Predicting stem diameters and aboveground biomass of individual trees using remote sensing data-Reference-Cited by-同舟云学术

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Predicting stem diameters and aboveground biomass of individual trees using remote sensing data

Published:2018-02 Issue: Volume:85 Page:367-376
ISSN:1470-160X
Container-title:Ecological Indicators
language:en
Short-container-title:Ecological Indicators

Author:

Dalponte Michele,Frizzera Lorenzo,Ørka Hans Ole,Gobakken Terje,Næsset Erik,Gianelle Damiano

Funder

hyperBio project

BIONÆR program of the Research Council

TerraTec AS

Publisher

Elsevier BV

Subject

Ecology,Ecology, Evolution, Behavior and Systematics,General Decision Sciences

Reference23 articles.

1. Characterizing forest species composition using multiple remote sensing data sources and inventory approaches;Ørka;Scand. J. For. Res.,2013

2. Quantifying forest canopy traits: imaging spectroscopy versus field survey;Asner;Remote Sens. Environ.,2015

3. Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation;Asner;Science,2017

4. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data;Breidenbach;Remote Sens. Environ.,2010

5. Creating a virtual tropical forest from three-dimensional aerial imagery to estimate carbon stocks;Brown;Ecol. Appl.,2005

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2. Is Your Training Data Really Ground Truth? A Quality Assessment of Manual Annotation for Individual Tree Crown Delineation;Remote Sensing;2024-07-30

3. Enhancing precision in coastal dunes vegetation mapping: ultra-high resolution hierarchical classification at the individual plant level;International Journal of Remote Sensing;2024-06-26

4. LiDAR Data Fusion to Improve Forest Attribute Estimates: A Review;Current Forestry Reports;2024-06-21

5. Two-step carbon storage estimation in urban human settlements using airborne LiDAR and Sentinel-2 data based on machine learning;Urban Forestry & Urban Greening;2024-04

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