Using Historical Maps in Scientific Studies - 6 Angebote vergleichen

Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Lagernd, zzgl. Versandkosten.
This first SpringerBrief provides a brief review on cartographic practices and their changes. Then this brief presents example case studies of using historical maps in scientific studies and their real-world applications. Next, it describes the challenges and best practices in extracting and modeling map contents. Such a state-of-the-art introduction manual can help researchers interested in using the embedded human knowledge in historical maps to better understand the possibilities of current tools and to employ an efficient workflow for generating reusable datasets. This brief also discusses the current trend and outlook in making large numbers of historical maps searchable by location, time, and content and make their content machine-understandable and available to everyone everywhere. Detailed knowledge of the past is a critical component for the success in studies in a variety of fields, including humanities, social sciences, and life sciences. Historical maps are a valuable source of geographical and political information (e.g., historical place names, landmarks, natural features, and transportation networks) from the distant past all the way to the near present. Also, they are often the only source that provides professionally surveyed historical data. Today, map archives such as the David Rumsey Map Collection, USGS National Geologic Map Database, USGS Topographic Maps, OldMapsOnline.org, and the National Library of Scotland, store thousands of historical maps in either paper or scanned format. With this exponential growth of available map scans in the archives and on the internet, a variety of disciplines grows interests in using historical maps in their studies. However, researchers can spend a great deal of time and effort converting the content of relevant maps to a usable format (from images) and modeling the map content so that the raw data in maps can be distilled into knowledge that can be used to answer research questions. This process is heavily labor intensive, and the result is that researchers do not get as far as they could have in their work because of the lack of knowledge about automatic map processing and data modeling tools and practices. The primary audience for this brief includes scientists and researchers whose research requires long-term historical geographic data, as well as librarians. Also, anyone who loves maps will enjoy this SpringerBrief. Soft cover.

Lieferung aus: Deutschland, Versandkostenfrei.
Using Historical Maps in Scientific Studies: This first SpringerBrief provides a brief review on cartographic practices and their changes. Then this brief presents example case studies of using historical maps in scientific studies and their real-world applications. Next, it describes the challenges and best practices in extracting and modeling map contents. Such a state-of-the-art introduction manual can help researchers interested in using the embedded human knowledge in historical maps to better understand the possibilities of current tools and to employ an efficient workflow for generating reusable datasets. This brief also discusses the current trend and outlook in making large numbers of historical maps searchable by location, time, and content and make their content machine-understandable and available to everyone everywhere. Detailed knowledge of the past is a critical component for the success in studies in a variety of fields, including humanities, social sciences, and life sciences. Historical maps are a valuable source of geographical and political information (e.g., historical place names, landmarks, natural features, and transportation networks) from the distant past all the way to the near present. Also, they are often the only source that provides professionally surveyed historical data. Today, map archives such as the David Rumsey Map Collection, USGS National Geologic Map Database, USGS Topographic Maps, OldMapsOnline.org, and the National Library of Scotland, store thousands of historical maps in either paper or scanned format. With this exponential growth of available map scans in the archives and on the internet, a variety of disciplines grows interests in using historical maps in their studies. However, researchers can spend a great deal of time and effort converting the content of relevant maps to a usable format (from images) and modeling the map content so that the raw data in maps can be distilled into knowledge that can be used to answer research questions. This process is heavily labor intensive, and the result is that researchers do not get as far as they could have in their work because of the lack of knowledge about automatic map processing and data modeling tools and practices. The primary audience for this brief includes scientists and researchers whose research requires long-term historical geographic data, as well as librarians. Also, anyone who loves maps will enjoy this SpringerBrief. Englisch, Taschenbuch.

Lieferung aus: Kanada, Lagernd, zzgl. Versandkosten.
Yao-Yi Chiang, Weiwei Duan, Books, Science and Nature, Using Historical Maps In Scientific Studies: Challenges And Best Practices, This  first SpringerBrief provides a brief review on cartographic practices and their changes. Then this brief presents example case studies of using historical maps in scientific studies and their real-world applications. Next, it describes the challenges and best practices in extracting and modeling map contents. Such a state-of-the-art introduction manual can help researchers interested in using the embedded human knowledge in historical maps to better understand the possibilities of current tools and to employ an efficient workflow for generating reusable datasets. This brief also discusses the current trend and outlook in making large numbers of historical maps searchable by location, time, and content and make their content machine-understandable and available to everyone everywhere. Detailed knowledge of the past is a critical component for the success in studies in a variety of fields, including humanities, social sciences, and life sciences. Historical maps are a valuable source of geographical and political information (e.g., historical place names, landmarks, natural features, and transportation networks) from the distant past all the way to the near present. Also, they are often the only source that provides professionally surveyed historical data. Today, map archives such as the David Rumsey Map Collection, USGS National Geologic Map Database, USGS Topographic Maps, OldMapsOnline.org, and the National Library of Scotland, store thousands of historical maps in either paper or scanned format. With this exponential growth of available map scans in the archives and on the internet, a variety of disciplines grows interests in using historical maps in their studies. However, researchers can spend a great deal of time and effort converting the content of relevant maps to a usable format (from images) and modeling the map content so that the raw data in maps can be distilled into knowledge that can be used to answer research questions. This process is heavily labor intensive, and the result is that researchers do not get as far as they could have in their work because of the lack of knowledge about automatic map processing and data modeling tools and practices. The primary audience for this brief  includes scientists and researchers whose research  requires long-term historical geographic data, as well as librarians. Also, anyone who loves maps will enjoy this SpringerBrief. .

Lieferung aus: Deutschland, Versandkostenfrei.
Using Historical Maps in Scientific Studies: This SpringerBrief provides a brief review on cartographic practices and their changes. This brief also presents example case studies using historical maps in scientific studies and their real-world applications. The authors describe the challenges and best practices in extracting and modeling map Contents in this brief. This state-of-the-art introduction manual will help researchers, professionals and students interested in using the embedded human knowledge in historical maps to better understand the possibilities of current tools and to employ an efficient workflow for generating reusable datasets. Finally, this SpringerBrief discusses the current trend and outlook in making large numbers of historical maps searchable by location, time, and content and make their content machine-understandable and available to everyone everywhere. Englisch, Taschenbuch.

Lieferung aus: Japan, Lagernd, zzgl. Versandkosten.
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! eBook.

Lieferung aus: Deutschland, Noch nicht erschienen. Versandkostenfrei.
Von Händler/Antiquariat, Amazon.de.
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