Examining the potential of Landsat imagery for the estimation of forest stand-level structures and an analysis of pine stumpage prices based on timber sale characteristics
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Landsat imagery has been used for the estimation of forest stand-level characteristics with various techniques. We reviewed peer-reviewed research that employed Landsat imagery for the purpose of estimating forest stand-level characteristics from 1995 to 2012. Particularly, we focused on the study areas, forest parameters examined and technologies of classification employed. We investigated the trends and changes in using Landsat imagery for the estimation of forest stand-level characteristics. In terms of forest stand-level characteristics that have been estimated, above ground biomass (AGB) was thoroughly researched, but forest stand height and crown closures were estimated less frequently. In techniques employed, various forms of regression analysis seem to be the most used method and k-nearest neighbor followed it, and the other techniques were not employed enough but increasingly used. Given the proven abilities of Landsat imagery for the estimation of forest structural characteristics, we estimated forest structure in the State of Georgia. We estimated premature forest areas where the age is 15 or under 15 using Landsat satellite imagery in southeastern Georgia. For the estimation of premature forest areas in Georgia, we employed three technologies: maximum likelihood classification (MLC), regression analysis, and k-nearest neighbor (kNN). In terms of overall accuracy, MLC and kNN produced relatively high-level accuracy. The kappa coefficient shows consistent results with overall accuracy. Additionally, to research the implicit value of sale characteristics on the change of stumpage price, we developed a regression model with various sale characteristics to have insight into the change of timber price. Based on Timber Mart-South data collected from 1998 to 2007 in 11 southern states, we adopted a hedonic pricing method for the association of stumpage price of pine sawtimber with timber sale characteristics. We found that the stumpage price of pine sawtimber is positively related to sale size, contract length, sealed bid offering, and the number of bidders. It is also found that the presence of above average or excellence in grade, market conditions, and logging conditions made huge positive impacts on the stumpage price of pine sawtimber.