干旱区生态环境知识资源中心(Arid): Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems

Arid

DOI	10.1016/j.scitotenv.2023.161716
	Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems
	Qader, Sarchil Hama; Utazi, Chigozie Edson; Priyatikanto, Rhorom; Najmaddin, Peshawa; Hama-Ali, Emad Omer; Khwarahm, Nabaz R.; Tatem, Andrew J.; Dash, Jadu
通讯作者	Qader, SH
来源期刊	SCIENCE OF THE TOTAL ENVIRONMENT
ISSN	0048-9697
EISSN	1879-1026
出版年	2023
卷号	869
英文摘要	Low levels of agricultural productivity are associated with the persistence of food insecurity, poverty, and other socio-economic stresses. Mapping and monitoring agricultural dynamics and production in real-time at high spatial resolu-tion are essential for ensuring food security and shaping policy interventions. However, an accurate yield estimation might be challenging in some arid and semi-arid regions since input datasets are generally scarce, and access is re-stricted due to security challenges. This work examines how well Sentinel-2 satellite sensor-derived data, topographic and climatic variables, can be used as covariates to accurately model and predict wheat crop yield at the farm level using statistical models in low data settings of arid and semi-arid regions, using Sulaimani governorate in Iraq as an example. We developed a covariate selection procedure that assessed the correlations between the covariates and their relationships with wheat crop yield. Potential non-linear relationships were investigated in the latter case using regression splines. In the absence of substantial non-linear relationships between the covariates and crop yield, and residual spatial autocorrelation, we fitted a Bayesian multiple linear regression model to model and predict crop yield at 10 m resolution. Out of the covariates tested, our results showed significant relationships between crop yield and mean cumulative NDVI during the growing season, mean elevation, mean end of the season, mean maximum temperature and mean the start of the season at the farm level. For in-sample prediction, we estimated an R2 value of 51 % for the model, whereas for out-of-sample prediction, this was 41 %, both of which indicate reasonable predictive performance. The calculated root-mean-square error for out-of-sample prediction was 69.80, which is less than the standard deviation of 89.23 for crop yield, further showing that the model performed well by reducing prediction var-iability. Besides crop yield estimates, the model produced uncertainty metrics at 10 m resolution. Overall, this study showed that Sentinel-2 data can be valuable for upscaling field measurement of crop yield in arid and semi-arid regions. In addition, the environmental covariates can strengthen the model predictive power. The method may be applicable in other areas with similar environments, particularly in conflict zones, to increase the availability of agricultural statistics.
类型	Article
语种	英语
开放获取类型	hybrid, Green Accepted
收录类别	SCI-E
WOS记录号	WOS:000924993100001
WOS关键词	SENSED VEGETATION INDEXES ; TIME-SERIES ; PRIMARY PRODUCTIVITY ; PHENOLOGY ; SIMULATION ; COVER ; GLOBELAND30 ; LEVEL
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398504
推荐引用方式 GB/T 7714	Qader, Sarchil Hama,Utazi, Chigozie Edson,Priyatikanto, Rhorom,et al. Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems[J],2023,869.
APA	Qader, Sarchil Hama.,Utazi, Chigozie Edson.,Priyatikanto, Rhorom.,Najmaddin, Peshawa.,Hama-Ali, Emad Omer.,...&Dash, Jadu.(2023).Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems.SCIENCE OF THE TOTAL ENVIRONMENT,869.
MLA	Qader, Sarchil Hama,et al."Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems".SCIENCE OF THE TOTAL ENVIRONMENT 869(2023).