|UAV hyperspectral and lidar data and their fusion for arid and semi‐arid land vegetation monitoring|
TT Sankey, J McVay, TL Swetnam, MP McClaran, P Heilman, M Nichols
Remote Sensing in Ecology and Conservation 4 (1), 20-33, 2017
|Coevolution of nonlinear trends in vegetation, soils, and topography with elevation and slope aspect: A case study in the sky islands of southern Arizona|
JD Pelletier, GA Barron‐Gafford, DD Breshears, PD Brooks, J Chorover, ...
Journal of Geophysical Research: Earth Surface 118 (2), 741-758, 2013
|LiDAR‐derived snowpack data sets from mixed conifer forests across the Western United States|
AA Harpold, Q Guo, N Molotch, PD Brooks, R Bales, JC Fernandez‐Diaz, ...
Water Resources Research 50 (3), 2749-2755, 2014
|Laser vision: lidar as a transformative tool to advance critical zone science|
AA Harpold, JA Marshall, SW Lyon, TB Barnhart, BA Fisher, M Donovan, ...
|Topographically driven differences in energy and water constrain climatic control on forest carbon sequestration|
TL Swetnam, PD Brooks, HR Barnard, AA Harpold, EL Gallo
Ecosphere 8 (4), e01797, 2017
|Quantifying Topographic and Vegetation Effects on the Transfer of Energy and Mass to the Critical Zone|
JC Craig Rasmussen Jon D. Pelletier, Peter A. Troch, Tyson L. Swetnam
Vadose Zone Journal, 2015
|Application of metabolic scaling theory to reduce error in local maxima tree segmentation from aerial LiDAR|
TL Swetnam, DA Falk
Forest Ecology and Management 323, 158-167, 2014
|Fusing tree‐ring and forest inventory data to infer influences on tree growth|
MEK Evans, DA Falk, A Arizpe, TL Swetnam, F Babst, KE Holsinger
Ecosphere 8 (7), e01889, 2017
|Reconstructing landscape pattern of historical fires and fire regimes|
T Swetnam, DA Falk, AE Hessl, C Farris
The landscape ecology of fire, 165-192, 2011
|Which way do you lean? Using slope aspect variations to understand Critical Zone processes and feedbacks|
JD Pelletier, GA Barron‐Gafford, H Guttierez‐Jurado, ELS Hinckley, ...
Earth Surface Processes and Landforms, 2018
|Comparing selected fire regime condition class (FRCC) and LANDFIRE vegetation model results with tree-ring data|
TL Swetnam, PM Brown
International Journal of Wildland Fire 19 (1), 1-13, 2010
|Discriminating disturbance from natural variation with LiDAR in semi‐arid forests in the southwestern USA|
TL Swetnam, AM Lynch, DA Falk, SR Yool, DP Guertin
Ecosphere 6 (6), 1-22, 2015
|Asymmetry of weathering‐limited hillslopes: the importance of diurnal covariation in solar insolation and temperature|
JD Pelletier, TL Swetnam
Earth Surface Processes and Landforms 42 (9), 1408-1418, 2017
|Estimating forage utilization with drone-based photogrammetric point clouds|
JK Gillan, MP McClaran, TL Swetnam, P Heilman
Rangeland ecology & management 72 (4), 575-585, 2019
|A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage|
J Perdrial, PD Brooks, T Swetnam, KA Lohse, C Rasmussen, M Litvak, ...
Biogeochemistry 138 (3), 225-243, 2018
|Considerations for achieving cross-platform point cloud data fusion across different dryland ecosystem structural states.|
TL Swetnam, JK Gillan, TT Sankey, M McClaran, M Nichols, P Heilman, ...
Frontiers in Plant Science 8, 2144, 2018
|LiDAR-based estimation of forest floor fuel loads using a novel distributional approach|
JAN van Aardt, M Arthur, G Sovkoplas, TL Swetnam
Proceedings of SilviLaser, 1-8, 2011
|Estimating individual tree mid-and understory rank-size distributions from airborne laser scanning in semi-arid forests|
TL Swetnam, DA Falk, AM Lynch, SR Yool
Forest Ecology and Management 330, 271-282, 2014
|Cordilleran forest scaling dynamics and disturbance regimes quantified by aerial LiDAR|
Tucson, AZ: University of Arizona. Dissertation. 277 p., 2013
|Jetstream—Early operations performance, adoption, and impacts|
DY Hancock, CA Stewart, M Vaughn, J Fischer, JM Lowe, G Turner, ...
Concurrency and Computation: Practice and Experience 31 (16), e4683, 2019