This paper reviews LiDAR ground filtering algorithms used in the process of creating Digital Elevation Models. We discuss critical issues for the development and application of LiDAR ground filtering algorithms, including filtering procedures for different feature types, and criteria for study site selection, accuracy assessment, and algorithm classification. This review highlights three feature types for which current ground filtering algorithms are suboptimal, and which can be improved upon in future studies: surfaces with rough terrain or discontinuous slope, dense forest areas that laser beams cannot penetrate, and regions with low vegetation that is often ignored by ground filters.

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Urban and vegetation morphology profiles are important factors in local climate-related studies, but they are not as easily measured as land cover information to study urban landscape at metropolitan area. This study aims to develop a GIS-based Local Climate Zones (LCZs) mapping scheme to map and compare the LCZs for three major metropolitans in Texas: Dallas-Fort Worth (DFW), Austin, and San Antonio. Based on an analysis of the land cover and urban morphology, variables including land cover, height of roughness elements, building surface fraction, pervious surface fraction (PSF), and land use planning codes were generated and selected as LCZs classification properties. Then we designed the LCZs mapping scheme with decision-making algorithm was built for LCZs mapping. The key findings of LCZs of our study areas are that: 1) Most of the urbanized area are categorized into LCZ "open" types (characterized by building surface fraction of 15-40% and pervious surface fraction of 30-60%) for all three metropolitan areas with different proportions and spatial diversity; 2) LCZ D Low plants is dominant in areas surrounding DFW, while LCZ A Dense trees and LCZ D Low plants are dominant in Austin and San Antonio with clear regional contrast; 3) LCZs maps are in accordance with the underlying regional environment of the areas. Our study indicated that LiDAR-derived products can support LCZs mapping to identify urban morphological information and standardize the mapping scheme for further comparative studies of metropolitan areas.

For solitary carnivores a polygynous mating system should lead to predictable patterns in space-use dynamics. Females should be most influenced by resource distribution and abundance, whereas polygynous males should be strongly influenced by female spatial dynamics. We gathered mean annual home-range-size estimates for male and female bobcats ( Lynx rufus (Schreber, 1777)) from previous studies to address variation in home-range size for this solitary, polygynous carnivore that ranges over much of North America. Mean annual home ranges for bobcats (171 males, 214 females) from 29 populations covering the entire north to south and east to west range demonstrated female home-range sizes varied more than an order of magnitude and that, on average, males maintained home ranges 1.65 times the size of females. Male home-range sizes scaled isometrically with female home-range sizes indicating that male bobcats increase their home-range size proportional to female home-range size. Using partial correlation analysis we also detected an inverse relationship between environmental productivity, estimated using the normalized difference vegetation index, and home-range size for females but not males. This study provides one of the few empirical assessments of how polygyny influences home-range dynamics for a wide-ranging carnivore.