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Using data science and landscape approach to sustain historic cities

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using data science and landscape approach to sustain historic citiesby Ali Moazzeni Khorasgani.
Author:	Moazzeni Khorasgani, Ali.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xvii, 106 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Historic sitesData processing.
Online resource:	https://doi.org/10.1007/978-3-031-68161-5
ISBN:	9783031681615$q(electronic bk.)

Using data science and landscape approach to sustain historic cities
Moazzeni Khorasgani, Ali.

Using data science and landscape approach to sustain historic cities[electronic resource] /by Ali Moazzeni Khorasgani. - Cham :Springer Nature Switzerland :2024. - xvii, 106 p. :ill. (some col.), digital ;24 cm.

Chapter 1 Introduction -- Chapter 2 Understanding Historic Cities -- Chapter 3 Evolution of Regeneration Development -- Chapter 4 Landscape Approach for Historic City Sustainability -- Chapter 5 Data Science for Historic City Analysis -- Chapter 6 Sustainable Development Strategies for Historic Cities -- Chapter 7 Conclusion: Integrating Landscape and Data Science Approaches.

This book comprehensively explores sustaining historic cities using a landscape approach and data science. The author offers valuable insights for professionals and enthusiasts interested in preserving and developing urban heritage through a data driven approach. Drawing on the synergy between landscape architecture and data science, the book delves into the intricate interplay between historical, cultural, and environmental factors in urban settings. Readers will understand how to navigate historic cities' complex challenges through case studies, research findings, and practical methodologies. The book equips readers with innovative strategies for preserving the authenticity of these cities while embracing sustainable development practices. By blending theory and real-world applications, this book is a comprehensive guide for creating thriving, resilient, and culturally rich urban environments. Integrates landscape architecture and data science disciplines to tackle the complexities of sustaining historic cities; Offers a unique perspective that bridges the gap between heritage preservation and data-driven methodologies; Gives practical insights into how landscape and data science approaches have been successfully applied.

ISBN: 9783031681615$q(electronic bk.)

Standard No.: 10.1007/978-3-031-68161-5doiSubjects--Topical Terms:

982428
Historic sites
--Data processing.

LC Class. No.: CC135

Dewey Class. No.: 363.690285

Using data science and landscape approach to sustain historic cities
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505 0 $a Chapter 1 Introduction -- Chapter 2 Understanding Historic Cities -- Chapter 3 Evolution of Regeneration Development -- Chapter 4 Landscape Approach for Historic City Sustainability -- Chapter 5 Data Science for Historic City Analysis -- Chapter 6 Sustainable Development Strategies for Historic Cities -- Chapter 7 Conclusion: Integrating Landscape and Data Science Approaches.
520 $a This book comprehensively explores sustaining historic cities using a landscape approach and data science. The author offers valuable insights for professionals and enthusiasts interested in preserving and developing urban heritage through a data driven approach. Drawing on the synergy between landscape architecture and data science, the book delves into the intricate interplay between historical, cultural, and environmental factors in urban settings. Readers will understand how to navigate historic cities' complex challenges through case studies, research findings, and practical methodologies. The book equips readers with innovative strategies for preserving the authenticity of these cities while embracing sustainable development practices. By blending theory and real-world applications, this book is a comprehensive guide for creating thriving, resilient, and culturally rich urban environments. Integrates landscape architecture and data science disciplines to tackle the complexities of sustaining historic cities; Offers a unique perspective that bridges the gap between heritage preservation and data-driven methodologies; Gives practical insights into how landscape and data science approaches have been successfully applied.
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