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

PSC In The News

RSS Feed icon

Seefeldt criticizes Kansas legislation restricting daily cash withdrawals from public assistance funds

Prescott says sex offender registries may increase recidivism by making offender re-assimilation impossible

Frey says rising numbers of younger minority voters mean Republicans must focus on fiscal not social issues

Highlights

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Elizabeth Bruch wins ASA award for paper in mathematical sociology

Spring 2015 PSC newletter available now

Formal demography workshop and conference at UC Berkeley, August 17-21

Next Brown Bag

PSC Brown Bags will be back fall 2015


Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm

Publication Abstract

Bergen, K.M., Daniel Brown, J.F. Rutherford, and E.J. Gustafson. 2005. "Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm." Remote Sensing of Environment, 97(4): 434-446.

A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our results, we a) stratified the classification using predefined ecoregions, b) developed statistical relationships by ecoregion between land-cover proportions derived from the 1980 national-level classification and aggregate statistical data that were available in time series for all regions in the U.S., c) classified multi-temporal AVHRR data using a process that constrained the results to the estimated proportions of land covers in ecoregions within a multi-objective land allocation (MOLA) procedure, d) interpreted land cover from a sample of aerial photographs from 2000, following the protocols used to produce the 1980 classification for use in accuracy assessment of land cover and land-cover change data, and e) compared land cover and land-cover change results for the MOLA method with an unsupervised classification alone. Overall accuracies for the 2000 MOLA and unsupervised land-cover classifications were 85% and 82%, respectively. On average, the 1980-2000 land-cover change RMSEs were one order of magnitude lower using the MOLA method compared with those based on the unsupervised data. (C) 2005 Elsevier Inc. All rights reserved

DOI:10.1016/j.rse.2005.03.016 (Full Text)

Public Access Link

Country of focus: United States of America.

Browse | Search : All Pubs | Next