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所在平台: Udemy |
课程主页: https://www.udemy.com/course/open-source-gis-remote-sensing-for-conservation-advanced/
课程评论：没有评论
**课程名称：** 开源地理信息系统（GIS）与遥感技术在保护领域的应用（高级） **课程概述：** 本高级课程建立在初级课程的知识和技能基础上，深入探讨空间分析在野生动物和环境保护领域的进阶应用。课程适合已完成初级课程的学习者，或已具备中级GIS技能并希望在保护领域进行技能更新或提升的学习者。 课程由经验丰富的GIS与遥感专家Josef Clifford开发，并与肯尼亚野生动物研究与培训研究所（WRTI）及伦敦动物学会（ZSL）的科学家们合作，确保内容严谨且高度相关。课程将使用真实数据，包括肯尼亚大象的GPS追踪数据，并包含解决现实世界问题的实践活动。 学员将有机会使用包含重要Google Earth Engine（GEE）代码库的资源，该库易于改编，可用于执行广泛的遥感任务。课程内容涵盖多种应用，包括： * 利用Google Earth Engine访问各类环境栅格数据集。 * 运用栅格处理和分析工具，为加蓬森林象开发栖息地适宜性加权地图。 * 探讨数字高程模型（DEMs）。 * 分析气候和环境数据的空间及时间变化趋势。 * 介绍遥感的基本理论。 * 探索一系列开源数据集。 * 执行多种分析，如计算归一化植被指数（NDVI）异常值以研究植被健康，并分析野火对加拿大影响的趋势。 * 探讨Habitat Connectivity Analysis in Linkage Mapper和Home Range Analysis in R等附加工作流程。 课程主要使用QGIS、Google Earth Engine，以及R和其他工具。 **目标受众：** * 已完成初级GIS与遥感在保护领域应用课程的学习者。 * 已具备中级GIS技能，并希望在环境保护领域深化应用的学习者。 * 对利用空间技术解决保护问题感兴趣的研究人员、学生和从业者。
Building on the foundational knowledge and skills you will have developed in the beginner's course, this course dives into more advanced applications of spatial analysis in wildlife and environment conservation. It's suitable for students who have completed the beginner's course, or who already have an intermediate level of GIS and looking to refresh or enhance their skills applied to the field of conservation. Developed by Josef Clifford, an experienced GIS & remote sensing specialist, the course curriculum and content was developed in collaboration with scientists from the Wildlife Research and Training Institute (WRTI) in Kenya and the Zoological Society of London (ZSL) to ensure the content is rigorous and relevant. Real data is used throughout, including GPS tracking data of Kenyan elephants, with hands-on activities to solve real-world problems. In addition, students will have access to a wide range of resources including an indispensable Google Earth Engine conservation code repository which can be easily adapted to conduct a wide range of remote sensing tasks. We will cover a multitude of applications ranging from harnessing Google Earth Engine to access a range of environmental raster datasets, employing raster processing and analysis tools to develop a weighted habitat suitability map for forest elephants in Gabon, exploring digital elevation models (DEMs), and analysing spatial and temporal trends in climatic and environmental data. We will introduce the essential theory of remote sensing, explore a range of open source datasets and conduct a variety of analyses such as calculating the Normalised Difference Vegetation Index (NDVI) anomaly to investigate vegetation health and charting trends to analyse the impacts of wildfires in Canada. Finally we will explore some additional workflows including habitat connectivity analysis in Linkage Mapper and home range analysis in R. The course will primarily utilise QGIS as well as Google Earth Engine, plus R and other tools. Good luck and I hope you enjoy the course!
