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

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

Abstract: About the Author:

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

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

Analysis of Land Use And Land Cover Changes Using Gis, Rs And Determination of Deforestation Factors Using Unsupervised Classification And Clustering

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

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

Monitoring of Forest Cover Change in Sundarban mangrove forest using Remote sensing and GIS

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

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

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

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 Intellectual Advancements and Research in Engineering Computations

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

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

7.1 INTRODUCTION 7.2 OBJECTIVE

Environmental Impact Assessment Land Use and Land Cover CISMHE 7.1 INTRODUCTION

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

Change Detection of Land-use and Land-cover of Shirpur Tehsil: A Spatio-Temporal Analysis Yogesh Mahajan 1, Bharat Patil 2, Sanjay Patil 3

AGRY 545/ASM 591R. Remote Sensing of Land Resources. Fall Semester Course Syllabus

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

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

CHANGES IN VIJAYAWADA CITY BY REMOTE SENSING AND GIS

Spatio-Temporal changes of Land use/land cover of Pindrangi Village Using High Resolution Satellite Imagery

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

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

Quantifying Land Use/Cover Dynamics of Nainital Town (India) Using Remote Sensing and GIS Techniques

LAND CAPABILITY CLASSIFICATION FOR INTEGRATED WATERSHED DEVELOPMENT BY APPLYING REMOTE SENSING AND GIS TECHNIQUES

Identification of Land use and Land cover Changes using Remote Sensing and GIS

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

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

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

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

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

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

International Journal of Scientific Research and Reviews

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

Monitoring Vegetation Growth of Spectrally Landsat Satellite Imagery ETM+ 7 & TM 5 for Western Region of Iraq by Using Remote Sensing Techniques.

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

GROUNDWATER CONFIGURATION IN THE UPPER CATCHMENT OF MEGHADRIGEDDA RESERVOIR, VISAKHAPATNAM DISTRICT, ANDHRA PRADESH

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

A Small Migrating Herd. Mapping Wildlife Distribution 1. Mapping Wildlife Distribution 2. Conservation & Reserve Management

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

American International Journal of Research in Humanities, Arts and Social Sciences

Impact of Dam and Weirs on Cross-Sectional Characteristics of Urmodi Channel, Maharashtra: An Approach to Geoinformatics

Geospatial technology for land cover analysis

HIGH RESOLUTION SATELLITE DATA FOR LAND USE/LAND COVER MAPPING IN ROHTAK DISTRICT HARYANA, INDIA

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

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

CHANGE DETECTION USING REMOTE SENSING- LAND COVER CHANGE ANALYSIS OF THE TEBA CATCHMENT IN SPAIN (A CASE STUDY)

Dr. S.SURIYA. Assistant professor. Department of Civil Engineering. B. S. Abdur Rahman University. Chennai

International Journal of Modern Trends in Engineering and Research e-issn No.: , Date: April, 2016

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

Accuracy Assessment of Land Use & Land Cover Classification (LU/LC) Case study of Shomadi area- Renk County-Upper Nile State, South Sudan

VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA USING REMOTE SENSIGN AND GIS TECHNIQUES

Progress and Land-Use Characteristics of Urban Sprawl in Busan Metropolitan City using Remote sensing and GIS

RESEARCH METHODOLOGY

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

VILLAGE INFORMATION SYSTEM (V.I.S) FOR WATERSHED MANAGEMENT IN THE NORTH AHMADNAGAR DISTRICT, MAHARASHTRA

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

Summary Description Municipality of Anchorage. Anchorage Coastal Resource Atlas Project

Urban Area Delineation Using Pattern Recognition Technique

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

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

Wastelands Analysis and Mapping of Bhiwani District, Haryana

Overview of Remote Sensing in Natural Resources Mapping

An Investigation into Land Use and Land Cover Change through Object Based Classification (A Case Study of South Haldwani, Uttarakhand, India)

LAND USE/LAND COVER CLASSIFICATION AND ACCURACY ASSESSMENT USING SATELLITE DATA - A CASE STUDY OF BHIND DISTRICT, MADHYA PRADESH

Table 4.1 Images used for the Study. Spatial Resolution (Meter) Resolution (Bits) 30 (For 6th band 120)

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

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

Landuse Pattern Analysis Using Remote Sensing: A Case Study of Mau District, India

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

Land Use and Land Cover Detection by Different Classification Systems using Remotely Sensed Data of Kuala Tiga, Tanah Merah Kelantan, Malaysia

We greatly appreciate the review of the manuscript by the anonymous referee#3. We hereby put forth the clarifications as follows.

