• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • No language data
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Land Cover and Use Change in Utah: A Comparison of Field- vs. Aerial Image-Based Observations

Bakken, Jennifer Lynn 01 August 2018 (has links)
The Image-based Change Estimation program (ICE) was developed by the US Forest Service Forest Inventory & Analysis (FIA) program and the Geospatial Technology Applications Center in response to the 2014 Farm Bill calling for more timely and accurate estimates of land cover and use change. ICE monitors change throughout the US on a state by state basis by assessing each FIA plot using high resolution imagery from two dates in time. In the western US, FIA measures 10% of the plots each year to report on status, trends, and sustainability of our Nation’s forests. However, this 10 year cycle misses disturbances because a temporal gap occurs from disturbance event to measurement. This study compares field- and image-based observations of land cover and use change to improve sampling procedures in Utah. Image-based data collected from 2011 and 2014 imagery and field-based plots measured between 2011 and 2016 are compared using three methods to compile the ICE data, termed hierarchical, majority, and point center, to determine a standardized system and better understand their relationships. Additionally, ICE change agents were compared with causes of tree mortality observed on FIA forest plots to assess how well ICE evaluates causes of change and the differences of change vs. mortality agents were explored by conducting a second review of the imagery to find trends in data discrepancies. This knowledge can help image interpreters better recognize and identify change.

Page generated in 0.1093 seconds