Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area

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
刊名	CHINESE GEOGRAPHICAL SCIENCE
	2019-02-01
卷号	29 期号:1 页码:166-180
关键词	fractional vegetation cover (FVC) Sentinel-2A (S2) unmanned aerial vehicle (UAV) image pixel dichotomy model regression model
ISSN号	1002-0063
DOI	10.1007/s11769-018-1010-2
通讯作者	Zhang, Tinglong(dargon810614@126.com) ; Bu, Chongfeng(buchongfeng@163.com)
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).
资助项目	National Natural Science Foundation of China[41301451] ; National Natural Science Foundation of China[41541008] ; Fundamental Research Funds for the Central Universities[2452018144]
WOS关键词	SPECTRAL INDEXES ; SENTINEL-2 ; RANGELANDS ; IMAGERY
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000455227500013
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/50607]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Tinglong; Bu, Chongfeng
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]. CHINESE GEOGRAPHICAL SCIENCE,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.