Using satellite imagery and the k-nearest neighbors technique as a bridge between strategic and management forest inventories

50 citations recorded by the source corpus.

How researchers see this paper

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

Combining ALS and NFI training data for forest management planning: a case study in Kuortane, Western Finland (2009, methodology): “Kilpela ¨inen and Tokola 1999, Holmstro ¨m et al. 2001; Hyvo ¨nen et al. 2005; McRoberts 2008 ).”
Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data (2009, methodology): “…& Strahler, 1985; Woodcock et al., 1997; Cohen& Spies,1990; Song&Woodcock, 2003; Song, 2007), stem density (Cohen & Spies, 1992; Hudak et al., 2006; McRoberts, 2008), basal area (Franklin, 1986; Franco-Lopez et al., 2001; Hudak et al., 2006; McRoberts et al., 2007; McRoberts, 2008; Wolter et al.,…”
Optimizing the k-Nearest Neighbors technique for estimating forest aboveground biomass using airborne laser scanning data (2015, background): “Tomppo and Halme (2004), McRoberts (2008), Tomppo, Gagliano, De Natale, Katila and McRoberts (2009), and Holopainen et al. (2010) all illustrate the use of GAs to determine the optimal elements for weighted Euclidean distance represented by diagonal matrices, M.”
Multi-sensor data fusion for estimating forest species composition and abundance in northern Minnesota (2011, background): “…satellite sensor data (e.g., Landsat or SPOT) poses unique challenges in regions where species diversity and structural complexity arehigh (Wolter et al., 1995, 2008; Franco-Lopezet al., 2001;Reeseet al., 2002; Leckie et al., 2005; McRoberts, 2008; Stabach et al., 2009; Bauer et al., 2009).”