shepshed leisure centre

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Shepshed Leisure Centre- GIS Analysis

SHEPSHED LEISURE CENTRE PROPOSAL

GIS SITE EVALUATION GORDON BEST, M.ENG CIVIL ENGINEERING

CONTENTS

1. Introduction ........................................................................................................................................................ 3

2. Background Information ..................................................................................................................................... 3

3. Boolean & Fuzzy Logic ........................................................................................................................................ 4

4. Report Methodology & Map Derivation ............................................................................................................. 5

5. Results of GIS Analysis ........................................................................................................................................ 6

5.1 Boolean Logic ............................................................................................................................................... 6

5.2 Fuzzy Logic .................................................................................................................................................... 7

6. Site Choice & Justification .................................................................................................................................. 9

7. Additional Data ................................................................................................................................................. 12

8. Evaluation of Fuzzy Logic Use ........................................................................................................................... 13

9. Conclusion ........................................................................................................................................................ 14

10.Appendices ...................................................................................................................................................... 15

Appendix 1- Reclassification Tables Used In Boolean Logic ............................................................................. 15

Appendix 2- Types of Overlay Used In IDRISI ................................................................................................... 15

Appendix 3- Coverages Used For Boolean Logic .............................................................................................. 16

Appendix 4- Coverages Used For Fuzzy Logic................................................................................................... 16

Appendix 4- Fuzzy Logic Assumption Coverages .............................................................................................. 17

Appendix 5- Additional Population and Distance Buffers ................................................................................ 17

Appendix 6- Suitability Area Distribution ......................................................................................................... 18

Appendix 7- Flood Data, Black Brook ............................................................................................................... 18

11.References ....................................................................................................................................................... 19

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TABLE OF FIGURES

Figure 1- Shepshed 2011 Census Data, LSR Online 2013 ........................................................................................ 4

Figure 2- Shepshed Area, Google Maps 2016 ......................................................................................................... 3

Figure 3- Types of Boolean Operators, Bhowmick 2014 ........................................................................................ 4

Figure 4- Sigmoidal Membership Function, Spatial Analysis Toolbox, ARC GIS 2016 ............................................. 4

Figure 5- Potential Sites Identified Using Boolean Logic, IDRISI, 2016 ................................................................... 6

Figure 6-Boolean Logic Potential Sites and Area Data, IDRISI 2016 ....................................................................... 7

Figure 7- Potential Sites Identified Using Fuzzy Logic, IDRISI, 2016 ....................................................................... 9

Figure 8- Fuzzy Logic Suitability Category Areas, IDRISI, 2016 ............................................................................... 9

Figure 9- Selected Boolean Logic Site, Overlaid Google Maps, 2016 ................................................................... 10

Figure 10- Selected Fuzzy Logic Site, Overlaid Google Maps, 2016 ...................................................................... 10

Figure 11- Digimap Ordnance Survey Map of Site 1, DIGIMAP, 2016 .................................................................. 11

Figure 12- Potential Sites and Population Areas, Boolean, IDRISI, 2016 .............................................................. 16

Figure 13- Potential Sites and Population Areas, Fuzzy, IDRISI, 2016 .................................................................. 16

Figure 14- ENTEC Shepshed Flood Plain Analysis, (ENTEC, 2008 ......................................................................... 17

Figure 15- Coverage 1 ........................................................................................................................................... 17

Figure 16- Coverage 2 ........................................................................................................................................... 17

Figure 17- Coverage 3 ........................................................................................................................................... 17

Figure 18- Coverage 1 ........................................................................................................................................... 17

Figure 19- Coverage 2 ........................................................................................................................................... 17

Figure 20- Coverage 3 ........................................................................................................................................... 17

Figure 21- Population Buffer ................................................................................................................................ 17

Figure 22- Road Buffer .......................................................................................................................................... 17

Figure 23-Slope Buffer .......................................................................................................................................... 17

Figure 24- Distance Buffer .................................................................................................................................... 17

Figure 25- Population Buffer ................................................................................................................................ 17

Figure 26-Urban Buffer ......................................................................................................................................... 17

Figure 28-Suitability Areas .................................................................................................................................... 17

Figure 29- Black Brook Flood Data, ENTEC 2008 .................................................................................................. 17

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1. INTRODUCTION

This report will undergo analysis of potential sites to locate a leisure centre in the Shepshed, Leicestershire area

using Boolean and fuzzy logic on IDRISI Geographical Information System (GIS) spatial analysis software.

