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高分一号卫星高时空分辨率植被指数产品验证与分析 被引量:2

Verification and analysis of high spatial-temporal resolution vegetation index product based on GF-1 satellite data
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摘要 归一化差值植被指数NDVI (Normalized Difference Vegetation Index)是使用率最高的植被指数,但现有的NDVI产品时间分辨率跟空间分辨率不足,限制了其在一定区域范围的精细化动态监测应用。高分一号(GF-1)宽幅卫星WFV (Wide Field View)具有4 d重访周期、16 m空间分辨率,在长时间序列动态监测中具有巨大潜力。本文对基于GF-1宽幅相机数据生产的全国2018年—2020年16 m 10 d的MuSyQ NDVI产品与基于Google Earth Engine (GEE)的Landsat 7、Landsat 8和Sentinel-2数据生产的Landsat NDVI、Sentinel-2 NDVI产品进行了一致性与差异性分析。结果显示MuSyQ NDVI产品空间分布更加连续,没有其他两个产品显示的条带特征;MuSyQ NDVI产品的有效数据比例更高,尤其是分布在北方及青藏高原的农作物和草地类型,具有更好的空间连续性。时间尺度上,由于GF-1/WFV相比于其他两种产品具有更高频次的观测,MuSyQ NDVI时间序列曲线更加平滑且连续,跳跃现象不明显,且能表现出更细节的植被生长特征及物候特征。在空间和时间尺度上,GF-1/NDVI产品提供的高时空分辨率的NDVI产品较已有产品更优,为后续植被动态研究中NDVI产品的选择提供了有用的信息,对于较大空间范围内的长时间序列精细化监测更具有优势。 The rapid development of remote sensing technology has promoted the generation of different vegetation index products.Normalized Difference Vegetation Index(NDVI)is the vegetation index with the highest utilization rate.However,the existing NDVI products have insufficient time resolution and spatial resolution,thereby limiting the fine dynamic monitoring application in a certain region.The Wide-Field View(WFV)of GF-1 satellite data has a 4-day revisit period and 16 m spatial resolution,indicating its great potential in long-time series dynamic monitoring.The objective of this study is to establish a method for generating a 16 m/10-day NDVI product based on GF-1 images from 2018 to 2020.In this study,the GF-1 NDVI products of 16 m and 10 days from 2018 to 2020 are produced based on GF-1 WFV.Moreover,Landsat NDVI and sentinel-2 NDVI products are produced based on landsat7,landsat8,and sentinel-2 data in the Google Earth engine database.The quantitative analysis and evaluation of time,spatial consistency,spatial continuity,and product comparison are performed from the space and time scale.In January and August,the spatial distribution of MuSyQ NDVI,Landsat NDVI,and sentinel-2 NDVI products in China is reasonable and consistent.MuSyQ NDVI’s lack of space in January is lower than that of two other products.The frequency distribution histogram of MuSyQ NDVI,Landsat NDVI,and sentinel-2 NDVI differs.The difference among the three products is concentrated in the range of±0.2,the peak value is at 0,and the frequency is close to 70%.These findings indicate that MuSyQ NDVI has good spatial consistency with the two other NDVI products.In Northeast China,Northwest China,and Qinghai Tibet Plateau,MuSyQ NDV has a lower loss rate and better spatial continuity than the two other products.Moreover,the spatial continuity of products is high.On the whole,the effective value ratio of the MuSyQ NDVI product is better than that of the two other products;in particular,the effective value ratios of the MuSyQ NDVI product in farmland and grassland areas are 28.6(70%)and 30.27(70%),respectively,which are higher than those of the two other NDVI products.In the forest area,the effective value ratio of MuSyQ NDVI is also slightly better than that of the two other products.The three NDVI products have good consistency and phenological characteristics in the time series of farmland and grassland.In the deciduous broad-leaved forest area,the three products have similar seasonal variation laws.They fluctuate greatly in the time series curve in the evergreen broad-leaved forest and evergreen coniferous forest area.The consistency of MuSyQ NDVI,Landsat NDVI,and sentinel-2 NDVI in nonforest sites is higher than that in forest sites.In terms of spatial and temporal scales,the high spatial-temporal resolution NDVI products provided by GF-1/NDVI products are better than the existing products.They also provide useful information for selecting NDVI products in subsequent vegetation dynamic research.Moreover,they have advantages for long-time series fine monitoring in an extensive spatial range.
作者 张召星 李静 柳钦火 赵静 董亚冬 李松泽 文远 于文涛 ZHANG Zhaoxing;LI Jing;LIU Qinhuo;ZHAO Jing;DONG Yadong;LI Songze;WEN Yuan;YU Wentao(State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处 《遥感学报》 EI CSCD 北大核心 2023年第3期665-676,共12页 NATIONAL REMOTE SENSING BULLETIN
基金 高分辨率对地观测系统重大专项(编号:21-Y20B02-9003-19/22,21-Y20B01-9001-19/22) 中国科学院空天信息创新研究院重点部署项目(编号:E0Z202010F)。
关键词 高分一号(GF-1) 植被指数 高分辨率 时空特征 交叉验证 GF-1 vegetation index high resolution spatiotemporal characteristics cross validation
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