138,86 €
154,29 €
-10% with code: EXTRA
Advances in Remote Sensing for Global Forest Monitoring
Advances in Remote Sensing for Global Forest Monitoring
138,86
154,29 €
  • We will send in 10–14 business days.
The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In…
  • Publisher:
  • ISBN-10: 3036512527
  • ISBN-13: 9783036512525
  • Format: 17 x 24.4 x 2.9 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Advances in Remote Sensing for Global Forest Monitoring (e-book) (used book) | bookbook.eu

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The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.

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  • Publisher:
  • ISBN-10: 3036512527
  • ISBN-13: 9783036512525
  • Format: 17 x 24.4 x 2.9 cm, hardcover
  • Language: English English

The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.

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