“A Framework for GeoDesign” – Carl Steinitz’s Preconference Seminar at the 2012 Esri UC

Dr. Carl Steinitz

Dr. Carl Steinitz

Dr. Carl Steinitz will be offering a preconference seminar on geodesign at the 2012 Esri User Conference:

“Dr. Steinitz provides an in-depth overview of GeoDesign processes, looking at both rural and urban environments. He describes a framework for doing GeoDesign (design in geographic space) using six model types for assessing the geographic context, for proposing changes and for evaluating the consequences of those changes. He then shows how this framework and these models can be used to understand, plan and manage a variety of landuse/management projects. He presents nine different strategies for proposing change and shows how they can be applied to different problem types at different scales, discussing the pros and cons of each in different situations. The seminar provides the participants with the equivalent of a graduate level seminar on GeoDesign.”

This seminar will be held from 1:30 p.m. to 5:00 p.m. on Sunday, 21 July 2012 in San Diego, California

LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada

Remote Sensing, 2012, 4(4), 830-848

Paul Treitz, Kevin Lim, Murray Woods, Doug Pitt, Dave Nesbitt and Dave Etheridge

“Over the past two decades there has been an abundance of research demonstrating the utility of airborne light detection and ranging (LiDAR) for predicting forest biophysical/inventory variables at the plot and stand levels. However, to date there has been little effort to develop a set of protocols for data acquisition and processing that would move governments or the forest industry towards cost-effective implementation of this technology for strategic and tactical (i.e., operational) forest resource inventories. The goal of this paper is to initiate this process by examining the significance of LiDAR data acquisition (i.e., point density) for modeling forest inventory variables for the range of species and stand conditions representing much of Ontario, Canada.

Sample model predicted surface generated from LiDAR height and density metrics (i.e., Gross Merchantable Volume (GMV)) for the Romeo Malette Forest (RMF).

Sample model predicted surface generated from LiDAR height and density metrics (i.e., Gross Merchantable Volume (GMV)) for the Romeo Malette Forest (RMF).

“Field data for approximately 200 plots, sampling a broad range of forest types and conditions across Ontario, were collected for three study sites. Airborne LiDAR data, characterized by a mean density of 3.2 pulses m−2 were systematically decimated to produce additional datasets with densities of approximately 1.6 and 0.5 pulses m−2. Stepwise regression models, incorporating LiDAR height and density metrics, were developed for each of the three LiDAR datasets across a range of forest types to estimate the following forest inventory variables: (1) average height (R2(adj) = 0.75–0.95); (2) top height (R2(adj) = 0.74–0.98); (3) quadratic mean diameter (R2(adj) = 0.55–0.85); (4) basal area (R2(adj) = 0.22–0.93); (5) gross total volume (R2(adj) = 0.42–0.94); (6) gross merchantable volume (R2(adj) = 0.35–0.93); (7) total aboveground biomass (R2(adj) = 0.23–0.93); and (8) stem density (R2(adj) = 0.17–0.86). Aside from a few cases (i.e., average height and density for some stand types), no decimation effect was observed with respect to the precision of the prediction of the majority of forest variables, which suggests that a mean density of 0.5 pulses m−2 is sufficient for plot and stand level modeling under these diverse forest conditions across Ontario.”