Demonstrating intermediate visual analysis and pattern recognition using a processing model in ERDAS Imagine and ArcGIS. Training sites were used to train algorithm (trees, water, houses/urban ISA areas) to classify image to impervious surface area (ISA) then re-projected data and overlay in other geographic data.

1. A GIS-based approach to
characterize urbanization at the
sub-watershed scale
in Mill Creek,OH
Jaleann M. Matos-Mc
Clurg

2. Talk Outline
 Purpose
 Data and Scales of Analysis
 Study Area
 Research Framework
 Research Questions
 Data Sources
 GIS Data Manipulation
 Maps
 Metadata Discussion
 LULC Reclassification Strategy
 More Maps
 Remote Sensing & GIS
 Future Work

3. Purpose
 To characterize urbanization growth with
two landscape-based indicators:
 (1) Population density (people/mi2
)
 (2) Land-use/Land-cover (LULC)

4. Data and Scales of Analysis
 Sub-watershed scale
 Population density by census tracts
 Land-cover (County & Sub-watershed scale)
 LULC- “crude classification” without user changes
 LULC data – Reclassification*
 LC change“stats” & display*
* Sub-watershed scale only

6. Research Framework
 Goal: Characterize urbanization.
 Increase of average population at sub-
watershed scale since 1920’s from cities
and townships.
 LULC changes could trigger disturbance of
hydrological flows and pathways.
 Temporal growth of impervious surface
areas (ISAs) as urbanization expands.

7. Research Questions
 (1) What is the spatial-temporal dynamic of
urbanization at the sub-watershed and county
scales?
 (2) Does a population density or land-cover
based approach help describe urban change?
 (3) How does the spatial-temporal
characterization of urbanization at the sub-
watershed scale relate to changes in the
hydrological flow regime? (Master Thesis Main RQ)

8. Data Sources
 Census Tract Data (1970-2000)-Geolytics, Inc.
 Land-use/Land-cover (LULC)
 Data
 USGS EROS Data Center (EDC)
 Historical LULC derived from 1970’s and 1980’s
aerial photography.
 National Land-cover Dataset (NLCD) derived from
early 1990’s using Landsat TM satellite images.
 USGS EDC
 NALC triplicates – Landsat MSS satellite data.

9. GIS Data Manipulation
Geo-processing
Operations
“Clipping”
Calculate
& Recalculate
Area using
Xtools
Export
Data to Excel
Import Utility 71
(.e00)
Arc Toolbox: Define
PCS and GCS
“if undefined”
Reproject Data
Raster Calculator
Operations
Attribute Data
Manipulation
& Use of
display “rules”
Vectorization
Add summarized
“stats” to layout
Spatial Analyst:Reclassify

10. Maps

12. Average population density within Mill Creek,OH
sub-watershed at multiple geographical
scales of analysis
0
1000
2000
3000
4000
5000
6000
1905 1925 1945 1965 1985 2005
Decennial Census Year
Populationdensity
(people/mi2
)
Cities & Townships
(estimated)
Sub-watershed-census
tracts
County (Butler & Hamilton)-
census tracts
Urban population density
threshold

13. County-level
Average population density by census tracts at the county level
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
1965 1970 1975 1980 1985 1990 1995 2000 2005
Decennial Census Year
Populationdensity(people/mi2)
061=Hamilton Co.
017=Butler Co.
Average (061& 017)
Urban population density threshold

14. County-level within sub-watershed
Average population density by census tracts at the watershed level
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
5500
1965 1970 1975 1980 1985 1990 1995 2000 2005
Decennial Census Year
Populationdensity
(people/mi2)
061=Hamilton Co.
017=Butler Co.
Average (061 & 017)
Urban population density threshold

17. Metadata Discussion
 Useful to get information about spatial data
in general.
 For example …PCS, GCS, data quality,
intended applications, etc.
 Often, LULC data has different LULC
classification schemes.
 I compiled a “summary table” from LULC
and NLCD classification schemes.

18. LULC Reclassification
Strategy
Goal: Translate LULC into more
“condensed” LULC classes

19. Level I Level II (1970’s/1980’s) Level II (early 1990’s)
1. Residential/Urban
11. Residential
16. Mixed Urban or Built-up Land
17. Other Urban Built-up Land
21. Low Intensity Residential
22. High Intensity Residential
2. CIT
Commercial
Industrial
Transportation
12. Commercial & Services
13. Industrial
14. Transportation
15. Industrial and Commercial
Complexes
23. Commercial/Industrial
/Transportation
3. Agricultural Land
21. Cropland and Pasture
24. Other Agricultural
81. Pasture/Hay
82. Row Crops
4. Forest Land
41. Deciduous Forest
42. Evergreen Forest
43. Mixed Forest
61. Forested Wetland
62. Non-forested Wetland
76. Transitional Areas
41. Deciduous Forest
42. Evergreen Forest
43. Mixed Forest
91. Woody Wetlands
92. Emergent Herbaceous
Wetlands
85. Urban Recreational
Grasses
5. Water
53. Reservoirs 11. Open Water

22. 30.7
41.5
10.9 8.6
56.7
18.4
1
26.1
0
10
20
30
40
50
60
Percent(%)
Residential/Urban CIT Agriculture Forest
LULC class
LULC trends in Mill Creek,OH sub-watershed
1970
1990

24. Remote Sensing & GIS
1994 DOQQ’s
(Ancillary Data)
Unsupervised
Classification
w/ 30 classes
Classify to generate
“Binary Masks”
0=Undeveloped
1=Developed
Model Builder:
1991_bm+1986_bm=LC CHANGE 86-91
Remote
Sensing
GIS: Characterize LC change
Raster Calculator
1991_bm+1986_bm
= LC Change 86-91

26. Future Work
 Sub-watershed Scale
 Compare urban census tracts by LC code (reclassified)
and quantify their relative area.
 Generate a LC map of change between 1970 & 1990.
 Regional & Methodological Scale
 Expand geographical area of analysis.
 Develop a “Hybrid GIS-based Framework” that considers
simultaneously LC change and population density changes
to characterize urbanization.

27. Questions/Suggestions?