Change Detection Methods Using Band Ratio and Raster to Vector Transform

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

Advanced Image Analysis in Disaster Response

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

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

Urban Growth Analysis: Calculating Metrics to Quantify Urban Sprawl

Journal of Asian Scientific Research STUDYING OF THE ENVIRONMENTAL CHANGES IN MARSH AREA USING LANDSAT SATELLITE IMAGES

Changing Urban Built-up Area of Sangli-Miraj and Kupwad Municipal Corporation, Maharashtra (India): Using Satellite Data and GIS

Monitoring and Change Detection along the Eastern Side of Qena Bend, Nile Valley, Egypt Using GIS and Remote Sensing

Coastal Landuse Change Detection Using Remote Sensing Technique: Case Study in Banten Bay, West Java Island, Indonesia

LAND SUITABILITY STUDY IN LAND DEGRADED AREA DUE TO MINING IN DHANBAD DISTRICT, JHARKHAND.

Yaneev Golombek, GISP. Merrick/McLaughlin. ESRI International User. July 9, Engineering Architecture Design-Build Surveying GeoSpatial Solutions

Modeling Urban Land Cover Growth Dynamics Based on Land Change Modeler (LCM) Using Remote Sensing: A Case Study of Gurgaon, India

Flood hazard mapping in Urban Council limit, Vavuniya District, Sri Lanka- A GIS approach

Abstract. 1. Introduction. 2. Materials and Methods. 2.1 Study Area

Modeling the Change of Mangrove Forests in Irrawaddy Delta, South Myanmar

Change Detection Across Geographical System of Land using High Resolution Satellite Imagery

International Journal of Scientific & Engineering Research, Volume 3, Issue 11, November ISSN

This is trial version

Multifunctional theory in agricultural land use planning case study

RESULT. 4.1 Temporal Land use / Land Cover (LULC) inventory and Change Analysis

CHAPTER V LAND USE / LAND COVER AND SITE SUITABILITY ANALYSIS

Remote Sensing and GIS Techniques for Monitoring Industrial Wastes for Baghdad City

Land Use and Land Cover Mapping and Change Detection in Jind District of Haryana Using Multi-Temporal Satellite Data

A NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) TIME-SERIES OF IDLE AGRICULTURE LANDS: A PRELIMINARY STUDY

Transcription:

IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) e-issn: 2321 0990, p-issn: 2321 0982.Volume 3, Issue 6 Ver. II (Nov. - Dec. 2015), PP 55-60 www.iosrjournals.org Application of Remote Sensing Techniques for Change Detection in Land Use/ Land Cover of Ratnagiri District, Maharashtra Balu L. Rathod 1, Jagdish B. Sapkale 2 1 Assistant Professor, Department of Geography, Kankavli College, Kankavli, District- Sindhudurg, Maharashtra, India (Ph.D. Scholar, Department of Geography, Shivaji University, Kolhapur) 2 Assistant Professor, Department of Geography, Shivaji University, Kolhapur, Maharashtra, India. Abstract: Remote sensing data and imageries have been used for the assessment and monitoring of land use and land cover changes, so that available resources of any region may be used properly. In the coastal areas of Maharashtra, catastrophic and human interventions are highly influencing on coastal resources. Now there is an urgent need to use the sustainable resources by reducing the rate of degradation. The present study is an attempt to analysis the change detection in the major aspects of land use and land cover in the Ratnagiri district of Maharashtra. Satellite images of the years 1989, 1999 and 2009 have been obtained from Global Land Cover Facility (GLCF) & NRSC and used for the analysis of periodic changes in LULC of Ratnagiri. Keywords: LISS-III, LULC, GLCF, Change detection, Degradation, I. Introduction The Ratnagiri district covers 8,16,424 hectares of the total area of the district having nine tehsils (fig 1). Most of the part is covered by forest with undulating landscape. Various resources are available in the district, but needs proper management. Therefore remote sensing techniques for monitoring the natural resources is the proper way that can also give information about the vulnerable sites of degradation from time to time. In the past three decades, there has been a growing trend in the development of the change detection techniques using remote sensing data. Remote Sensing (RS) and Geographical Information System (GIS) are now providing new tools for ecosystem management. The data is collected by remote sensing, enables the synoptic analysis of earth system functions; also change at local, regional and global scale over times. Such data also provides an important link between intensive, localized ecological research and regional, national and international conservation and management of biological diversity (Wilkie and Finn, 1996 ; Lillesand et al., 2008). Land use is defined as the use of land for economic purpose by human beings. The land use includes agricultural land, built-up land, recreational area, wildlife management area etc. Land cover refers to the physical characteristics of earth s surface, distribution of vegetation, water, soil and other physical features of the land including those created solely by human activities, e.g. settlement. (Anderson, 1976). Figure : 1 Tehsil wise Area of Ratnagiri district DOI: 10.9790/0990-03625560 www.iosrjournals.org 55 Page

