Accessible light detection and ranging: estimating large tree density for habitat identification
Abstract Large trees are important to a wide variety of wildlife, including many species of conservation concern, such as the California spotted owl (Strix occidentalis occidentalis). Light detection and ranging (LiDAR) has been successfully utilized to identify the density of large‐diameter trees,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-12-01
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| Series: | Ecosphere |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ecs2.1593 |
| _version_ | 1818558313507323904 |
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| author | Heather A. Kramer Brandon M. Collins Claire V. Gallagher John J. Keane Scott L. Stephens Maggi Kelly |
| author_facet | Heather A. Kramer Brandon M. Collins Claire V. Gallagher John J. Keane Scott L. Stephens Maggi Kelly |
| author_sort | Heather A. Kramer |
| collection | DOAJ |
| description | Abstract Large trees are important to a wide variety of wildlife, including many species of conservation concern, such as the California spotted owl (Strix occidentalis occidentalis). Light detection and ranging (LiDAR) has been successfully utilized to identify the density of large‐diameter trees, either by segmenting the LiDAR point cloud into individual trees, or by building regression models between variables extracted from the LiDAR point cloud and field data. Neither of these methods is easily accessible for most land managers due to the reliance on specialized software, and much available LiDAR data are being underutilized due to the steep learning curve required for advanced processing using these programs. This study derived a simple, yet effective method for estimating the density of large‐stemmed trees from the LiDAR canopy height model, a standard raster product derived from the LiDAR point cloud that is often delivered with the LiDAR and is easy to process by personnel trained in geographic information systems (GIS). Ground plots needed to be large (1 ha) to build a robust model, but the spatial accuracy of plot center was less crucial to model accuracy. We also showed that predicted large tree density is positively linked to California spotted owl nest sites. |
| first_indexed | 2024-12-14T00:11:00Z |
| format | Article |
| id | doaj.art-00dc0844807a44578a29639cbf7f911f |
| institution | Directory Open Access Journal |
| issn | 2150-8925 |
| language | English |
| last_indexed | 2024-12-14T00:11:00Z |
| publishDate | 2016-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecosphere |
| spelling | doaj.art-00dc0844807a44578a29639cbf7f911f2022-12-21T23:25:45ZengWileyEcosphere2150-89252016-12-01712n/an/a10.1002/ecs2.1593Accessible light detection and ranging: estimating large tree density for habitat identificationHeather A. Kramer0Brandon M. Collins1Claire V. Gallagher2John J. Keane3Scott L. Stephens4Maggi Kelly5Ecosystem Sciences Division Department of Environmental Science, Policy, and Management University of California 130 Mulford Hall Berkeley California 94720 USACenter for Fire Research and Outreach University of California Berkeley California 94720 USAUSDA Forest Service Pacific Southwest Research Station 1731 Research Park Drive Davis California 95618 USAUSDA Forest Service Pacific Southwest Research Station 1731 Research Park Drive Davis California 95618 USAEcosystem Sciences Division Department of Environmental Science, Policy, and Management University of California 130 Mulford Hall Berkeley California 94720 USAEcosystem Sciences Division Department of Environmental Science, Policy, and Management University of California 130 Mulford Hall Berkeley California 94720 USAAbstract Large trees are important to a wide variety of wildlife, including many species of conservation concern, such as the California spotted owl (Strix occidentalis occidentalis). Light detection and ranging (LiDAR) has been successfully utilized to identify the density of large‐diameter trees, either by segmenting the LiDAR point cloud into individual trees, or by building regression models between variables extracted from the LiDAR point cloud and field data. Neither of these methods is easily accessible for most land managers due to the reliance on specialized software, and much available LiDAR data are being underutilized due to the steep learning curve required for advanced processing using these programs. This study derived a simple, yet effective method for estimating the density of large‐stemmed trees from the LiDAR canopy height model, a standard raster product derived from the LiDAR point cloud that is often delivered with the LiDAR and is easy to process by personnel trained in geographic information systems (GIS). Ground plots needed to be large (1 ha) to build a robust model, but the spatial accuracy of plot center was less crucial to model accuracy. We also showed that predicted large tree density is positively linked to California spotted owl nest sites.https://doi.org/10.1002/ecs2.1593Californiacanopy heighthabitatlarge treelight detection and rangingspotted owl |
| spellingShingle | Heather A. Kramer Brandon M. Collins Claire V. Gallagher John J. Keane Scott L. Stephens Maggi Kelly Accessible light detection and ranging: estimating large tree density for habitat identification Ecosphere California canopy height habitat large tree light detection and ranging spotted owl |
| title | Accessible light detection and ranging: estimating large tree density for habitat identification |
| title_full | Accessible light detection and ranging: estimating large tree density for habitat identification |
| title_fullStr | Accessible light detection and ranging: estimating large tree density for habitat identification |
| title_full_unstemmed | Accessible light detection and ranging: estimating large tree density for habitat identification |
| title_short | Accessible light detection and ranging: estimating large tree density for habitat identification |
| title_sort | accessible light detection and ranging estimating large tree density for habitat identification |
| topic | California canopy height habitat large tree light detection and ranging spotted owl |
| url | https://doi.org/10.1002/ecs2.1593 |
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