The designer has outlined the following site requirements:

Within 500m of the town of Shepshed

Within 450m of a motorway or A and B class roads

On a slope of less than 2.5%

On Agricultural Grade III land

At least 2.5 Hectares in area

Firstly, the report will explain how the two methodologies were used to produce the site choice maps, and

outline the parameters which resulted in differing recommendations for the leisure centre site using each

method.

Secondly, the site choice will then be justified using data gathered from GIS analysis of population distribution,

accessibility, and other relevant factors.

Thirdly, the advantages and disadvantages for each methodology will be outlined, allowing an evaluation of

which potential site would be best for the leisure centre.

Finally, an evaluation of fuzzy logic methodology for spatial analysis in GIS will be conducted using the findings

of the methodology and from a literature review of existing material on the subject.

2. BACKGROUND INFORMATION

Shepshed is a town in Leicestershire, England, with a population of 13,505 (2011 UK Census, LSR Online, 2013).

Links to the nearby M1 motorway have resulted in a highly commuter based population, travelling to larger cities

such as Loughborough. Census data demonstrates a primarily middle age demographic, with slightly fewer above

65 and below 25 (Fig.1).

Figure 1- Shepshed 2011 Census Data, LSR Online 2013 Figure 2- Shepshed Area, Google Maps 2016

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3. BOOLEAN & FUZZY LOGIC

GIS is a tremendous resource during project development, allowing complex and substantial datasets to be easily

visualised through a graphical interface. This interface allows effective and detailed analysis to be accomplished,

using multiple modelling systems and operators.

Two of these systems are Boolean and fuzzy logic. The Boolean logic analyses the dataset by indicating whether

or not the relevant data meets certain criteria, for example if it is over 2.5% slope, or within a known floodplain.

Boolean logic uses various operators (Fig.3) to overlay multiple criterions, allowing decisions to be made

regarding a particular site.

Due to the true/ false nature of Boolean logic, the outputs can only be binary, i.e. 1 or 0, also known as

membership or non-membership, where 1 will definitely occur and 0 will definitely not. This output provides a

precise analysis of a dataset, however the requirements of a project can frequently be dynamic, for example

how close a person would be willing to walk to a bus stop. The answer is unlikely to be an exact value, but more

an educated approximation.

This approximation is implemented in Fuzzy logic, where values between 0 and 1 represent the likelihood of an

outcome occurring, whereby 0.9 represents a high likelihood of someone travelling a certain distance to a bus

stop, and 0.1 indicates a low likelihood. These values can then be graphically represented using transition zones

and inflection points to determine areas of uncertainty. The four inflection points; a, b, c and d, indicate the

point where membership of the curve becomes 0, becomes 1, falls below 1, and becomes 0 again respectively.

This visual representation of the data is known as the Sigmoidal Membership Function (Fig. 4).

Figure 3- Types of Boolean Operators, Bhowmick 2014

Figure 4- Sigmoidal Membership Function, Spatial Analysis Toolbox, ARCGIS, 2016

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These parameters can be adjusted according to the findings of the initial investigation, and from existing

datasets on the same topic. Fuzzy logic is ideal when the parameters of the site cannot be clearly defined, and

require uncertainty to be considered.

4. REPORT METHODOLOGY & MAP DERIVATION

In order to analyse potential locations for the leisure centre, several spatial datasets, or coverages, were used.

These datasets provide information on land use, topography, and the layout of infrastructure in the area. The

coverages were:

Nwcompo- Composite map of the area

Nwland- Land use in the area

Nwroads- Road layouts

Nwtopo- Area topography

Nwurban- Urban area layout

Popln- Shepshed population data

Commands were carried out on the coverages to meet the criteria required by the design team, and ensure that

a feasible area was found for the site.

These commands were:

SURFACE- calculates slope of surface cells from topography

DISTANCE- calculates exact distance from each cell to a set of target cells

RECLASS- creates new map by reclassifying values of existing coverage

DISPLAY- allows the user to view and interact with maps

OVERLAY- overlaps two map images to form a new map for evaluation

GROUP- creates polygons in an image from shared attributes

AREA- creates a new image using area values of land use

FUZZY- evaluates fuzzy logic membership values for the dataset

By using these commands, the areas near Shepshed which met the client’s needs using Boolean and fuzzy logic

could be found. This process will be further explained later in the report.

