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所在平台: Udemy |
课程主页: https://www.udemy.com/course/gis-geospatial-analysis-with-python-geopandas-and-folium/
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课程名称：《使用Python、Geopandas和Folium进行GIS与地理空间分析》 课程概述：欢迎参加《使用Python、Geopandas和Folium进行GIS与地理空间分析》课程。 本课程是一门全面的项目导向课程，逐步教您如何利用GIS进行城市规划的地理空间分析技术。 您将构建多个项目，如绘制人口密度图、监测空气质量、绘制洪水风险、绘制雪覆盖以及建模和优化路线。 本课程将使用Python库，如Pandas、Geopandas、Folium、Geocoder和Ipyleaflet，完美结合地理空间分析与城市规划，为您提供练习编程技能和提高地理空间知识的理想机会。 在第一部分中，您将学习地理空间分析的基本原理，包括其用例、工作流程以及GIS的技术挑战和限制。 接下来的部分将学习地理空间数据可视化方法，如分级色图、热图、3D图、流图、点图和图示图。这一部分非常关键，因为它为您提供了有效向城市规划相关利益相关者和决策者传达分析结果所需的工具。 随后，我们将从Kaggle下载地理空间数据集，其中包含人口统计数据、土地利用数据和气候数据等有价值的信息。在开始项目之前，我们将学习基本的地理空间技术，如导入地理数据、展示交互式地图、提取地图坐标、计算两个位置之间的距离、使用邻近分析查找附近城市以及进行地理编码和反向地理编码。这一部分为您提供了有效处理地理空间数据的基本技能和知识，使您为即将到来的项目做好充分准备。 接下来，我们将开始项目，共有五个项目。第一项目将分析人口密度，以识别高密度区域并评估其城市规划的适宜性。第二项目将着重监测空气质量，识别高污染水平地区及其对公共健康和环境的影响。第三项目将绘制洪水风险区域，以促进灾难准备和减缓措施实施。第四项目将绘制雪覆盖情况，以支持冬季运输规划和寻找安全的旅行路线。最后，在第五项目中，您将开发最优交通路线，以提高效率并减少城市通勤者的旅行时间。 在开始学习之前，我们要问自己一个问题：为什么要学习地理信息系统和地理空间分析？地理信息系统对于理解数据中的空间关系和模式至关重要，使我们能够做出明智的决策，更有效地解决现实问题。这些技术在城市规划、环境科学和公共健康等多个行业中起着关键作用，帮助我们分析空间数据，获得有意义的见解以改善决策。此外，地理信息技术还提供了大量商业机会，如开发自定义GIS应用程序，包括物业估值工具、供应链优化平台或旅游路线规划器等。 通过本课程，您可以期待学习以下内容： - 地理空间分析的基本原理及其应用案例 - 地理空间分析工作流程，包括数据收集、预处理、清理、探索性数据分析、空间分析和建模 - 地理空间数据可视化方法如分级色图、热图、3D图等 - 使用Geopandas、Folium和Ipyleaflet展示交互式地图和地形图 - 计算位置之间的距离和提取地理坐标 - 进行地理编码及反向地理编码 - 进行邻近分析以查找附近城市 - 分析和计算人口密度、空气质量指数、洪水风险和雪覆盖情况 - 使用Open Street Map Network X进行路线建模和优化 - 使用Dijkstra算法优化公交路线 本课程提供了一个全面的学习平台，使您掌握地理空间分析并应用于实际项目中。
Welcome to GIS & Geospatial Analysis with Python, Geopandas, and Folium course. This is a comprehensive project-based course where you will learn step-by-step on how to perform geospatial analysis techniques specifically leveraging GIS for urban planning. You will build projects like mapping population density, monitoring air quality, mapping flood risks, mapping snow cover, modeling and optimizing routes, and we will be using Python libraries like Pandas, Geopandas, Folium, Geocoder, and Ipyleaflet. The course perfectly combines geospatial analysis with urban planning, providing an ideal opportunity to practice your programming skills while improving your geospatial knowledge. In the introduction session, you will learn the basic fundamentals of geospatial analysis, such as getting to know its use cases, understanding geospatial analysis workflow, learning about technical challenges and limitations in GIS. Then, in the next section, we will learn about geospatial data visualization methods like choropleth maps, heatmaps, 3D maps, flow maps, point maps, and cartogram maps. This section is very critical because it provides you with the necessary tools to communicate your analysis effectively to stakeholders and decision-makers involved in urban planning. Afterward, in the next section, we will download geospatial datasets from Kaggle, the datasets contain valuable information like demographic data, land use data, and climate data. Before starting the project, we will learn about basic geospatial techniques, like importing geospatial data, displaying interactive maps, extracting coordinates from map, calculating distance between two locations, finding nearby cities using proximity analysis, performing geocoding and reverse geocoding. This section is very essential because it provides you with the fundamental skills and knowledge needed to effectively work with geospatial data and prepare you well for the upcoming projects. In the next section, we will start the projects. There will be five projects. In the first project, you will analyze population density to identify densely populated areas and assess their suitability for urban planning initiatives. For the second project, you will focus on monitoring air quality to identify areas with high pollution levels and assess their impact on public health and the environment. In the third project, you will map flood risk areas to facilitate disaster preparedness and mitigation efforts. In the fourth project, you will map snow cover to support transportation planning and finding safer travel routes during winter season. Lastly, in the fifth project, you will develop optimal transportation routes to improve efficiency and reduce travel times for urban commuters.First of all, before getting into the course, we need to ask ourselves this question: why should we learn about geographic information systems and geospatial analysis? Well, here is my answer: geographic information systems are essential for understanding spatial relationships and patterns in data, enabling us to make informed decisions and solve real-world problems more effectively. These technologies play a crucial role in various industries, for example, urban planning, environmental science, and public health, allowing us to analyze spatial data and derive meaningful insights for better decision-making. Additionally, there are tons of business opportunities, for example, you can develop custom GIS applications like property valuation tools, supply chain optimization platforms, or tourism route planners. These applications leverage location-based insights to drive decision-making and enhance operational efficiency.Below are things that you can expect to learn from this course:Learn the basic fundamentals of geospatial analysis and its use casesLearn geospatial analysis workflow. This section covers data collection, data preprocessing, data cleaning, exploratory data analysis, spatial analysis, and modelingLearn about geospatial data visualization methods like choropleth maps, heatmaps, 3D maps, flow maps, point maps, and cartogram mapsLearn how to display interactive map and topographic map using Geopandas, Folium, and IpyleafletLearn how to calculate distance between two locationsLearn how to extract geographic coordinates from mapLearn how to perform geocoding and reverse geocodingLearn how to conduct proximity analysis for finding nearby citiesLearn how to analyze and calculate population densityLearn how to visualize population density on interactive mapLearn how to analyze air quality indexLearn how to monitor air quality in multiple locationsLearn how to analyze and calculate flood riskLearn how to map flood risk on interactive mapLearn how to analyze snowfall and snow depth in multiple locationsLearn how to map snow cover using FoliumLearn how to model and optimize route using Open Street Map Network XLearn how to model and optimize bus routes using Dijkstra algorithm
