In order to join virtual sessions, you must be registered and logged-in(Were you registered for the in-person meeting in Denver? if yes, just log in.) 
Note: All session times are in Mountain Daylight Time.

Combining ArcGIS and R to model aircraft sound and inform management of human impacts in Arctic Alaska

Authors: Timothy J Fullman*, The Wilderness Society, R. Travis Belote, The Wilderness Society, Stuart Smith, True North GIS, Gregory H Aplet, The Wilderness Society
Topics: Spatial Analysis & Modeling, Applied Geography, Coupled Human and Natural Systems
Keywords: Sound modeling, aircraft, GIS, conservation, Arctic, disturbance, Alaska
Session Type: Paper
Presentation File: No File Uploaded


Human development and land conversion are altering the face of the globe at a drastic rate. It is increasingly recognized, however, that human impacts extend beyond the footprint of development, stretching over wildlands that otherwise appear intact. In northern Alaska, concerns have been raised for decades about the influence of aircraft noise on animals and subsistence hunters. We modeled aircraft sound across the North Slope of Alaska using commercially-available aircraft data and the Sound Mapping Tools (SMT) ArcGIS toolbox. SMT accounts for source and environmental characteristics and effects of terrain shielding on sound propagation, but the point-based tool has limitations for handling extensive datasets over large areas and for modeling effects of linear features, such as moving aircraft. To overcome these limitations, we fit a linear mixed effects model using the SMT-modeled sound levels as the response variable and the SMT input parameters and Euclidean distance as the independent variables. Resulting sound prediction surfaces were highly correlated with those generated by SMT (r = 0.97) and ran about 13 times faster than the SMT-based model. We modelled sound for one week per month across an entire year, allowing comparison of patterns over time and production of an annual average sound surface. Aircraft sound levels were lowest in the eastern Arctic National Wildlife Refuge. This technique has great applicability for modeling sound with extensive, linear-based datasets over large areas and can be used to inform conservation and management efforts to monitor and mitigate noise effects in wildland areas.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login