干旱区生态环境知识资源中心(Arid): Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape

Arid

DOI	10.1080/2150704X.2020.1767823
	Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape
	Kganyago, Mahlatse; Mhangara, Paidamwoyo; Alexandridis, Thomas; Laneve, Giovanni; Ovakoglou, Georgios; Mashiyi, Nosiseko
通讯作者	Kganyago, M
来源期刊	REMOTE SENSING LETTERS
ISSN	2150-704X
EISSN	2150-7058
出版年	2020
卷号	11 期号:10 页码:883-892
英文摘要	This study validated SNAP-derived LAI from Sentinel-2 and its consistency with existing global LAI products. The validation and inter-comparison experiments were performed on two processing levels, i. e., Top-of-Atmosphere and Bottom-of-Atmosphere reflectances and two spatial resolutions, i.e., 10 m, and 20 m. These were chosen to determine their effect on retrieved LAI accuracy and consistency. The results showed moderate R-2, i.e., similar to 0.6 to similar to 0.7 between SNAP-derived LAI and in-situ LAI, but with high errors, i.e., RMSE, BIAS, and MAE >2 m(2) m(-2) with marked differences between processing levels and insignificant differences between spatial resolutions. In contrast, inter-comparison of SNAP-derived LAI with MODIS and Proba-V LAI products revealed moderate to high consistencies, i. e., R-2 of similar to 0.55 and similar to 0.8 respectively, and RMSE of similar to 0.5 m(2) m(-2) and similar to 0.6 m(2) m(-2), respectively. The results in this study have implications for future use of SNAP-derived LAI from Sentinel-2 in agricultural landscapes, suggesting its global applicability that is essential for large-scale agricultural monitoring. However, enormous errors in characterizing field-level LAI variability indicate that SNAP-derived LAI is not suitable for precision farming. In fact, from the study, the need for further improvement of LAI retrieval arises, especially to support farm-level agricultural management decisions.
类型	Article
语种	英语
开放获取类型	hybrid, Green Published
收录类别	SCI-E
WOS记录号	WOS:000547031100001
WOS关键词	ESSENTIAL CLIMATE VARIABLES ; GEOV1 LAI ; DERIVATION ; RESOLUTION ; ALGORITHM ; MODIS
WOS类目	Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/324991
作者单位	[Kganyago, Mahlatse; Mashiyi, Nosiseko] South African Natl Space Agcy, Earth Observat, Enterprise Bldg,Mark Shuttleworth St, ZA-0001 Pretoria, South Africa; [Kganyago, Mahlatse; Mhangara, Paidamwoyo] Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Johannesburg, South Africa; [Alexandridis, Thomas; Ovakoglou, Georgios] Aristotle Univ Thessaloniki, Sch Agr, Lab Remote Sensing Spect & GIS, Thessaloniki, Greece; [Laneve, Giovanni] Sapienza Univ Roma, Scuola Ingn Aerosp, Rome, Italy
推荐引用方式 GB/T 7714	Kganyago, Mahlatse,Mhangara, Paidamwoyo,Alexandridis, Thomas,et al. Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape[J],2020,11(10):883-892.
APA	Kganyago, Mahlatse,Mhangara, Paidamwoyo,Alexandridis, Thomas,Laneve, Giovanni,Ovakoglou, Georgios,&Mashiyi, Nosiseko.(2020).Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape.REMOTE SENSING LETTERS,11(10),883-892.
MLA	Kganyago, Mahlatse,et al."Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape".REMOTE SENSING LETTERS 11.10(2020):883-892.