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.
frontage towns
confluence towns
Lewistown, PA
1877
Bellefonte, PA
1874
Laporte, PA
1943
Lancaster, PA
1864
Figure 7. Sample map analyses
Figure 8. Historic mapping
water: the confluence of two or more major streams provides boundaries or otherwise influences form; often proximal to and/or oriented toward the smaller streams; average flood rates (M = 0.48, S = 0.27) are similar to frontage towns, but the highest frequencies and FldA values (M = 0.59, S = 0.24) are found here topography: very often found where streams have carved out niches in more mountainous regions; shape values (M = 0.36, S = 0.06) are similar to bisected towns and reflect how physical growth has been limited by availability of flat land with towns often taking on dynamic forms that follow terrain and hydrologic systems infrastructure: limited room and the need for flowing water (power production, waste disposal, etc) necessitated the placement of infrastructure along stream fronts; transportation scores (M = 0.39, S = 0.21) are on par with frontage towns.
bisected towns water: form of bisected towns largely influenced by a single stream; unique in that a single town’s boundaries encompass both banks; limited stream gage data available; however, FldA (M = 0.18, S = 0.18) is lower than confluence or frontage towns and similar to early stream towns ; topography: towns are often constrained by topography but differ from confluence towns in that stream valleys are wider/larger or streams have meandered through the approximate center of the mountain valley infrastructure: like frontage towns, town centers (D) have tended to develop close to streams (M = 0.17, S = 0.06); transportation and industrial infrastructure tend to occur along one stream bank - likely where flatter land exists and away from town; this has provided some separation of land uses
Elmira, NY Bellefonte, PA Clearfield, PA Middleburg, PA York, PA
early stream towns water: developed along lower order streams (M = 0.21, S = 0.10); in some instances, towns appear ordered by these small streams, but this is not always the case (D: M = 0.36, 0.21); existing or man-made features (e.g. lakes & dams) have increased visibility and influence of certain waterfronts (e.g. Laporte, Cooperstown); except in valleys, flooding is not a major concern topography: while not a requirement, towns are often located in mountainous regions proximal to headwater streams; limited availability of flat land may not be the only reason for their relatively compact size/shape (e.g. historic economic role) infrastructure: access to the towns has remained limited (T: M = 0.11, S = 0.13) and populations (M = 0.07, S = 0.13), areas (M = 0.09, S = 0.07) and other measures of growth (e.g. shape) are lowest amongst the sample set.
Cooperstown, NY Laporte, PA Lebanon, PA Montrose, PA New Bloomfield, PA Wellsboro, PA
annexed stream towns water: only one (1) county seat falls within this category, possibly implying the important role of streams on growth within the Basin. initially, town development may have little or no actual or planned physical relationship with proximal streams; over time, physical growth has caused a figurative ‘annexation’ of the stream into town boundaries. distance to stream is amongst the highest (D = 0.88), and, while flood frequency is high (F = 0.64), FldA is low (0.10) topography: based on such a small sample, it hypothesized that towns of this nature will be found in less mountainous regions (e.g. piedmont or coastal plan) where development was not greatly inhibited by topography infrastructure: transportation does not appear to follow stream networks; industry may have developed near streams, but not necessarily within town boundaries; agriculture predominates
Lancaster, PA
Figure 4. Generalized riverfront town typologies
Figure 5. Typology charts
Figure 6. Typological descriptions
Based on literature review, quantitative analysis, and mapping exercises, five riverfront town typologies for the Susquehanna River Basin were described. These are not thought to represent discrete scenarios and likely occur along a dynamic continuum. Some towns share facets of multiple typologies. Further analysis of individual towns - as with historic mapping - will likely necessitate refinement of these typologies and, possibly, reclassification of individual towns.
For each riverfront town type (except the annexed town type), mean values and standard deviations were calculated. See figure 2 for an explanation of chart interpretation.
The above descriptions are generalized and based upon the author’s observations made during the course of this study. It is likely that further examination would further reveal nuances within each type and necessitate their refinement. It will be especially important to further enhance descriptions of the ‘annexed stream’ town, because only a single example was noted.
