|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/land-cover-classification-in-google-earth-engine/
课程评论：没有评论
**课程名称：** Google Earth Engine 中的土地覆盖分类 **课程概述：** 本课程旨在教授学员使用 Google Earth Engine (GEE) 和随机森林算法进行土地覆盖分类。课程内容深入且结构严谨，适合学生、地理空间专业人士、环境科学家和研究人员。通过在土耳其科尼亚Çumra地区进行的案例研究，学员将学会将土地划分为水体、植被、城市和裸地四个类别，并掌握先进的机器学习技术和云平台应用。 **课程亮点：** * **无需编程或遥感经验**：课程从基础概念讲起，循序渐进。 * **实践操作**：通过真实的 Çumra 地区土地覆盖图绘制案例，巩固学习成果。 * **专业技能培养**：掌握卫星影像预处理、机器学习模型开发与验证、地理空间数据解读等关键技能。 * **应用广泛**：学习成果可应用于环境管理、城市规划、农业监测等领域。 * **成果产出**：课程结束后，学员能独立生成一份专业的 Çumra 地区土地覆盖图。 **学习目标：** * 熟练运用 Google Earth Engine 进行土地覆盖分类。 * 掌握随机森林等机器学习算法在土地覆盖分类中的应用。 * 学会对卫星影像进行预处理和质量控制。 * 能够开发、训练和评估土地覆盖分类模型。 * 理解和解释分类结果，并能生成高质量的土地覆盖图。 **本课程将帮助您：** * 提升在地理空间分析领域的专业能力。 * 为应对全球环境挑战贡献力量。 * 解锁卫星影像的潜力，更好地理解和描绘我们的世界。
Welcome to an in-depth and rigorously structured course designed to equip learners with the expertise to perform land cover classification using Random Forest within Google Earth Engine (GEE). This course is tailored for students, geospatial professionals, environmental scientists, and researchers seeking to harness satellite imagery for precise land cover mapping. Through a comprehensive case study in Çumra District, Konya, Türkiye, participants will develop proficiency in classifying land into four categories-Water, Vegetation, Urban, and Bare Land-utilizing state-of-the-art machine learning techniques and cloud-based geospatial platforms. No prior experience in coding or remote sensing is required, as this course provides a systematic progression from foundational concepts to advanced applications, ensuring accessibility for beginners and value for experienced learners.Upon completion, you will produce a professional-grade land cover map of Çumra District, demonstrating mastery of Random Forest and GEE. You will gain the ability to preprocess satellite imagery, develop and validate machine learning models, and interpret geospatial data, skills highly valued in academia and industries such as environmental management, urban planning, and agricultural monitoring.Embark on a transformative learning journey to master land cover classification with Random Forest in Google Earth Engine. This course offers a unique opportunity to develop cutting-edge skills through a practical, real-world project in Çumra District, equipping you to address global environmental challenges. Enroll now to gain expertise in geospatial analysis, contribute to sustainable development. Begin your journey today and unlock the potential of satellite imagery to map and understand our world.