Land use refers to the purpose of land reserves, for example, recreation, wildlife habitat or agriculture. Land use applications involve both baseline mapping and subsequent monitoring, since timely information is required to know the current quantity of land and the type of its usage and to identify the land use changes from year to year. Satellite remote sensing data i.e. images and soft data is the most common data source for change detection, quantification, and mapping of LULC patterns and variations can be easily detected due to its repetitive data acquisition, digital format suitable for computer processing, and accurate georeferencing procedures (Anderson, 1976; Chen, Vierling, & Deering, 2005; Jensen, 2005; ). Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. One of the major applications of remotely-sensed data obtained from Earth-orbiting satellites is change detection because of repetitive coverage at short intervals and consistent image quality (Anderson, 1976). Amount of degradation can be easily accessed using these advances tools and techniques ( Sapkale & Rathod, 2014; 2015). II. Data And Methods Land use and land cover classification through supervised classification methods by using LANDSAT, TM, Satellite image of Ratnagiri Coastal Resource for the years 1989 has been performed/ done. LANDSAT, ETM, Satellite image of Ratnagiri Coastal Resource 1999 and LISS-III Satellite image of Ratnagiri Coastal Resource 2009 were also used to carry out change detection analysis. Satellite images of the years 1989, 1999 and 2009 have been obtained from Global Land Cover Facility (GLCF) & NRSC. The resolution was 30 meters for Landsat data and 23.5 m. LISS III image. During analysis 4-5% error occurs due to variation in the resolution of the images. The Land Use/ Land Cover classification has been performed through supervised classification method using Digital Image Processing software. Erdas Imagine and ArcGIS software are powerful tools for extracting the land use and land cover layers from Ratnagiri Coastal Resource. III. Discussions And Results LAND USE / LAND COVER MAPPING AND CHANGE ANALYSIS: The land use and land cover classes includes agricultural land, forest/vegetation, built up area, water bodies and fallow land. It is the broad classification of the land use and land cover of study area. Table No. 1 LAND USE / LAND COVER CLASSIFICATION IMAGE-YEAR-1989 Sr. No Class Name Area in (Approx) Area in Percentage% 1 Built-up 816.433 0.10 2 Cropped 58864.819 7.21 3 Open land 165409.325 20.26 4 Dense forest 26289.142 3.22 5 Sparse forest/trees 518598.241 63.52 6 Water body 16981.806 2.08 7 Barren land 29146.658 3.57 Total Area 816106.424 100 CROPPED AREA: The cropped land may be defined broadly as land that is used primarily for production of food and fodder. Cropped land occupies sizeable area. Rice, Vegetables are the major crops in this region. In the year 1989 the cropped land is covered by 7.21% of the total area under these categories. In 1999 about 11.65% of the total area is under cropped in the region. In 2009 about 13.47% of the total area is under cropped. In Ratnagiri district the cropped area has increased by 1.82% in 20 years from 1989 to 2009. There is a positive change in agricultural land in these 20 years (table no. 1 to 5). BUILTUP AREA :The built-up land cover is reported from Ratnagiri district in the year of 1989 is 0.10%. The total area covered by built-up land in the years 1999 and 2009 is 0.59% and 2.46% respectively. It can be observed that in these 20 years, from 1989 to 2009 the built-up area has increased by 1.87%. There is a positive change in built-up land in these 20 years. It has also seen that an analytical result for built-up area in the district gives the lower values, because most of the region is occupied by undulating topography, the settlements in the village areas have covered by large size trees-probably mango trees. DOI: 10.9790/0990-03625560 www.iosrjournals.org 56 Page

