Paper Title
Impact Of Urban Growth On Vegetation Cover In World Heritage City Of Kandy, Sri Lanka: An Assessment Using Gis And Rs Techniques

The rapid urban growth occurring in developing countries today is mostly spontaneous and causes to create many environmental problems that demand urgent attention. The paper attempts to examine the impact of urban growth on vegetation cover in Kandy city, Sri Lanka with GIS and RS techniques. Measuring the built up area expansion, detecting changes of natural vegetation cover, and identifying how the correlation between urban growth and vegetation cover has changed over time are the objectives of this paper. The paper uses Urban Index (UI), Normalized Difference Vegetation Index (NDVI) and linear regression technique to achieve the above objectives. Depending on the data availability Landsat satellite images in 1980, 1994, 2003, 2007 and 2015 with moderate resolution were obtained from USGS server. Image processing and related mapping were done with Arc GIS 10.2 software. Microsoft Excel 2007 was used to perform regression analysis. As results reveal, during the corresponding period built up area of the city has expanded significantly while vegetation cover in the city has adversely been impacted. Only the very high vegetation category remains unchanged since its recognition as reserved forest while all the other categories of forest in the city under the threat of reduction. Correlation analysis which was performed to seek what extent these two phenomena are correlated shows that a crucial negative correlation is present between UI-NDVI. Correlation between UI and NDVI has gradually increased and it was much strong in 2015 indicating the problem of losing forested areas. This indicates that the city is losing its greenness due to modification of land surfaces. If necessary actions are not implemented in this connection many environmental problems will arise in near future and city will be uncomfortable place for living and working for the city uses. Therefore, this study strongly recommends to take necessary actions to control the problem of decrease the greener areas in the city. Keywords: Kandy City, Landsat Images, UI, NDVI, Linear Regression Model