Oral Abstract Details

Author(s):
Jeffrey Hepinstall-Cymerman

Affiliation:
University of Georgia

Presentation Type:
Oral

Topic Area:
Monitoring and predicting human influences on landscapes and ecosystems

Abstract Text:
Urbanization and the resulting changes in land cover have myriad impacts on ecological systems. Monitoring these changes across large spatial extents and long time spans requires synoptic remotely sensed data with an appropriate temporal sequence. I used a multi-temporal (1986, 1991, 1995, 1999, 2002) land cover dataset for a six-county area surrounding the Seattle metropolitan region to explore changes in landscape composition and configuration before and after the implementation of 1990 growth management legislation. Between 1986 and 2002, urban land cover increased from 8 to 18% of the study area, while lowland deciduous and mixed forests decreased from 21 to 14%, and grass and agriculture decreased from 11 to 8%. The intensity of urban land cover also increased with 252 km2 in Heavy Urban (80-100% impervious surface) in 1986 increasing to 629 km2 by 2002. Increasingly across all time periods, the majority of new areas were located outside of the 2002 urban growth boundaries (UGB; from 58% of new urban between 1986-1991 to 74% between 1999 and 2002). In addition, new developed land outside of the 2002 UGB increased more rapidly than areas within the urban growth boundaries. For example, more than three times the land area was developed outside of the UGB between 1999 and 2002 than inside (417.3 km2 and 140.1 km2, respectively). Urban sprawl, as estimated by the amount of developed land per capita, increased overall within the region, but the more rural counties within commuting distance to cities showed the highest rate of increase. These results potentially indicate that the intended effect of the 1990 Growth Management Act to direct growth within the urban growth boundaries may not have been accomplished by 2002. The ecological systems that are present in this region were likely significantly altered by these changes in land cover. Multi-temporal land cover datasets can be used to develop models forecasting future land cover change or combined with ecological data to explore how landscape change affect ecological systems.