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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-earth-observation-with-ai-google-earth-engine/
课程评论：没有评论
**课程名称：** 精通人工智能与谷歌地球引擎的地球观测 **课程概述：** 本课程旨在帮助学员掌握利用谷歌地球引擎（Google Earth Engine, GEE）和人工智能（AI）分析卫星影像、监测环境变化的能力。课程内容涵盖遥感基础、机器学习和深度学习在地学分析中的应用。 学员将从GEE和遥感入门开始，学习如何访问和处理卫星影像。随后，课程将深入探讨土地利用和土地覆盖（LULC）制图，讲解如何运用机器学习和深度学习技术对地表进行有效分类。 此外，课程还将教授时间序列影像的可视化，使学员能够创建动态展示长期变化的动画。学员将接触到真实的全球环境应用案例，包括森林火灾制图、利用多源卫星数据分析洪水以及滑坡易发性制图。课程还将重点讲解利用深度学习进行变化检测，这是一项追踪地表变化的关键技术。 **通过本课程，学员将能够：** * 熟练运用GEE进行卫星影像处理和可视化。 * 应用机器学习和深度学习进行LULC分类。 * 开展洪水、森林火灾和滑坡等灾害的制图工作。 * 运用变化检测技术监测环境变化。 无论您是研究人员、学生还是GIS专业人士，本课程都将为您提供利用前沿地理空间技术分析地球动态表面的实用技能。 **课程大纲：** 无
Harness the power of Google Earth Engine (GEE) and Artificial Intelligence (AI) to analyze satellite imagery and monitor environmental changes. This comprehensive course will guide you through the fundamentals of remote sensing, machine learning, and deep learning for geospatial analysis.You will start with an introduction to GEE and remote sensing, learning how to access and process satellite imagery. From there, you'll dive into Land Use and Land Cover (LULC) mapping, applying machine learning and deep learning techniques to classify landscapes effectively.The course also covers time-series image visualization, allowing you to create animated representations of changes over time. You'll explore real-world environmental applications, including forest fire mapping, flood analysis using multiple satellite datasets, and landslide susceptibility mapping. Additionally, you will learn change detection analysis using deep learning, a crucial technique for tracking landscape modifications.By the end of this course, you will have the skills to:Utilize GEE for satellite image processing and visualizationImplement machine learning and deep learning for LULC classificationConduct disaster mapping for floods, forest fires, and landslidesApply change detection techniques to monitor environmental transformationsWhether you are a researcher, student, or GIS professional, this course will equip you with practical skills to analyze Earth's dynamic surface using cutting-edge geospatial technologies.
