{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T04:26:30Z","timestamp":1776140790727,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T00:00:00Z","timestamp":1469404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012287","name":"Andrew Sabin Family Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012287","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Winston Salem Foundation"},{"DOI":"10.13039\/100001451","name":"Amazon Conservation Association","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001451","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Unmanned aerial vehicles (UAVs) can provide new ways to measure forests and supplement expensive or labor-intensive inventory methods. Forest carbon, a key uncertainty in the global carbon cycle and also important for carbon conservation programs, is typically monitored using manned aircraft or extensive forest plot networks to estimate aboveground carbon density (ACD). Manned aircraft are only cost-effective when applied to large areas (&gt;100,000 ha), while plot networks are most effective for total C stock estimation across large areas, not for quantifying spatially-explicit variation. We sought to develop an effective method for frequent and accurate ACD estimation at intermediate scales (100\u2013100,000 ha) that would be sensitive to small-scale disturbance. Using small UAVs, we collected imagery of 516 ha of lowland forest in the Peruvian Amazon. We then used a structure-from-motion (SFM) approach to create a 3D model of forest canopy. Comparing SFM- and airborne Light Detection and Ranging (LiDAR)-derived estimates of canopy height and ACD, we found that SFM estimates of top-of-canopy height (TCH) and ACD were highly correlated with previous LiDAR estimates (r = 0.86\u20130.93 and r = 0.73\u20130.94 for TCH and ACD, respectively, at 0.1\u20134 ha grain sizes), with r = 0.92 for ACD determination at the 1 ha scale, despite SFM and LiDAR measurements being separated by two years in a dynamic forest. SFM and LiDAR estimates of mean TCH and mean ACD were highly similar, differing by only 0.4% and 0.04%, respectively, within mature forest. The technique allows inexpensive, near-real-time monitoring of ACD for ecological studies, payment for ecosystem services (PES) ventures, such as reducing emissions from deforestation and forest degradation (REDD+), forestry enterprises, and governance.<\/jats:p>","DOI":"10.3390\/rs8080615","type":"journal-article","created":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T10:04:26Z","timestamp":1469441066000},"page":"615","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":87,"title":["Rapid Assessments of Amazon Forest Structure and Biomass Using Small Unmanned Aerial Systems"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8646-9042","authenticated-orcid":false,"given":"Max","family":"Messinger","sequence":"first","affiliation":[{"name":"Department of Biology, Wake Forest University, 1834 Wake Forest Rd, Winston Hall, Winston-Salem, NC 27109, USA"},{"name":"Center for Energy, Environment, and Sustainability, Wake Forest University, 1834 Wake Forest Rd., Winston-Salem, NC 27109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7893-6421","authenticated-orcid":false,"given":"Gregory","family":"Asner","sequence":"additional","affiliation":[{"name":"Department of Global Ecology, Carnegie Institution for Science, 260 Panama St, Stanford, CA 94305, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miles","family":"Silman","sequence":"additional","affiliation":[{"name":"Department of Biology, Wake Forest University, 1834 Wake Forest Rd, Winston Hall, Winston-Salem, NC 27109, USA"},{"name":"Center for Energy, Environment, and Sustainability, Wake Forest University, 1834 Wake Forest Rd., Winston-Salem, NC 27109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1038\/ngeo671","article-title":"CO2 emissions from forest loss","volume":"2","author":"Morton","year":"2009","journal-title":"Nat. Geosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1111\/j.1755-263X.2008.00011.x","article-title":"Is oil palm agriculture really destroying tropical biodiversity?","volume":"1","author":"Koh","year":"2008","journal-title":"Conserv. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1046\/j.1523-1739.2001.01089.x","article-title":"Synergistic effects of subsistence hunting and habitat fragmentation on Amazonian forest vertebrates","volume":"15","author":"Peres","year":"2001","journal-title":"Conserv. Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ecoleng.2015.09.075","article-title":"Reforestation with four native tree species after abandoned gold mining in the Peruvian Amazon","volume":"85","author":"Huayllani","year":"2015","journal-title":"Ecol. