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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-gis-understand-the-theory-and-practice/
课程评论：没有评论
课程名称：地理信息系统中的机器学习：理解理论与实践 课程简介： 你是否渴望运用机器学习技术进行地理空间分析，但又不知道从何开始？欢迎参加我们的课程，旨在让你掌握机器学习在地理信息系统（GIS）和遥感领域的理论和实践知识。无论你对土地利用和土地覆盖制图、分类还是基于对象的图像分析感兴趣，该课程都能满足你的需求。 课程亮点： - 深入理解机器学习在GIS和遥感中的应用理论与实践 - 应用机器学习算法，包括随机森林、支持向量机和决策树 - 完成一个完整的GIS项目，进行动手演练 - 利用云计算和大数据分析，使用Google Earth Engine - 适合各个领域的专业人士 - 提供逐步指导和可下载的实用材料 课程重点： 该综合性课程探讨机器学习在地理空间分析中的应用，结合理论与实践。完成课程后，你将具备运用机器学习进行多种地理空间任务的知识和信心。 你将学习： - 安装开源GIS软件（QGIS和OTB工具箱）及其配置 - 熟悉QGIS软件界面，包括组件和插件 - 使用多种机器学习算法（如随机森林、支持向量机、决策树）在QGIS中分类卫星图像 - 在QGIS中进行图像分割 - 使用云计算平台Google Earth Engine准备你的第一幅土地覆盖图 适合人群： 该课程面向广泛的受众，包括地理学家、程序员、社会科学家、地质学家以及任何在各自领域使用地图的专业人士。如果你预见到需要使用先进的机器学习算法进行土地覆盖和土地利用制图的任务，这门课程将赋予你应对这些地理空间挑战的技能。 课程包含： 获得逐步指导、实用材料、数据集及QGIS和Google Earth Engine的动手练习指导。今天就报名，解锁机器学习在地理空间分析中的潜力吧！
Are you eager to harness the power of Machine Learning for geospatial analysis, but not sure where to start? Welcome to our course, designed to equip you with the theoretical and practical knowledge of Machine Learning applied in the fields of Geographic Information Systems (GIS) and Remote Sensing. Whether you're interested in land use and land cover mapping, classifications, or object-based image analysis, this course has you covered.Course Highlights:Theoretical and practical understanding of Machine Learning applications in GIS and Remote SensingApplication of Machine Learning algorithms, including Random Forest, Support Vector Machines, and Decision TreesCompletion of a full GIS project with hands-on exercisesUtilization of cloud computing and Big Data analysis through Google Earth EngineIdeal for professionals across various fieldsStep-by-step instructions and downloadable practical materialsCourse Focus:This comprehensive course delves into the realm of Machine Learning in geospatial analysis, offering a blend of theory and practical application. Upon course completion, you will possess the knowledge and confidence to harness Machine Learning for a wide range of geospatial tasks.What You'll Learn:Installing open-source GIS software (QGIS, OTB toolbox) and proper configurationNavigating the QGIS software interface, including components and plug-insClassifying satellite images with diverse Machine Learning algorithms (e.g., Random Forest, Support Vector Machines, Decision Trees) in QGISConducting image segmentation in QGISPreparing your inaugural land cover map using the cloud computing platform Google Earth EngineWho Should Enroll:This course caters to a diverse audience, including geographers, programmers, social scientists, geologists, and any professionals who employ maps in their respective fields. If you anticipate tasks that demand state-of-the-art Machine Learning algorithms for tasks like land cover and land use mapping, this course empowers you with the skills to address such geospatial challenges.INCLUDED IN THE COURSE: Gain access to step-by-step instructions, practical materials, datasets, and guidance for hands-on exercises in QGIS and Google Earth Engine. Enroll today to unlock the potential of Machine Learning for geospatial analysis!
