Applying Geographic Information Systems to Real-world Issues - Urban Sprawl

Case Study Proposal:

PROPSED TITLE:

Population Growth in Prince William County, Virginia and its Implications on the Environment.

ABSTRACT 

This study will examine the continuous urban sprawl and suburban development in Prince William County, Virginia.  Prince William County is located in the region of Northern Virginia, which is a part of the Washington DC Metropolitan greater region.  Urban development disrupts hydrological and ecological systems, in addition to isolating and degrading local natural habitats.  Over the past few decades, Prince William County has transformed from a rural area with two main population centers, Manassas and Woodbridge, to a thriving society.  Today, these two population centers now are interconnected with a steady stream of roads and neighborhoods.  20 years ago, this area was quiet and had quite a lower population. In 20 years, the population has almost doubled from approximately 216,000 in 1990 to approximately 402,000 in 2010. In addition the county is projected to grow to approximately 555,000 in another 20 years; the county had nearly doubled its population every 20 years since 1950 (population was 22,000 in 1950).  The growth of this county has led to a decline in agriculture and an increase in pollution.  These constraints from growth and development have ultimately resulted in several ecological issues that this study will attempt to address.   Furthermore, this study will identify the spatial patterns associated with the growth and how it has grown over the years. 

RASTER LAYERS

Maps (i.e. Historic, topographic, pre-1990 census maps)  – Any scanned map that has features that can be digitized to fill in gaps from all other data used.

SRTM – Any type of elevation data needs to be used in order to explain why certain areas have not been affected by urban sprawl.

Orthorectified Aerial Imagery – This type of imagery will provide most of the historical data needed to determine foundation data for comparing the present to the past.  Each image used can be digitized to extract data into vector format.

Satellite Imagery – This type of imagery will allow various types of sensors to determine changes via comparing two or more images identify change detection in vegetation, ecology, infrastructure, and other important features in foundation data.

Table 1. Satellite remote sensing data for ecological research.

Satellite	Launch	Sensors	spectrum	spatial resolution (m)	temporal resolution (days)
Landsat	1972	MSS, TM	V, IR	15-80	16
SPOT	1986	HRV	V, IR	10-20	5-26
IRS	1988	LISS, WiFS	V, IR	5-200	5-24
NOAA	1970	AVHRR	V, IR	1100	0.5
OrbView	1998	SeaWiFS	V, IR	1100	1
Terra	1999	MODIS	V, IR	250-1000	2
ERS	1991	AMI	microwave	20	variable
RADARSAT	1995	SAR	microwave	20	“
IKONOS	2000	IKONOS	V, IR	1-4	“
KOMPSAT	2000	EOC, OSMI	V	6-800	“

Source: http://www.klter.org/EVENTS/Conference00/html/leegusung.htm

VECTOR LAYERS

LULC (Land use land cover), including current and historical datasets  – This provides an idea of where the different feature classes of land type and uses are located.

Census: 1990 and newer census tracts, population – Census data reveals where the population is with any given area.

Hydrographic: rivers, streams, lakes, watershed – Hydrographic features are part of a foundation dataset.

Infrastructure: roads, rails, powerlines, pipelines – Infrastructure features are part of a foundation dataset.

Environment: Air Quality maintenance area, water quality monitoring station – Reveals location of areas that monitor changes in the environment.  This allows for the validity of data acquired in relation to air and water quality data compared to sensors that capture quality via remote sensing.

Boundary: County and cities – Provides an outline for the areas of interest.

METHODOLOGY

The methodology used for studying the issue of population affecting the local ecology requires two different datasets themed to a specific time frame, one pre-1990 dataset and one post-1990 dataset.  The area of interest that will be studied is within the county borders of Prince William County, Virginia, including the cities of Occoquan, Manassas, and Manassas Park.  A foundation dataset based on the aforementioned criteria is needed to identify changes and challenges that urban growth has had within the county.  GIS allows this foundation dataset to be overlaid with land cover and other raster and vector files that have a relation to identifying the affects of increased population in the county with files that can help determine factors that affect the ecology such has changes in county infrastructure.

In order to accomplish this, GIS plays an instrumental role in conducting spatial analysis between feature classes and identifying relationships among the two topics: population and ecology.

Not all datasets are readily available in can be used immediately for spatial analyses.  Most of all raster files in this project will have to be scanned and inputted into the system.  At this point, each file, whther it is a photographic image or a map needs to be spatially referenced in the area it is detailing.  Digitizing these types of files is a necessity once the files are geo-referenced in order to extrapolate any valuable vector datasets from the map or images, such as landcover and landuse, vegetation, missing pieces to infrastructure (i.e. roads, buildings, parks, waterways, et cetera), et cetera.  Most of the raster files that are not used for creating vector datasets will be used for identifying air quality, pollution, water quality, and most other ecological readings within the county.

Population data acquired from the U.S. Census Bureau and Aerial Photography will be monitored over the past 60 years, in 5 to 10 year increments depending on how much the population has changed the landscape of the county.  Each 10 year increment changes will be identified in GIS and then compared to see the progression of change temporally.  The decrease of agricultural land will also be identified in GIS via this process.

CONCLUSION

The results of this project should determine what areas within Prince William County have endured more drastic changes than other areas, as well as what areas need to be protected from any further development.  In addition, this project will visually and temporally depict the changes over time in regards to population growth, infrastructure changes, changes in water levels, air quality animations, and vegetation changes.  Overall, the results will identify spatial patterns that have directly impacted how the area has grown into what it is today from what it was 60 years ago, while simultaneously affecting the ecology of the area.

LIMITATIONS

This most anticipated roadblock will be the acquisition of data needed to fulfill all the requirements in order to do spatial analysis and observations.  Secondary to do this, the time involved to complete this project will be dependent on the amount of change and extraction that is needed from the ingestion of maps or photographic images.  The more gaps in the vector data, the more time needed to extract from the raster files.