EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link: https://ebookbell.com/faq

We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.

For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Big Data Computing For Geospatial Applications Zhenlong Li Wenwu Tang

Name: Big Data Computing For Geospatial Applications Zhenlong Li Wenwu Tang
SKU: BELL-43084756
Price: 31.00 USD
Availability: InStock
Rating: 5 (88 reviews)

SKU: BELL-43084756

$ 31.00 ~~$ 45.00~~ (-31%)

5.0

88 reviews

Big Data Computing For Geospatial Applications Zhenlong Li Wenwu Tang instant download after payment.

Publisher: MDPI

File Extension: PDF

File size: 36.53 MB

Pages: 222

Author: Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan

ISBN: 9783039432455, 3039432451

Language: English

Year: 2020

Product desciption

Big Data Computing For Geospatial Applications Zhenlong Li Wenwu Tang by Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan 9783039432455, 3039432451 instant download after payment.

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.