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所在平台: Udemy |
课程主页: https://www.udemy.com/course/google-earth-engine-machine-learning-geospatial-analysis/
课程评论：没有评论
课程名称：Google Earth Engine 机器学习与变化检测 课程概述：土地利用/覆盖（LULC）制图与变化检测 本课程旨在提升您的地理空间分析技能，使您熟练掌握土地利用和覆盖（LULC）制图及变化检测的技术。该课程专为具备基本地理信息系统（GIS）、地理空间数据和遥感基础知识的用户设计，帮助他们掌握进行高级地理空间分析所需的知识和工具。 课程亮点： - 详尽讲解机器学习算法及其实际应用 - 深入理解 Google Earth Engine 在 LULC 制图和变化检测中的应用 - 步骤指南，教授遥感数据获取、预处理、光谱指数计算和变化地图设计 - 实际项目与练习，巩固技能 - 可下载的材料，包括数据和 Java 代码文件 - 未来资源的访问，支持您的地理空间工作 课程重点： 该课程不仅仅是理论学习，更注重动手实践。您将掌握无监督和监督分类策略，这是 GIS 和遥感分析师的基本技能。完成课程后，您将能够自信地进行高级地理空间分析，包括使用 Google Earth Engine 的机器学习算法进行制图和变化检测，所有操作均基于真实和开放获取的数据。 为何选择此课程： 与其他培训资源不同，本课程的每一课都旨在以明确和可行的方式提升您的 GIS 和遥感技能。您将具备分析空间数据的能力，并因掌握先进的 GIS 技能以及前沿的 LULC 技术而获得未来雇主的认可。 您将学到： - Google Earth Engine 登录与界面导航 - 云端数据预处理和光谱指数计算 - JavaScript 简介 - 机器学习理论及其在 GIS 中的应用 - 使用各种机器学习算法（监督和无监督）对卫星图像进行分类 - 数据收集、验证和准确性评估 - Google Earth Engine 中的变化检测技术 - 在云端完成自己的地理空间项目 立即注册： 如果您是地理学家、程序员、社会科学家、地质学家或任何希望在其领域中使用 LULC 地图的专业人士，并希望掌握用于土地覆盖和土地利用制图的先进分类算法，本课程将是您的解决方案。现在就报名，解锁解决复杂地理空间挑战的信心与专业知识！ 课程包含： 您将获得全课程使用的数据和 Java 代码文件，并享有所需的未来资源，使本课程成为您地理空间职业生涯的有价值投资。立即注册，利用这些特别的材料！
Land Use/Land Cover Mapping and Change Detection with Machine Learning in Google Earth EngineAre you ready to elevate your geospatial analysis skills and become proficient in land use and land cover (LULC) mapping and change detection? This comprehensive course is designed to empower users who have a basic background in GIS, geospatial data, and remote sensing with the knowledge and tools required for advanced geospatial analysis.Course Highlights:Extensive coverage of machine learning algorithms and their practical applicationIn-depth understanding of Google Earth Engine for LULC mapping and change detectionStep-by-step guidance on acquiring satellite data, preprocessing, spectral indices calculation, and change map designReal-world projects and practical exercises to reinforce your skillsDownloadable materials, including data and Java code filesAccess to future resources to support your geospatial endeavorsCourse Focus:This course is more than just theory; it's about hands-on learning and practical implementation. You'll gain proficiency in unsupervised and supervised classification strategies for LULC mapping, which is a fundamental skill for GIS and remote sensing analysts. By the end of this course, you'll feel confident in performing advanced geospatial analysis, including machine learning algorithms for mapping and change detection, all using real and openly available data in Google Earth Engine.Why Choose This Course:Unlike other training resources, every lecture in this course aims to enhance your GIS and remote sensing skills in a clear and actionable manner. You'll be equipped to analyze spatial data for your own projects and earn recognition from future employers for your advanced GIS skills and knowledge of cutting-edge LULC techniques.What You'll Learn:Google Earth Engine sign-in and interface navigationData preprocessing on the cloud and spectral indices calculationIntroduction to JavaScriptMachine learning theory and its application in GISClassification of satellite images using various machine learning algorithms (supervised and unsupervised) in Google Earth EngineTraining, validation data collection, and accuracy assessmentChange detection techniques in Google Earth EngineCompletion of your own geospatial project on the cloudEnroll Today:If you're a geographer, programmer, social scientist, geologist, or any professional seeking to use LULC maps in your field and want to master state-of-the-art classification algorithms for tasks like land cover and land use mapping, this course is your solution. Sign up now and unlock the confidence and expertise to tackle complex geospatial challenges!INCLUDED IN THE COURSE: You'll have access to all the data used throughout the course, along with Java code files. Plus, you'll enjoy access to future resources, making this course a valuable investment in your geospatial career. Enroll today and take advantage of these special materials!
