高分一号卫星高时空分辨率植被指数产品验证与分析

张召星; 李静; 柳钦火; 赵静; 董亚冬; 李松泽; 文远; 于文涛

doi:10.11834/jrs.20231710

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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
Verification and analysis of high spatial-temporal resolution vegetation index product based on GF-1 satellite data
2023年27卷第3期页码：665-676
收稿：2021-11-08，

纸质出版：2023-03-07
DOI： 10.11834/jrs.20231710
稿件说明：

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张召星，李静，柳钦火，赵静，董亚冬，李松泽，文远，于文涛.2023.高分一号卫星高时空分辨率植被指数产品验证与分析.遥感学报，27（3）： 665-676 DOI： 10.11834/jrs.20231710.

Zhang Z X，Li J，Liu Q H，Zhao J，Dong Y D，Li S Z，Wen Y and Yu W T. 2023. Verification and analysis of high spatial-temporal resolution vegetation index product based on GF-1 satellite data. National Remote Sensing Bulletin， 27（3）：665-676 DOI： 10.11834/jrs.20231710.

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。

Abstract

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.

关键词

Keywords

references

An Y Z , Gao W , Gao Z Q , Liu C S and Shi R H . 2015 . Trend analysis for evaluating the consistency of Terra MODIS and SPOT VGT NDVI time series products in China . Frontiers of Earth Science , 9 ( 1 ): 125 - 136 [ DOI: 10.1007/s11707-014-0428-9 http://dx.doi.org/10.1007/s11707-014-0428-9 ]

Baret F , Morissette J T , Fernandes R A , Champeaux J L , Myneni R B , Chen J , Plummer S , Weiss M , Bacour C , Garrigues S and Nickeson J E . 2006 . Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: proposition of the CEOS-BELMANIP . IEEE Transactions on Geoscience and Remote Sensing , 44 ( 7 ): 1794 - 1803 [ DOI: 10.1109/tgrs.2006.876030 http://dx.doi.org/10.1109/tgrs.2006.876030 ]

Beck H E , McVicar T R , van Dijk A I J M , Schellekens J , de Jeu R A M and Bruijnzeel L A . 2011 . Global evaluation of four AVHRR-NDVI data sets: intercomparison and assessment against Landsat imagery . Remote Sensing of Environment , 115 ( 10 ): 2547 - 2563 [ DOI: 10.1016/j.rse.2011.05.012 http://dx.doi.org/10.1016/j.rse.2011.05.012 ]

Beck P S A and Goetz S J . 2011 . Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences . Environmental Research Letters , 6 ( 4 ): 045501 [ DOI: 10.1088/1748-9326/6/4/045501 http://dx.doi.org/10.1088/1748-9326/6/4/045501 ]

Camacho F , Cernicharo J , Lacaze R , Baret F and Weiss M . 2013 . GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: validation and intercomparison with reference products . Remote Sensing of Environment , 137 : 310 - 329 [ DOI: 10.1016/j.rse.2013.02.030 http://dx.doi.org/10.1016/j.rse.2013.02.030 ]

Cao M K and Woodward F I . 1998 . Dynamic responses of terrestrial ecosystem carbon cycling to global climate change . Nature , 393 ( 6682 ): 249 - 252 [ DOI: 10.1038/30460 http://dx.doi.org/10.1038/30460 ]

Fan L , Gao Y , Brück H and Bernhofer C . 2009 . Investigating the relationship between NDVI and LAI in semi-arid grassland in Inner Mongolia using in-situ measurements . Theoretical and Applied Climatology , 95 ( 1/2 ): 151 - 156 [ DOI: 10.1007/s00704-007-0369-2 http://dx.doi.org/10.1007/s00704-007-0369-2 ]

Gobron N , Pinty B , Verstraete M and Govaerts Y . 1999 . The MERIS Global Vegetation Index (MGVI): description and preliminary application . International Journal of Remote Sensing , 20 ( 9 ): 1917 - 1927 [ DOI: 10.1080/014311699212542 http://dx.doi.org/10.1080/014311699212542 ]

Hird J N and McDermid G J . 2009 . Noise reduction of NDVI time series: an empirical comparison of selected techniques . Remote Sensing of Environment , 113 ( 1 ): 248 - 258 [ DOI: 10.1016/j.rse.2008.09.003 http://dx.doi.org/10.1016/j.rse.2008.09.003 ]

Ichii K , Kawabata A and Yamaguchi Y . 2002 . Global correlation analysis for NDVI and climatic variables and NDVI trends: 1982-1990 . International Journal of Remote Sensing , 23 ( 18 ): 3873 - 3878 [ DOI: 10.1080/01431160110119416 http://dx.doi.org/10.1080/01431160110119416 ]

