{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T03:00:47Z","timestamp":1774494047748,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T00:00:00Z","timestamp":1689120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]},{"name":"NISAR mission","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]},{"name":"National Science Foundation","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]},{"name":"Smithsonian Institution","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]},{"name":"National Zoological Park","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]},{"name":"HSBC Climate Partnership","award":["80NM0018D0004"],"award-info":[{"award-number":["80NM0018D0004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Emerging satellite radar and lidar platforms are being developed to produce gridded aboveground biomass (AGB) predictions that are poised to expand our understanding of global carbon stocks and changes. However, the spatial resolution of AGB map products from these platforms is often larger than the available field plot data underpinning model calibration and validation efforts. Intermediate-resolution\/extent remotely sensed data, like airborne lidar, can serve as a bridge between small plots and map resolution, but methods are needed to estimate and propagate uncertainties with multiple layers of data. Here, we introduce a workflow to estimate the pixel-level mean and variance in AGB maps by propagating uncertainty from a lidar-based model using small plots, taking into account prediction uncertainty, residual uncertainty, and residual spatial autocorrelation. We apply this workflow to estimate AGB uncertainty at a 100 m map resolution (1 ha pixels) using 0.04 ha field plots from 11 sites across four ecoregions. We compare uncertainty estimates using site-specific models, ecoregion-specific models, and a general model using all sites. The estimated AGB uncertainty for 1 ha pixels increased with mean AGB, reaching 7.8\u201333.3 Mg ha\u22121 for site-specific models (one standard deviation), 11.1\u201328.2 Mg ha\u22121 for ecoregion-specific models, and 21.1\u201322.1 Mg ha\u22121 for the general model for pixels in the AGB range of 80\u2013100 Mg ha\u22121. Only 3 of 11 site-specific models had a total uncertainty of &lt;15 Mg ha\u22121 in this biomass range, suitable for the calibration or validation of AGB map products. Using two additional sites with larger field plots, we show that lidar-based models calibrated with larger field plots can substantially reduce 1 ha pixel AGB uncertainty for the same range from 18.2 Mg ha\u22121 using 0.04 ha plots to 10.9 Mg ha\u22121 using 0.25 ha plots and 10.1 Mg ha\u22121 using 1 ha plots. We conclude that the estimated AGB uncertainty from models estimated from small field plots may be unacceptably large, and we recommend coordinated efforts to measure larger field plots as reference data for the calibration or validation of satellite-based map products at landscape scales (\u22650.25 ha).<\/jats:p>","DOI":"10.3390\/rs15143509","type":"journal-article","created":{"date-parts":[[2023,7,13]],"date-time":"2023-07-13T01:52:25Z","timestamp":1689213145000},"page":"3509","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Small Field Plots Can Cause Substantial Uncertainty in Gridded Aboveground Biomass Products from Airborne Lidar Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3464-1151","authenticated-orcid":false,"given":"K. C.","family":"Cushman","sequence":"first","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA"}]},{"given":"Sassan","family":"Saatchi","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA"}]},{"given":"Ronald E.","family":"McRoberts","sequence":"additional","affiliation":[{"name":"Raspberry Ridge Analytics, Hugo, MN 55038, USA"},{"name":"Department of Forest Resources, University of Minnesota, Saint Paul, MN 55108, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8461-9713","authenticated-orcid":false,"given":"Kristina J.","family":"Anderson-Teixeira","sequence":"additional","affiliation":[{"name":"Conservation Ecology Center, Smithsonian\u2019s National Zoo and Conservation Biology Institute, Front Royal, VA 22630, USA"},{"name":"Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Panama City 0843-03092, Panama"}]},{"given":"Norman A.","family":"Bourg","sequence":"additional","affiliation":[{"name":"Conservation Ecology Center, Smithsonian\u2019s National Zoo and Conservation Biology Institute, Front Royal, VA 22630, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6054-7695","authenticated-orcid":false,"given":"Bruce","family":"Chapman","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8302-6908","authenticated-orcid":false,"given":"Sean M.","family":"McMahon","sequence":"additional","affiliation":[{"name":"Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Panama City 0843-03092, Panama"},{"name":"Smithsonian Environmental Research Center, Edgewater, MD 21037, USA"}]},{"given":"Christopher","family":"Mulverhill","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA"},{"name":"Department of Forest Resources Management, University of British Columbia, Vancouver, BC V6T 1Z4, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"eabe9829","DOI":"10.1126\/sciadv.abe9829","article-title":"Changes in Global Terrestrial Live Biomass over the 21st Century","volume":"7","author":"Xu","year":"2021","journal-title":"Sci. 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