Integration of National Forest Inventory and Nationwide Airborne Laser Scanning Data to Improve Forest Yield Predictions in North-Western Spain

Integration of National Forest Inventory and Nationwide Airborne Laser Scanning Data to Improve Forest Yield Predictions in North-Western Spain

The prediction of growing stock volume is one of the commonest applications of remote sensing to support the sustainable management of forest ecosystems. In this study, we used data from the 4th Spanish National Forest Inventory (SNFI-4) and from the 1st nationwide Airborne Laser Scanning (ALS) surv...

Full description

Bibliographic Details
Main Authors: Alís Novo-Fernández, Marcos Barrio-Anta, Carmen Recondo, Asunción Cámara-Obregón, Carlos A. López-Sánchez
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Remote Sensing
Subjects:
national forest inventory
airborne laser scanning
forest yield
regression
machine learning techniques
Online Access:https://www.mdpi.com/2072-4292/11/14/1693

Internet

https://www.mdpi.com/2072-4292/11/14/1693

Similar Items