Jiang J Y , Xiao Z Q , Wang J D and Song J L . 2014 . Sequential method with incremental analysis update to retrieve leaf area index from time series MODIS Reflectance Data . Remote Sensing , 6 ( 10 ): 9194 - 9212 [ DOI: 10.3390/rs6109194 http://dx.doi.org/10.3390/rs6109194 ]

Li S Z , Li J , Yu W T , Zhang Z X , Wu S L , Zhong B and Liu Q H . 2022 . A dataset of 16 m/10-day normalized difference vegetation index of MuSyQ GF-series ( 2018 - 2020 , China, Version 01). China Scientific Data , 7 ( 1 ): 231 - 240

李松泽 , 李静 , 于文涛 , 张召星 , 吴善龙 , 仲波 , 柳钦火 . 2022 . MuSyQ高分16米空间分辨率10天合成的NDVI植被指数产品(2018-2020年中国01版) . 中国科学数据 , 7 ( 1 ): 231 - 240 [ DOI: 10.11922/csdata.2021.0030.zh http://dx.doi.org/10.11922/csdata.2021.0030.zh ]

Lin X N , Niu J Z , Berndtsson R , Yu X X , Zhang L and Chen X W . 2020 . NDVI dynamics and its response to climate change and reforestation in Northern China . Remote Sensing , 12 ( 24 ): 4138 [ DOI: 10.3390/rs12244138 http://dx.doi.org/10.3390/rs12244138 ]

Liu Q H , Wen J G , Zhou X , Zhao J , Li Z Y , Li X , Ma M G , Wang W Z , Liao X H , Liu S M , Fan W J , Xiao Q , Zhong B , Li J , Xin X Z , Li L , Jia L , Gao Z H , Jin J D , Liang S , Xin J , Liao C J and Wu Y R . 2023 . Technique system of remote sensing product generation and validation of GF common products . National Remote Sensing Bulletin ， 27 ( 3 ): 544 - 562

柳钦火 , 闻建光 , 周翔 , 赵坚 , 李增元 , 李新 , 马明国 , 王维真 , 廖小罕 , 刘绍民 , 范闻捷 , 肖青 , 仲波 , 李静 , 辛晓洲 , 李丽 , 贾立 , 高志海 , 金家栋 , 梁师 , 邢进 , 廖楚江 , 吴一戎 . 2023 . 高分遥感共性产品生成和真实性检验技术体系 . 遥感学报 , 27 ( 3 ): 544 - 562 [ DOI： 10.11834/jrs.20235022 http://dx.doi.org/10.11834/jrs.20235022 ]

Ma Q , Su Y J , Luo L P , Li L , Kelly M and Guo Q H . 2018 . Evaluating the uncertainty of Landsat-derived vegetation indices in quantifying forest fuel treatments using bi-temporal LiDAR data . Ecological Indicators , 95 : 298 - 310 [ DOI: 10.1016/j.ecolind.2018.07.050 http://dx.doi.org/10.1016/j.ecolind.2018.07.050 ]

Maisongrande P , Duchemin B and Dedieu G . 2004 . VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products . International Journal of Remote Sensing , 25 ( 1 ): 9 - 14 [ DOI: 10.1080/0143116031000115265 http://dx.doi.org/10.1080/0143116031000115265 ]

Mao D H , Wang Z M , Luo L and Ren C Y . 2012 . Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China . International Journal of Applied Earth Observation and Geoinformation , 18 : 528 - 536 [ DOI: 10.1016/j.jag.2011.10.007 http://dx.doi.org/10.1016/j.jag.2011.10.007 ]

Peng J , Liu Z H , Liu Y H , Wu J S and Han Y A . 2012 . Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent . Ecological Indicators , 14 ( 1 ): 28 - 39 [ DOI: 10.1016/j.ecolind.2011.08.011 http://dx.doi.org/10.1016/j.ecolind.2011.08.011 ]

Sajadi P , Sang Y F , Gholamnia M , Bonafoni S , Brocca L , Pradhan B and Singh A . 2021 . Performance evaluation of long NDVI timeseries from AVHRR, MODIS and landsat sensors over landslide-prone locations in Qinghai-Tibetan Plateau . Remote Sensing , 13 ( 16 ): 3172 [ DOI: 10.3390/rs13163172 http://dx.doi.org/10.3390/rs13163172 ]

Song Y , Ma M G and Veroustraete F . 2010 . Comparison and conversion of AVHRR GIMMS and SPOT VEGETATION NDVI data in China . International Journal of Remote Sensing , 31 ( 9 ): 2377 - 2392 [ DOI: 10.1080/01431160903002409 http://dx.doi.org/10.1080/01431160903002409 ]

