About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping
Forest height is a fundamental parameter in forestry. Tree height is widely used to assess a site’s productivity both in forest ecology research and forest management. Thus, a precise height measure represents a necessary step for the estimation of carbon storage at the local, national, and global s...
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ftdoajarticles:oai:doaj.org/article:b6e02e9817ea4a3ebb0aaec318122d34 2024-01-07T09:47:08+01:00 About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping Samuele De Petris Filippo Sarvia Enrico Borgogno-Mondino 2022-06-01T00:00:00Z https://doi.org/10.3390/f13070969 https://doaj.org/article/b6e02e9817ea4a3ebb0aaec318122d34 EN eng MDPI AG https://www.mdpi.com/1999-4907/13/7/969 https://doaj.org/toc/1999-4907 doi:10.3390/f13070969 1999-4907 https://doaj.org/article/b6e02e9817ea4a3ebb0aaec318122d34 Forests, Vol 13, Iss 7, p 969 (2022) tree height uncertainty hypsometer forest biomes variance propagation law Google Earth Engine Plant ecology QK900-989 article 2022 ftdoajarticles https://doi.org/10.3390/f13070969 2023-12-10T01:42:33Z Forest height is a fundamental parameter in forestry. Tree height is widely used to assess a site’s productivity both in forest ecology research and forest management. Thus, a precise height measure represents a necessary step for the estimation of carbon storage at the local, national, and global scales. In this context, error in height measurement necessarily affects the accuracy of related estimates. Ordinarily, forest height is surveyed by ground sampling adopting hypsometers. The latter suffers from many errors mainly related to the correct tree apex identification (not always well visible in dense stands) and to the measurement process itself. In this work, a statistically based operative method for estimating height measurement uncertainty ( <semantics> σ H </semantics> ) was proposed using the variance propagation law. Some simulations were performed involving several combinations of terrain slope, tree height, and survey distances by modelling the <semantics> σ H </semantics> behaviour and its sensitivity to such parameters. Results proved that <semantics> σ H </semantics> could vary between 0.5 m and up to 20 m (worst case). Sensitivity analysis shows that terrain slopes and distance poorly affect <semantics> σ H </semantics> , while angles are the main drivers of height uncertainty. Finally, to give a practical example of such deductions, tree height uncertainty was mapped at the global scale using Google Earth Engine and summarized per forest biomes. Results proved that tropical biomes have higher uncertainty (from 1 m to 4 m) while shrublands and tundra have the lowest (under 1 m). Article in Journal/Newspaper Tundra Directory of Open Access Journals: DOAJ Articles Forests 13 7 969 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
tree height uncertainty hypsometer forest biomes variance propagation law Google Earth Engine Plant ecology QK900-989 |
spellingShingle |
tree height uncertainty hypsometer forest biomes variance propagation law Google Earth Engine Plant ecology QK900-989 Samuele De Petris Filippo Sarvia Enrico Borgogno-Mondino About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
topic_facet |
tree height uncertainty hypsometer forest biomes variance propagation law Google Earth Engine Plant ecology QK900-989 |
description |
Forest height is a fundamental parameter in forestry. Tree height is widely used to assess a site’s productivity both in forest ecology research and forest management. Thus, a precise height measure represents a necessary step for the estimation of carbon storage at the local, national, and global scales. In this context, error in height measurement necessarily affects the accuracy of related estimates. Ordinarily, forest height is surveyed by ground sampling adopting hypsometers. The latter suffers from many errors mainly related to the correct tree apex identification (not always well visible in dense stands) and to the measurement process itself. In this work, a statistically based operative method for estimating height measurement uncertainty ( <semantics> σ H </semantics> ) was proposed using the variance propagation law. Some simulations were performed involving several combinations of terrain slope, tree height, and survey distances by modelling the <semantics> σ H </semantics> behaviour and its sensitivity to such parameters. Results proved that <semantics> σ H </semantics> could vary between 0.5 m and up to 20 m (worst case). Sensitivity analysis shows that terrain slopes and distance poorly affect <semantics> σ H </semantics> , while angles are the main drivers of height uncertainty. Finally, to give a practical example of such deductions, tree height uncertainty was mapped at the global scale using Google Earth Engine and summarized per forest biomes. Results proved that tropical biomes have higher uncertainty (from 1 m to 4 m) while shrublands and tundra have the lowest (under 1 m). |
format |
Article in Journal/Newspaper |
author |
Samuele De Petris Filippo Sarvia Enrico Borgogno-Mondino |
author_facet |
Samuele De Petris Filippo Sarvia Enrico Borgogno-Mondino |
author_sort |
Samuele De Petris |
title |
About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
title_short |
About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
title_full |
About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
title_fullStr |
About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
title_full_unstemmed |
About Tree Height Measurement: Theoretical and Practical Issues for Uncertainty Quantification and Mapping |
title_sort |
about tree height measurement: theoretical and practical issues for uncertainty quantification and mapping |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/f13070969 https://doaj.org/article/b6e02e9817ea4a3ebb0aaec318122d34 |
genre |
Tundra |
genre_facet |
Tundra |
op_source |
Forests, Vol 13, Iss 7, p 969 (2022) |
op_relation |
https://www.mdpi.com/1999-4907/13/7/969 https://doaj.org/toc/1999-4907 doi:10.3390/f13070969 1999-4907 https://doaj.org/article/b6e02e9817ea4a3ebb0aaec318122d34 |
op_doi |
https://doi.org/10.3390/f13070969 |
container_title |
Forests |
container_volume |
13 |
container_issue |
7 |
container_start_page |
969 |
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1787429101357760512 |