谢志英，詹培，李雪莹.XXXX.应用于陆表物候监测的遥感指数多维度评估.遥感学报，XX（XX）： 1-20
Sun Lixin，Zhu Wenquan，Xie Zhiying，Zhan Pei，Li Xueying. XXXX. Multi-dimension evaluation of remote sensing indices for land surface phenology monitoring. National Remote Sensing Bulletin， XX（XX）：1-20
针对陆表植被物候监测已发展了很多遥感指数，但不同遥感指数表征陆表植被季节性变化的能力存在差异。目前，有关陆表植被物候遥感指数的评估大多在不同标准下开展，导致研究结果间的可比性较差，致使无法根据不同区域选择出最佳的遥感指数，从而影响大尺度（如半球乃至全球）的陆表物候监测精度。本文在北半球中高纬度地区，以75个碳通量塔站点的406条记录和129个物候相机站点的482条记录为参考标准，对10种遥感指数应用于陆表物候监测的能力进行了系统性评估，并从两个精度评估视角（物候提取准确度、物候变化趋势一致性）、四个维度（植被类型、地理环境、物候类型、物候事件）对比分析了各种情况下的最佳遥感指数及其精度。虽然部分遥感指数在多数情况下均表现最佳，但不同植被类型、地理环境、物候类型（功能物候、结构物候）、物候事件（春季、秋季）组合情况下的最佳遥感指数并不聚焦于少数几种，而是散布于各类遥感指数之中；即使是采用了最佳遥感指数，但在某些情况下，其用于陆表物候监测的误差仍较大。从不同的精度评估视角来看，物候提取准确度高的遥感指数并不一定与物候变化趋势一致性高的遥感指数相对应，说明应根据关注视角来选择最佳遥感指数。本文研究结果可为不同情况下的陆表植被物候监测提供最佳遥感指数选择依据，从而有利于提高大尺度的陆表植被物候监测精度以及评估其不确定性。
Many remote sensing indices have been developed for land surface phenology monitoring, but there are differences in the ability of different remote sensing indices to represent the seasonal changes of land surface vegetation. At present, the evaluations of remote sensing indices for land surface phenology monitoring are mostly carried out under different standards, resulting in poor comparability among research results. Thus it`s impossible to select the best remote sensing indices according to different regions based on those research results, which would have an impact on the large-scale (e.g. hemispheric and even global) land surface phenology monitoring. Taking 406 records from 75 carbon flux tower stations and 482 records from 129 phenological camera stations as the reference standard, this paper systematically evaluated the application of 10 remote sensing indexes in monitoring land surface phenology in the middle and high latitudes of the northern hemisphere. In addition, the best remote sensing indices and their accuracy under different conditions are also compared and analyzed from two evaluation perspectives (including phenological extraction accuracy and phenological change trend consistency) and four dimensions (including vegetation type, geographical environment, phenological type and phenological event).Although some remote sensing indices are the best in most conditions, the best remote sensing indices for different vegetation types, geographical environment, phenological types (functional phenology, structural phenology) and phenological events (spring and autumn) don`t focus on a few of remote sensing indices, but are scattered among all kinds of them. Even with the best remote sensing index, the error of land surface phenology monitoring is still large in some conditions. From different evaluation perspectives, the remote sensing indices with a high accuracy of phenology extraction are not exactly the same as those with a high consistency of phenological change trend, which suggested that the best remote sensing index should be selected according to the objects. The results of this paper can provide the best remote sensing index selection basis for land surface phenology monitoring under different conditions, which will be helpful to improve the accuracy of large-scale land surface phenology monitoring and evaluate its uncertainty.
遥感指数陆表植被物候植被类型地理环境结构物候功能物候
remote sensing indexland surface phenologyvegetation typegeographical environmentstructural phenologyfunctional phenology
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