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5. RESULTS OF GIS ANALYSIS

5.1 BOOLEAN LOGIC

Using the more specific Boolean logic, the coverages and commands used result in the following suitable areas

for the development of the leisure centre. Fig.5 was created with the OVERLAY command once factors relating

to the design brief had been implemented into the dataset, as completed using the RECLASS command. These

reclassifications can be seen in Appendix One, with OVERLAY types in Appendix Two.

As indicated in green, there are two sites which meet all client requirements for the development, one to the

South of the main urban area of Shepshed, and another to the East. They are referred to throughout this report

as Site 1 and 2 respectively.

This map was created through the use of three coverages to ensure the parameters for design were met by the

commands previously discussed, these can be seen in Appendix Three.

Figure 5- Potential Sites Identified Using Boolean Logic, IDRISI, 2016

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The area of Site 1 using Boolean logic was calculated to be 8 hectares and Site 2 as 4.5 hectares, as indicated by

the AREA command output (Fig.6).

5.2 FUZZY LOGIC

The more approximate fuzzy logic methodology naturally leads to a larger area of potential sites, primarily due

to several decisions being made regarding the size of the transition zone for several variables.

These variables were determined as:

Allowable distance from Shepshed

A- 0m B-50m C-500m D-800m

Distance from Main Roads

A- 0m B-50m C-450m D-1500m

Allowable Slope

A-n/a B-n/a C-2.5% D-8%

The cell size in IDRISI is 50m, hence the 0m and 50m range for A and B, and why C and D values are factors of

50. Furthermore, the values for C were pre-defined by the design spec for IDRISI.

The maximum distance from Shepshed, D, was established from distance decay studies from the US National

Library, suggesting that 0.5 miles (800m) is the mean acceptable distance for walking to leisure facilities. (NCBI,

2012)

The maximum distance from main roads was approximated at 1500m, in order to ensure a high level of

accessibility. This was further backed up by the US National Library.

The maximum allowable slope was selected to be 8% due to the British Standard maximum for paths and routes.

(Sensory Trust, 2016)

Category Hectares

1 8

2 4.5

Figure 6- Boolean Logic Potential Sites & Area Data

Client Selected Design Assumption

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All coverages which were created from the assumptions of: distance from Shepshed, distance from main roads,

and slope, can be seen in Appendix Four, with further buffers created in Appendix Five.

With these decisions implemented into the fuzzy logic model of the coverages, Fig.7 was created.

This map was developed using three primary coverages to meet the design parameters, using the commands

discussed in Section 4, in particular FUZZY, these coverages can be seen in Appendix Three. Suitability categories

ranging from 1-100% for feasible sites have been created, relating to design factors such as; slope, distance to

urban zones,and promixity to A,B,C Class Roads and a motorway.

From this result, the uncertainty accounted for in the Fuzzy Logic can be used as a tool for considering expansion

and further development in the area, where site conditions may not be perfect, but may facilitate some level of

growth.

Figure 7- Potential Sites Identified Using Fuzzy Logic, IDRISI, 2016

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The total area of 100% suitable cells (Fig.8) was 17.75 Hectares; of which 4.5 Hectares were found in Site 1, and

8 Hectares in Site 2 (as calculated for Boolean logic), complete data can be found in Appendix Six. However, the

area of the sites within 1-100% suitability was 17.75 Hectares for Site 1, and 11.5 Hectares for Site 2, indicating

that although Site 2 has a larger area of 100% suitable land, the potential for expansion is greater at Site 1.

Reformatting the map window of “popln” to identical grid coordinates as the other coverages (0,119,120,239)

allowed IDRISI to overlay the population data with existing coverages. It was expected that this would

demonstrate changes to the size of the recommended site. However, since the maximum walking distance was

estimated to be relatively high C (500m) and D (800m), the areas were not affected. Such findings should be

noted by the design team, allowing sensitivity analysis to be conducted if the public feedback indicated that

800m was too far to walk to the leisure centre.

6. SITE CHOICE & JUSTIFICATION

The Sports England Design Guidance Notes have been consulted to determine the exact site requirements for

the leisure centre.

