URBANIZATION AND CHANGING GREEN SPACES IN INDIAN CITIES (CASE STUDY CITY OF PUNE)

Similar documents
Landuse and Landcover change analysis in Selaiyur village, Tambaram taluk, Chennai

Abstract: About the Author:

Urban Expansion of the City Kolkata since last 25 years using Remote Sensing

Urban Hydrology - A Case Study On Water Supply And Sewage Network For Madurai Region, Using Remote Sensing & GIS Techniques

Geospatial Information for Urban Sprawl Planning and Policies Implementation in Developing Country s NCR Region: A Study of NOIDA City, India

Land Use Changing Scenario at Kerniganj Thana of Dhaka District Using Remote Sensing and GIS

Investigation of the Effect of Transportation Network on Urban Growth by Using Satellite Images and Geographic Information Systems

Urban Sprawl Mapping and Landuse Change Detection in and around Udupi Town: A Remote Sensing based Approach

APPLICATION OF LAND CHANGE MODELER FOR PREDICTION OF FUTURE LAND USE LAND COVER A CASE STUDY OF VIJAYAWADA CITY

Spatiotemporal Analysis of Noida, Greater Noida and Surrounding Areas (India) Using Remote Sensing and GIS Approaches

URBAN CHANGE DETECTION OF LAHORE (PAKISTAN) USING A TIME SERIES OF SATELLITE IMAGES SINCE 1972

Application of Remote Sensing Techniques for Change Detection in Land Use/ Land Cover of Ratnagiri District, Maharashtra

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 7, No 1, 2016

Abstract: Introduction: 10 th ESRI India User Conference 2009 Geography in Action

Abstract. TECHNOFAME- A Journal of Multidisciplinary Advance Research. Vol.2 No. 2, (2013) Received: Feb.2013; Accepted Oct.

EFFECT OF WATERSHED DEVELOPMENT PROGRAMME IN GUDHA GOKALPURA VILLAGE, BUNDI DISTRICT, RAJASTHAN - A REMOTE SENSING STUDY

7.1 INTRODUCTION 7.2 OBJECTIVE

CHANGES IN VIJAYAWADA CITY BY REMOTE SENSING AND GIS

Effect of land use/land cover changes on runoff in a river basin: a case study

International Journal of Intellectual Advancements and Research in Engineering Computations

Wastelands Analysis and Mapping of Bhiwani District, Haryana

Submitted to: Central Coalfields Limited Ranchi, Jharkhand. Ashoka & Piparwar OCPs, CCL

INVESTIGATION LAND USE CHANGES IN MEGACITY ISTANBUL BETWEEN THE YEARS BY USING DIFFERENT TYPES OF SPATIAL DATA

Critical Assessment of Land Use Land Cover Dynamics Using Multi-Temporal Satellite Images

About the Author: Abstract:

Urban Expansion and Loss of Agricultural Land: A Remote Sensing Based Study of Shirpur City, Maharashtra

Chitra Sood, R.M. Bhagat and Vaibhav Kalia Centre for Geo-informatics Research and Training, CSK HPKV, Palampur , HP, India

SPATIO-TEMPORAL ANALYSIS OF URBAN POPULATION GROWTH AND DISTRIBUTION IN AURANGABAD CITY

1. Introduction. Chaithanya, V.V. 1, Binoy, B.V. 2, Vinod, T.R. 2. Publication Date: 8 April DOI: /cloud.ijarsg.

Environmental Impact Assessment Land Use and Land Cover CISMHE 7.1 INTRODUCTION

Accuracy Assessment of Land Cover Classification in Jodhpur City Using Remote Sensing and GIS

PREDICTION OF FUTURE LAND USE LAND COVER CHANGES OF VIJAYAWADA CITY USING REMOTE SENSING AND GIS

Urban Sprawl Prediction and Change Detection Analysis in and around Thiruvannamalai Town Using Remote Sensing and GIS

Mapping and Spatial Characterisation of Major Urban Centres in Parts of South Eastern Nigeria with Nigeriasat-1 Imagery

LAND USE AND LAND COVER ANALYSIS USING 8- BAND DATA: A CASE STUDY OF BELGAUM CITY AND ITS SURROUNDING.

