城市规划遥感数据评价。基于多光谱和高光谱数据的应用实例

G. Abbate, L. Fiumi, C. De Lorenzo, R. Vintilă
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引用次数: 14

摘要

大多数城市规划者和管理人员已经认识到,城市地区需要根据资源可持续性标准进行仔细的设计/重新设计和深思熟虑的管理。涉及的方面包括保护自然和人力资源、明智的能源和水管理、减少空气污染和交通管制、人口的健康和福祉、保护文化遗产、住宅区的舒适标准、工业生产、工艺保存等。需要先进的领土规划/管理工具。决策应该基于“适当的”信息。数据集必须准确、客观、可靠、全面并始终保持最新。必须从所有可用信息中提取特定数据/信息,但必须为特定目的收集某些数据/信息。本文是为罗马市开展GIS(地理信息系统)和DSS(决策支持系统)的更广泛研究工作的一部分。专题地图是根据精确的地理编码遥感图像绘制的,用于绘制“城市规划指导表”。一个多学科团队在这个范围内开展协调工作。本文介绍了基于不同卫星(ESA-ERS, Landsat, SPOT)的多光谱数据和来自飞机的MIVIS高光谱数据的集成,在罗马市的应用实例和结果。土地覆被类型、地表组成和形态高度复杂,与城市化地区发生的各种现象(物理、化学、社会、经济等)直接相关。人们的注意力集中在气候、城市元素、模式和材料上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of remote sensing data for urban planning. Applicative examples by means of multispectral and hyperspectral data
Most city planners and managers already recognize that urban areas require careful design/re-design and considered management, based on resource sustainability criteria. Involved aspects range from protection of natural and human resources, wise energy and water management, reduction of air pollution and traffic control, health and well-being of population, safeguard of cultural heritage, comfort standards in residential districts, industrial production, craftsmanship preservation, etc. Advanced instruments for territorial planning/management are required. Decisions should be based on "proper" information. Data set has to be accurate, objective, reliable, comprehensive and always up-to-date. Specific data/information have to be extracted out of all available information but some data/information have to be collected specifically for the purpose. This article is part of a wider research effort to carry out GIS (geographical information system) and a DSS (decision support system) for the city of Rome. Thematic maps are derived from accurately geo-coded remotely sensed images and used to draw "Guidance Tables for Urban Planning." A multidisciplinary team carries out coordinated work to this scope. Application examples and results for the city of Rome are illustrated in this paper, based on integration of multispectral data from various satellites (ESA-ERS, Landsat, SPOT) and MIVIS hyperspectral data from aircraft. High complexity has been observed in land cover types, surface composition and morphology, which is directly interrelated with all phenomena taking in urbanized areas (i.e. physical, chemical, social, economic, etc.). Attention has been focused on climate, urban elements, patterns and materials.
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