Effect on Water Quality of Urbanization within the James River Basincourses.washington.edu ›...

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Landscape Modeling and Geovisualization Workshop Landscape Modeling and Geovisualization Workshop Effect on Water Quality of Urbanization Effect on Water Quality of Urbanization within the James River Basin within the James River Basin Chris Wood Chris Wood 1,2,6 1,2,6 , Holly Neill , Holly Neill 3 3 and L. Monika Moskal and L. Monika Moskal 4,5 4,5 1 1 Remote Sensing and Geospatial Analysis Laboratory Remote Sensing and Geospatial Analysis Laboratory Department of Geography Geology and Planning Department of Geography Geology and Planning Southwest Missouri State University Southwest Missouri State University http://ozarksgeography.smsu.edu/RSGAL/ http://ozarksgeography.smsu.edu/RSGAL/ 2 2 Computer Science Department Computer Science Department Southwest Missouri State University Southwest Missouri State University 3 3 James River Basin Partnership James River Basin Partnership http://www.jrbp.smsu.edu/ http://www.jrbp.smsu.edu/ 4 4 Assistant Professor Assistant Professor Department of Geography Geology and Planning Department of Geography Geology and Planning Southwest Missouri State University Southwest Missouri State University 5 5 Director Director 6 6 Graduate Student Assistant (JRBP) Graduate Student Assistant (JRBP) Remote Sensing and Geospatial Analysis Laboratory Remote Sensing and Geospatial Analysis Laboratory Department of Geography Geology and Planning Department of Geography Geology and Planning Southwest Missouri State University Southwest Missouri State University

Transcript of Effect on Water Quality of Urbanization within the James River Basincourses.washington.edu ›...

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Landscape Modeling and Geovisualization WorkshopLandscape Modeling and Geovisualization Workshop

Effect on Water Quality of Urbanization Effect on Water Quality of Urbanization within the James River Basinwithin the James River Basin

Chris WoodChris Wood1,2,61,2,6, Holly Neill, Holly Neill3 3 and L. Monika Moskaland L. Monika Moskal4,54,5

11Remote Sensing and Geospatial Analysis LaboratoryRemote Sensing and Geospatial Analysis LaboratoryDepartment of Geography Geology and PlanningDepartment of Geography Geology and PlanningSouthwest Missouri State UniversitySouthwest Missouri State Universityhttp://ozarksgeography.smsu.edu/RSGAL/http://ozarksgeography.smsu.edu/RSGAL/

22Computer Science DepartmentComputer Science DepartmentSouthwest Missouri State UniversitySouthwest Missouri State University

33 James River Basin PartnershipJames River Basin Partnershiphttp://www.jrbp.smsu.edu/http://www.jrbp.smsu.edu/

44Assistant ProfessorAssistant ProfessorDepartment of Geography Geology and PlanningDepartment of Geography Geology and PlanningSouthwest Missouri State UniversitySouthwest Missouri State University

55DirectorDirector66Graduate Student Assistant (JRBP)Graduate Student Assistant (JRBP)Remote Sensing and Geospatial Analysis Laboratory Remote Sensing and Geospatial Analysis Laboratory Department of Geography Geology and PlanningDepartment of Geography Geology and PlanningSouthwest Missouri State UniversitySouthwest Missouri State University

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James River Basin, MOJames River Basin, MO•• Located in southwest MissouriLocated in southwest Missouri•• James River flows southwestJames River flows southwest

through the basinthrough the basin•• Springfield, in the north, largestSpringfield, in the north, largest

urban area within the basinurban area within the basin•• James River Basin PartnershipJames River Basin Partnership

(JRBP) is an autonomous(JRBP) is an autonomousnotnot--forfor--profit organization working to protect and profit organization working to protect and improve the water quality in springs, stream, rivers and improve the water quality in springs, stream, rivers and lakes within the basinlakes within the basin

•• Grant funds provided to JRBP for nonGrant funds provided to JRBP for non--point source point source conservation programs are being used for educational conservation programs are being used for educational and restoration programs within the basinand restoration programs within the basin

•• Overall goal of improving water quality by addressing Overall goal of improving water quality by addressing nonnon--point source pollution. point source pollution.

