Using satellite imagery as ancillary data for increasing the precision of estimates for the Forest Inventory and Analysis program of the USDA Forest Service

By Ronald E. McRoberts, G. Holden, M. D. Nelson, G. Liknes, Dale D. Gormanson. 2005

96 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/cc43d3452585f4732d475c0affa5d9c20d6d71e4

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In Ecology

In Environmental Engineering

In Nature and Landscape Conservation

Citations in the corpus

Adapting National Forest Inventories to changing requirements - the case of the Swedish National Forest Inventory at the turn of the 20th century (2014, methodology): “Secondly, auxiliary information can be used in the estimation phase, for example through post-stratification (Nilsson et al. 2003; McRoberts et al. 2006) or model-assisted estimation (Särndal et al.”
Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery (2009, unknown): “E. McRoberts). l rights reserved. distribution of forest resources (McRoberts, 2006; McRoberts et al., 2002, 2005; Reese et al., 2003; Tomppo, 1991; Tomppo & Halme, 2004).”
Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery (2007, methodology): “…imagery has been accepted as a source of ancillary data that can be used with stratified estimation techniques to increase the precision of estimates with little corresponding increase in costs (Hansen & Wendt, 2000; Liknes et al., 2004; McRoberts et al., 2006, 2002a,b; Nilsson et al., 2005).”
Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance (2016, background): “This design is assumed to produce a random equal probability sample (McRoberts et al. 2005).”
Inference for lidar-assisted estimation of forest growing stock volume (2013, background): “…which conducts the NFI of the United States of America, has devoted considerable effort to investigating stratified estimation using remotely sensed data (Hansen & Wendt, 2000; Liknes et al., 2004, 2009; McRoberts et al., 2002a, 2002b, 2006, 2012; Nelson et al., 2005; Westfall et al., 2011).”
Seeing the forest beyond the trees (2015, methodology): “…to their plot network as an ‘inventory’, Mitchard et al. (2014) conflate measurement protocol in the field (i.e. wherein all trees are inventoried) with strategic planning to sample biomass and other forest properties as conducted by national forest inventories (e.g. McRoberts et al., 2005).”