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Note from Land Portal:
Taylor & Francis Online contains many publications related to land issues, though mostly at the charge of a fee.
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Displaying 341 - 345 of 661high-resolution GIS null model of potential forest expansion following land use changes in Norway
During recent decades, forests have expanded into new areas throughout the whole of Norway. The processes explained as causing the forest expansion have focused mainly on climate or land use changes. To enable a spatially explicit separation of the effects following these two main drivers behind forest expansion, the authors set out to model the potential for natural forest regeneration following land use abandonment, given the present climatic conditions.
Forest Fuel Reduction and Biomass Supply: Perspectives from Southern Private Landowners
Removing excess biomass from fire-hazardous forests can serve dual purposes: enhancing the health and sustainability of forest ecosystems and supplying feedstock for energy production. The physical availability of this biomass is fairly well-known, yet availability does not necessarily translate into actual supply. We assess the perception and behavior of private forestland owners in the southern United States with respect to thinning overstocked forests for bioenergy production.
Mean shift-based clustering of remotely sensed data with agricultural and land-cover applications
The mean shift (MS) algorithm is based on a statistical approach to the clustering problem. Specifically, the method is a variant of density estimation. We revisit in this article the MS paradigm and its use for clustering of remotely sensed images. Specifically, we investigate further the classification accuracy of remotely sensed images as a function of various MS parameters, such as the variant used, kernel type, dimensionality, kernel bandwidth, etc.
Employing lidar data to identify butterfly habitat characteristics of four contrasting butterfly species across a diverse landscape
Lidar and orthophotograph-derived land cover are combined with in situ vegetation measurements to assess habitat characteristics typifying four species of butterflies with differing habitat preferences across a large spatial extent (∼30,000 ha) in northern Idaho, USA. Lidar data are employed to characterize both vegetation structure and topography, whereas digital orthophotographs and in situ vegetation measurements are employed to quantify surrounding land use and larval host plant cover, respectively.
Geographically weighted methods for estimating local surfaces of overall, user and producer accuracies
The confusion matrix is the standard way for reporting the accuracy of land cover and other information classified from remote-sensing imagery. This letter describes a geographically weighted method for generating spatially distributed measures of accuracy (overall, user and producer accuracies) from a logistic geographically weighted regression. A kernel-based approach defines the data and weights that are used to calculate the accuracies at each location in the study area.