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Intercomparison and validation of five existing leaf chlorophyll content products over China

Authors :
Xiaohan Wang
Jing Li
Hu Zhang
Qinhuo Liu
Liangyun Liu
Chenpeng Gu
Faisal Mumtaz
Jing Zhao
Yadong Dong
Junhua Bai
Tianjia Chu
Chang Liu
Li Guan
Wenjiang Huang
Source :
International Journal of Applied Earth Observations and Geoinformation, Vol 130, Iss , Pp 103930- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Leaf chlorophyll content (LCC) is crucial in plant physiology and ecological research. Although several LCC products have recently been generated at a regional or global scale, understanding their accuracy is still a concern in the scientific community. We intercompared and analyzed five existing LCC products (MuSyQ LCC, MODIS LCC, MERIS LCC, GLCC, and GLOBMAP MERIS LCC) over China in terms of spatial continuity and spatiotemporal consistency over seven plant functional types. The products of 2011 and 2019 over China were used in this study. Research findings indicate (1) the 30 m-resolution MuSyQ LCC has the highest accuracy compared to field LCC of cropland and grassland types, with an RMSE of 19.5 μg/cm2, while MODIS LCC product demonstrates a more robust fit to the measured LCC, with an R2 of 0.341. (2) Interpolation of products with lower spatial resolution e.g. MODIS LCC, MERIS LCC, and GLOBMAP MERIS LCC, generally improves spatial continuity. The non-interpolated 30 m MuSyQ LCC exhibits good regional continuity due to its high spatial resolution. The lowest spatial continuity is found over shrubs for all products. (3) MODIS LCC and MuSyQ LCC of 2019 demonstrate high overall spatial consistency and exhibit the highest correlation over cropland sites. MODIS LCC and GLOBMAP MERIS LCC of 2011 demonstrate high temporal consistency over deciduous forests, evergreen forests, grasslands, and shrubs sites. The most robust overall temporal consistency is exhibited among all products in the deciduous needleleaved forest, followed by evergreen needleleaved forest and grassland. The findings of this research are essential for improving leaf chlorophyll content inversion algorithms and for understanding and better use of LCC products in land surface models.

Details

Language :
English
ISSN :
15698432
Volume :
130
Issue :
103930-
Database :
Directory of Open Access Journals
Journal :
International Journal of Applied Earth Observations and Geoinformation
Publication Type :
Academic Journal
Accession number :
edsdoj.8bbdacb5a1384f8d859170fb01225765
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jag.2024.103930