Modelling and Predicting the Growing Stock Volume in Small-Scale Plantation Forests of Tanzania Using Multi-Sensor Image Synergy

Modelling and Predicting the Growing Stock Volume in Small-Scale Plantation Forests of Tanzania Using Multi-Sensor Image Synergy

Remotely sensed assisted forest inventory has emerged in the past decade as a robust and cost efficient method for generating accurate information on forest biophysical parameters. The launching and public access of ALOS PALSAR-2, Sentinel-1 (SAR), and Sentinel-2 together with the associated open-so...

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Bibliographic Details
Main Authors: Ernest William Mauya, Joni Koskinen, Katri Tegel, Jarno Hämäläinen, Tuomo Kauranne, Niina Käyhkö
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Forests
Subjects:
multi-source data
planted forests
forest inventory
linear regression
Sentinel
stratification
Online Access:https://www.mdpi.com/1999-4907/10/3/279

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https://www.mdpi.com/1999-4907/10/3/279

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