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An object-based image analysis approach for determining the pattern of urban growth in the first planned city of India

机译:基于对象的图像分析方法,用于确定印度第一个计划城市的城市增长模式

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The world is undergoing the most significant wave of urban growth in history. It is expected that by 2030 the number of people living in the cities will increase to about 5 billion. The rapid urbanization has led to complex problems, including a reduction in vegetation cover, the formation of the urban heat island effect, environmental pollution, reduced open space, etc. This study intends to explore the spatial patterns of urbanization and its impact on the environment in and around Chandigarh- the first planned city of India. Chandigarh was originally planned for a population of 5 lakh, but the city has expanded rapidly over the last four decades and faces problems common to other growing cities in India, including the proliferation of slums and squatter settlements. The areas adjacent to the city boundary also face similar issues. The study presents the methods and results of an object-based classification and post-classification change detection on multi-temporal Landsat data (1978-2017). The processed data was used as an input for object-based classification using image segmentation algorithm of eCognition Developer software. The results show that maximum urbanization has taken place in the last decade in the southern and north-western directions outside the city as a result of the development of an international airport, new sectors and approach roads on the vegetated areas. As a result, maximum changes could be seen in the class vegetation as it has been rapidly changed to built-up areas. The results of this kind of study may hold immense value for planning the urban sprawl areas where up-to-date information is lacking because of the rapid pace of development.
机译:世界正经历着历史上最重要的城市增长浪潮。预计到2030年,城市居民人数将增加到约50亿。快速的城市化带来了复杂的问题,包括植被覆盖减少,城市热岛效应的形成,环境污染,开放空间的减少等。本研究旨在探讨城市化的空间格局及其对环境的影响。在昌迪加尔及其周围地区-印度第一个计划中的城市。昌迪加尔原计划人口为50万,但该市在过去的40年中迅速发展,面临着印度其他发展中城市常见的问题,包括贫民窟和棚户区的扩散。与城市边界相邻的区域也面临类似的问题。该研究提出了基于对象的分类和分类后变化检测的方法和结果,该方法基于多时态Landsat数据(1978-2017年)。使用eCognition Developer软件的图像分割算法,将处理后的数据用作基于对象的分类的输入。结果表明,过去十年来,由于国际机场的发展,植被带上的新部门和道路的发展,城市外的南部和西北方向实现了最大程度的城市化。结果,由于已经迅速地改变为建成区,因此在类别植被中可以看到最大的变化。这种研究的结果对于规划城市蔓延地区可能具有巨大的价值,这些城市由于发展速度快而缺乏最新信息。

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