气候变化领域集成服务门户(CCPortal): Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network

CCPortal

DOI	10.3390/rs12203304
	Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network
	Yu, Lihong; Shang, Jiali; Cheng, Zhiqiang; Gao, Zebin; Wang, Zixin; Tian, Luo; Wang, Dantong; Che, Tao; Jin, Rui; Liu, Jiangui; Dong, Taifeng; Qu, Yonghua
发表日期	2020
EISSN	2072-4292
卷号	12 期号:20
英文摘要	Accurate and continuous monitoring of leaf area index (LAI), a widely-used vegetation structural parameter, is crucial to characterize crop growth conditions and forecast crop yield. Meanwhile, advancements in collecting field LAI measurements have provided strong support for validating remote-sensing-derived LAI. This paper evaluates the performance of LAI retrieval from multi-source, remotely sensed data through comparisons with continuous field LAI measurements. Firstly, field LAI was measured continuously over periods of time in 2018 and 2019 using LAINet, a continuous LAI measurement system deployed using wireless sensor network (WSN) technology, over an agricultural region located at the Heihe watershed at northwestern China. Then, cloud-free images from optical satellite sensors, including Landsat 7 the Enhanced Thematic Mapper Plus (ETM+), Landsat 8 the Operational Land Imager (OLI), and Sentinel-2A/B Multispectral Instrument (MSI), were collected to derive LAI through inversion of the PROSAIL radiation transfer model using a look-up-table (LUT) approach. Finally, field LAI data were used to validate the multi-temporal LAI retrieved from remote-sensing data acquired by different satellite sensors. The results indicate that good accuracy was obtained using different inversion strategies for each sensor, while Green Chlorophyll Index (CIgreen) and a combination of three red-edge bands perform better for Landsat 7/8 and Sentinel-2 LAI inversion, respectively. Furthermore, the estimated LAI has good consistency with in situ measurements at vegetative stage (coefficient of determination R-2 = 0.74, and root mean square error RMSE = 0.53 m(2) m(-2)). At the reproductive stage, a significant underestimation was found (R-2 = 0.41, and 0.89 m(2) m(-2) in terms of RMSE). This study suggests that time-series LAI can be retrieved from multi-source satellite data through model inversion, and the LAINet instrument could be used as a low-cost tool to provide continuous field LAI measurements to support LAI retrieval.
英文关键词	leaf area index; PROSAIL; look-up-table (LUT); multi-source satellite data; LAINet; wireless sensor network (WSN)
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS关键词	LEAF-AREA INDEX ; VEGETATION INDEXES ; GREEN LAI ; CHLOROPHYLL CONTENT ; GLOBAL PRODUCTS ; VALIDATION ; REFLECTANCE ; ALGORITHM ; MODEL
WOS记录号	WOS:000585647600001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/241065
作者单位	[Yu, Lihong; Wang, Zixin; Tian, Luo; Wang, Dantong; Qu, Yonghua] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China; [Yu, Lihong; Wang, Zixin; Tian, Luo; Wang, Dantong; Qu, Yonghua] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100875, Peoples R China; [Yu, Lihong; Wang, Zixin; Tian, Luo; Wang, Dantong; Qu, Yonghua] Beijing Normal Univ, Beijing Engn Res Ctr Global Land Remote Sensing P, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing 100875, Peoples R China; [Yu, Lihong; Shang, Jiali; Liu, Jiangui; Dong, Taifeng] Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON K1A 0C6, Canada; [Cheng, Zhiqiang] Fujian Normal Univ, Inst Geog, Fuzhou 350007, Peoples R China; [Gao, Zebin] Beijing XiaoBaiShiJi Network Tech Co Ltd, Beijing 100084, Peoples R China; [Che, Tao; Jin, Rui] Northwest Inst Ecoenvironm & Resources CAS, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China; [Che, Tao; Jin, Rui] Chinese Ac...
推荐引用方式 GB/T 7714	Yu, Lihong,Shang, Jiali,Cheng, Zhiqiang,et al. Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network[J]. 中国科学院西北生态环境资源研究院,2020,12(20).
APA	Yu, Lihong.,Shang, Jiali.,Cheng, Zhiqiang.,Gao, Zebin.,Wang, Zixin.,...&Qu, Yonghua.(2020).Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network.REMOTE SENSING,12(20).
MLA	Yu, Lihong,et al."Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network".REMOTE SENSING 12.20(2020).