Modelling of the Interaction Between Urban Sprawl and Agricultural Landscape Around Denizli City, Turkey

IMPACT OF URBAN EVOLUTION ON LAND-USE CHANGE OF SARGODHA CITY, PAKISTAN

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 4, No 4, 2014

Comparison of MLC and FCM Techniques with Satellite Imagery in A Part of Narmada River Basin of Madhya Pradesh, India

Use of Corona, Landsat TM, Spot 5 images to assess 40 years of land use/cover changes in Cavusbasi

Land Use/Land Cover Mapping in and around South Chennai Using Remote Sensing and GIS Techniques ABSTRACT

Most people used to live like this

1. Introduction. S.S. Patil 1, Sachidananda 1, U.B. Angadi 2, and D.K. Prabhuraj 3

Habitat Mapping using Remote Sensing for Green Infrastructure Planning in Anguilla

Remote Sensing and GIS Application in Change Detection Study Using Multi Temporal Satellite

The Study of Impact of Urbanization on Urban Heat Island with Temperature Variation Analysis of MODIS Data Using Remote Sensing and GIS Technology

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 4, No 2, 2013

MAPPING LAND USE/ LAND COVER OF WEST GODAVARI DISTRICT USING NDVI TECHNIQUES AND GIS Anusha. B 1, Sridhar. P 2

Introduction to GIS. Dr. M.S. Ganesh Prasad

Study of Land Use and Land Cover of Chaksu block, Jaipur through Remote Sensing and GIS

ANALYSIS OF URBAN PLANNING IN ISA TOWN USING GEOGRAPHIC INFORMATION SYSTEMS TECHNIQUES

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 2, 2015

CHAPTER 4 HIGH LEVEL SPATIAL DEVELOPMENT FRAMEWORK (SDF) Page 95

Coalfields Limited. Based on Satellite Data for the Year Central Coalfields Limited Ranchi, Jharkhand. Submitted to:

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 1, 2011

VISUALIZATION URBAN SPATIAL GROWTH OF DESERT CITIES FROM SATELLITE IMAGERY: A PRELIMINARY STUDY

Detection of Land Use and Land Cover Change around Eti-Osa Coastal Zone, Lagos State, Nigeria using Remote Sensing and GIS

Urban Tree Canopy Assessment Purcellville, Virginia

Vegetation Change Detection of Central part of Nepal using Landsat TM

Landuse/Landcover Change Detection in Umshing- Mawkynroh of East Khasi Hills District, Meghalaya Using Spatial Information Technology

INDIANA ACADEMIC STANDARDS FOR SOCIAL STUDIES, WORLD GEOGRAPHY. PAGE(S) WHERE TAUGHT (If submission is not a book, cite appropriate location(s))

SRJIS/BIMONTHLY/S. A. BORUDE. ( ) APPLICATION OF SPATIAL VARIATION URBAN DENSITY MODEL: A STUDY OF AHMEDNAGAR CITY, MAHARASHTRA, INDIA

Analysis of Landuse, Landcover Change and Urban Expansion in Akure, Nigeria (pp )

World Geography. WG.1.1 Explain Earth s grid system and be able to locate places using degrees of latitude and longitude.

Digital Change Detection Using Remotely Sensed Data for Monitoring Green Space Destruction in Tabriz

Geospatial technology for land cover analysis

The main objectives of the present study are mentioned as follows:

Monitoring and Temporal Study of Mining Area of Jodhpur City Using Remote Sensing and GIS

STEREO ANALYST FOR ERDAS IMAGINE Stereo Feature Collection for the GIS Professional

CHAPTER 2 REMOTE SENSING IN URBAN SPRAWL ANALYSIS

CORRELATION BETWEEN URBAN HEAT ISLAND EFFECT AND THE THERMAL INERTIA USING ASTER DATA IN BEIJING, CHINA

Measuring Disaster Risk for Urban areas in Asia-Pacific

STUDY OF NORMALIZED DIFFERENCE BUILT-UP (NDBI) INDEX IN AUTOMATICALLY MAPPING URBAN AREAS FROM LANDSAT TM IMAGERY

Development of a Web Based Land Information System (LIS) using Integrated Remote Sensing and GIS Technology for Guwahati City, India

Post Independence Trends of Urbanization and Role of Small and Medium Towns in Maharashtra- A Geographical Analysis

Urban Growth Analysis In Akure Metropolis

A Logistic Regression Method for Urban growth modeling Case Study: Sanandaj City in IRAN

