Details

Autor(en) / Beteiligte

• Lehnert, Lukas W.
• Meyer, Hanna
• Obermeier, Wolfgang A.
• Silva, Brenner
• Regeling, Bianca
• Bendix, Jörg

Titel

Hyperspectral Data Analysis in R : The hsdar Package

Ist Teil von

• Journal of statistical software, 2019-05, Vol.89 (12), p.1-23

Ort / Verlag

Foundation for Open Access Statistics

Erscheinungsjahr

2019

Link zum Volltext

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Hyperspectral remote sensing is a promising tool for a variety of applications including ecology, geology, analytical chemistry and medical research. This article presents the new hsdar package for R statistical software, which performs a variety of analysis steps taken during a typical hyperspectral remote sensing approach. The package introduces a new class for efficiently storing large hyperspectral data sets such as hyperspectral cubes within R. The package includes several important hyperspectral analysis tools such as continuum removal, normalized ratio indices and integrates two widely used radiation transfer models. In addition, the package provides methods to directly use the functionality of the caret package for machine learning tasks. Two case studies demonstrate the package's range of functionality: First, plant leaf chlorophyll content is estimated and second, cancer in the human larynx is detected from hyperspectral data.