{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T03:38:03Z","timestamp":1773200283120,"version":"3.50.1"},"reference-count":112,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,12]],"date-time":"2018-03-12T00:00:00Z","timestamp":1520812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA) to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg\/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.<\/jats:p>","DOI":"10.3390\/rs10030442","type":"journal-article","created":{"date-parts":[[2018,3,12]],"date-time":"2018-03-12T13:13:48Z","timestamp":1520860428000},"page":"442","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA"],"prefix":"10.3390","volume":"10","author":[{"given":"Karis","family":"Tenneson","sequence":"first","affiliation":[{"name":"RedCastle Resources, Inc. Contractor to USDA Forest Service Geospatial Technology and Applications Center, Salt Lake City, UT 84119, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8199-3328","authenticated-orcid":false,"given":"Matthew","family":"Patterson","sequence":"additional","affiliation":[{"name":"RedCastle Resources, Inc. Contractor to USDA Forest Service Geospatial Technology and Applications Center, Salt Lake City, UT 84119, USA"},{"name":"Department of Urban Design and Planning, College of the Built Environment, University of Washington, Seattle, WA 98195, USA"}]},{"given":"Thomas","family":"Mellin","sequence":"additional","affiliation":[{"name":"USDA Forest Service, Southwestern Regional Office, Albuquerque, NM 87102, USA"}]},{"given":"Mark","family":"Nigrelli","sequence":"additional","affiliation":[{"name":"USDA Forest Service, Coconino National Forest, Flagstaff, AZ 86001, USA"}]},{"given":"Peter","family":"Joria","sequence":"additional","affiliation":[{"name":"USDA Forest Service, Southwestern Regional Office, Albuquerque, NM 87102, USA"}]},{"given":"Brent","family":"Mitchell","sequence":"additional","affiliation":[{"name":"RedCastle Resources, Inc. Contractor to USDA Forest Service Geospatial Technology and Applications Center, Salt Lake City, UT 84119, USA"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1111\/j.1523-1739.2004.521_1.x","article-title":"Forest restoration and fire: Principles in the context of place","volume":"18","author":"Brown","year":"2004","journal-title":"Conserv. Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7537","DOI":"10.1038\/ncomms8537","article-title":"Climate-induced variations in global wildfire danger from 1979 to 2013","volume":"6","author":"Jolly","year":"2015","journal-title":"Nat. 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