Using Geographic Information Systems and Remote Sensing Technology to Analyze Land Use Change in Harbin, China from 2005 to 2015

A GIS based Land Capability Classification of Guang Watershed, Highlands of Ethiopia

Spatio-Temporal Analysis of Land Cover/Land Use Changes Using Geoinformatics (A Case Study of Margallah Hills National Park)

A Review of Concept of Peri-urban Area & Its Identification

A Framework for the Study of Urban Health. Abdullah Baqui, DrPH, MPH, MBBS Johns Hopkins University

URBAN SPRAWL AND SPATIO TEMPORAL ANALYSIS OF HISAR CITY IN HARYANA USING REMOTE SENSING & GIS TECNOLOGY

M.C.PALIWAL. Department of Civil Engineering NATIONAL INSTITUTE OF TECHNICAL TEACHERS TRAINING & RESEARCH, BHOPAL (M.P.), INDIA

Urban Area Delineation Using Pattern Recognition Technique

Discerning sprawl factors of Shiraz city and how to make it livable

NETWORK ANALYSIS FOR URBAN EMERGENCY SERVICES IN SOLAPUR CITY, INDIA: A GEOINFORMATIC APPROACH

Land Use/Cover Changes & Modeling Urban Expansion of Nairobi City

Land Use Changes in Haryana Sub-Region of Chandigarh Periphery Controlled Area: A Spatio- Temporal Study

GEOSPATIAL TECHNOLOGY IN ENVIRONMENTAL IMPACT ASSESSMENTS RETROSPECTIVE.

West meets East: Monitoring and modeling urbanization in China Land Cover-Land Use Change Program Science Team Meeting April 3, 2012

Applications of GIS and Remote Sensing for Analysis of Urban Heat Island

Thematic Mapping in Siwani Area, District Bhiwani using Remote Sensing and Gis

IMAGE CLASSIFICATION TOOL FOR LAND USE / LAND COVER ANALYSIS: A COMPARATIVE STUDY OF MAXIMUM LIKELIHOOD AND MINIMUM DISTANCE METHOD

Land Restoration /Reclamation Monitoring of Opencast Coal Mines of WCL Based On Satellite Data for the Year 2009 CMPDI. A Miniratna Company

International Journal of Scientific Research and Reviews

Delineation of Groundwater Potential Zone on Brantas Groundwater Basin

THE REVISION OF 1:50000 TOPOGRAPHIC MAP OF ONITSHA METROPOLIS, ANAMBRA STATE, NIGERIA USING NIGERIASAT-1 IMAGERY

The Road to Data in Baltimore

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 7, No 1, 2016

Transcription:

URBANIZATION AND CHANGING GREEN SPACES IN INDIAN CITIES (CASE STUDY CITY OF PUNE) Padigala Bhaskar* Faculty of Sustainable Environment and Climate Change, Center for Environmental Planning & Technology, Ahmedabad-380009, India * Author for Correspondence ABSTRACT Urban green spaces are one of the most significant elements of any urban ecosystem, both due to its ecosystem dynamics and its essential contribution in well being of human race. However, it is ironic that despite of its immense significance, vegetation is undergoing destruction and degradation in the modern times due to rapid and haphazard urbanization in developing countries, making urban settlements major source of GHG emissions and at the same time making them more vulnerable to global environmental change impacts. Hence, landuse/landcover and green cover changes monitoring becomes very crucial in decision making and conserving green spaces in cities and at this stage significant contributions can be provided by remote sensing technologies. The study deals with changes with urban Land Use / Land Cover Changes using remote sensing technique. For this purpose Landsat ETM+ images of 1999 and 2009 was obtained for the study area. Land use / land cover change pattern was mapped by supervised classification with the maximum likelihood classification algorithm. Results showed that city s built up area has increased from 30.86% in 1999 to 48.50% in 2009, whereas barren & fallow land area has decreased considerably from 36.20% in 1999 to 21.80% in 2009. A total of 7.24 sq km. of combined vegetated (sparse and dense) area has been lost between 1999 and 2009. Key Words: Urbanization, Urban Green Spaces, Land Use / Land Cover Changes, Remote Sensing, Landsat INTRODUCTION With only 2% of the world population urbanized in 1800, global urban population reached 15% mark in 1900 and today almost 1,80,000 people are added to the world's urban population every day (Pitale, 2011). Hence, making urbanization an inevitable and yet favoured phenomenon for development of any nation on this planet. Urbanization is the spatial concentration of people and economic activity (Roberts and Kanaley, 2006) can simply be defined as the transformation of rural society into an urban society and is a result of socioeconomic and political growth leading to formation and expansion of urban agglomerations and city centres along with changing rural institutions, organizations and land use pattern. With increase in supporting factors like mechanisation of transport and goods production, better health services has led to the increase in the world population especially the urban population which consequently has increased the demand for dwelling places and hence leading to exponential increase in the growth of new cities and rapid expansion of the existing ones. Amidst demand exceeding the supply of dwellings and associated infrastructure resulting scenario what is being observed is that; all over the world especially in the developing countries it the haphazard urban development and urban sprawl along the urban amenities and infrastructure like roads and highways. The urban population in India at the beginning of 20th century was only 25.85 million constituting 10.84 per cent of India's population in 1901, which increased to 285.35 million comprising 27.78 per cent of total population in 2001 (Singh, 2006) with natural growth contributing about 60% and rest added by migration and expansion of cities (Sivaramakrishnan et al., 2005). India s urban population grew from 286 million in 2001 to 377 million in 2011 an increment of 91 million, which is larger than the rural 148

