利用卫星图像监测城市化进程的云解决方案

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Ion-Dorinel Filip , Cristian Cune , Florin Pop
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引用次数: 0

摘要

随着越来越多的人希望通过迁移到城市地区来提高生活质量,大量可用的卫星数据以及人们对城市化研究日益浓厚的兴趣促使本文提出了一种更好地监督城市化进程的方法。该项目对环境研究人员或希望做出明智决策的市民特别有用。该项目利用多光谱卫星图像云服务 Sentinel Hub 访问 Sentinel 2 数据,自动检测罗马尼亚城市环境的变化。Sentinel Hub 的光谱波段描述了表面的反射特性,可用于计算光谱指数,从而突出卫星图像中的模式。本文分析了成功绘制建筑密集区地图的两个城市指数和评估城市化地区植被程度的植被指数。它采用不同的方法来增强每种指数,并在一个城市快速扩张的城镇中对其性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud-based solution for urbanization monitoring using satellite images
Motivated by the large amount of available satellite data and increasing interest in the study of urbanization, this paper presents a way for better supervision of urbanization, as more and more people are looking to increase their quality of life by migrating to urban areas. This project is particularly useful for environmental researchers or citizens who are looking to make informed decisions. This project utilizes Sentinel Hub, a multi-spectral satellite imagery cloud service, to access Sentinel 2 data to detect changes in Romania’s urban environment automatically. Sentinel Hub’s spectral bands, which describe the reflectance properties of a surface, are used to compute spectral indices that highlight patterns in satellite images. The paper analyzes two urban indices that successfully map build-up regions and a vegetation index that assesses the degree of vegetation in an urbanized area. It employs different methods to enhance each index and evaluates its performance in a town that has seen rapid urban expansion.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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