SpringerBriefs in Geography

This book illustrates the first connection between the map user community and the developers of digital map processing technologies by providing several applications, challenges, and best practices in working with historical maps. After the introduction chapter, in this book, Chapter 2 presents a variety of existing applications of historical maps to demonstrate varying needs for processing historical maps in scientific studies (e.g., thousands of historical maps from a map series vs. a few historical maps from various publishers and with different cartographic styles). Chapter 2 also describes case studies introducing typical types of semi-automatic and automatic digital map processing technologies. 
The case studies showcase the strengths and weaknesses of semi-automatic and automatic approaches by testing them in a symbol recognition task on the same scanned map. Chapter 3 presents the technical challenges and trends in building a map processing, modeling, linking, and publishing framework. The framework will enable querying historical map collections as a unified and structured spatiotemporal source in which individual geographic phenomena (extracted from maps) are modeled (described) with semantic descriptions and linked to other data sources (e.g., DBpedia, a structured version of Wikipedia). Chapter 4 dives into the recent advancement in deep learning technologies and their applications on digital map processing. The chapter reviews existing deep learning models for their capabilities on geographic feature extraction from historical maps and compares different types of training strategies. A comprehensive experiment is described to compare different models and their performance.
Historical maps are fascinating to look at and contain valuable retrospective place information difficult to find elsewhere. However, the full potential of historical maps has not been realized because the users of scanned historical maps and the developers of digital map processing technologies are from a wide range of disciplines and often work in silos. Each chapter in this book can be read individually, but the order of chapters in this book helps the reader to first understand the “product requirements” of a successful digital map processing system, then review the existing challenges and technologies, and finally follow the more recent trend of deep learning applications for processing historical maps. 
The primary audience for this book includes scientists and researchers whose work requires long-term historical geographic data as well as librarians. The secondary audience includes anyone who loves maps!

The book provides a complete vision about Spanish sustainable renovation of buildings situation at this moment, analysing legal and technological context and opportunities that economic stimulus —by means of direct aids— and the use of BIM methodologies offers a standardization of high scale interventions.

Nowadays, BIM models let us integrate multiple quantitative parameters that can agile the information to interchange between stakeholders. Using this potential to standardize protocols of interventions and share knowledge is necessary to face a high scale intervention that our cities need.

Climatic Emergency and socioeconomic crisis caused by recent events —COVID-19 and hydrocarbons crisis— are the two principal struggles we face as society. European Politics, embodied by National Energy and Climate Plans (NECPs) developed by each region give the way to the green transition of different productive sectors.

Our building stock is responsible for approximately 36% of the CO2 emissions in the European Union. For this reason, these policies focus a large part of their efforts on economically incentivizing a new development model for the building sector that is committed to the large-scale renovation of the existing real estate stock and that, through the reduction of energy demand and of emissions, manage to reduce the environmental impact of these.

Next Generation EU is the new recovery instrument that aims to mobilize investments towards strategic sectors for the reorientation of the production model that, among other measures, contributes to decarbonization through the promotion of energy efficiency and the deployment of renewable energies.

Urban expansion beyond the city’s administrative boundaries has altered villages to a great extent. These peri-urban villages are experiencing unforeseen changes in demographic, economic, land-use, and environmental characteristics. The concept of peri-urbanization is grabbing the attention of urban planners and policymakers globally. To understand the dynamics of the peri-urban region it is crucial to examine multiple rural and urban characteristics. This book studies major changes in population, land and development with the integration of remotely sensed data and census data for 615 peri-urban villages surrounding Ahmedabad city of India. The chapters of the book are designed to cover key aspects of peri-urban change with geospatial methods. This book offers a comprehensive understanding and importance of analyzing peri-urban dynamics at the smallest spatial unit. It provides a detailed conceptual and methodological framework for the students and researchers to study peri-urbanization as well as for the policymakers to redefine the urban policies.