population increment of 90.5 million for the first time since independence (Bhagat, 2011) and is expected to hit figure of 550 million or 42% of the total population by 2030 (Roberts and Kanaley, 2006). Table 1: Table Showing Pattern of Urbanization in India Census Year Urban Population Percentage Urban Annual Exponential urban (in millions) growth rate 1961 78.94 17.97-1971 109.11 19.91 3.23 1981 159.46 23.34 3.79 1991 217.18 25.72 3.09 2001 286.12 27.86 2.75 2011 377.10 31.16 2.76 Source: Bhagat, 2011 With growing cities the demand of resources like water, land etc. has grown proportionally to the growing rate of the urban population. Hence, Cities are experiencing increasing signs of environmental stress, notably in the form of poor air quality, excessive noise, and traffic congestion (Ruangrit & Sokhi, 2004). At the same time, irregular and unsustainable extension of cities has caused destruction of urban green areas and resulted from increasing demand for land (Hassan-Ali Laghai et al., 2012). Urban green spaces are an integral part of any city landscape, providing city and its residents with numerous benefits both tangible and in-tangible (Gaodi et al., 2010), ecosystem services like pollutant sequestration and ambient temperature regulation etc. (Nowak et al, 2006) (Jim and Chen, 2008), social services and health (Grahn and Stigsdotter, 2003), and also economic services like tourism, increased property prices etc. (Chaudhry and Tewari, 2010) (Luttik, 2000). But it is ironic that despite realising the numerous benefits availed by green spaces in an urban ecosystem, yet vegetation is undergoing destruction and degradation in the modern times due to rapid and haphazard urbanization in developing countries, making urban settlements major source of GHG emissions and at the same time making them more vulnerable to global environmental change impacts. Hence, the main objective of this study was to analyse the urbanization trend and to find out reasons which are motivating modern cities to favour developmental models wherein urban green spaces are being treated as liability and hurdle in the growth of the city instead of an asset for overall social, environmental and economical growth and how this developmental trend will impact the cities especially in developing countries in future with threats like climate change and global warming adding up to the prevailing environmental issues. Study Area Pune City (Pune municipal corporation limit), lies between latitudes 18 25' N and 18 37' N and 73 44' E and 73 57' E longitudes covering an area of 243.84 sq km. Situated on the Deccan plateau and lies on leeward side of the Western Ghats and is at a height of 560m above the mean sea level. The establishment of the city goes back to the 8th century when it was a tiny agricultural city and under British rule in 1857 the total area for Pune was around 7.74 sq. Km, which increased to 138.98 sq. Km in 1958. Total area of Pune city has increased from 145.92 sq km to 243.84 sq km with addition of 23 villages to the old municipal limit in year 1999 (See table 2) (CDP, 2006). As per provisional census data for 2011, demographically Pune city is the 9 th largest city in India with a population of 3,115,431 (Census, 2011). Using remote sensing and entropy technique analysis (Shekhar, 2004) revealed that the Pune city is under highest rate of sprawl, and the sprawl is taking place along the national highway at the cost of adjacent agricultural, forestlands. City has lost 37.75% of cultivable land between the period of 1980 and 2001. Presently almost 70-80% of open/vacant/cultivable land has been brought under urban land use and open lands located inside the city and close to the outskirts of the city are being mostly converted into big townships, new colonies, Institutions, shopping complexes or apartment complexes (Desai et al, 2009). 149

