Cargando…
How to map forest structure from aircraft, one tree at a time
Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recogn...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010772/ https://www.ncbi.nlm.nih.gov/pubmed/29938078 http://dx.doi.org/10.1002/ece3.4089 |
_version_ | 1783333656197070848 |
---|---|
author | Dalponte, Michele Frizzera, Lorenzo Gianelle, Damiano |
author_facet | Dalponte, Michele Frizzera, Lorenzo Gianelle, Damiano |
author_sort | Dalponte, Michele |
collection | PubMed |
description | Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand‐level approaches. In this study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs’ height and crown diameter; then, using newly developed allometries, the ITCs’ diameter at breast height (DBH) and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R (2) = .85 and .78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area‐based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R (2) = .46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area‐based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics. |
format | Online Article Text |
id | pubmed-6010772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60107722018-06-22 How to map forest structure from aircraft, one tree at a time Dalponte, Michele Frizzera, Lorenzo Gianelle, Damiano Ecol Evol Original Research Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand‐level approaches. In this study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs’ height and crown diameter; then, using newly developed allometries, the ITCs’ diameter at breast height (DBH) and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R (2) = .85 and .78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area‐based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R (2) = .46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area‐based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics. John Wiley and Sons Inc. 2018-05-08 /pmc/articles/PMC6010772/ /pubmed/29938078 http://dx.doi.org/10.1002/ece3.4089 Text en © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Dalponte, Michele Frizzera, Lorenzo Gianelle, Damiano How to map forest structure from aircraft, one tree at a time |
title | How to map forest structure from aircraft, one tree at a time |
title_full | How to map forest structure from aircraft, one tree at a time |
title_fullStr | How to map forest structure from aircraft, one tree at a time |
title_full_unstemmed | How to map forest structure from aircraft, one tree at a time |
title_short | How to map forest structure from aircraft, one tree at a time |
title_sort | how to map forest structure from aircraft, one tree at a time |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010772/ https://www.ncbi.nlm.nih.gov/pubmed/29938078 http://dx.doi.org/10.1002/ece3.4089 |
work_keys_str_mv | AT dalpontemichele howtomapforeststructurefromaircraftonetreeatatime AT frizzeralorenzo howtomapforeststructurefromaircraftonetreeatatime AT gianelledamiano howtomapforeststructurefromaircraftonetreeatatime |