Keywords:
LAND USE, LAND COVER, DEMOGRAPHICS,
Project Information:
Progress
:The research has closely followed the objectives that were included in the original internal grant proposal . The initial analysis is focusing on six Maryland counties (Queen Anne's, Frederic, Harford, Washington, Anne Arundel, and Calvert). A number of data layers has been obtained and put into the standard ReVA-MAIA projections for each of these counties, including MdProperty View data (incorporates MD State Department of Assessments and Taxation property records), block (total population and household density) and blockgroup (educational status, population composition, housing characteristics) level 1990 Census data, physiographic data (streams, land cover, elevation, soils, major water bodies), roadways, railways, Federal lands, state parks and recreation areas, golf courses and schools. These data will be used both in an analysis of land use and land cover relationships as well as in the calibration of a development suitability index model. Data for six additional counties will be used for an independent method evaluation. Major data sources (census, MRLC, road and railways) being used are from the late 80's or early 90's. MdPropertyView includes construction through 1998, providing data to analyze what features on the landscape explain the subsequent development.
A literature review of locational factors affecting development was completed in the initial quarter of the project. In the course of this review, 30+ factors to consider for incorporation into a suitability index model were identified. Two counties (Frederick and Queen Anne's, MD) are being used to screen the usefulness of these factors, develop feasible metrics for them, and develop the appropriate structure for index values. A preliminary assessment of the impact of several factors on recent construction (1991-1998), including distance to major roads, proximity to any paved roads, proximity to major water bodies, socio-economic status index, % sewer connections, current and neighboring land cover, slope, and median year built has been completed for the two initial development counties. Additional factors that will be investigated include: distance to major intersections, railroads, land fills, elementary schools, and shopping areas; inside or outside of city limits, block level population density, soil characteristics, and access to major employment centers. We have data in-house to support some representation of each of these factors. A travel time (service area) coverage to the central business district of each major metropolitan area is being developed using Network Analyst and estimates of speeds based on Tiger file road type classification and state speed limits by road type.
A prototype for the suitability index model has been developed in an ArcView Avenue framework. At present, only four factors are included but this number is expanding as appropriate metrics are generated. The automated Windows-based format will allow more rapid testing of weighting factors and index structures, and also serve as the basis for a distributable desktop product at the end of the project.
Evaluation of land use and land cover relationships are being explored through analysis and comparisons of property records, block and block group level census data, and MRLC data. This analysis considers the appropriate resolution for utilizing each of these data sources as well as serving as a quality control on the data sources themselves. The original concept of this study was to use the MRLC as the base data for identifying developed land use. However, relationships must be developed to correct for low density development areas that are not identified within the landscape characterization data set.
Generally, the project is on target according to the time line included in the grant proposal with dates corrected for the 2/99 rather than the original 10/98 start date. The analysis of NALC and aerial photo analysis has not been initiated.This segment of the
Relevance
:Land use is a primary driver in generating the exposure of both terrestrial and aquatic ecosystems to a wide range of stressors including pesticides, sediments, nutrients, hydrologic response, and direct habitat destruction. Understanding the dynamics of land use change and the relationship between land use and land cover is essential to understand not only the potential landscape ecosystem impacts, but also to adequately estimate regional scale stressor exposure. The development of methods to aid in translating land cover imagery to actual pollutant/stressor loading and habitat disruption due to on the ground land use and its change could substantially reduce uncertainty in exposure assessments. A systematic methodology to project potential land use/land cover conversions is an essential component of vulnerability assessments and as a guide to understanding the potential effectiveness in proposed mitigation strategies. Understanding the potential for a shift in stressors distributions in a region will substantially increase the quality of our exposure and vulnerability assessments.
Clients
:Region 3 and 4
Project IDs:
ID Code
:5418
Project type
:OMIS