A Planning Tool for Conservationists: Spatial Modeling of Past and Future Land Use in Vermont Towns [Home] [Project] |
sources: U.S. Census of Housing and Population, 1950-1990
sources: U.S. Census of Housing and Population, 1970-1990
A Model of Land Use Conversion in Vermont Towns In a project funded by theOrton FamilyFoundation, researchers at theUniversity of Vermont'sSpatial Analysis Laboratory are developing apredictive model of landscape change. By visualizing the pattern and pace at whichthe landscape is being settled, communities can plan the layout of their town whileensuring for the future needs and services of their townspeople. The objective of the project is to provide planners and policy-makers witha predictive model of development patterns in Vermont towns. The final product willbe a statistical model with estimated coefficients for those socioeconomic and physicalparameters found to most significantly influence land use conversion. Understandingthe demographic forces that act as causal factors to land use conversion will allowplanners and policy-makers to craft policy that guides social trends so as to induce adesired landscape pattern. Drivers of Land Use Conversion Research has shown that social and economic factors are drivers of land use change and forest fragmentation. Significant drivers includepopulation density,road density, and distance from urban centers. Socio-economic drivers interact with biophysical factors such as soil,elevation,slope and vegetation interact to determine the extent of land use change. In Vermont, the interaction between socio-economic and biophysical factors and their relation to land use change is uncertain. To date, no empirical studies in Vermont have examined spatial patterns of land use change as a function of socio-economic factors and land use. The development of the predictive model will occur in three stages. The first stage characterizes recent trends of land cover type distributions in Vermonttowns. A change detection analysis using satellite imagery will provide the baselinespatial data needed to quantitatively discern socioeconomic and physiographic forcesdriving the patterns of land use. Landscape change dectection aims to discern differences in land usepatterns over time by comparing images of the same location on different dates. Landsat Multispectral Scanner (MSS) images from the early 1970s, mid1980s, and early 1990s were the primary data source. Vermont spans portions offour MSS scenes (1329, 1330, 1429, 1430) therefore at least three images per scene werecompared. Additional imagery was required to fill in clouded areas for some scenesand periods. Ancillary data incorporated into this analysis include a land cover mapgenerated from 1992-93 LANDSAT TM imagery and slope data derived from 1:24,000 and1:100,000 scale USGS contour maps. The type and location of change targeted in thisanalysis are:
To obtain a complete land cover distribution for each period, areaclassified as no change is characterized using the 1992-93 LANDSAT TM derived land coverproduct. All image processing was conducted in ERDAS IMAGINE. Classification of the change areas relies on decision rule algorithms(DRA), or conditional logic statements, in IMAGINE's spatial modeler module. DRAstatement integrate differencing, image band ratios, and ancillary data to define changeclasses. Clouds and haze effects were minimized by eclectic use of multipleimages. An accuracy validation of the classification will be conducted usingreference points acquired from aerial photography and satellite imagery from the threetime periods. One element in modeling the change in the distribution of land uses is tounderstand the social and economic trends occurring in Vermont towns. Having anunderstanding for the demographic underpinnings of Vermont's communities will allow forthe visualization of the future Vermont landscape. Therefore, concurrently,ArcView-compatible databases of socioeconomic indicators are being developed for each townin Vermont. Data-formatting is being conducted in ArcInfo 7.1.2. Each townwill have access to several coverages that exhibit town-level social and economictrends. Socioeconomic variables visualized in these coverages include (but are notlimited to): population change, population density, number of housing units, percent ofhousing units held for occasional use, distribution of labor force, educationalattainment, property tax rates, traffic volume, per capita income, employment status andtravel distance the capital. The demographic information used in the Spatial Model of Land Use areprovided here for use by the Vermont community. Click on a county to obtain county-level andtown-level socioeconomic information
In the final stage of this project, the socioeconomic and demographic datalisted above will be related to the observed changes in the distribution of land uses. This analysis will estimate the correlation of social and physical variables theconversion of land from undeveloped to developed uses and vice versa. Factors foundto significantly influence land use conversion will serve as parameters in a predictivemodel of development for Vermont's towns. Last update: 25 April 2000
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