Figure 1: Demographic Trend of Pune City (Source: Census of India, 1951-2011) Year Total Area (sq km.) Table 2: Morphological Development of Pune City Area Added (sq km.) Name of the Added Area 1857 7.74 South Shankarsheth road to Ambila Road, NE right Bank of Mutha River, East Wesley road to new Modikana near Nagzari 1889 9.86 2.12 Area between Shankarsheth road, Satara road and Golibar maidan 1890 18.04 8.17 Erandawana and Bhamburda village 1931 18.79 0.75 Parvati gaothan and area till Hingne 1935 19.05 0.26 Chaturshringi area 1958 138.98 27.02 Inclusion of 18 villages 1975 138.05-0.84 Exclusion of some part of Bhosari 1981 146.95 7.33 Inclusion of Sutarwadi 1983 146.11 0.014 Inclusion of survey no. 79 of Ghorpadi 1997 243.87 97.84 Inclusion of 23 villages Source: CDP, 2006 MATERIALS AND METHODS Data Acquisition and Image Processing For studying the temporal changes in land-use /land-cover and green spaces pattern of Pune city, survey of India (SOI) toposheets (Sheet Number 47 F 10,13,14,15 and 47 J 2; scale 1:50000 and year 1972) and Landsat 7 ETM+ satellite imagery of November month for year 1999 (WRS-2, Path- 147, Row 47) and 2009 (WRS -2, Path - 147, Row 47) with 30 m resolution were acquired. The following SOI toposheets on 1:50000 scales were used as base maps. Atmospheric corrections band combination manipulation, band stretching, and contrast adjustment image enhancement tools were employed on satellite images using remote sensing software s ERDAS IMAGINE 9.1, ArcGIS version 9.3 and ENVI 4.7. In the field, an exploratory survey of the study area was done using Garmin 12X-GPS, with reference to the 1: 50,000 scale SOI toposheets maps, and was used to delineate the ground control points all over the study area. With the help of GCP s and respective points on satellite images the satellite images of year 150

1999 and 2009 were georefrenced and the study area (Pune municipal corporation) boundary was delineated and digitized for further analysis in ERDAS IMAGINE 9.1 software. Visual Interpretation & NDVI Mapping Typically, false-colour composite images are employed in visual image interpretation, for this study Landsat 7 ETM + bands 4, 3, and 2 were combined to make FCC images for year 1999 and 2009,where band 4 represented the red, band 3 represented the green, and band 2 represented the blue portions of the electromagnetic spectrum. In this scheme of band combination type of FCC images, vegetation appears in different shades of red depending on the types and conditions of the vegetation, since it has a high reflectance in the NIR band (Crisp, 2001). Respectively, urban structures appear bluish white in colour whereas; dark shades of blue represent water bodies. NDVI is a good indicator of the ability for vegetation to absorb photosynthetically active radiation and has been widely used by researchers to estimate green biomass (Lillesand & Kiefer, 2004) (Wang et al, 2003). The calculation of Normalized Difference Vegetation Index (NDVI) is done using near-infrared (NIR) and visible (VIS) bands as follows (Mariappan, 2010). NDVI = (NIR VIS)/ (NIR+VIS)...Eq. (1) For this study band 4 and 3 for year 1999 and 2009 were selected and analysed using eq. (1), resultant obtained was the single band dataset with values ranging from between -1.0 and 1.0 (See fig 1), where lower values corresponds to correspond to built structures, barren areas of rock, sand. Moderate and high values represent sparse and dense vegetation (Esri, 2008). Image Classification & Accuracy Assessment Landsat 7 ETM+ satellite images were classified using supervised image classification with maximum likelihood algorithm (see fig 2). This Classification uses the training data by means of estimating means and variances of the classes, which are used to estimate probabilities and also consider the variability of brightness values in each class (Perumal & Bhaskaran, 2010). For this study, 75 training site were randomly selected and ERDAS Imagine 9.1 software was used to classify the satellite images for year 1999 and 2009 based on the landuse characteristics and spectral signature of the selected training sites. Satellite images of year 1999 and 2009 were later classified into five classes (level I classification) considered for the study are built-up land, barren & fallow land, water bodies, sparse (shrub, grassland, and agricultural land) & dense vegetation based on the supervised classification technique and land use/land cover areas were calculated using Arc GIS software. During field survey landuse characteristics of the training sites was also recorded which in later stages of the data analysis were used as ground truth observation points. These GTO points were used to assess the overall mapping accuracy using the error matrix. The overall accuracy of the output was calculated using following equation: Overall mapping Accuracy: D/ N x 100%...Eq. (2) Where: D = Total number of corrected cells as summed along the diagonal N = total number of cells in error matrix RESULTS AND DISCUSSION Pune is growing exponentially both in terms of spatial extent, economic activities and demography. Remote Sensing analysis of satellite images of Pune city (1999 and 2009) was used for land use/ land use changes assessment, analysis indicated the alarming rate and manner in which of urbanization and urban sprawl is occurring in Pune. Results (see table 1) showed that Pune s built up area has increased from 30.86% in 1999 to 48.50% in 2009 i.e. substantial increase of 43.01 sq km. of area in just last 10 years, on the other hand barren & fallow land area has decreased considerably from 36.20% in 1999 to 21.80 % in 2009. Major objective of the study was to analyse the changing trend of the urban green spaces in the city, it was noticed that both sparse and dense vegetation showed decrease in areas of 5.58 and 1.66 sq km. respectively in past 10 years. Thus, this analysis highlights that the city is under high pressure of urbanization and sprawl, and its 151

