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{ "item_title" : "Spatial Analysis Using Big Data", "item_author" : [" Yoshiki Yamagata", "Hajime Seya "], "item_description" : "Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. ", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/12/813/127/0128131276_b.jpg", "price_data" : { "retail_price" : "150.00", "online_price" : "150.00", "our_price" : "150.00", "club_price" : "150.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Spatial Analysis Using Big Data|Yoshiki Yamagata

Spatial Analysis Using Big Data : Methods and Urban Applications

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Overview

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others.

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Details

  • ISBN-13: 9780128131275
  • ISBN-10: 0128131276
  • Publisher: Academic Press
  • Publish Date: November 2019
  • Dimensions: 9 x 6 x 0.64 inches
  • Shipping Weight: 0.9 pounds
  • Page Count: 302

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