遥感课程的设计与方法

Josep Sitjar Suñer
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引用次数: 0

摘要

遥感为地理信息系统专家提供了将有用而有力的信息整合到他们的分析中的可能性。由于在地理空间行业工作的任何人都需要至少具备遥感原理和方法的基本知识,因此我们将这一能力作为地理信息系统分析在线硕士学位课程的必修科目。这门遥感课程的主题是根据我们在该领域的经验选择的,同时也得到了GI2NK和EO4GEO项目开发的知识体系等工具的支持。这些应用程序对于任何开始创建新课程的人都非常有用,因为它们考虑了与不同部门相关的专家的建议:从大学到私营公司,也从公共部门。本课程以实际工作为基础,但由于本课程是介绍性的,而且大多数学生对遥感的原理并不熟悉,因此有必要开始了解电磁辐射、电磁波谱、光谱特征、波段等基本概念。之后,他们准备开始为特定项目搜索最佳图像,执行图像增强和校正,计算指数并应用监督和无监督分类。在课程中,鼓励学生使用开源软件开发必修课和选修课。大多数教程都是基于QuantumGIS及其一些主要扩展来处理光栅数据和遥感图像,但也有基于GRASS Gis和SNAP的教程。然而,学生有完全的自由选择任何可用的软件(开源或非开源)来执行强制性活动,导师也愿意为他们解决疑问。最后,该模块设计用于哥白尼和陆地卫星图像的实践。使用这些免费的目录提供了免费分析世界各地现象的可能性,它使学生能够更经济地开展自己的项目。此外,陆地卫星图像的历史序列对于评估长时间的变化非常有用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and methodology for a remote sensing course
Remote sensing offers Geographic Information Systems specialists the possibility of integrating useful and powerful information into their analyses. As at least a basic knowledge of remote sensing principles and methodologies are desirable for anyone working in the geospatial industry, we include this competence as a mandatory subject in the curricula of our online master’s degree in GIS analysis. The topics of this remote sensing course have been selected based on our experience in the sector, but also with the support of tools like the body of knowledge developed by the GI2NK and EO4GEO projects. These applications can be very useful for anyone starting with the creation of new courses, as they take into consideration the recommendations of experts related to different sectors: from university to private companies, and also from the public sector. The course is fundamentally based on practical work, but since it is introductory and most of the students are not familiar with the principles of remote sensing, it is essential for them to start understanding basic concepts such as electromagnetic radiation, electromagnetic spectrum, spectral signature, bands, etc. After that, they are prepared to start searching the best images for a specific project, perform image enhancements and corrections, compute indices and apply supervised and unsupervised classifications. During the course, students are encouraged to use open-source software to develop the mandatory activities and the optional ones. Most of the tutorials are based on QuantumGIS and some of its main extensions to work with raster data and remote sensing images, but there are also tutorials based on GRASS Gis and SNAP. Nevertheless, students have total freedom to choose any available software (open-source or not) to perform the mandatory activities, and the tutor is open to resolving doubts about them. Finally, the module is designed to practice with Copernicus and Landsat images. The use of these free catalogues offers the possibility to analyse phenomena from all over the world without cost, and it empowers students to carry out their own projects more economically. Also, the historical series of Landsat Images is very useful to evaluate changes over long periods of time
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