Work

Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass

Year: 2014

Type: article

Source: Remote Sensing of Environment

DOI: 10.1016/j.rse.2014.07.028

Authors: F.E. Fassnacht, F. Hartig, H. Latifi, C. Berger, J. Hernández, P. Corvalán, B. Koch

Institutions: Karlsruhe Institute of Technology, University of Freiburg, University of Würzburg, Friedrich Schiller University Jena, University of Chile

Language: English

Topic: Remote Sensing and LiDAR Applications

Subfield: Forestry

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Life on land, Climate action

Open Access status: green

Funder: National Aeronautics and Space Administration

OpenAlex ID: W2020520344

FWCI: 32.14

Cites: 90

Cited by: 457

Related to: 10