中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Evaluation of Sampling Methods for Validation of Remotely Sensed Fractional Vegetation Cover

文献类型:SCI/SSCI论文

作者Mu X. H.; Hu, M. G.; Song, W. J.; Ruan, G. Y.; Ge, Y.; Wang, J. F.; Huang, S.; Yan, G. J.
发表日期2015
关键词validation sampling methods fractional vegetation cover remote sensing product scaling bias spatial autocorrelation model optimization design images variables ndvi
英文摘要Validation over heterogeneous areas is critical to ensuring the quality of remote sensing products. This paper focuses on the sampling methods used to validate the coarse-resolution fractional vegetation cover (FVC) product in the Heihe River Basin, where the patterns of spatial variations in and between land cover types vary significantly in the different growth stages of vegetation. A sampling method, called the mean of surface with non-homogeneity (MSN) method, and three other sampling methods are examined with real-world data obtained in 2012. A series of 15-m-resolution fractional vegetation cover reference maps were generated using the regressions of field-measured and satellite data. The sampling methods were tested using the 15-m-resolution normalized difference vegetation index (NDVI) and land cover maps over a complete period of vegetation growth. Two scenes were selected to represent the situations in which sampling locations were sparsely and densely distributed. The results show that the FVCs estimated using the MSN method have errors of approximately less than 0.03 in the two selected scenes. The validation accuracy of the sampling methods varies with variations in the stratified non-homogeneity in the different growing stages of the vegetation. The MSN method, which considers both heterogeneity and autocorrelations between strata, is recommended for use in the determination of samplings prior to the design of an experimental campaign. In addition, the slight scaling bias caused by the non-linear relationship between NDVI and FVC samples is discussed. The positive or negative trend of the biases predicted using a Taylor expansion is found to be consistent with that of the real biases.
出处Remote Sensing
7
12
16164-16182
语种英语
ISSN号2072-4292
DOI标识10.3390/rs71215817
源URL[http://ir.igsnrr.ac.cn/handle/311030/43556]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Mu X. H.,Hu, M. G.,Song, W. J.,et al. Evaluation of Sampling Methods for Validation of Remotely Sensed Fractional Vegetation Cover. 2015.

入库方式: OAI收割

来源:地理科学与资源研究所

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