Johannes Rahlf
Remote Sensing of Environment · 2018–2020
A researcher in the Science corpus: 2 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Papers from Johannes Rahlf's perspective
Ordered by how strongly the researchers Johannes Rahlf trusts endorse each paper. Same corpus, a different order for every researcher.
- Random Forests
- Semi-automatic classification of tree species in different forest ecosystems by spectral and geometric variables derived from Airborne Digital Sensor (ADS40) and RC30 data
- Combining ensemble modeling and remote sensing for mapping individual tree species at high spatial resolution
- High-Resolution Global Maps of 21st-Century Forest Cover Change (Science)
- Sampling Techniques for Forest Inventories
- Species Spectral Signature: Discriminating closely related plant species in the Amazon with Near-Infrared Leaf-Spectroscopy
- Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery
- A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales (International Journal of Applied Earth Observation and Geoinformation)
- Review of studies on tree species classification from remotely sensed data
- Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification