Most similar neighbor imputation of forest attributes using metrics derived from combined airborne LIDAR and multispectral sensors

Most similar neighbor imputation of forest attributes using metrics derived from combined airborne LIDAR and multispectral sensors

In the context of predicting forest attributes using a combination of airborne LIDAR and multispectral (MS) sensors, we suggest the inclusion of normalized difference vegetation index (NDVI) metrics along with the more traditional LIDAR height metrics. Here the data fusion method consists of back-pr...

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Bibliographic Details
Main Authors: Ruben Valbuena, Ana Hernando, Jose Antonio Manzanera, Eugenio Martínez-Falero, Antonio García-Abril, Blas Mola-Yudego
Format: Article
Language:English
Published: Taylor & Francis Group 2018-12-01
Series:International Journal of Digital Earth
Subjects:
airborne laser scanning
forest attribute prediction
multispectral imagery
data fusion
nearest neighbor
Online Access:http://dx.doi.org/10.1080/17538947.2017.1387183

Internet

http://dx.doi.org/10.1080/17538947.2017.1387183

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