Source:- Based on Global Land Cover Facility (GLCF) DOI: 10.9790/0990-03625560 www.iosrjournals.org 57 Page

DOI: 10.9790/0990-03625560 www.iosrjournals.org 58 Page

Table No. 2 LAND USE / LAND COVER CLASSIFICATION IMAGE-YEAR-1999 Sr. No Class Name Area in Area in Percentage% 1 Builtup 4816.954 0.59 2 Cropped 95114.444 11.65 3 Open land 187126.443 22.92 4 Dense forest 67110.792 8.22 5 Sparse forest/trees 433770.852 53.13 6 Water body 12899.641 1.58 7 Barren land 15267.297 1.87 Total Area 816106.424 100 Table No. 3 LAND USE / LAND COVER CLASSIFICATION IMAGE-YEAR-2009 Sr. No Class Name Area in Area in Percentage% 1 Builtup 20002.608 2.45 2 Cropped 109728.595 13.44 3 Open land 91032.279 11.15 4 Dense forest 50782.132 6.22 5 Sparse forest/trees 507821.326 62.20 6 Water body 10531.985 1.29 7 Barren land 26207.493 3.21 Total Area 816106.418 100 OPEN LAND AREA : In the Ratnagiri district some area covered with open land. The open land refers to the land, may be uncultivated and unused land. In the year 1989, the open land has occupied 22.92% of total area of region. From 1999 to 2009, it is 22.92% and 11.17% respectively. In Ratnagiri district the open land area has decreased by -11.75% in 20 years from 1989 to 2009. There is a negative change in open land area in these 20 years. DENSE FOREST AREA : The area under forest includes the land classified as forest under any legal enactment dealing with forest or administrated for forest, whether state-owned or private, and whether wooded or maintained as potential forest land. The areas where crops are raised in the forests and grazing lands or areas open for grazing within the forests are included under forest area (National Commission on Agriculture, 1976). The present Ratnagiri district is located in coastal and hilly region with uneven topography covered by dense vegetation. Most of the area is under dense forests. Table No. 4 LAND USE/ LAND COVER CHANGE FROM 1989 TO 1999 Year-1989 Year-1999 Difference Change (1989 to 1999) Sr. Class Name Area in Area in % Area in Area in % Area in Area in % No 1 Builtup 816.433 0.10 4816.954 0.59 4000.522 0.49 2 Cropped 58864.819 7.21 95114.444 11.65 36249.625 4.44 3 Open land 165409.325 20.26 187126.443 22.92 21717.118 2.66 4 Dense forest 26289.142 3.22 67110.792 8.22 40821.65 5.00 5 Sparse forest* 518598.241 63.52 433770.852 53.13-84827.38-10.39 6 Water body 16981.806 2.08 12899.641 1.58-4082.165-0.5 7 Barren land 29146.658 3.57 15267.297 1.87-13879.36-1.7 Total Area 816106.424 100 816106.424 100 * Scattered trees with different species and bushes/shrubs are included. DOI: 10.9790/0990-03625560 www.iosrjournals.org 59 Page

