Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Frey says China is source country of most new U.S. immigrants

Rodriguez, Geronimus, Bound and Dorling find excess mortality among blacks influences key elections

Kruger says high concentration of local fast food outlets is risk factor for obesity

Highlights

Cheng wins ASA Outstanding Graduate Student Paper Award

Hicken wins 2015 UROP Outstanding Research Mentor Award

U-M ranked #1 in Sociology of Population by USN&WR's "Best Graduate Schools"

PAA 2015 Annual Meeting: Preliminary program and list of UM participants

Next Brown Bag

Mon, May 18
Lois Verbrugge, Disability Experience & Measurement

Propagating error in land-cover-change analyses: impact of temporal dependence under increased thematic complexity

Publication Abstract

Burnicki, A.C., Daniel Brown, and P. Goovaerts. 2010. "Propagating error in land-cover-change analyses: impact of temporal dependence under increased thematic complexity." International Journal of Geographical Information Science, 24(7): 1043-1060.

We examined the impact of temporal dependence between patterns of error in classified time-series imagery through a simulation modeling approach. This research extended the land-cover-change simulation model we previously developed to investigate: (1) the assumption of temporal independence between patterns of error in classified time-series imagery; and (2) the interaction of patterns of change and patterns of error in a post-classification change analysis. In this research, the thematic complexity of the classified land-cover maps was increased by increasing the number of simulated land-cover classes. Simulating maps with increased categorical resolution permitted the incorporation of: (1) higher-order, more complex spatial and temporal interactions between land-cover classes; and (2) patterns of error that better reproduce the complex error interactions that often occur in time-series classified imagery. The overall modeling framework was divided into two primary components: (1) generation of a map representing true change; and (2) generation of a suite of change maps that had been perturbed by specific patterns of error. All component maps in the model were produced using simulated annealing, which enabled us to create a series of map realizations with user-defined spatial and temporal patterns. Comparing the true map of change to the error-perturbed maps of change using accuracy assessment statistics showed that increasing the temporal dependence between classification errors did not improve the accuracy of resulting maps of change when the categorical scale of the land-cover classified maps was increased. The increased structural complexity within the time series of maps effectively inhibited the impact of temporal dependence. However, results demonstrated that there are interactions between patterns of error and patterns of change in a post-classification change analysis. These interactions played a major role in determining the accuracy associated with the maps of change.

DOI:10.1080/13658810903279008 (Full Text)

Country of focus: United States of America.

Browse | Search : All Pubs | Next