Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 108; pp. 273 - 290
• Main Authors: Verrelst, Jochem, Camps-Valls, Gustau, Muñoz-Marí, Jordi, Rivera, Juan Pablo, Veroustraete, Frank, Clevers, Jan G.P.W., Moreno, José
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2015
• Subjects: algorithms; Bio-geophysical variables; Hybrid; image analysis; Machine learning; monitoring; Non-parametric; Operational variable retrieval; Parametric; Physical; regression analysis; remote sensing; satellites; spectrometers; uncertainty; vegetation; Physical; Bio-geophysical variables; Non-parametric; Operational variable retrieval; Machine learning; Hybrid; Parametric

Forthcoming superspectral satellite missions dedicated to land monitoring, as well as planned imaging spectrometers, will unleash an unprecedented data stream. The processing requirements for such large data streams involve processing techniques enabling the spatio-temporally explicit quantification...