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遥感技术与应用  2023, Vol. 38 Issue (4): 978-989    DOI: 10.11873/j.issn.1004-0323.2023.4.0978
遥感应用     
基于不同植被指数的重庆地区物候参数提取对比研究
李云龙1(),李军1,2,3(),常梓煜1
1.重庆师范大学地理与旅游学院,重庆 401331
2.重庆市高校GIS应用研究重点实验室,重庆 401331
3.三峡库区地表过程与环境遥感重庆市重点实验室,重庆 401331
A Comparative Study on the Extraction of Phenological Parameters in Chongqing Area based on Different Vegetation Indices
Yunlong LI1(),Jun LI1,2,3(),Ziyu CHANG1
1.College of Geography and Tourism,Chongqing Normal University,Chongqing 401331,China
2.Key Laboratory of GIS Application of Chongqing,Chongqing 401331,China
3.Chongqing Key Laboratory of Earth Surface Processes and Environmental Remote Sensing in the Three Gorges Reservoir Area,Chongqing 401331,China
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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:①EVI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%。③SOS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。

关键词: 多云雾地区MODIS植被指数植被物候参数地形因子    
Abstract:

It is an important basis of analyzing long-term phenological changes that extracting phenological parameters 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 sensing 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 differences 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 SOSEVI2 was the highest (16.36%), while the lowest SOSNDVI 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 increase of altitude,and EOSNDVI and LOSNDVI were significantly different from EOSEVI/EOSEVI2 and LOSEVI/LOSEVI2 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.

Key words: Cloudy and foggy areas    MODIS vegetation index    Vegetation phenological parameters    Topographic factors
收稿日期: 2022-04-15 出版日期: 2023-09-11
ZTFLH:  Q948  
基金资助: 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)
通讯作者: 李军     E-mail: lyl16790@163.com;junli@cqnu.edu.cn
作者简介: 李云龙(1998-),男,四川攀枝花人,硕士研究生,主要从事植被遥感监测研究。E?mail:lyl16790@163.com
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引用本文:

李云龙,李军,常梓煜. 基于不同植被指数的重庆地区物候参数提取对比研究[J]. 遥感技术与应用, 2023, 38(4): 978-989.

Yunlong LI,Jun LI,Ziyu CHANG. A Comparative Study on the Extraction of Phenological Parameters in Chongqing Area based on Different Vegetation Indices. Remote Sensing Technology and Application, 2023, 38(4): 978-989.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2023.4.0978        http://www.rsta.ac.cn/CN/Y2023/V38/I4/978

图1  植被覆盖及选点审图号:GS(2019)1838
图2  曲线拟合值与原始值差异
图3  草地EVI、EVI2、NDVI时序以及曲线拟合
图4  耕地EVI、EVI2、NDVI时序以及曲线拟合
图5  林地EVI、EVI2、NDVI时序以及曲线拟合
图6  2010~2019年关键物候参数(SOS,EOS,LOS)提取结果(day)审图号:GS(2019)1838
图7  2010~2019年关键物候参数(SOS,EOS,LOS)变化趋势(d·10a-1)审图号:GS(2019)1838
图8  基于不同植被指数提取的关键物候参数(SOS,EOS,LOS)之间的差值对比审图号:GS(2019)1838
图9  物候始期(SOS)变化趋势显著性审图号:GS(2019)1838
NDVIEVIEVI2
SOS3.76%0.61%0.58%
EOS1.64%0.35%0.33%
LOS0.01%0.00%0.00%
表1  物候参数缺失占比
图10  重庆的气象地理分区
图11  不同海拔上物候参数差异
图12  不同植被类型上物候参数差异
坡向物候参数东北东南西南西西北
SOSEVI9192939395949291
SOSEVI29293939495959392
SOSNDVI8181808183838181
EOSEVI319321327331333331328323
EOSEVI2320322328332334332329324
EOSNDVI348348348349350351350349
LOSEVI228229235238238237235231
LOSEVI2228229235238239237235231
LOSNDVI267268269269268268269269
表2  不同坡向上物候参数差异/d
图13  不同坡度上物候参数差异
图14  林地上植被物候与气象因素的关系
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