Spatiotemporal Informatics for Sustainable Forest Production Utilizing Forest Inventory and Remotely Sensed Data

The interrelationship between trees and humans is primordial. As pressures on natural resources grow and become more complex this innate connection drives an increased need for improved data and analytical techniques for assessing the status and trends of forests, trees, their products, and their services. Techniques for using readily available data such as the Forest Inventory and Analysis (FIA) database and output from forest disturbance detection algorithms derived from Landsat data, such as Vegetation Change Tracker (VCT), for estimating forest attributes across time from the state and inventory unit level down to the stand and pixel level are presented. Progressively more comprehensive harvest and parcel boundary records are incorporated appropriately. Quantification of attributes, including non-timber forest products and fine-scale age estimates, across the landscape both historically and into the future is emphasized. Spatial information on the distribution of forest resources by age-class provides knowledge of timber volume through time and across the landscape to support forest management for sustained production. In addition to monitoring forest resources in regards to their value as products for human consumption, their measurement facilitates analysis of the relationship of their spatial and temporal abundance to other resources such as water and wildlife.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Geospatial and Environmental Analysis

Department dc:contributor.department

Geography

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2017

Author dc:creator

• Kauffman, Jobriath Scott

Chair dc:contributor.committeechair

• Prisley, Stephen P.

Committee members dc:contributor.committeemember

• Coulston, John W.
• Thomas, Valerie A.
• Shao, Yang

• forest products
• decision support
• FIA
• VCT
• Landsat
• county parcel data
• Machine learning
• automated
• forest age map

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:9634

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/74974