干旱区生态环境知识资源中心(Arid): Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area

Arid

DOI	10.1007/s11769-018-1010-2
	Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area
	Liu, Qiuyu 1; Zhang, Tinglong 1; Li, Yizhe 1; Li, Ying 1; Bu, Chongfeng 2; Zhang, Qingfeng 1
通讯作者	Zhang, Tinglong ; Bu, Chongfeng
来源期刊	CHINESE GEOGRAPHICAL SCIENCE
ISSN	1002-0063
EISSN	1993-064X
出版年	2019
卷号	29 期号:1 页码:166-180
英文摘要	The estimation of fractional vegetation cover (FVC) is important for identifying and monitoring desertification, especially in arid and semiarid regions. By using regression and pixel dichotomy models, we present the comparison of Sentinel-2A (S2) multispectral instrument (MSI) and Landsat 8 (L8) operational land imager (OLI) data regarding the retrieval of FVC in a semi-arid sandy area (Mu Us Sandland, China, in August 2016). A combination of unmanned aerial vehicle (UAV) high-spatial-resolution images and field plots were used to produce verified data. Based on a normalized difference vegetation index (NDVI) regression model, the results showed that, compared with that of L8, the coefficient of determination (R-2) of S2 increased by 26.0%, and the root mean square error (RMSE) and the sum of absolute error (SAE) decreased by 3.0% and 11.4%, respectively. For the ratio vegetation index (RVI) regression model, compared with that of L8, the R-2 of S2 increased by 26.0%, and the RMSE and SAE decreased by 8.0% and 20.0%, respectively. When the pixel dichotomy model was used, compared with that of L8, the RMSE of S2 decreased by 21.3%, and the SAE decreased by 26.9%. Overall, S2 performed better than L8 in terms of FVC inversion. Additionally, in this paper, we develop a verified scheme based on UAV data in combination with the object-based classification method. This scheme is feasible and sufficiently robust for building relationships between field data and inversion results from satellite data. Further, the synergy of multi-source sensors (especially UAVs and satellites) is a potential effective way to estimate and evaluate regional ecological environmental parameters (FVC).
英文关键词	fractional vegetation cover (FVC) Sentinel-2A (S2) unmanned aerial vehicle (UAV) image pixel dichotomy model regression model
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	Bronze
收录类别	SCI-E
WOS记录号	WOS:000455227500013
WOS关键词	SPECTRAL INDEXES ; SENTINEL-2 ; RANGELANDS ; IMAGERY
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	西北农林科技大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/214886
作者单位	1.Northwest A&F Univ, Coll Nat Resources & Environm, Yangling 712100, Shaanxi, Peoples R China; 2.Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, 26 Xinong Rd, Yangling 712100, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Liu, Qiuyu,Zhang, Tinglong,Li, Yizhe,et al. Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area[J]. 西北农林科技大学,2019,29(1):166-180.
APA	Liu, Qiuyu,Zhang, Tinglong,Li, Yizhe,Li, Ying,Bu, Chongfeng,&Zhang, Qingfeng.(2019).Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area.CHINESE GEOGRAPHICAL SCIENCE,29(1),166-180.
MLA	Liu, Qiuyu,et al."Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area".CHINESE GEOGRAPHICAL SCIENCE 29.1(2019):166-180.