The notes suggest three overall objectives which make up the site selection:

High Accessibility Potential

High Level Amenity

Community Engagement Potential

-Sports England Design Guidance Notes

With these three overall objectives, more specific objectives for the site can be established:

Potential for Co-location

Public transport Links

Location Prominence for Public Communication

Parking Provision & Emergency Vehicle Access

-Sports England Design Guidance Notes

Figure 8- Fuzzy Logic Suitability Category Areas, IDRISI

2016

Category Hectares

1 8.7500000

2 2.5000000

3 6.5000000

4 11.5000000

5 2.7500000

6 3.0000000

7 5.7500000

8 14.2500000

9 7.5000000

10 17.7500000

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With these objectives considered, the 4.5 Hectare Site 1, to the South of Shepshed, has been selected for the

site of the leisure centre, as seen below in Boolean and fuzzy logic (100% Suitability- Green).

Although the maps suggest there are larger areas near the town, e.g. at Site 2, the area suggested by Boolean

logic at Site 1 meets all the necessary design requirements, as well as creating additional opportunities which

these larger areas do not.

The decision to choose Site 1 over any other potential sites which met the design requirements was made from

the following observations:

1. Universal private and public vehicular access from M1 & A,B,C Class Roads (200m from A512, 500m

from B591, 1.3km from M1 Junction 23)

2. Within walking distance from urban area (450m from town, 800m from town centre, 6 minutes’ walk

at average speed (5mph))(BHF.org, 2015)

3. Low environmental impact on existing nearby farmland and disused land

4. Room to expand if required

5. Ideal distance from urban boundary to not interfere with town planning, yet close enough for ease of

access.

6. Neighbouring inactive quarry on A512, potential Brownfield expansion site (regeneration)

7. Close proximity to local bus services to Loughborough and neighbouring towns along A512

8. Nearby electrical substation for ease of grid connection (as indicated in Fig.12)

9. Nearby local industrial estate for cooperation and commercial synergy

10. Ease of access for local schools and sports groups

Rejected Site 2 Rejected Site 2

Selected Site 1 Selected Site 1

Figure 9- Selected Boolean Logic Site, Overlaid Google Maps, 2016

Figure 10-Selected Fuzzy Logic Site, Overlaid Google Maps, 2016

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Site 2 to the East of Shepshed did meet several requirements, but the location was evaluated to be inferior

compared to Site 1. For example, the location of the M1 was deemed to limit the local accessibility (private,

public and emergency vehicles), and expansion potential, since the junction to access and exit the M1 is situated

nearer to selected Site 1 (Fig.11), in addition to causing local conflicts relating to noise pollution, air quality and

visual intrusion. Therefore, although Site 1 is slightly smaller than Site 2, the other characteristics of the site

make make for a more feasible and beneficial location for a leisure centre.

Figure 11- Digimap Ordnance Survey Map of Site 1, DIGIMAP, 2016

Site 1

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7. ADDITIONAL DATA

The proximity of the potential sites in relation to population areas are shown in Fig.13 & 14, again using Boolean

and Fuzzy logic. These maps include the town of Shepshed, but also the wider area, including the periphery of

Loughborough to the East and several smaller rural communities.

As demonstrated by Fig.14, the floodplain of the Blackbrook will not impact the proposed leisure centre at Site

1. The data provided by ENTEC development plans, and the Charnwood Local Authority Interactive Maps indicate

protection from annual rise in river depths, but also from 100 year flood events (Data provided in Appendix

Seven).

Figure 12- Potential Sites and Population Areas, Boolean, IDRISI, 2016 Figure 13- Potential Sites and Population Areas, Fuzzy, IDRISI, 2016

Figure 14- ENTEC Shepshed Flood Plain Analysis, (ENTEC, 2008)

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8. EVALUATION OF FUZZY LOGIC USE

Fuzzy logic has tremendous potential in determining suitable sites in GIS application. By incorporating a degree

of uncertainty with the data, e.g. how the definition of “far away” can be interpreted, more accurate maps can

be created for spatial analysis. However, the success is determined by the accuracy of the assumptions made to

create the transition zones of the dataset. In this study, the recommended walking and proximity to road

distances were taken from external studies, meaning that their accuracy and usefulness in this context cannot

be guaranteed. In order to ensure the data is realistic, leading to the optimum site being selected, studies should

be conducted within the Shepshed community. By involving stakeholders and community members, a clearer

picture can be developed of how the geographical variables of potential sites may affect the overall success of

the project.

A literature review of fuzzy logic Success in GIS highlights several potential advantages and disadvantages of use.