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Land Use/Land Cover Land Use/Land Cover James River Basin, MOJames River Basin, MO

Land Use/Land Cover map produced by MoRAP

ImperviousHigh intensity urbanLow intensity urbanBarren or sparsely vegetated

Cropland

Grassland

Deciduous forestEvergreen forestMixed forestDeciduous woody/herbaceousEvergreen woody/herbaceousMixed woody/herbaceousWoody-dominated wetland

Herbaceous-dominated wetland

Open water

Urban

Cropland

Grassland

Forest and Woodland

Water

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Urban Growth of Springfield, MOUrban Growth of Springfield, MO

•• Springfield is amongst the fastest growing urban areas in the coSpringfield is amongst the fastest growing urban areas in the countryuntry•• Population change of Springfield and surrounding areas:Population change of Springfield and surrounding areas:

–– 1972 Population1972 Population•• Greene Co. (163,400)Greene Co. (163,400)•• Christian Co. (20,500)Christian Co. (20,500)

–– 1990 Population1990 Population•• Greene Co. (207,949)Greene Co. (207,949)

–– Springfield (141,115)Springfield (141,115)•• Christian Co. (32,644)Christian Co. (32,644)

–– Ozark (5,118), Nixa (5,131)Ozark (5,118), Nixa (5,131)

–– 2000 Population2000 Population•• Greene Co.Greene Co.

–– Springfield (151,580)Springfield (151,580)•• Christian Co. (54,285)Christian Co. (54,285)

–– Ozark (9,665), Nixa (12,124)Ozark (9,665), Nixa (12,124)

•• Concerned with the effect of this urban sprawl on surrounding enConcerned with the effect of this urban sprawl on surrounding environmentvironment•• How to translate measured effects into a medium that could be usHow to translate measured effects into a medium that could be used to ed to

educate the general publiceducate the general public

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Springfield, MOSpringfield, MO1972197236,996 Acres of urban36,996 Acres of urban

20002000103,567 Acres of urban (11,504 acre 103,567 Acres of urban (11,504 acre increase)increase)

Urban and land cover change results from MoRAP

020,00040,00060,00080,000

100,000120,000140,000

1972 1979 1984 1988 1992 2000

Years

Acr

es

ForestGrasslandCroplandBareUrban

Land Cover 1972 - 2000

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1972

2000

•• LandSatLandSat Imagery for Imagery for Springfield covering Springfield covering various 6 years withinvarious 6 years within[1972 [1972 –– 2000]2000]

•• Imagery classified Imagery classified according to various according to various landland--use, landuse, land--cover cover typestypes

•• Concerned with increase Concerned with increase in urbanization and in urbanization and decrease in forested decrease in forested areas throughout this areas throughout this periodperiod

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Effect of Urban GrowthEffect of Urban Growth

•• James River on James River on ‘‘badbad’’ (impaired (impaired waterways) EPA listwaterways) EPA list

•• The continued urban growth in the area The continued urban growth in the area has had significant effect on surrounding has had significant effect on surrounding environmentenvironment

•• Specifically the water quality in Specifically the water quality in surrounding water ways is impairedsurrounding water ways is impaired

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Measuring Water Quality ChangeMeasuring Water Quality Change

•• Historical water quality data does not date Historical water quality data does not date back that farback that far

•• In fact water quality data for selected In fact water quality data for selected locations only available from 2002 locations only available from 2002 onwardsonwards

•• Change was assumed to be linear and Change was assumed to be linear and back projected to 1972back projected to 1972

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Visualizing Urban Growth EffectsVisualizing Urban Growth Effects

•• Perform temporal analysis on study areaPerform temporal analysis on study area•• Calculate relevant landscape metricsCalculate relevant landscape metrics•• Progress from Progress from ‘‘standardstandard’’ temporal change temporal change

analysis to generating moving animations; analysis to generating moving animations; producing 3D visualizations of change producing 3D visualizations of change within the study areawithin the study area

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Temporal AnalysisTemporal Analysis

