This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive userâs guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations readers will gain an understanding of the main concepts and techniques using dynamic graphics for thematic mapping statistical graphing and most centrally the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed but no previous knowledge of GIS or mapping is required. Key Features: ⢠Includes spatial perspectives on cluster analysis⢠Focuses on exploring spatial data⢠Supplemented by extensive support with sample data sets and examples on the GeoDaCenter website This book is both useful as a reference for the software and as a text for students and researchers of spatial data science. | An Introduction to Spatial Data Science with GeoDa Volume 1: Exploring Spatial Data
Price now:
From
to
Price History:
Details:This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive userâs guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations readers will gain an understanding of the main concepts and techniques using dynamic graphics for thematic mapping statistical graphing and most centrally the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed but no previous knowledge of GIS or mapping is required. Key Features: ⢠Includes spatial perspectives on cluster analysis⢠Focuses on exploring spatial data⢠Supplemented by extensive support with sample data sets and examples on the GeoDaCenter website This book is both useful as a reference for the software and as a text for students and researchers of spatial data science. | An Introduction to Spatial Data Science with GeoDa Volume 1: Exploring Spatial Data
Price now:
From
to
Hive Books
2.61% (+ ÂŁ1.96)
New
ÂŁ76.95
Routledge
25.00% (+ ÂŁ15.40)
New
ÂŁ76.99
This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive userâs guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations readers will gain an understanding of the main concepts and techniques using dynamic graphics for thematic mapping statistical graphing and most centrally the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed but no previous knowledge of GIS or mapping is required. Key Features: ⢠Includes spatial perspectives on cluster analysis⢠Focuses on exploring spatial data⢠Supplemented by extensive support with sample data sets and examples on the GeoDaCenter website This book is both useful as a reference for the software and as a text for students and researchers of spatial data science. | An Introduction to Spatial Data Science with GeoDa Volume 1: Exploring Spatial Data
General | |
---|---|
Brand | Taylor & Francis Ltd |
Size | Large |
Sellers offer a range of delivery options, so you can choose the one thatâs most convenient for you. Many sellers offer free delivery. You can always find the postage cost and estimated delivery date in a sellerâs listing. You'll then be able to see a full list of delivery options during checkout. These can include: Express delivery, Standard delivery, Economy delivery, Click & Collect, Free local collection from seller.
Your options for returning an item vary depending on what you want to return, why you want to return it, and the seller's return policy. If the item is damaged or doesn't match the listing description, you can return it even if the seller's returns policy says they don't accept returns. If you've changed your mind and no longer want an item, you can still request a return, but the seller doesn't have to accept it. If the buyer changes their mind about a purchase and wants to return an item, they may need to pay return postage costs, depending on the seller's return policy. Sellers can provide a return postage address and additional return postage information for the buyer. Sellers pay for return postage if there's a problem with the item. For example, if the item doesn't match the listing description, is damaged or defective or is counterfeit. By law, customers in the European Union also have the right to cancel the purchase of an item within 14 days beginning from the day you receive, or a third party indicated by you (other than the carrier) receives, the last good ordered by you (if delivered separately). This applies to all products except for digital items (e.g. Digital Music) that are provided immediately to you with your acknowledgement, and other items such as video, DVD, audio, video games, Sex and Sensuality products and software products where the item has been unsealed.
Sellers have to offer a refund for certain items only if they are faulty, such as: Personalised items and custom-made items, Perishable items, Newspapers and magazines, Unwrapped CDs DVDs and computer software. If you used your PayPal balance or bank account to fund the original payment, the refunded money will go back to your PayPal account balance. If you used a credit or debit card to fund the original payment, the refunded money will go back to your card. The seller will effect the refund within three working days but it may take up to 30 days for Paypal to process the transfer. For payments funded partially by a card and partially by your balance/bank, the money taken from your card will go back to your card and the remainder will return to your PayPal balance.