Sugiura K , Nagai S , Nakai T and Suzuki R . 2013 . Application of time-lapse digital imagery for ground-truth verification of satellite indices in the boreal forests of Alaska . Polar Science , 7 ( 2 ): 149 - 161 [ DOI: 10.1016/j.polar.2013.02.003 http://dx.doi.org/10.1016/j.polar.2013.02.003 ]

Tian X P , Liu S H , Sun L and Liu Q . 2018 . Retrieval of aerosol optical depth in the arid or semiarid region of Northern Xinjiang, China . Remote Sensing , 10 ( 2 ): 197 [ DOI: 10.3390/rs10020197 http://dx.doi.org/10.3390/rs10020197 ]

Tucker C J , Pinzon J E , Brown M E , Slayback D A , Pak E W , Mahoney R , Vermote E F and El Saleous N . 2005 . An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data . International Journal of Remote Sensing , 26 ( 20 ): 4485 - 4498 [ DOI: 10.1080/01431160500168686 http://dx.doi.org/10.1080/01431160500168686 ]

Tucker C J , Slayback D A , Pinzon J E , Los S O , Myneni R B and Taylor M G . 2001 . Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999 . International Journal of Biometeorology , 45 ( 4 ): 184 - 190 [ DOI: 10.1007/s00484-001-0109-8 http://dx.doi.org/10.1007/s00484-001-0109-8 ]

Vancutsem C , Pekel J F , Bogaert P and Defourny P . 2007 . Mean Compositing, an alternative strategy for producing temporal syntheses. Concepts and performance assessment for SPOT VEGETATION time series . International Journal of Remote Sensing , 28 ( 22 ): 5123 - 5141 [ DOI: 10.1080/01431160701253212 http://dx.doi.org/10.1080/01431160701253212 ]

Vannoppen A and Gobin A . 2021 . Estimating farm wheat yields from NDVI and meteorological data . Agronomy , 11 ( 5 ): 946 [ DOI: 10.3390/agronomy11050946 http://dx.doi.org/10.3390/agronomy11050946 ]

Wu X D , Wen J G , Xiao Q , Li X , Liu Q , Tang Y , Dou B C , Peng J J , You D Q and Li X W . 2015 . Advances in validation methods for remote sensing products of land surface parameters . Journal of Remote Sensing , 19 ( 1 ): 75 - 92

吴小丹 , 闻建光 , 肖青 , 李新 , 刘强 , 唐勇 , 窦宝成 , 彭菁菁 , 游冬琴 , 李小文 . 2015 . 关键陆表参数遥感产品真实性检验方法研究进展 . 遥感学报 , 19 ( 1 ): 75 - 92 [ DOI: 10.11834/jrs.20154009 http://dx.doi.org/10.11834/jrs.20154009 ]

Xu B D , Li J , Park T , Liu Q H , Zeng Y L , Yin G F , Zhao J , Fan W L , Yang L , Knyazikhin Y and Myneni R B . 2018 . An integrated method for validating long-term leaf area index products using global networks of site-based measurements . Remote Sensing of Environment , 209 : 134 - 151 [ DOI: 10.1016/j.rse.2018.02.049 http://dx.doi.org/10.1016/j.rse.2018.02.049 ]

Zhang H , Li J , Zhang Z X , Wu S L , Zhong B and Liu Q H . 2022 . A dataset of 16m/10-day leaf area indices of MuSyQ GF-series ( 2018 - 2020 , China, Version 01). China Scientific Data , 7 ( 1 ): 211 - 220

张虎 , 李静 , 张召星 , 吴善龙 , 仲波 , 柳钦火 . 2022 . MuSyQ高分16米分辨率10天合成的叶面积指数产品(2018-2020年中国01版) . 中国科学数据 , 7 ( 1 ): 211 - 220 [ DOI: 10.11922/csdata.2021.0029.zh http://dx.doi.org/10.11922/csdata.2021.0029.zh ]

Zhang X , Liu L Y , Chen X D , Gao Y , Xie S and Mi J . 2021 . GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery . Earth System Science Data , 13 ( 6 ): 2753 - 2776 [ DOI: 10.5194/essd-13-2753-2021 http://dx.doi.org/10.5194/essd-13-2753-2021 ]

Zhao J , Li J , Zhang Z X , Wu S L , Zhong B and Liu Q H . 2022 . A dataset of 16 m/10-day fractional vegetation cover of MuSyQ GF-series ( 2018 - 2020 , China, Version 01). China Scientific Data , 7 ( 1 ): 221 - 230

赵静 , 李静 , 张召星 , 吴善龙 , 仲波 , 柳钦火 . 2022 . MuSyQ高分16米空间分辨率10天合成的植被覆盖度产品(2018-2020年中国01版) . 中国科学数据 , 7 ( 1 ): 221 - 230 [ DOI: 10.11922/11-6035.csd.2021.0037.zh http://dx.doi.org/10.11922/11-6035.csd.2021.0037.zh ]

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