A study by Imperial College London named Fuzzy Logic and Its Uses: Article 2 (1995) demonstrates the massive

potential of fuzzy logic to engage a huge amount of data, sort this data, and allow spatial analysis, all while

considering a degree of uncertainty. This facility can be used in more ways than just site selection; but in

manufacturing, epidemiology, and a vast array of other fields. (Real-Life Applications of Fuzzy Logic, Singh &

Gupta, 2013)

The accuracy of the fuzzy logic system may be appropriate for this site development, with relatively limited site

requirements, but when more than ten variables are required to be implemented, the process can become

lengthy and complex, as found in Fuzzy Logic: A “Simple” Solution for Complexities in Neurosciences? (2011) by

Godil et al. When such analysis takes excessive time, decisions can be made without adequate data to back these

up, resulting in poorly located, constructed or operated projects.

Additionally, logician Susan Haack has discussed that although there is frequently a need for uncertainty to be

considered, where variables such as distance or community circumstance are concerned, in many cases a

concrete figure should be calculated as a variable limit for best accuracy. She argues that fuzzy logic is only

needed when the limit is completely unknown due to changing conditions or non-linear variables, rather than

simply uncalculated. Fuzzy Logic Objections, Imperial College London (1995)

Furthermore, there is no universal framework for Fuzzy logic analysis for site selection in GIS application, so

consistently accurate transition zones may be difficult to accomplish, as outlined in Error, Accuracy, and Precision

by Foote & Huebner of the University of Colorado (2015).

The lack of a coordinated framework may be down to software access, project type, technical abilities, or a

variety of other factors, but to ensure a model is adopted universally to ensure all site location tasks are accurate,

a consistent methodology may be required.

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9. CONCLUSION

By using IDRISI GIS software, potential site locations have been carefully, accurately and comprehensively

investigated to ensure the most suitable site for the client was found, ruling out areas which did not meet the

strict size, land type and proximity requirements of the design brief. By using both Boolean and Fuzzy logic to

locate the optimum site, an array of factors could be considered; including the slope of land, and proximity to

roads or urban areas. The Boolean logic allowed the sites which did not meet ideal requirements to be

immediately eliminated, potentially speeding up the design process, by giving an early indication of potential

sites to developers. By using the Fuzzy Logic in collaboration to Boolean logic, a more realistic notion of sites can

be suggested. By implementing assumptions made regarding slope limits and the distances which members of

the public would be willing to walk, the subtle differences in site conditions can be uncovered and applied to

decision making.

Site 1 to the South of Shepshed was selected due to the high level of accessibility from A, B and C Class Roads,

and the M1 motorway. The proposed site is within 15 minutes walking distance from the town centre, providing

a high level of footfall, and opportunity for public engagement, as prioritised in the Sports England Design

Guidance Notes. Furthermore, a nearby industrial estate provides an opportunity for business cooperation and

partnership. There is room to expand, should the opportunity arise, as the Fuzzy logic map demonstrates,

allowing scope for further developments in the future.

2748 words

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APPENDICES

Appendix 1- Reclassification Tables Used In Boolean Logic

This appendix demonstrates the reclassifications which took place under Boolean logic to meet the design

requirements.

Appendix 2- Types of Overlay Used In IDRISI

This appendix defines the types of overlay which were used to create new coverages to be used for spatial analysis.

First + Second: The pixel values for both images are added together.

First - Second: Pixels from image two are subtracted from image one

First x Second: The pixels from both images are multiplied together

First / Second: Pixels from image one are divided by image two.

First - Second / First + Second: Divides the subtraction calculation of the images by the addition value.

First to the power of the Second: Takes pixels in image one by the power of the second image.

Minimum: The minimum value in both images is taken forward.

Maximum: The maximum value in both images is taken forward

First coverages second, except where zero: Coverages the second image with the first image’s pixels,

unless the first image pixel value is zero. In this case, the value of the second image will be taken

forward.

Input xdurban

Output xburban

New Value 0 1 0

Range From 0 50 501

To Just < 50 501 999999

Input nwroads

Output xrroads

New Value 8 0

Range From 3 12

To Just < 12 14

Input xstopo

Output xrtopo

New Value 1 0 0

Range From 0 2.5 501

To Just < 2.5 100 999999

Input nwland

Output xrland

New Value 1 0 0

Range From 6 8 1

To Just < 8 10 6

Input xarea

Output xsite1

New Value 0 14 0

Range From 0 2.5 100

To Just < 2.5 100 999999

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Appendix 3- Coverages Used For Boolean Logic

This appendix demonstrates the coverages which were created using Boolean logic

Appendix 4- Coverages Used For Fuzzy Logic

This appendix demonstrates the coverages which were created using fuzzy logic.

