|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-for-spatial-data-analysis-with-earth-engine-and-qgis/
课程评论：没有评论
**课程名称：** QGIS与Google Earth Engine Python API空间分析 **课程概述：** 本课程旨在教授学员如何利用Google Earth Engine (GEE) Python API和QGIS软件进行高效的空间数据分析。课程将涵盖从安装GEE插件到使用Python API访问、下载、可视化海量卫星遥感数据，并进行信息提取和特征分析。 **核心内容：** * **GEE Python API入门：** 学习如何在Python环境中启动和使用GEE API。 * **QGIS GEE插件安装与使用：** 掌握在QGIS中安装和配置GEE插件，实现桌面端的数据访问和初步分析。 * **卫星数据访问与处理：** * 加载和处理Landsat、Sentinel、MODIS、CHIRPS、VIIRS等多种卫星传感器数据。 * 掌握云掩膜算法，去除影像中的云层。 * 计算植被指数（如NDVI）。 * **高级分析技术：** * 图像分类（CART算法）和聚类分析。 * 线性回归分析。 * 应用全球土地覆盖产品（如NLCD, MODIS Land Cover）。 * **数据输出与应用：** * 导出处理后的影像和视频。 * 通过示例数据、脚本和真实世界应用，学以致用。 * 解决软件成本高的问题，课程将全程使用开源工具（GEE Python API和QGIS）。 **学习收获：** 完成本课程后，学员将能够独立利用GEE Python API和QGIS进行大规模卫星数据的获取、处理、分析和可视化，并提取有价值的空间信息。课程提供的所有示例脚本和数据将作为额外福利，帮助学员快速入门和深入学习。 **适用人群：** 希望利用先进的开源工具进行遥感影像分析和空间数据处理的地理信息科学、环境科学、计算机科学等领域的研究人员、学生和专业人士。
Do you want to access satellite sensors using Earth Engine Python API?Do you want to learn the QGIS Earth Engine plugin?Do you want to visualize and analyze satellite data in Python?Enroll in my new QGIS and Google Earth Engine Python API for Spatial Analysis course.I will provide you with hands-on training with example data, sample scripts, and real-world applications. By taking this course, you be able to install QGIS and Earth Engine plugins. Then, you will have access to satellite data using the Python API.In this QGIS and Google Earth Engine Python API for Spatial Analysis course, I will help you get up and running on the Earth Engine Python API and QGIS. By the end of this course, you will have access to all example scripts and data such that you will be able to access, download, visualize big data, and extract information.In this course, we will cover the following topics:Introduction to Earth Engine Python API Install the QGIS Earth Engine PluginLoad Landsat Satellite DataCloud Masking AlgorithmCalculate NDVIAccess Sentinel, Landsat, MODIS, CHIRPS, and VIIRS dataExport images and videosProcess image collectionsCART classificationClustering analysisLinear regressionGlobal Land Cover Products (NLCD, and MODIS Land Cover)One of the common problems with learning image processing is the high cost of software. In this course, I entirely use the Google Earth Engine Python API and QGIS open-source tools. All sample data and scripts will be provided to you as an added bonus throughout the course.Jump in right now to enroll. To get started click the enroll button.
