摘要
基于不同植被指数提取物候参数是分析长时间物候变化的重要基础。以多云雾的重庆地区为例,使用2010~2019年MODIS NDVI/EVI/EVI2共3种长时序的植被指数数据,通过D-L滤波方法分析了不同植被指数特征;并使用动态阈值法和趋势分析法,对比研究了基于3种植被指数提取的物候参数结果及其随不同地形因子的分异规律,结果如下:(1)EVI和EVI2的时间序列拟合曲线比NDVI的拟合曲线更加平滑,3种植被指数原始值与拟合值的差值主要分布为NDVI(0.05~0.18)、EVI(0.03~0.11)、EVI2(0.03~0.1)。(2)基于3种植被指数提取的物候参数在空间分布和变化趋势上呈现一致性,其中EVI和EVI2提取的植被指数参数皆相近,相差5d之内占比79%以上,SOSEVI2变化显著性区域所占比面积最高(16.36%),SOSNDVI最低为12.37%。(3)SOS随海拔升高而推迟,EOS随海拔升高先延后再提前,LOS随海拔升高先延长后缩短,且EOSNDVI、LOSNDVI随着海拔增加分别与EOSEVI/EOSEVI2、LOSEVI/LOSEVI2差异增大,不同植被类型上,EVI提取的物候参数与EVI2相近,变化趋势具有一致性。与NDVI相比,EVI和EVI2能更好提取对云雾地区物候参数,结果相近;基于EVI和EVI2提取的物候参数的地形效应更明显。
It is an important basis of analyzing long-term phenological changes that extracting phenological pa⁃rameters based on different vegetation indices.Takes the cloudy and foggy area,Chongqing,as an example.Three long-term vegetation index data of NDVI,EVI,and EVI2 are extracted based on MODIS remote sens⁃ing images from 2010 to 2019,and the characteristics of different vegetation indexes are analyzed through D-L filtering.The results,which is of phenological parameters extracted based on three vegetation indices,were studied using dynamic threshold method and trend analysis method,and their response relationships and differ⁃ences to topographic factors are compared.The results are as follows:①The time series fitting curve of EVI and EVI2 is smoother than the fitting curve of NDVI.The differences between the original values of the three vegetation indices and the fitted values are mainly distributed in NDVI(0.05~0.18),EVI(0.03~0.11),EVI2(0.03~0.1).②The spatial distribution and change trend of the phenological parameters extracted from the three plantations were consistent.The vegetation index parameters extracted from EVI and EVI2 were similar,accounting for more than 79%within 5 days,and the significant change area of SOS EVI2 was the highest(16.36%),while the lowest SOS NDVI was 12.37%.③SOS was delayed with the increase of altitude,EOS was delayed and then advanced with the increase of altitude,LOS was extended and then shortened with the in⁃crease of altitude,and EOS_(NDVI)and LOS_(NDVI)were significantly different from EO_(SEVI)/EOS_(EVI2)and LOS_(EVI)/LOS_(E⁃VI2)with the increase of altitude,respectively.The phenological parameters extracted by EVI were similar to those of EVI2,and the variation trend was consistent.The phenological parameters can be better extracted based on EVI/EVI2 in cloud and fog areas,and the results are similar and can be used interchangeably.The phenological parameters extracted based on EVI and EVI2 have more obvious differences in altitude,slope,and slope direction.
作者
李云龙
李军
常梓煜
LI Yunlong;LI Jun;CHANG Ziyu(College of Geography and Tourism,Chongqing Normal University,Chongqing 401331,China;Key Laboratory of GIS Application of Chongqing,Chongqing 401331,China;Chongqing Key Laboratory of Earth Surface Processes and Environmental Remote Sensing in the Three Gorges Reservoir Area,Chongqing 401331,China)
出处
《遥感技术与应用》
CSCD
北大核心
2023年第4期978-989,共12页
Remote Sensing Technology and Application
基金
重庆市前沿与应用基础研究计划一般项目(cstc2015jcyjA0332)
国家自然科学基金(51308575)
中国科学院重点部署项目(KZZD-EW-TZ-18)资助。
关键词
多云雾地区
MODIS植被指数
植被物候参数
地形因子
Cloudy and foggy areas
MODIS vegetation index
Vegetation phenological parameters
Topo⁃graphic factors
