Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors

Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors

Abstract Background The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of tota...

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Bibliographic Details
Main Authors: Svetlana Saarela, André Wästlund, Emma Holmström, Alex Appiah Mensah, Sören Holm, Mats Nilsson, Jonas Fridman, Göran Ståhl
Format: Article
Language:English
Published: SpringerOpen 2020-07-01
Series:Forest Ecosystems
Subjects:
Aboveground biomass assessment
Forest mapping
Gauss-Newton Regression
Hierarchical Model-Based inference
LiDAR maps
National Forest Inventory
Online Access:http://link.springer.com/article/10.1186/s40663-020-00245-0

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http://link.springer.com/article/10.1186/s40663-020-00245-0

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