RS GIS FOR GROWTH AND EXPANSION OF

CITY (URBAN SPRAWL)

PRESENTED BY :-

MADHAVI LATHA BHUMIREDDYPRIYANKA KANPHADE

Urban Expansion & Sprawl?• As population increases in an area or a city, the boundary of

the city expands in an unplanned manner to accommodate

the growth; this expansion is termed as sprawl

• It is the spread of human population away from central urban

areas into previously remote and rural areas.

• Urban sprawl is an uncontrolled and uncoordinated spread of

urban population around a city.

• Expansion of town and cities is considered with respect to the

increase of the size of a built-up area.

URBAN SPRAWL

URBAN SPRAWL

• Population growth

• Industrialization

• Living and property cost

• Lack of affordable housing

• Independence of decision

• Lack of proper planning policies

• Large plot Size

CAUSES CONSEQUENCES

• Impacts on Wildlife and Ecosystem

• Loss of Farmland

• Poor Air Quality

• Inflated Infrastructure and Public

Service Costs

• Impacts on Water Quality and

Quantity

• formation of slums

• increase traffic congestions

CASE STUDY 1

REMOTE SENSING, GEOGRAPHIC INFORMATION SYSTEMSAND SHANNON’S ENTROPY: MEASURING URBAN SPRAWL

IN A MOUNTAINOUS ENVIRONMENTL. C. O. Verzosa , R. M. Gonzalez

• Baguio city is a mountainous region in Phillipines.

• DATA USED

SATELLITE DATA Landsat Images (1979, 1989, 1992, 2002)

Aerial Photographs (2003)

Topographic Map National Mapping and Resource Information Agency

• SOFTWARE USED

ENVI 4.3®

ERDAS-Imagine

GIS software ArcGIS 9.3®.

• The integration of RS and GIS is used in adopting Shannon’s entropy to measure

urban sprawl.

Shannon’s entropy is an index used in quantifying the degree of dispersion or concentration of built-up areas. given by,

Where, pi is the probability or proportion of occurrence of a phenomenon in the ith spatial unit out of n units, and thus, is given by

where Xi is the area of built-up at the ith unit

METHODOLOGY:

SIGNIFICANCE OF ENTROPY VALUE

0 – concentrated patternlog n – maximum value denotes dispersed distribution.

Increasing entropy values indicates continuous dispersion with built-up highly occurring. Decreasing values signifies that an area is becoming less fragmented and homogenously covered, thus, further occurrence of built-up is less likely to happen.

OBSERVATIONS:

• This study shows that entropy is a good indicator in identifying and monitoring land development—that is, dispersion and concentration of built-up areas.

• Remote sensing data are more widely used for the analysis of pattern and process rather than understanding the causes or consequences.

• Conventionally provides a means of accessing a large geographical area with limited time and resources.

CASE STUDY 2

Evaluation of Urban Sprawl and Land use Land cover Change using Remote Sensing and GIS Techniques: A Case

Study of Jaipur City, India Sunil Sankhala, B. K. Singh

• Jaipur is situated in Rajasthan at 26.92°N latitude & 75.82°E longitude.

• Data Sources :

1. Satellite Data:

I. IRS LISS II (1995);

II. IRS LISS III (2000, 2006);

III. LANDSAT TM (2010)

2. Survey of India Toposheets: 54A/4, 54B/1, 45N/5, 45M/12, 45M/16, 45N/13,

45N/9, 45N/10, 45N/14 of Jaipur district and adjoining districts.

• Software used:

ERDAS-Imagine 9.2

GIS software Arc GIS 9.2 & Arc view 3.2

METHODOLOGY:

• IRS LISS-II (1995), LISS-III (2000, 2006) and LANDSAT TM (2010) satellite images have been used for generation of land use/ land cover map.• The satellite data was enhanced before classification using

histogram equalization in ERDAS Imagine .• The data was resampled to a common spatial resolution of

23.5 m.• Then Landuse/landcover classification was performed

through digitization processes.

MAP SHOWING LINEAR URBAN SPRAWL

MAP SHOWING LEAPFROG URBAN SPRAWL

OBSERVATIONS:

• The sprawl location maps generated from the interpretation of satellite imagery reveals that sprawl is towards the north-west and south-east of the city.

• The prime causes behind such expansion has been availability of land at considerably cheaper rate in those areas, good transport communicational network, availability of better infrastructural and institutional amenities, nearness to the main city

• Jaipur is witnessing three major kind of sprawling, (i) Linear, (ii) Leap frog, (iii)Radial. At some places polycentric sprawl is also observed.

CONCLUSION:

• Remote sensing and GIS techniques facilitates delineation, tracking down and monitoring of urban development.

• RS provides pattern recognition techniques to classify land cover based on their spectral characteristics on satellite images.

• Satellite data are found to be useful in mapping and quantifying the extent of urban area in different time periods.

• GIS enables the proper handling of databases necessary for the integration of data from different sources and for analysing the urban sprawl extent.

REFERENCES• L. C. O. Verzosa, R. M. Gonzalez, Austria, July 5–7, 2010, “Remote Sensing,

Geographic Information Systems And Shannon’s Entropy: Measuring Urban Sprawl In A Mountainous Environment”

• Feng Li, Prof. Dr.-Ingo . Stefan Siedentop ,” Applying Remote Sensing And GIS On Monitoring And Measuring Urban Sprawl –A Case Study Of China”

• Sunil Sankhala , B. K. Singh , IJETAE, Volume 4, Issue 1, January 2014, “Evaluation Of Urban Sprawl And Land Use Land Cover Change Using Remote Sensing And GIS Techniques: A Case Study Of Jaipur City, India “

• B. Bhatta ,” Analysis Of Urban Growth And Sprawl From Remote Sensing Data, Causes And Consequences Of Urban Growth And Sprawl, Springer Chapter 2”

• Monalisha Mishra, Kamal Kant Mishra, A.P. Subudhi, “Urban Sprawl Mapping And Land Use Change Analysis Using Remote Sensing And GIS (case Study Of Bhubaneswar City, Orissa)”