Figure 15- Coverage 1 Figure 16- Coverage 2 Figure 17- Coverage 3

Figure 18- Coverage 1 Figure 19- Coverage 2 Figure20- Coverage 3

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Appendix 4- Fuzzy Logic Assumption Coverages

This appendix demonstrates the coverages which were created to implement the assumptions made in fuzzy

logic.

Appendix 5- Additional Population and Distance Buffers

This appendix demonstrates additional coverages which were used to ensure accuracy of the previous

coverages, and to justify the site choice.

Figure 21- Population Buffer Figure 22- Road Buffer Figure 23- Slope Buffer

Figure 24- Distance Buffer Figure 25- Population Buffer Figure 26- Urban Buffer

Figure 27- Boolean Road Buffer

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Appendix 6- Suitability Area Distribution

This appendix represents the areas of suitability ranging from 1-100%.

Appendix 7- Flood Data, Black Brook

This appendix demonstrates potential flood events for the Black Brook near Shepshed.

AOD= Above Ordnance Datum

Figure 29- Black Brook Flood Data, ENTEC 2008

Category Hectares Legend

19 17.7500000 100% Suitability

20 10.5000000 90-99% Suitability

21 3.5000000 80-89% Suitability

22 6.2500000 70-79% Suitability

23 2.0000000 60-69% Suitability

24 2.2500000 50-59% Suitability

25 5.7500000 40-49% Suitability

26 0.5000000 30-39% Suitability

27 6.0000000 20-29% Suitability

28 6.0000000 10-19% Suitability

29 19.7500000 1-9% Suitability

Figure 28- Suitability Areas

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10. REFERENCES

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Identify The Suitable Sites For Artificial Recharge". ResearchGate. N.p., 2014. Web. 4 Mar. 2016.

Colorado.edu,. "Error, Accuracy, And Precision". N.p., 2016. Web. 4 Mar. 2016.

Desktop.arcgis.com,. "ARCGIS". N.p., 2016. Web. 4 Mar. 2016.

Doc.ic.ac.uk,. "Surprise 96". N.p., 2016. Web. 4 Mar. 2016.

Leistershire Parish Council. (2016). Interactive Map. [online] Available at:

http://http%3A%2F%2Fshepshed.leicestershireparishcouncils.org%2Fuploads%2F17520c9da080aa89

04456012.doc&usg=AFQjCNEBTNvan4HMRX3kdOgs0bPXHoDAHg&bvm=bv.116274245,d.ZWU&cad=r

ja [Accessed 11 Mar. 2016].

LSR ONLINE,. "Census Data". N.p., 2016. Web. 4 Mar. 2016.

Mtholyoke.edu,. "GIS Use". N.p., 2016. Web. 4 Mar. 2016.

Shamim, Muhammad Shahzad et al. "Fuzzy Logic: A "Simple" Solution For Complexities In

Neurosciences?". Surgical Neurology International 2.1 (2011): 24. Web. 4 Mar. 2016.

Singh, Harpreet et al. "Real-Life Applications Of Fuzzy Logic". Advances in Fuzzy Systems 2013 (2013):

1-3. Web. 4 Mar. 2016.

Sloan, Peggy, Julius Gy Fabos, and Jack Ahern. Improved Land Use Decision-Making In Rural

Communities. Amherst, Mass.: Massachusetts Agricultural Experiment Station, College of Food and

Natural Resources, University of Massachusetts at Amherst, 1992. Print.

Sport England,. "Sports Hall Design". N.p., 2016. Web. 4 Mar. 2016.

Trust, Sensory. "Outdoor Access: Handrails. Sensory Trust.". Sensorytrust.org.uk. N.p., 2016. Web. 4

Mar. 2016.

Webmap.charnwood.gov.uk. (2016). Cadcorp Web Map Layers. [online] Available at:

http://webmap.charnwood.gov.uk/webmaplayers/ [Accessed 11 Mar. 2016].

Yang, Yong, and Ana V. Diez-Roux. "Walking Distance By Trip Purpose And Population Subgroups".

American Journal of Preventive Medicine 43.1 (2012): 11-19. Web. 4 Mar. 2016.

shepshed leisure centre

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