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{ "item_title" : "Feature Papers for Land Innovations - Data and Machine Learning", "item_author" : [" Chuanrong Zhang "], "item_description" : "The Special Issue Feature Papers for Land Innovations-Data and Machine Learning makes valuable contributions relating to spatial data science for obtaining, processing, analyzing, harnessing, and visualizing social, economic, environmental, and other data related to land. In particular, this Special Issue welcame geospatial artificial intelligence and machine learning techniques for dealing with spatial big data, including remotely sensed data and social media data. Manuscripts can be theoretical, applied, or review articles. Interdisciplinary manuscripts were particularly welcome as well.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/72/580/083/3725800839_b.jpg", "price_data" : { "retail_price" : "86.66", "online_price" : "86.66", "our_price" : "86.66", "club_price" : "86.66", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Feature Papers for Land Innovations - Data and Machine Learning|Chuanrong Zhang

Feature Papers for Land Innovations - Data and Machine Learning

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Overview

The Special Issue "Feature Papers for Land Innovations-Data and Machine Learning" makes valuable contributions relating to spatial data science for obtaining, processing, analyzing, harnessing, and visualizing social, economic, environmental, and other data related to land. In particular, this Special Issue welcame geospatial artificial intelligence and machine learning techniques for dealing with spatial big data, including remotely sensed data and social media data. Manuscripts can be theoretical, applied, or review articles. Interdisciplinary manuscripts were particularly welcome as well.

Details

  • ISBN-13: 9783725800834
  • ISBN-10: 3725800839
  • Publisher: Mdpi AG
  • Publish Date: January 2024
  • Dimensions: 9.61 x 6.69 x 0.81 inches
  • Shipping Weight: 1.59 pounds
  • Page Count: 242

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