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Estimation of mean dominant height using NAIP digital aerial photogrammetry and lidar over mixed deciduous forest in the southeastern USA

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dc.contributor.authorPrior, Elizabeth M.en
dc.contributor.authorThomas, Valerie A.en
dc.contributor.authorWynne, Randolph H.en
dc.coverage.countryUnited Statesen
dc.date.accessioned2022-12-15T13:42:49Zen
dc.date.available2022-12-15T13:42:49Zen
dc.date.issued2022-06en
dc.description.abstractIn the absence of complete lidar coverage, digital surface models (DSMs) and point clouds produced from the United States Department of Agriculture National Agriculture Imagery Program (NAIP) are increasingly being analyzed for quality and application feasibility. This study compared canopy heights derived from NAIP DSMs (10 m) and point clouds to those derived from lidar data collected over Mountain Lake Biological Station and the Great Smoky Mountains Twin Creeks Site by the National Ecological Observatory Network (NEON) Airborne Observation Platform for 62 mixed deciduous tree plots. Mean dominant height (MDH) was estimated using lidar and the NAIP products using the 90th percentile of heights in a given plot as the independent variable for both the lidar-and NAIP-derived point clouds. The dependent variable was field-measured MDH, calculated using the four tallest trees for each 0.04-hectare plot based on the NEON woody vegetation structure dataset. All data (field and remotely sensed) were collected in 2018. Using maximum likelihood spatial error model for all analyses, the NAIP DSM (10 m resolution) resulted in a strong relationship with MDH (coefficient of determination (R-2) = 0.90, standard error (SE) = 1.71 m). However, the 90th percentiles of heights derived from the point clouds were better at estimating MDH than was the comparatively coarse resolution DSM (NAIP point clouds: R-2 = 0.94, SE = 1.40 m; lidar: R-2 = 0.95, SE= 1.29 m, respectively) and are strongly correlated to each other (R-2 = 0.99, SE = 0.68 m). The main limitation of the NAIP datasets was found to be where shadowing occurred due to steep terrain in the Great Smoky Mountain site. These areas resulted in erroneously high vegetation heights. Mean dominant heights estimated using NAIP DSMs and point clouds are thus comparable to those estimated using lidar data in these closed-canopy temperate deciduous forests where shadowing from steep terrain is not present. The utility of both the NAIP-derived 10 m DSM and the point clouds for estimating tree heights paves the way for statewide mapping of heights over the deciduous forests in Tennessee, Virginia, and possibly beyond.en
dc.description.notesThis work was supported by the Virginia Tech Interdisciplinary Graduate Education Program in Remote Sensing and the National Sci-ence Graduate Research Fellowship Program under Grant No.1840995. The authors would like to acknowledge Margaret Cumberland (NEON Field Ecologist II) for her guidance on the NEON woody structure data. Special thanks to the university departments for ensuring access to re-sources during the COVID-19 pandemic.en
dc.description.sponsorshipVirginia Tech Interdisciplinary Graduate Education Program in Remote Sensing and the National Science Graduate Research Fellowship Program [1840995]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1016/j.jag.2022.102813en
dc.identifier.eissn1872-826Xen
dc.identifier.issn1569-8432en
dc.identifier.other102813en
dc.identifier.urihttp://hdl.handle.net/10919/112903en
dc.identifier.volume110en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectForestryen
dc.subjectLidaren
dc.subjectAirborne laser scanningen
dc.subjectDigital aerial photogrammetryen
dc.subjectMean dominant heighten
dc.titleEstimation of mean dominant height using NAIP digital aerial photogrammetry and lidar over mixed deciduous forest in the southeastern USAen
dc.title.serialInternational Journal of Applied Earth Observation and Geoinformationen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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