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Water, Land, and Forest Susceptibility and Sustainability

Bag om Water, Land, and Forest Susceptibility and Sustainability

Water, Land, and Forest Susceptibility and Sustainability, Volume 1: Geospatial Approaches & Modeling brings an interdisciplinary perspective to solving complex problems in sustainability, utilizing the latest research and technologies, and includes case studies that emphasize the applications of remote sensing, GIS, and image processing for addressing the current state and future needs to achieve sustainability. As forests, land, and water are among the most precious resources on earth, emphasizing the need to conserve them for future generations and, of course, a safe and sustainable planet. The assessment of the susceptibility of all these three precious resources must therefore be addressed to inform their sustainable management. This 1st volume encourages adaptive activities among experts employed in interdisciplinary fields, from data mining and machine learning to environmental science by linking geospatial computational intelligence technology to forest, land and water issues.

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  • Sprog:
  • Ukendt
  • ISBN:
  • 9780323918800
  • Indbinding:
  • Paperback
  • Sideantal:
  • 576
  • Udgivet:
  • 29. november 2022
  • Størrelse:
  • 235x33x192 mm.
  • Vægt:
  • 1202 g.
  • 8-11 hverdage.
  • 21. november 2024
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Water, Land, and Forest Susceptibility and Sustainability, Volume 1: Geospatial Approaches & Modeling brings an interdisciplinary perspective to solving complex problems in sustainability, utilizing the latest research and technologies, and includes case studies that emphasize the applications of remote sensing, GIS, and image processing for addressing the current state and future needs to achieve sustainability. As forests, land, and water are among the most precious resources on earth, emphasizing the need to conserve them for future generations and, of course, a safe and sustainable planet. The assessment of the susceptibility of all these three precious resources must therefore be addressed to inform their sustainable management. This 1st volume encourages adaptive activities among experts employed in interdisciplinary fields, from data mining and machine learning to environmental science by linking geospatial computational intelligence technology to forest, land and water issues.

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