Improving the Spatial Prediction of Sand Content in Forest Soils Using a Multivariate Geostatistical Analysis of LiDAR and Hyperspectral Data

Improving the Spatial Prediction of Sand Content in Forest Soils Using a Multivariate Geostatistical Analysis of LiDAR and Hyperspectral Data

Soil sand particles play a crucial role in soil erosion because they are more susceptible to being detached and transported by erosive forces than silt and clay particles. Therefore, in soil erosion assessment and mitigation, it is crucial to model and predict soil sand particles at unsampled locati...

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Bibliographic Details
Main Authors: Annamaria Castrignanò, Gabriele Buttafuoco, Massimo Conforti, Mauro Maesano, Federico Valerio Moresi, Giuseppe Scarascia Mugnozza
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Remote Sensing
Subjects:
forest soils
data fusion
topographic attributes
soil spectroscopy
external drift
Online Access:https://www.mdpi.com/2072-4292/15/18/4416

Internet

https://www.mdpi.com/2072-4292/15/18/4416

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