taking place by grabbing and converting existing habitat like agricultural, barren, fallow land & forestlands into built habitat and grey infrastructure. The overall mapping accuracy of the land use/ land cover map was 86.73%. Figure 2: Visual Interpretation & NDVI Mapping 152

Figure 3: Landuse/Landcover Changes in Pune City Presently city is experiencing large number of immigration from other regions of state and nation in search of economic opportunities, which is leading up to leapfrog increase in the city population 153

Landuse Class Table 3: Land Use/ Land Cover Changes in Pune City Area Area in Area in Area in in 2009 1999 (Sq. 2009 1999 (%) Km.) (Sq. Km.) (%) Area Difference (Sq. Km.) Area Difference (%) Water Bodies 1.47 1.20 3.58 2.93-0.66-0.27 Built Area 30.86 48.50 75.25 118.26 43.01 17.64 Barren & Fallow Land 36.20 21.80 88.27 53.16-35.11-14.40 Dense Vegetation 13.50 12.82 32.92 31.26-1.66-0.68 Sparse vegetation 17.97 15.68 43.82 38.23-5.58-2.29 Total Vegetation 31.47 28.50 76.74 69.49-7.24-2.97 Figure 4: Graphical Representation Landuse/Landcover Changes in Pune City 154

consequently escalating demand for allocation of residential sector in developmental plans and increased allocation of land and funds for associated infrastructure to facilitate such a large population. This scenario is leading into increased need for vacant land for both residential purpose and infrastructural services (roads etc). This urgent and growing need is taking its toll on the other habitats of the city, like urban green spaces, barren and fallow lands, agricultural lands are being converted into residential complexes and shopping malls, also encroachment of hill slopes and riverbeds by slums have led to degradation of both these habitats. Green cover is also being depleted not in forest only but also on other fronts, like, artificial plantations of exotic species etc this is leading not only degradation of local habitat but also disturbing the local biodiversity. Thus, clearly highlighting the issue of rapid urbanization due to exponential increase of population in urban centres leading to various environmental issues both at regional and collectively at global level. Despite all the rapid urbanization and land conversion into built up areas, one interesting and important observation was made i.e. the improvement of vegetation on few hills and hill slopes. This has been observed through NDVI mapping, visual assessment, and literature review and field survey of the study area. Satellite images for year 1999 showed maximum hill areas were under sparse vegetation, but by next 10 years these vegetation can be classified under dense vegetation. This analysis can be attributed to the fact that, during 1980s mass plantations and declarations of Parvati-Pachgaon and Bhamburda (Vetal hill) hills as forest parks by forest department, converted these hills which earlier were almost barren with scattered grass into with dense vegetation. Lastly it can be concluded from this study that, urbanization and urban sprawl is one of the most important and urgent issue which all developing countries like India are facing, and it needs to tackled holistically involving all stakeholders like general public, corporate sector and NGO s, not just the decision makers of any urban ecosystem. And to facilitate these conservative measurers remote sensing can play a vital role in both monitoring the landuse changes and sustainable urban planning. REFERENCES Arc GIS 9.2 Desktop Help (2008). Using the NDVI Process [Online], Environmental Systems Research Institute, Inc. Available: