Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables

By K. Nurminen, M. Karjalainen, Xiaowei Yu, Juha Hyyppä, Eija Honkavaara. 2013

132 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/3ed67cbb707e3ab1e92610e1e3b49c8a36617cf1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Joanne C. White
2. M. Wulder
3. Eduardo González-Ferreiro
4. Ramón Alberto Díaz-Varela
5. Margarida Tomé
6. Nicholas C. Coops
7. Zhe Zhu

In Environmental Engineering

1. Joanne C. White
2. Nicholas C. Coops
3. M. Wulder
4. Eduardo González-Ferreiro
5. Ramón Alberto Díaz-Varela
6. Margarida Tomé
7. C. Stepper

In Nature and Landscape Conservation

1. Eduardo González-Ferreiro
2. Margarida Tomé
3. M. Wulder
4. Nicholas C. Coops
5. Joanne C. White
6. C. Stepper

Citations in the corpus

• Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal (2016, methodology): “…cloud, a digital terrain model (DTM), a digital surface model (DSM), and a canopy height model (CHM) –computed by subtracting DTM from DSM– can be obtained, and individual tree attributes can be measured in the same way that processing ALS (Airborne Laser Scanning) data (Nurminen et al., 2013).”
• Comparing ALS and Image-Based Point Cloud Metrics and Modelled Forest Inventory Attributes in a Complex Coastal Forest Environment (2015, background): “, [8,16]) with minimal impact on model outcomes quantified thus far [7].”