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1126\/science.1117682","article-title":"Species loss and aboveground carbon storage in a tropical forest","volume":"310","author":"Bunker","year":"2005","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1016\/j.cosust.2012.09.013","article-title":"Synergies of multiple remote sensing data sources for REDD+ monitoring","volume":"4","author":"Herold","year":"2012","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1038\/nclimate1354","article-title":"Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps","volume":"2","author":"Baccini","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1080\/17538947.2014.990526","article-title":"A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems","volume":"9","author":"Lu","year":"2014","journal-title":"Int. J. Digit. Earth"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1111\/j.1461-0248.2008.01169.x","article-title":"Clustered disturbances lead to bias in large-scale estimates based on forest sample plots","volume":"11","author":"Fisher","year":"2008","journal-title":"Ecol. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"E5224","DOI":"10.1073\/pnas.1412999111","article-title":"Amazonian landscapes and the bias in field studies of forest structure and biomass","volume":"111","author":"Marvin","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1016\/j.rse.2009.11.002","article-title":"Fusion of LiDAR and imagery for estimating forest canopy fuels","volume":"114","author":"Erdody","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.rse.2013.04.005","article-title":"High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision","volume":"136","author":"Dandois","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1126\/science.1070656","article-title":"Determination of deforestation rates of the world\u2019s humid tropical forests","volume":"297","author":"Achard","year":"2002","journal-title":"Science"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2540","DOI":"10.1111\/gcb.12605","article-title":"Determination of tropical deforestation rates and related carbon losses from 1990 to 2010","volume":"20","author":"Achard","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"18454","DOI":"10.1073\/pnas.1318271110","article-title":"Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring","volume":"110","author":"Asner","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"033543","DOI":"10.1117\/1.3223675","article-title":"Automated mapping of tropical deforestation and forest degradation: CLASlite","volume":"3","author":"Asner","year":"2009","journal-title":"J. Appl. Remote Sens."},{"key":"ref_17","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_18","doi-asserted-by":"crossref","unstructured":"Swenson, J.J., Carter, C.E., Domec, J.-C., and Delgado, C.I. (2011). Gold mining in the Peruvian Amazon: Global prices, deforestation, and mercury imports. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0018875"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Finer, M., and Novoa, S. MAAP Synthesis #1: Patterns and Drivers of Deforestation in the Peruvian Amazon. Available online: http:\/\/maaproject.org\/2015\/maap-synthesis1\/.","DOI":"10.1002\/9783527678679.dg07075"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1177\/194008291200500202","article-title":"Dawn of drone ecology: low-cost autonomous aerial vehicles for conservation","volume":"5","author":"Koh","year":"2012","journal-title":"Trop. Conserv. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1890\/120150","article-title":"Lightweight unmanned aerial vehicles will revolutionize spatial ecology","volume":"11","author":"Anderson","year":"2013","journal-title":"Front. Ecol. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s11263-007-0107-3","article-title":"Modeling the world from Internet photo collections","volume":"80","author":"Snavely","year":"2008","journal-title":"Int. J. Comput. Vis."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.3390\/rs2041157","article-title":"Remote sensing of vegetation structure using computer vision","volume":"2","author":"Dandois","year":"2010","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"922","DOI":"10.3390\/f4040922","article-title":"A Photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery","volume":"4","author":"Lisein","year":"2013","journal-title":"Forests"},{"key":"ref_25","first-page":"131","article-title":"Measuring forest canopy height using a combination of LiDAR and aerial photography data","volume":"XXXIV-3\/W4","author":"Achaichia","year":"2001","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"9632","DOI":"10.3390\/rs70809632","article-title":"Inventory of small forest areas using an unmanned aerial system","volume":"7","author":"Puliti","year":"2015","journal-title":"Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3390\/f7030062","article-title":"Assessment of forest structure using two UAV techniques: A comparison of airborne laser scanning