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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城市成长模式

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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:世界正在经历历史上最重要的城市增长浪潮。预计到2030年,住在城市的人数将增加到约50亿。快速城市化导致了复杂的问题,包括降低植被覆盖,城市热岛效果的形成,环境污染,降低空间等。本研究打算探讨城市化的空间模式及其对环境的影响昌迪加尔及其周围地区 - 印度第一个计划。 Chandigarh最初计划为5万人口,但该市在过去的四十年里迅速扩大,并面临印度其他不断增长的城市的常见问题,包括贫民窟和寮屋居所的扩散。与城市边界相邻的区域也面临着类似的问题。该研究提出了对多时间LANDSAT数据(1978-2017)的基于对象的分类和分类后变更检测的方法和结果。处理后的数据用作基于对象的分类的输入,使用了Ecognition Developer软件的图像分割算法。结果表明,由于国际机场,新行业和植被领域的方法道路,城市南部和西北方向的最大十年的最大城市化发生了最大的城市化。因此,在类植被中可以看到最大变化,因为它已经迅速变为内置区域。这种研究的结果可能会持有规划城市蔓延地区的巨大价值,因为发展速度迅速缺乏最新信息。

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