http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?topic Name=Using_the_ NDVI_process [Accessed 15 March 2012] Bhagat R B (2011). Emerging Pattern of Urbanisation in India. Economic & Political Weekly xlvi(34) 10-12. Centre for Remote Imaging, Sensing and Processing (2001). Interpretation of Optical Images [Online], Centre for Remote Imaging, Sensing and Processing. Available: http://www.crisp.nus.edu.sg/~research/tutorial/opt_int.htm [Accessed 10 March 2012] Chaudhry P and Tewari V P (2010). Role of public parks/gardens in attracting domestic tourists: An example from City Beautiful of India, TOURISMOS (5) 101-109. Desai C G, Patil M B, Mahale V D and Umrikar B (2009). Application of remote sensing and geographic information system to study land use / land cover changes: a case study of Pune Metropolis. Advances in Computational Research 1(2) 10-13. Gaodi X, Wenhua L, Xiao Y, Zhang B, Chunxia L, Kai A, Wang J, Kang X and Wang J (2010). Forest ecosystem services and their values in Beijing. Chinese Geographical Science 20 51-58. Grahn P and Stigsdotter U A (2003). Landscape planning and stress. Urban Forestry & Urban Greening 2 001-018. Jain H K (2012). Pune city Population. [online], Available: http://www.census2011.co.in /census/city/ 375-pune.html Jim C Y and Chen W Y (2008) Assessing the ecosystem service of air pollutant removal by urban trees in Guangzhou. Journal of Environmental Management 88 665-676. 155

Laghai H A and Bahmanpour H (2012). GIS Application in Urban Green space Per Capita Evaluation (Case study: City of Tehran). Annals of Biological Research 3(5) 2439-2446. Lillesand T M and Kiefer R W (2004). Remote Sensing and Image Interpretation, fifth edition. John Wiley & Sons, Inc., New York, New York. Luttik J (2000) The value of trees, water and open space as reflected by house prices in the Netherlands. Landscape and Urban Planning 48 161-167. Mariappan N (2010). Net Primary Productivity Estimation of Eastern Ghats using. International Journal of Geomatics and Geosciences 1(3) 406-413 Nowak D J, Crane D E and Stevens J C (2006). Air pollution removal by urban trees and shrubs in the United States. Urban Forestry & Urban Greening 4 115-123. Perumal K and Bhaskaran R (2010). Supervised Classification Performance of Multispectral Images. Journal Of Computing, Vol. 2, No. 2, 124-129 Pitale S (2011). Urbanisation in India: An Overview. Golden Research Thoughts 1(2) 1-4 Pune Municipal Corporation (2006) City Development Plan, Pune Municipal Corporation, Available: http://www.punecorporation.org/pmcwebn/pmccdp.aspx Roberts B and Kanaley T B (2006). Urbanization and Sustainability in Asia: Case studies of good practices, Asian Development Bank. Available: http://www.adb.org/publications/urbanization-andsustainability-asia-good-practice-approaches-urban-region-development Ruangrit V and Sokhi B S (2004) Remote Sensing And Gis For Urban Green Space Analysis A Case Study Of Jaipur City, Rajasthan. Institute of Town Planners, India Journal 1(2) 55-67. Shekhar S (2004). Urban Sprawl Assessment: Entropy Approach, GIS@ development, Vo. 8, No.5,43-48, Available: ttp://geospatialworld.net/index.php?option=com_content&view=article&id=20786&itemid 1819. Singh R B (2006). Sustainable Urban Development, first edition, Concept Publishing Company (p) Ltd, New Delhi, India 105 Sivaramakrishnan K, Kundu A, and Singh (2005). Handbook of Urbanization in India: An Analysis of Trends and Processes. Oxford University Press, New Delhi. Wang J, Rich P M and Price K P (2003). Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. International Journal of Remote Sensing 24(11) 2345 2364. 156