Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Spatial Big Data Science : Classification Techniques for Earth Observation Imagery, Paperback / softback Book

Spatial Big Data Science : Classification Techniques for Earth Observation Imagery Paperback / softback

Paperback / softback

Description

Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation.

However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book. This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data.

Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning.

Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health.

Advanced level students in computer science will also find this book useful as a reference.

Information

Other Formats

Save 18%

£99.99

£81.75

Item not Available
 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information