•• Various Landsat Images of the study area Various Landsat Images of the study area were classified according to land use or were classified according to land use or land coverageland coverage–– water, grassland, forest, urban, cropland, water, grassland, forest, urban, cropland,

bare or sparsely populatedbare or sparsely populated

•• Compared to determine change in land Compared to determine change in land cover and land use over the last 30 yearscover and land use over the last 30 years

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Image ReclassificationImage Reclassification

•• When considering only urban growth, the other classes When considering only urban growth, the other classes are not requiredare not required

•• LandSatLandSat images were reimages were re--classified to binary form of classified to binary form of either either ““UrbanUrban”” or or ““Not UrbanNot Urban””

•• To allow images to be cascaded To allow images to be cascaded –– such that from any such that from any one point on the final image, one can determine exactly one point on the final image, one can determine exactly how it has changed over time how it has changed over time –– a matrix for the binary a matrix for the binary rere--classification was developed (shown on next slide)classification was developed (shown on next slide)

•• Fortunately in this case, once a pixel became urban it Fortunately in this case, once a pixel became urban it never changed after thatnever changed after that

•• Each image was reEach image was re--classified and cascaded, resulting in classified and cascaded, resulting in a final temporal analysis imagea final temporal analysis image

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Binary ReBinary Re--classification Matrixclassification Matrix

10241024UrbanUrban256256UrbanUrban6464UrbanUrban1616UrbanUrban44UrbanUrban11UrbanUrban

512512NotNot128128NotNot3232NotNot88NotNot22NotNot00NotNot

200020001992199219881988198419841979197919721972

6613651365UrbanUrban341341UrbanUrban8585UrbanUrban2121UrbanUrban55UrbanUrban11UrbanUrban

5513641364UrbanUrban340340UrbanUrban8484UrbanUrban2020UrbanUrban44UrbanUrban00NotNot

4413621362UrbanUrban338338UrbanUrban8282UrbanUrban1818UrbanUrban22NotNot00NotNot

3313541354UrbanUrban330330UrbanUrban7474UrbanUrban1010NotNot22NotNot00NotNot

2213221322UrbanUrban298298UrbanUrban4242NotNot1010NotNot22NotNot00NotNot

1111941194UrbanUrban170170NotNot4242NotNot1010NotNot22NotNot00NotNot

00682682NotNot170170NotNot4242NotNot1010NotNot22NotNot00NotNot

ScaledScaled200020001992199219881988198419841979197919721972

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The Case For AnimationThe Case For Animation

•• It is easily seen that the It is easily seen that the final classification image is final classification image is very difficult to understand very difficult to understand and is not visually aestheticand is not visually aesthetic

•• How to display something How to display something that has a 4D component that has a 4D component in/on a 2D (or 3D) in/on a 2D (or 3D) medium?medium?

•• By visualizing the reBy visualizing the re--classified image in another classified image in another manner the change in the manner the change in the study area becomes easier study area becomes easier to understandto understand

ReRe--classified Urban Growth Imageclassified Urban Growth Image

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Final AnimationsFinal Animations

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Urban visualizations conclusionsUrban visualizations conclusions•• The visualizations show temporal change and the dates The visualizations show temporal change and the dates

are recorded in top rightare recorded in top right--hand cornerhand corner•• The next step is to develop a similar overlay on top of The next step is to develop a similar overlay on top of

Lake Springfield with the subjective water quality Lake Springfield with the subjective water quality assessmentsassessments

•• To develop ecosystems that show grassland or forested To develop ecosystems that show grassland or forested areas when the land is not urban as well as houses areas when the land is not urban as well as houses when the land is urban requires incredible amount of when the land is urban requires incredible amount of computer resourcescomputer resources

•• It would be nice to have nonIt would be nice to have non--urban ecosystems in the urban ecosystems in the animations, the rendering process will be exponentially animations, the rendering process will be exponentially increased, but it is possibleincreased, but it is possible

•• Another possible alteration is draping facades over the Another possible alteration is draping facades over the buildings rather than using the default buildings provided buildings rather than using the default buildings provided by VNS, again considerably increasing rendering timeby VNS, again considerably increasing rendering time

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AcknowledgmentsAcknowledgments

http://ozarksgeography.smsu.edu/RSGAL/http://ozarksgeography.smsu.edu/RSGAL/