Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States
Remote sensing offers many advantages to supplement traditional, ground-based forest measurements, such as limiting time in the field and fast spatial coverage. Data from airborne laser scanning (lidar) have provided accurate estimates of forest height, where, and when available. However, lidar is e...
| Autores: | ; ; ; ; ; ; ; ; ; ; ; |
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| Tipo de documento: | Artículo |
| Estado: | Published version |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Institución: | UFLA |
| Repositorio: | Repositório Institucional da UFLA |
| Lenguaje: | Inglés |
| OAI Identifier: | oai:repositorio.ufla.br:1/58765 |
| Acceso en línea: | https://repositorio.ufla.br/handle/1/58765 |
| Nivel de acceso: | Acceso abierto |
| Palabra clave: | Remote sensing Height estimation Photogrammetry Canopy height model |
| _version_ | 1878762698744791041 |
|---|---|
| author | Ritz, Alison L. |
| author2 | Thomas, Valerie A. Wynne, Randolph H. Green, P. Corey Schroeder, Todd A. Albaugh, Timothy J. Burkhart, Harold E. Carter, David R. Cook, Rachel L. Campoe, Otávio C. Rubilar, Rafael A. Rakestraw, Jim |
| author2_role | author author author author author author author author author author author |
| author_browse | Albaugh, Timothy J. Burkhart, Harold E. Campoe, Otávio C. Carter, David R. Cook, Rachel L. Green, P. Corey Rakestraw, Jim Ritz, Alison L. Rubilar, Rafael A. Schroeder, Todd A. Thomas, Valerie A. Wynne, Randolph H. |
| author_facet | Ritz, Alison L. Thomas, Valerie A. Wynne, Randolph H. Green, P. Corey Schroeder, Todd A. Albaugh, Timothy J. Burkhart, Harold E. Carter, David R. Cook, Rachel L. Campoe, Otávio C. Rubilar, Rafael A. Rakestraw, Jim |
| author_role | author |
| bitstream_url_str_mv | https://repositorio.ufla.br/bitstreams/fb2a111f-5ec9-4a89-a547-9c6c35b701ef/download https://repositorio.ufla.br/bitstreams/42cb6440-3fe0-4824-b79f-04793b146bd5/download https://repositorio.ufla.br/bitstreams/5b92c703-c81d-4bde-84da-858ccf0c3713/download |
| collection | Repositório Institucional da UFLA |
| description | Remote sensing offers many advantages to supplement traditional, ground-based forest measurements, such as limiting time in the field and fast spatial coverage. Data from airborne laser scanning (lidar) have provided accurate estimates of forest height, where, and when available. However, lidar is expensive to collect, and wall-to-wall coverage in the United States is lacking. Recent studies have investigated whether point clouds derived from digital aerial photogrammetry (DAP) can supplement lidar data for estimating forest height due to DAP’s lower costs and more frequent acquisitions. We estimated forest heights using point clouds derived from the National Agricultural Imagery Program (NAIP) DAP program in the United States to create a predicted height map for managed loblolly pine stands. For 534 plots in Virginia and North Carolina, with stand age ranging from 1 year to 42 years old, field-collected canopy heights were regressed against the 90th percentile of heights derived from NAIP point clouds. Model performance was good, with an R2 of 0.93 and an RMSE of 1.44 m. However, heights in recent heavily thinned stands were consistently underestimated, likely due to between-row shadowing leading to a poor photogrammetric solution. The model was applied to non-thinned evergreen areas in Virginia, North Carolina, and Tennessee to produce a multi-state 5 m × 5 m canopy height map. NAIP-derived point clouds are a viable means of predicting canopy height in southern pine stands that have not been thinned recently. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | BR_b5c732044c41e4e870e571dda5c8a11a |
| institution | UFLA |
| instname_str | Universidade Federal de Lavras (UFLA) |
| language | eng |
| network_acronym_str | BR |
| network_name_str | Brasil |
| oai_identifier_str | oai:repositorio.ufla.br:1/58765 |
| publishDate | 2022 |
| publishDateSort | 2022 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| reponame_str | Repositório Institucional da UFLA |
| spelling | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States Ritz, Alison L. Thomas, Valerie A. Wynne, Randolph H. Green, P. Corey Schroeder, Todd A. Albaugh, Timothy J. Burkhart, Harold E. Carter, David R. Cook, Rachel L. Campoe, Otávio C. Rubilar, Rafael A. Rakestraw, Jim Remote sensing Height estimation Photogrammetry Canopy height model Remote sensing offers many advantages to supplement traditional, ground-based forest measurements, such as limiting time in the field and fast spatial coverage. Data from airborne laser scanning (lidar) have provided accurate estimates of forest height, where, and when available. However, lidar is expensive to collect, and wall-to-wall coverage in the United States is lacking. Recent studies have investigated whether point clouds derived from digital aerial photogrammetry (DAP) can supplement lidar data for estimating forest height due to DAP’s lower costs and more frequent acquisitions. We estimated forest heights using point clouds derived from the National Agricultural Imagery Program (NAIP) DAP program in the United States to create a predicted height map for managed loblolly pine stands. For 534 plots in Virginia and North Carolina, with stand age ranging from 1 year to 42 years old, field-collected canopy heights were regressed against the 90th percentile of heights derived from NAIP point clouds. Model performance was good, with an R2 of 0.93 and an RMSE of 1.44 m. However, heights in recent heavily thinned stands were consistently underestimated, likely due to between-row shadowing leading to a poor photogrammetric solution. The model was applied to non-thinned evergreen areas in Virginia, North Carolina, and Tennessee to produce a multi-state 5 m × 5 m canopy height map. NAIP-derived point clouds are a viable means of predicting canopy height in southern pine stands that have not been thinned recently. Elsevier RITZ, A. L. et al. Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States. International Journal of Applied Earth Observation and Geoinformation, [S.l.], v. 113, p. 1-13, Sept. 2022. DOI: 10.1016/j.jag.2022.103012. https://repositorio.ufla.br/handle/1/58765 |
| spellingShingle | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States Ritz, Alison L. Remote sensing Height estimation Photogrammetry Canopy height model |
| status_str | publishedVersion |
| title | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| title_full | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| title_fullStr | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| title_full_unstemmed | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| title_short | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| title_sort | Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States |
| topic | Remote sensing Height estimation Photogrammetry Canopy height model |
| topic_facet | Remote sensing Height estimation Photogrammetry Canopy height model |
| url | https://repositorio.ufla.br/handle/1/58765 |