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We extrapolated the vertical complexity captured by the Land, Vegetation, and Ice Sensor (LVIS) full-wave form LiDAR of boreal forests in the Alaska\u2013Yukon\u2013Northwest Territories region, utilizing predictors from Landsat images from 1989 to 2019. This included both single-year and long-term estimates of vegetation indices, alongside constant factors like terrain slope and location. Random forest regression models comparing the single-year and 15-year and 30-year time series models were applied. Additionally, the potential of estimating horizontal forest complexity from vertical complexity was explored using a moving window approach in the Kluane Valley. While the extended time series marginally enhanced model accuracy, a fine-tuned single-year model proved superior (R2 = 0.84, relative RRMSE = 8.4%). In estimating the horizontal complexity, the variance in a 5 \u00d7 5 moving window displayed the most promising results, aligning with traditional horizontal structure measures. Single-year Landsat models could potentially surpass time series models in predicting forest vertical complexity, with the added capability to estimate horizontal complexity using variance in a moving window approach.<\/jats:p>","DOI":"10.3390\/rs15225274","type":"journal-article","created":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T11:25:31Z","timestamp":1699356331000},"page":"5274","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Bridging the Gap: Comprehensive Boreal Forest Complexity Mapping through LVIS Full-Waveform LiDAR, Single-Year and Time Series Landsat Imagery"],"prefix":"10.3390","volume":"15","author":[{"given":"Nicolas","family":"Diaz-Kloch","sequence":"first","affiliation":[{"name":"Environmental and Life Sciences Graduate Program, Trent University, Peterborough, ON K9J 7B8, Canada"}]},{"given":"Dennis L.","family":"Murray","sequence":"additional","affiliation":[{"name":"Department of Biology, Trent University, Peterborough, ON K9J 7B8, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1126\/science.1201609","article-title":"A large and persistent carbon sink in the world\u2019s forests","volume":"333","author":"Pan","year":"2011","journal-title":"Science"},{"key":"ref_2","first-page":"480","article-title":"Mapping and monitoring carbon stocks with satellite observations: A comparison of methods","volume":"19","author":"Goetz","year":"2009","journal-title":"Carbon Balance Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/1750-0680-6-13","article-title":"Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+","volume":"6","author":"Herold","year":"2011","journal-title":"Carbon Balance Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-resolution global maps of 21st-century forest cover change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"521","DOI":"10.5589\/m14-004","article-title":"Interpretation of forest disturbance using a time series of Landsat imagery and canopy structure from airborne lidar","volume":"39","author":"Ahmed","year":"2014","journal-title":"Can. 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