Table No. 5 LAND USE/ LAND COVER CHANGE FROM 1999 TO 2009 Year-1999 Year-2009 Difference Change (1999 to 2009) Sr. Class Name Area in Area in % Area in Area in Area in Area in % No % 1 Builtup 4816.954 0.59 20002.608 2.46 15185.654 1.87 2 Cropped 95114.444 11.65 109728.595 13.47 14614.151 1.82 3 Open land 187126.443 22.92 91032.279 11.17-96094.164-11.75 4 Dense forest 67110.792 8.22 50782.132 6.23-16328.66-1.99 5 Sparse forest 433770.852 53.13 507821.326 62.13 74050.474 9.00 6 Water body 12899.641 1.58 10531.985 1.50-2367.656-0.08 7 Barren land 15267.297 1.87 26207.493 3.01 10940.196 1.14 Total Area 816106.424 100 816106.418 100 In 1989, the dense forest area was 3.22% of the total area in study region. In 1999 and 2009 the area of Ratnagiri district under dense forest area was 8.22% and 6.23% respectively. It can be observed that in these 20 years, almost 1.99% dense forest area cover has decreased in the study region. There is a negative change in dense forest area in two decades. SPARSE FOREST AREA: The Ratnagiri district is located in coastal and hilly region with uneven topography covered by sparse vegetation. Most of the area is under sparse forests with scattered trees of different species like mango and coconut, also accounted with bushes and shrubs. In 1989, the sparse forests cover was 63.52% of the total area in the study region. In 1999 and 2009 the area of Ratnagiri district under sparse forests was 53.13% and 62.13% respectively. It is observed that in these 20 years, almost 9.00% sparse forests area cover has increased in the study region. There is a positive change in sparse forests area cover in last two decades. Mango plantations on the slope of the hills are also one of the reasons for increasing the area of this category. WATER BODY: Water bodies include estuary, wells, lakes, ponds, river and stream. The percentage of water bodies in the region is 2.08% of the total area in the year 1989. The total area covered by water bodies in the years 1999 and 2009 was 1.58% and 1.50% respectively. The area under water bodies in Ratnagiri district has decreased from 1989 to 2009 by -0.08%. BARREN LAND: The Barren land is reported 3.57% in the year 1989. The total area covered by barren land in the years 1999 and 2009 is 1.87% and 3.01% respectively. In Ratnagiri district the area under barren land has increased by 1.14% in 20 years i.e. from 1989 to 2009. There is a positive change in barren land area in these 20 years. IV. Conclusion Updated information about land use and land cover of the present study area will help to overcome the problems in connection with the agricultural systems, forest cover, various infrastructures etc. Therefore it has suggested that, Remote sensing, GIS, GPS techniques should be used continuously for the management and development in the study area. The analytical results of the present research work, using TM and LISS III images have provided the major categories of the Land use and land cover of Ratnagiri district, still with reducing the errors, micro level study with analyzing sub categories of LULC may be suggested for accurate results. References [1] Anderson, James Richard. A land use and land cover classification system for use with remote sensor data. Vol. 964. US Government Printing Office, 1976. [2] Chen, X., Vierling, L., & Deering, D., A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98(1), 63-79, 2005. [3] Jensen, J. R. (2005). Introductory digital image processing: A remote sensing perspective (3rd Edn). Upper Saddle River, NJ: Prentice-Hall, 2005. [4] Lillesand, M. T., KIefer, W. R. and Chipman, N, J. (2008). : Remote sensing and image interpretation (6th ed). John Wiley and Sons, Inc, New York.. [5] Rathod, B.L, (2015), Coastal Resource Management Using Remote Sensing and GIS Techniques: A Case Study of Ratnagiri District, Maharashtra, (2015), Unpublished Ph.D. Dissertation. [6] Rathod, B. L., Sapkale, J.B., Status of Agriculture in Coastal Villages of Ratnagiri, Maharashtra.,.,International Journal of Scientific and Engineering Research, (IJSER), 6(9), 1556-1559 2015. [7] Sapkale, J.B., Rathod, B. L., Kharlands-An Agrarian Disaster in Coastal Areas of Southern Ratnagiri, Maharashtra: A Study Using Remote Sensing and GIS, International Refereed Journal of Engineering and Science (IRJES), 3(6), 71-78, 2014. [8] Socio-economic Review and Statistical Abstract Ratnagiri District 1980-2013. [9] Wilkie, D.S. and Finn, J.T. : Remote Sensing Imagery for Natural Resources Monitoring. Columbia University Press, New York., P.P.- 295. 1996. DOI: 10.9790/0990-03625560 www.iosrjournals.org 60 Page