使用机器学习地理空间应用程序进行建筑特征提取（True EPUB）

English | 2024 | ISBN: 9781003288046 | 127 pages | True EPUB | 5.59 MB

Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and machine learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others. Features

• Provides the basics of feature extraction methods and applications along with the fundamentals of machine learning

• Discusses in detail the application of machine learning techniques in geospatial building feature extraction

• Explains the methods for estimating object height from optical satellite remote sensing images using Python

• Includes case studies that demonstrate the use of machine learning models for building footprint extraction and photogrammetric methods for height assessment

• Highlights the potential of machine learning and geospatial technology for future project developments

This book will be of interest to professionals, researchers, and graduate students in geoscience and earth observation, machine learning and data science, civil engineers, and urban planners.

英文| 2024 |国际标准图书编号：9781003288046 | 127页|真正的EPUB | 5.59 MB 大型基础设施项目创建的大型地理空间数据集需要大量的计算资源来处理。特征提取是一种用于减少初始原始数据集以进行可管理图像处理的过程，机器学习（ML）是支持它的科学。本书重点介绍使用ML的光学地理空间数据的特征提取方法。它是开始信息提取职业生涯的专业人员和研究生的实用指南。它以易于理解的方式解释了空间特征提取，并包括如何收集空间特征的高度值、如何在地图环境中开发3D模型等真实案例研究。特征 •提供特征提取方法和应用的基础知识以及机器学习的基础知识 •详细讨论了机器学习技术在地理空间建筑特征提取中的应用 •解释使用Python从光学卫星遥感图像估计物体高度的方法 •包括案例研究，展示了如何使用机器学习模型进行建筑足迹提取和高度评估的摄影测量方法 •强调机器学习和地理空间技术对未来项目发展的潜力 这本书将引起地球科学和地球观测、机器学习和数据科学、土木工程师和城市规划师的专业人士、研究人员和研究生的兴趣。

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