Robert Jeansoulin – författare

This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild.

This book will teach you how to take advantage of the JavaScript language to process data provided on the Internet.

Much attention is given to the main JavaScript backbone: prototype based objects, and functional capabilities, while common features (loops, etc.) are summarized in a few cheat-sheets. Only operational features are detailed through the coding of several applications -the second and largest part of the book-, on free-access datasets (e.g. World Bank). It includes: cartography (SVG or API''s based), data-sheets access (via Ajax or Jsonp), video data and post-synchronization, and animation examples.

This book will teach you how to take advantage of the JavaScript language to process data provided on the Internet.

Much attention is given to the main JavaScript backbone: prototype based objects, and functional capabilities, while common features (loops, etc.) are summarized in a few cheat-sheets. Only operational features are detailed through the coding of several applications -the second and largest part of the book-, on free-access datasets (e.g. World Bank). It includes: cartography (SVG or API''s based), data-sheets access (via Ajax or Jsonp), video data and post-synchronization, and animation examples.

This book will teach you how to take advantage of the JavaScript language to process data provided on the Internet. Much attention is given to the main JavaScript backbone: prototype based objects, and functional capabilities, while common features (loops, etc.) are summarized in a few cheat-sheets. Only operational features are detailed through the coding of several applications -the second and largest part of the book-, on free-access datasets (e.g. World Bank). It includes: cartography (SVG or API's based), data-sheets access (via Ajax or Jsonp), video data and post-synchronization, and animation examples.

This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild.

Spatial information is pervaded by uncertainty. Indeed, geographical data is often obtained by an imperfect interpretation of remote sensing images, while people attach ill-defined or ambiguous labels to places and their properties. As another example, medical images are often the result of measurements by imprecise sensors (e.g. MRI scans). Moreover, by processing spatial information in real-world applications, additional uncertainty is introduced, e.g. due to the use of interpolation/extrapolation techniques or to conflicts that are detected in an information fusion step. To the best of our knowledge, this book presents the first overview of spatial uncertainty which goes beyond the setting of geographical information systems. Uncertainty issues are especially addressed from a representation and reasoning point of view. In particular, the book consists of 14 chapters, which are clustered around three central topics. The first of these topics is about the uncertainty in meaning of linguistic descriptions of spatial scenes. Second, the issue of reasoning about spatial relations and dealing with inconsistency in information merging is studied. Finally, interpolation and prediction of spatial phenomena are investigated, both at the methodological level and from an application-oriented perspective. The concept of uncertainty by itself is understood in a broad sense, including both quantitative and more qualitative approaches, dealing with variability, epistemic uncertainty, as well as with vagueness of terms.

Spatial information is pervaded by uncertainty. Indeed, geographical data is often obtained by an imperfect interpretation of remote sensing images, while people attach ill-defined or ambiguous labels to places and their properties. As another example, medical images are often the result of measurements by imprecise sensors (e.g. MRI scans). Moreover, by processing spatial information in real-world applications, additional uncertainty is introduced, e.g. due to the use of interpolation/extrapolation techniques or to conflicts that are detected in an information fusion step. To the best of our knowledge, this book presents the first overview of spatial uncertainty which goes beyond the setting of geographical information systems. Uncertainty issues are especially addressed from a representation and reasoning point of view. In particular, the book consists of 14 chapters, which are clustered around three central topics. The first of these topics is about the uncertainty in meaning of linguistic descriptions of spatial scenes. Second, the issue of reasoning about spatial relations and dealing with inconsistency in information merging is studied. Finally, interpolation and prediction of spatial phenomena are investigated, both at the methodological level and from an application-oriented perspective. The concept of uncertainty by itself is understood in a broad sense, including both quantitative and more qualitative approaches, dealing with variability, epistemic uncertainty, as well as with vagueness of terms.