results
discussion
• • • • • • •
• methodological linkages: Constructive quantitative and qualitative analyses frame an understanding of the region’s development by highlighting and framing linkages between examined variables. For instance, while quantitative analysis reveals the importance of transportation infrastructure in terms of town growth rates, qualitative typological analysis revealed how its historical development was influenced by topography and the location of industry. Related to the region’s streams, this, in turn, leads to the identification of an interesting phenomenon. Flood hazard risk, quantified by two distinct measures, was shown to have very little impact on growth. In some instances, it seems, residential flood plain use became a major phenomena only as land distant became scarce in more distal locations. • riverfront town typologies & waterfront development: The identification of town typologies was intended to generalize patterns of development across a large region, with an emphasis on the pervasive stream network of the Susquehanna River Basin. The examination of county seats within the Basin has made this role apparent. As communities reconsider their relationship with their streams (e.g. in terms of flood hazard mitigation or economic revitalization), linking water resources to other facets of development emphasizes these systems. Typological
• • • • • •
1875
water: smaller tributaries are often present, but town orientation and form are generally influenced by the largest adjacent stream; flood rates are similar other types; FldA is highly skewed (n=4) but trends toward middle value (M = 0.31, S = 0.23) topography: often found in larger, wider valleys, growth is less often restricted by topographic variation and trends linearly with streams; some of the highest relative S values (M = 0.41, S = 0.12) may be indicative of growth in surrounding areas infrastructure: town centers in close proximity to streams (M = 0.18, S = 0.14); though they exhibit the highest transportation scores (M = 0.43, stdev = 0.27), infrastructure is often located around contemporary or historic town boundaries or along opposite side of stream - often leading to major new development and a bisected appearance.
Bath, NY Havre de Grace, MD Carlisle, PA Hollidaysburg, PA Mifflintown, PA Towanda, PA Wilkes-Barre, PA Harrisburg, PA
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
Harrisburg, PA
quantitative analysis - charts: key variables in three (3) groups - highlighted in figures 2, 5, and 7. correlation tables and other detailed results - please see accompanying appendices. quantitative analysis - related variables: correlations (p<0.05) between T, E, GT/Gc & A shape measure as indicator of sprawl flood frequency - no significant correlation with growth rates; interestingly, samples from NY show a highly significant, positive correlation (p<0.001) between growth and flood frequency; a negative correlation (p<0.1) between FldA and F also exists qualitative analysis - typologies: map analysis revealed five (5) general Susquehanna riverfront typologies (figure 4) typological form was based on infrastructure, hydrology, topography, and growth with a single exception, all are represented by at least five (5) samples (M = 7.2, SD = 5.67) confluence town type is most prevalent (n=16). figures 5 & 6 depict quantitative and qualitative analyses of each type (respectively)
digital elevation model
major stream
100 year floodplain
current town boundary
US hwy or interstate
water body
minor stream
200 year floodplain
historic town boundary
existing railway
As part of the qualitative analysis portion of this study, historic maps of towns within the Basin were examined and digitized. By considering the dynamism of town boundaries, these maps provided a better understanding of the formation and persistence of the described typologies (figure 4). Once depicted three-dimensionally (above), they also provided insights into the influence of topography and hydrology on historic development (grey areas are derived from FEMA floodplain maps). As the use of GIS becomes ubiquitous, this method of visualization could become an important tool for examining planning and design along town stream fronts.
conclusions descriptions are not, however, intended to paint the region with several broad brushes. Rather, they are intended to provide an important contextual/regional understanding and inform the development of localized and community driven design and planning initiatives. For instance, a relative abundance of flat land has often led to sprawling conditions around frontage towns and removed populations (and a tax base) from flood plains. However, relatively light infrastructure development (e.g. roads) adjacent to streams may provide opportunities to redevelop stream/ river fronts that do not ignore flood plain risk. (Figure 7) • rivertown/rivercity concept and cultural regions: The rivertown concept is being utilized as a framework of economic and cultural revitalization to identify communities with sociocultural connections to streams/rivers in numerous parts of the country. Such river-community relationships are defined by the community itself, and, thus, this work was not intended to categorically define rivertowns. However, the potential existence of a greater cultural region that is shaped by the Basin’s stream network was a underlying facet of the work. Through the examination of physical manifestations of culture (Zelinsky, 1965) and the important role of streams in their development, this work reveals clues to the existence of such a cultural region.
By examining the physical relationships between town and stream, a framework for understanding the development of Susquehanna riverfront towns has been built upon quantitative and qualitative approaches. The primary challenge has been in understanding how very different analytical methods could actually begin to frame and build upon one another. Here, the development of a generalized typological framework and the utilization of supportive visualization provided the necessary linkages. Within the typologies, an understanding of how various regional and local conditions have influenced and can continue to influence waterfront development is revealed. By applying an understanding of regional opportunities and constraints within local town/community frameworks, design and planning can more successfully consider both bottom-up and top-down approaches. Due to the dynamic nature of cultural and environmental systems, these typologies are not intended to be concretely defined. Further analysis will only act to enhance typological descriptions. Certain variables (e.g. natural resource) warrant alternative/enhanced examination, and further qualitative analysis continues to reveal new areas (e.g. land use change) for investigation.