and structure from motion (SfM) point clouds","volume":"7","author":"Wallace","year":"2016","journal-title":"Forests"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.rse.2012.06.012","article-title":"Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion","volume":"124","author":"Asner","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.rse.2013.09.023","article-title":"Mapping tropical forest carbon: Calibrating plot estimates to a simple LiDAR metric","volume":"140","author":"Asner","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13895","DOI":"10.3390\/rs71013895","article-title":"Optimal altitude, overlap, and weather conditions for computer vision UAV estimates of forest structure","volume":"7","author":"Dandois","year":"2015","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"16738","DOI":"10.1073\/pnas.1004875107","article-title":"High-resolution forest carbon stocks and emissions in the Amazon","volume":"107","author":"Asner","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3770","DOI":"10.1016\/j.rse.2011.07.019","article-title":"Evaluating uncertainty in mapping forest carbon with airborne LiDAR","volume":"115","author":"Mascaro","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s00442-005-0100-x","article-title":"Tree allometry and improved estimation of carbon stocks and balance in tropical forests","volume":"145","author":"Chave","year":"2005","journal-title":"Oecologia"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1007\/s00442-011-2165-z","article-title":"A universal airborne LiDAR approach for tropical forest carbon mapping","volume":"168","author":"Asner","year":"2012","journal-title":"Oecologia"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1111\/geb.12168","article-title":"Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites","volume":"23","author":"Mitchard","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.1890\/12-0371.1","article-title":"Landscape-scale forest disturbance regimes in Southern Peruvian Amazonia","volume":"23","author":"Boyd","year":"2013","journal-title":"Ecol. Appl."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3949","DOI":"10.1073\/pnas.1202894110","article-title":"The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape","volume":"110","author":"Chambers","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_38","unstructured":"Gaulton, R., Taylor, J., and Watkins, N. Unmanned Aerial Vehicles for Pre-Harvest Biomass Estimation in Willow (Salix spp.) Coppice Plantations. Available online: https:\/\/geouav.teledetection.fr\/papers\/GEOSPATIAL_WEEK_2015_284.pdf."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"034009","DOI":"10.1088\/1748-9326\/4\/3\/034009","article-title":"Tropical forest carbon assessment: Integrating satellite and airborne mapping approaches","volume":"4","author":"Asner","year":"2009","journal-title":"Environ. Res. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2738","DOI":"10.1109\/TGRS.2013.2265295","article-title":"Direct georeferencing of ultrahigh-resolution UAV imagery","volume":"52","author":"Turner","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","first-page":"1225","article-title":"Assessment of C-band SRTM DEM in a dense equatorial forest zone","volume":"337","author":"Bourgine","year":"2005","journal-title":"Extern. Geophys. Clim. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.rse.2016.05.019","article-title":"Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry","volume":"183","author":"Cunliffe","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1111\/j.2041-210X.2011.00158.x","article-title":"Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles","volume":"3","author":"Getzin","year":"2012","journal-title":"Methods Ecol. Evol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"035005","DOI":"10.1088\/1748-9326\/3\/3\/035005","article-title":"Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates","volume":"3","author":"Grassi","year":"2008","journal-title":"Environ. Res. Lett."},{"key":"ref_45","unstructured":"Angelsen, A., Brown, S., Loisel, C., Peskett, L., Streck, C., and Zarin, D. (2009). Reducing Emissions from Deforestation and Forest Degradation (REDD): An Options Assessment Report, Food and Agriculture Organization of the United Nations (FAO). International Information System for the Agricultural Science and Technology (AGRIS)."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/8\/615\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:26:57Z","timestamp":1760210817000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/8\/615"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,25]]},"references-count":45,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2016,8]]}},"alternative-id":["rs8080615"],"URL":"https:\/\/doi.org\/10.3390\/rs8080615","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,7,25]]}}}