SATELLITE IMAGE PROCESSING METHODS TO IDENTIFY GREENSCAPES BUILDINGS AND WATER SHEDS FOR SMART CITY PLANNING USING IMPROVED K-MEANS METHODOLOGY

Abstract

Urban areas in the world accommodates more than half of the population of the Earth now lives in urban areas. There a strong need to rethink in city planning in efficient and modern ways for automatic decision makers. The sustainable development of urban areas is a challenge to be resolved and requires new, efficient, and user-friendly technologies and services. A well planned smart city to have planned urban area which could create sustainable economic development and improvement in quality of life, economy, mobility, environment, people, living and government. Even a good small change would have big impact on these areas, improving the well-being of its citizens.This paper is the outcome of the research made in the direction of finding optimization solution for the urban planner to give quality in reaching excellence in allocation of these key areas that can be achieved through computerized pattern matching for better utilization of urban landscapes. This technique is also used for identification of green landscapes and watersheds using satellite images. The objective is to integrate smart devices and gadgets for planning which would enrich city infrastructure and computer vision techniques may have an important role in city planning.