标题: Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades

作者: Guan, XB (Guan, Xiaobin); Shen, HF (Shen, Huanfeng); Wang, YC (Wang, Yuchen); Chu, D (Chu, Dong); Li, XH (Li, Xinghua); Yue, LW (Yue, Linwei); Li, W (Li, Wei); Liu, XX (Liu, Xinxin); Zhang, LP (Zhang, Liangpei)

来源出版物: BIG EARTH DATA DOI: 10.1080/20964471.2024.2448072 Early Access Date: JAN 2025 Published Date: 2025 JAN 15

摘要: Satellite normalized difference vegetation index (NDVI) time series, essential for ecological and environmental applications, is still limited by a trade-off between the spatiotemporal resolution and time coverage despite various global products. The Advanced Very High-Resolution Radiometer (AVHRR) instrument can provide the longest continuous time series since 1982, but with the drawback of coarse spatial resolution and poor data quality. To address this issue, a spatiotemporal fusion-based long-term NDVI product (STFLNDVI) since 1982 was generated in this study at a 1-km spatial resolution with monthly intervals, by fusing with the Moderate Resolution Imaging Spectroradiometer (MODIS) data. A multi-step processing fusion framework, containing temporal filtering, normalization, spatiotemporal fusion, and residual error correction, was employed to combine the superior characteristics of the two products, respectively. Simulated comparison with MODIS data and real-data assessments with true 1 km AVHRR data both confirm the ideal accuracy of the fusion product in spatial distribution and temporal variation, providing stable long-term results similar to MODIS data. We believe that the STFLNDVI product will be of great significance in characterizing the spatial patterns and long-term variations of global vegetation and the historical radiometric calibrations in AVHRR data gaps around the Arctic and instrument differences between MODIS and AVHRR should be further considered in the future.

作者关键词: NDVI; MODIS; AVHRR; spatiotemporal fusion; long-term

KeyWords Plus: LONG-TERM; SPOT-VEGETATION; REFLECTANCE; CONSISTENCY; PHENOLOGY; LANDSAT; DATASET; QUALITY; GIMMS; VIIRS

地址: [Guan, Xiaobin; Shen, Huanfeng; Wang, Yuchen; Chu, Dong; Li, Wei] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Guan, Xiaobin] Wuhan Univ, Key Lab GIS, Minist Educ, Wuhan, Peoples R China.

[Shen, Huanfeng; Zhang, Liangpei] Wuhan Univ, Key Lab Digital Mapping & Land Informat Applicat E, Natl Adm Surveying Mapping & Geoinformat, Wuhan, Peoples R China.

[Shen, Huanfeng] Collaborat Innovat Ctr Geospatial Technol, Wuhan, Peoples R China.

[Li, Xinghua] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan, Peoples R China.

[Yue, Linwei] China Univ Geosci, Sch Geog & Informat Engn, Wuhan, Peoples R China.

[Liu, Xinxin] Hunan Univ, Coll Elect & Informat Engn, Changsha, Peoples R China.

[Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying, Mapping & Remote Sensing, Wuhan, Peoples R China.

通讯作者地址: Shen, HF (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: shenhf@whu.edu.cn

影响因子：4.2