气候变化领域集成服务门户(CCPortal): Principal Component Analysis of TerraSAR-X backscatter and coherence stacks one year (2012-2013) in the Lena River Delta, links to GeoTIFFs

CCPortal

DOI	https://doi.org/10.1594/PANGAEA.872142
	Principal Component Analysis of TerraSAR-X backscatter and coherence stacks one year (2012-2013) in the Lena River Delta, links to GeoTIFFs
	Antonova; Sofia; Kääb; Andreas; Heim; Birgit; Langer; Moritz; Boike; Julia
发布日期	2016-02-15
数据集类型	dataset
英文简介	Principal Component Analysis (PCA) is a well-established technique in remote sensing for the visualization of multidimensional data. It reduces redundancy in multiband or multitemporal imagery, increases the signal-to-noise ratio and provides an opportunity to use multitemporal datasets for change detection. PCA transforms the axes of multidimensional data in such way that the new axes (the principal components) account for variances within the data, with the first PC accounting for the largest variance and the last PC accounting for the smallest variance.
空间范围	Median Latitude: 72.950000 * Median Longitude: 126.550000 * South-bound Latitude: 72.000000 * West-bound Longitude: 123.600000 * North-bound Latitude: 73.900000 * East-bound Longitude: 129.500000
语种	英语
国家	国际
学科大类	气候变化
学科子类	气候变化
文献类型	数据集
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/219104
推荐引用方式 GB/T 7714	Antonova,Sofia,Kääb,et al. Principal Component Analysis of TerraSAR-X backscatter and coherence stacks one year (2012-2013) in the Lena River Delta, links to GeoTIFFs.2016-02-15.https://doi.org/10.1594/PANGAEA.872142.