气候变化领域集成服务门户(CCPortal): Improving MODIS Gross Primary Productivity by Bridging Big-Leaf and Two-Leaf Light Use Efficiency Models

CCPortal

DOI	10.1029/2023JG007737
	Improving MODIS Gross Primary Productivity by Bridging Big-Leaf and Two-Leaf Light Use Efficiency Models
	Ma, Yongming; Guan, Xiaobin; Chen, Jing Ming; Ju, Weimin; Huang, Wenli; Shen, Huanfeng
发表日期	2024
ISSN	2169-8953
EISSN	2169-8961
起始页码	129
结束页码	5
卷号	129 期号:5
英文摘要	Gross primary productivity (GPP) is an important component of the terrestrial carbon cycle in climate change research. The global GPP product derived using Moderate Resolution Imaging Spectroradiometer (MODIS) data is perhaps the most widely used. Unfortunately, many studies have indicated evident error patterns in the MODIS GPP product. One of the main reasons for this is that the applied big-leaf (BL) MOD17 model cannot properly handle the variable relative contribution of sunlit and shaded leaves to the total canopy-level GPP. In this study, we developed a model for correcting the errors in the MODIS GPP product by bridging BL and two-leaf (TL) light use efficiency (LUE) models (CTL-MOD17). With the available MODIS GPP product, which considers environmental stress factors, the CTL-MOD17 model only needs to reuse the two inputs of the leaf area index (LAI) and incoming radiation. The CTL-MOD17 model was calibrated and validated at 153 global FLUXNET eddy covariance (EC) sites. The results indicate that the modeled GPP obtained with the correction model matches better with the EC GPP than the original MODIS GPP product at different time scales, with an improvement of 0.07 in R2 and a reduction in root-mean-square error (RMSE) of 117.08 g C m-2 year-1. The improvements are more significant in the green season when the contribution of shaded leaves is larger. In terms of the global spatial pattern, the obvious underestimation in the regions with high LAI and the overestimation in the low LAI regions of the MODIS GPP product is effectively corrected by the CTL-MOD17 model. This paper not only bridges the BL and TL LUE models, but also provides a new and simple method to obtain accurate GPP through reusing two inputs used in producing the MODIS GPP product. Gross primary productivity (GPP) is crucial for terrestrial carbon cycle study. The Moderate Resolution Imaging Spectroradiometer (MODIS) GPP data is perhaps the most widely used product, but many studies have indicated evident error patterns in it. These errors can be mainly explained by the applied big-leaf (BL) MOD17 model cannot properly handle the variable relative contribution of sunlit and shaded leaves to the total canopy-level GPP. As a result, this paper developed a novel and simple model (CTL-MOD17) to obtain accurate GPP by reusing two inputs data from the MODIS GPP product, based on a two-leaf (TL) theory. The CTL-MOD17 model is evaluated at 153 global FLUXNET eddy covariance (EC) sites, and compared with other TL GPP products and models. The results indicate that CTL-MOD17 can significantly improve the accuracy of MODIS GPP products at different time scales, to be similar to other TL models but with fewer data inputs. The obvious underestimation/overestimation of MODIS GPP in the high/low leaf area index (LAI) regions are all effectively corrected. This study proves the possibility of bridging the BL and TL models for the first time, which can be migrated to other BL products and models. A novel product-based model (CTL-MOD17) corrects Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product bias, achieving results similar to two-leaf models with fewer inputs It is the first time to prove the possibility of bridging the big-leaf and two-leaf models, which can be migrated to other big-leaf GPP products and models The obvious underestimation/overestimation of MODIS GPP in high/low LAI regions are all effectively corrected by the CTL-MOD17 model
英文关键词	gross primary productivity; MODIS; light use efficiency; two-leaf model; product correction
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary
WOS记录号	WOS:001227225400001
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/306841
作者单位	Wuhan University; University of Toronto; Zhaotong University; Fujian Normal University; Nanjing University
推荐引用方式 GB/T 7714	Ma, Yongming,Guan, Xiaobin,Chen, Jing Ming,et al. Improving MODIS Gross Primary Productivity by Bridging Big-Leaf and Two-Leaf Light Use Efficiency Models[J],2024,129(5).
APA	Ma, Yongming,Guan, Xiaobin,Chen, Jing Ming,Ju, Weimin,Huang, Wenli,&Shen, Huanfeng.(2024).Improving MODIS Gross Primary Productivity by Bridging Big-Leaf and Two-Leaf Light Use Efficiency Models.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,129(5).
MLA	Ma, Yongming,et al."Improving MODIS Gross Primary Productivity by Bridging Big-Leaf and Two-Leaf Light Use Efficiency Models".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 129.5(2024).