Susquehanna Streamfront Towns: Presentation Boards

Page 1

Figure 1. Susquehanna River Basin boundaries and hydrology counties with county seats ats outside of the basin

transportation infrastructure

Sixty-seven (67) counties within three (3) states contain land in the Basin. Only those county seats (35 plus an additional town in MD) situated primarily within the Basin were selected for analysis. Each is represented by a circle (approximately proportionate in terms of physical area) with colors indicating typologies (Figure 4).

county seats are color-coded and numbered based on typological categorization (see key) and are approximately proportionate in size to one another

canal, railroad, and highway infrastructure over time was quantified in a single score (T); here, only existing infrastructure has been mapped

Legend county land outside Basin

county boundary outside SRB

county land within Basin

county boundary within SRB

county seat outside Basin

major stream

county seat within Basin

minor stream

significant places institutions of higher education within approximately ten (10) miles of towns were represented by an education score (E). the distance from county courthouses (D) to streams was also examined

14 21

22

variables are identified near the top of the chart and are grouped into three (3) general categories

. R a

n

n ha

e

u sq

C

Su

floodplains proportions of town area (FldA) within the FEMA-determined 100 and 200 year flood plains was determined.

n

to

oc

oh

1

one (1) standard deviation

R. Ch

New York

23

11

em

20

ung

R.

Tioga R.

19

Harrisburg

17 6

streams

33

26 15 a n n

a h e

7

31

S Branch

29

9

West

35

34

u

q us

10

maximum adjacent stream order (S) was considered. where USGS stream gage data was available, flood frequencies (F) or return periods for NOAA-determined flood stages were calculated.

natural resources

25

27

based upon proximity to a number of resources (e.g. agricultural soils), a resource score (R) was developed. however, it was determined that this score did not adequately represent the complexity of this variable

32 12

30 28 4

ta

R.

riverfront towns key

5

a ni

Ju

18 16 8 3

frontage

confluence

1. Bath, NY 2. Havre de Grace, MD 3. Carlisle, PA 4. Hollidaysburg, PA 5. Mifflintown, PA 6. Towanda, PA 7. Wilkes-Barre, PA

20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35.

8. Harrisburg, PA

bisected

36

24

9. Bellefonte, PA 10. Clearfield, PA 11. Elmira, NY 12. Middleburg, PA 13. York, PA

nn

ha

ue

sq

Su

13

a

Pennsylvania

Binghamton, NY Cortland, NY Norwich, NY Owego, NY Bedford, PA Bloomsburg, PA Emporium, PA Danville, PA Huntingdon, PA Lewisburg, PA Lewistown, PA Lock Haven, PA Sunbury, PA Tunkhannock, PA Williamsport, PA Scranton, PA

early stream

annexed

14. 15. 16. 17. 18. 19.

36. Lancaster, PA

all rankings are relative to peers (i.e. 0.38 = 38% of the max value given in orange) maximum value: represents the largest value over the entire sample set

topography actual scores for each category can be derived by multiplying the relative rank by the maximum value

Maryland

R.

2

Susquehanna riverfront town typologies Author: Advisor: Committee: Committee:

Greg Tenn ............... Landscape Architecture Sean Burkholder ...... Landscape Architecture Thomas Yahner ........ Landscape Architecture Christopher Duffy .... Civil & Environmental Engineering

Cooperstown, NY Laporte, PA Lebanon, PA Montrose, PA Bloomfield, PA Wellsboro, PA

Figure 2. Quantitative analysis chart Scores were developed for a number of variables and were normalized (0.00-1.00) to enable comparison between towns. Average scores across the entire sample set are shown above, and utilization of the charts to derive actual values from normalized ones is described. For instance, to find the population density of Bellefonte, PA (figure 5), one would multiply the relative rank (0.40) by the maximum value (12.91) to obtain 5.16 persons/acre.

X

0.23 0.80 0.18 transportation higher education natural resources stream order

relative rank max value actual value (T) (E) (R) (S)

Variables flood frequency flood plain area % distance to stream town area shape measure population total population density town growth rate (avg) county growth rate (avg)

growth rate corr.

digital elevation models (DEMs) and orthoimagery were compiled. a measure of topographic variation was considered but had not been concluded. however, the data greatly facilitated qualitative assessments (figures 7-8).

Figure 3. Geographic information systems (GIS) (F) (FldA) (D) (A) (Shp) (Pop.) (Pop. Dens.) (GT) (CT) (r)

abstract

objectives

As physical manifestations of culture and society, the typological form of towns can provide clues to less tangible factors associated with their development. While the dynamic nature of river-community relationships makes them inherently complex, a better understanding of the physical interface between town and stream can provide insight into design and planning that is responsive to a region’s cultural landscapes. Largely shaped by its streams, the Susquehanna River Basin (the Basin) provides an opportunity to study how riverfront town typologies have developed. In particular, this study aims to examine how responses to a shared regional context have differentially influenced these physical relationships. In its initial phase, a research framework was developed to guide the selection of case studies from riverfront towns throughout the Basin. This framework emphasized the important historic roles of county seats and was developed through a quantitative analysis of factors thought to contribute to their growth. A number of variables, including transportation infrastructure, institutions of higher education, and flood recurrence rates, were examined. A subsequent qualitative examination of riverfront town typologies that utilized mapping exercises, historical map/document review, and first-hand observation was then conducted. This latter process was extremely important to the interpretation of the previous quantitative results through the development of generalizable riverfront town typologies. Ultimately, the combination of quantiative and qualitative analytical processes aided in understanding the influence of the region’s extensive stream network and provided insights into how waterfront design and planning initiatives might proceed within the region.

• regional development: examine factors hypothesized to have influenced growth and development within county seats of the Susquehanna River Basin; acquire understanding of the region’s shared and unique contemporary, historical and environmental contexts • riverfront town typologies: apply both quantitative and qualitative analytical methods to develop an understanding of factors hypothesized to impact growth of towns within the Basin and utilize these analyses to describe generalized typologies • rivertown concept: understand how and why the ‘rivertown’ concept is being emphasized by certain organizations, institutions, and communities within the region as a framework for economic and cultural revitalization • cultural regions: consider the possibility of riverfront towns/cities of the Basin as part of a larger cultural region framed by an extensive and influential stream network • future of waterfront development: consider how an understanding of regionally shared and locally unique facets of riverfront towns might inform future waterfront development within the Basin, especially within the rivertown framework

Most variables were visualized with the aid of GIS software (ESRI: ArcMap 10, ArcCatalog 10, and ArcScene 10). Data was compiled from a number of sources, including state and national level information clearing houses and other public or private institutions (e.g. universities). Where necessary, new data layers were created by the author. Due to the significant amount of time spent organizing and compiling data, it is hoped that the compiled geodatabases will be made publicly available.

methods • detailed methods: see accompanying appendices • case study selection (figure 1): for their important historic roles and relative stability, the 35 county seats within the Susquehanna River Basin were selected for analysis; because none exist in Maryland, Havre de Grace was also included in the analysis (n=36) • quantitative methods (figure 2): for each variable, a representative score was created based on data derived from geographic information systems (GIS) and/or literature; all scores were normalized to values between 0.001.00 to allow for easier visualization and direct comparisons to be made between individual towns and typologies. • qualitative assessment (figure 3): GIS analysis and available online mapping resources (e.g. Google, Bing) and literature review (including contemporary and historic maps) were the primary source materials for analysis. data layers (e.g. digital elevation models, hydrography, etc.) were acquired or created for utilization within the mapping exercise.


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