Applied Geospatial Data Science with Python: Leverage geospatial data analysis and modeling to find unique solutions to environmental problems

Intelligently connect data points and gain a deeper understanding of environmental problems through hands-on Geospatial Data Science case studies written in Python

The book includes colored images of important concepts

Key Features:

• Learn how to integrate spatial data and spatial thinking into traditional data science workflows
• Develop a spatial perspective and learn to avoid common pitfalls along the way
• Gain expertise through practical case studies applicable in a variety of industries with code samples that can be reproduced and expanded

Book Description:

Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python.

Throughout this book, you'll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You'll learn how to read, process, and manipulate spatial data effectively. With data in hand, you'll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you'll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries.

By the end of the book, you'll be able to tackle random data, find meaningful correlations, and make geospatial data models.

What You Will Learn:

• Understand the fundamentals needed to work with geospatial data
• Transition from tabular to geo-enabled data in your workflows
• Develop an introductory portfolio of spatial data science work using Python
• Gain hands-on skills with case studies relevant to different industries
• Discover best practices focusing on geospatial data to bring a positive change in your environment
• Explore solving use cases, such as traveling salesperson and vehicle routing problems

Who this book is for:

This book is for you if you are a data scientist seeking to incorporate geospatial thinking into your workflows or a GIS professional seeking to incorporate data science methods into yours. You'll need to have a foundational knowledge of Python for data analysis and/or data science.

透過以Python編寫的實際地理空間數據科學案例研究，智能地連接數據點並深入了解環境問題。

本書包含重要概念的彩色圖像。

主要特點：
- 學習如何將空間數據和空間思維融入傳統數據科學工作流程
- 培養空間觀點，並學習避免常見問題
- 通過可重現和擴展的代碼示例，在各種行業中應用實踐案例研究，提升專業知識

書籍描述：
當數據科學家面對眾多數據時，往往會迷失如何以有意義的方式呈現地理空間分析，以便讓每個人都能理解。使用Python來視覺化數據有助於非技術角色的利益相關者理解問題並尋求解決方案。本書的目標是幫助數據科學家和地理信息系統專業人員學習並實施使用Python進行地理空間數據科學工作流程。

在本書中，您將探索許多可用於開發端到端空間數據科學工作流程的Python地理空間庫。您將學習如何有效地讀取、處理和操作空間數據。有了數據，您將開始創建空間數據可視化，以更好地理解和講述數據的故事，包括靜態和動態地圖應用。隨著您的學習進展，您將開始開發聚類、回歸和優化等重點在地理空間上的人工智能和機器學習模型。這些使用案例可以作為各種行業中更高級工作的基礎。

通過閱讀本書，您將能夠處理隨機數據，找到有意義的相關性並建立地理空間數據模型。

您將學到的內容：
- 理解處理地理空間數據所需的基礎知識
- 在工作流程中從表格數據轉換為地理啟用數據
- 使用Python開發入門級的空間數據科學作品集
- 通過與不同行業相關的案例研究獲得實踐技能
- 探索解決旅行推銷員和車輛路線問題等使用案例
- 發現關注地理空間數據的最佳實踐，為環境帶來積極的改變

本書適合對將地理空間思維融入工作流程感興趣的數據科學家，或對將數據科學方法融入工作流程感興趣的地理信息系統專業人員。您需要具備Python數據分析和/或數據科學的基礎知識。