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The main objective of this study was to develop reliable processing and analysis techniques to facilitate the use of small-footprint lidar data for estimating tree crown diameter by measuring individual trees identifiable on the three-dimensional lidar surface. In addition, the study explored the importance of the lidar-derived crown diameter for estimating(More)
The principal study objective was to explore the feasibility of using small-footprint lidar data and multispectral imagery to estimate forest volume and biomass on small (0.017-ha) plots. In addition, the spatial dependency of residuals between ground-measured and lidar-estimated variables was investigated. The lidar data set was acquired over deciduous and(More)
—With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there(More)
WE ARE WRITING ON BEHALF OF THE 150 students attending Rowe-Clark Math and Science Academy, The Exelon Campus of Noble Street Charter School, and all of their teachers. Science reporter J. Mervis visited our campus for several hours this fall to observe our science and math classes, learn about our school, and interview students and teachers in preparation(More)
Quantification of biophysical parameters of urban trees is important for urban planning, and for assessing carbon sequestration and ecosystem services. Airborne lidar has been used extensively in recent years to estimate biophysical parameters of trees in forested ecosystems. However, similar studies are largely lacking for individual trees in urban(More)
This study evaluated the potential of an object-oriented approach to forest type classification as well as volume and biomass estimation using small-footprint, multiple return lidar data. The approach was applied to coniferous, deciduous , and mixed forest stands in the Virginia Piedmont, U.S.A. A multiresolution, hierarchical segmentation algorithm was(More)
The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000(More)