{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T22:43:25Z","timestamp":1774046605237,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,15]],"date-time":"2022-06-15T00:00:00Z","timestamp":1655251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute for Energy Solutions at the University of Arizona","award":["80NSSC18K0617"],"award-info":[{"award-number":["80NSSC18K0617"]}]},{"name":"Institute for Energy Solutions at the University of Arizona","award":["80NSSC21K1516"],"award-info":[{"award-number":["80NSSC21K1516"]}]},{"name":"Institute for Energy Solutions at the University of Arizona","award":["2017-68005-26867"],"award-info":[{"award-number":["2017-68005-26867"]}]},{"name":"NASA","award":["80NSSC18K0617"],"award-info":[{"award-number":["80NSSC18K0617"]}]},{"name":"NASA","award":["80NSSC21K1516"],"award-info":[{"award-number":["80NSSC21K1516"]}]},{"name":"NASA","award":["2017-68005-26867"],"award-info":[{"award-number":["2017-68005-26867"]}]},{"name":"NASA","award":["80NSSC18K0617"],"award-info":[{"award-number":["80NSSC18K0617"]}]},{"name":"NASA","award":["80NSSC21K1516"],"award-info":[{"award-number":["80NSSC21K1516"]}]},{"name":"NASA","award":["2017-68005-26867"],"award-info":[{"award-number":["2017-68005-26867"]}]},{"DOI":"10.13039\/100005825","name":"Sustainable Bioeconomy for Arid Regions (SBAR) USDA National Institute of Food and Agriculture (NIFA)","doi-asserted-by":"publisher","award":["80NSSC18K0617"],"award-info":[{"award-number":["80NSSC18K0617"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005825","name":"Sustainable Bioeconomy for Arid Regions (SBAR) USDA National Institute of Food and Agriculture (NIFA)","doi-asserted-by":"publisher","award":["80NSSC21K1516"],"award-info":[{"award-number":["80NSSC21K1516"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005825","name":"Sustainable Bioeconomy for Arid Regions (SBAR) USDA National Institute of Food and Agriculture (NIFA)","doi-asserted-by":"publisher","award":["2017-68005-26867"],"award-info":[{"award-number":["2017-68005-26867"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Guayule (Parthenium argentatum Gray) is a perennial desert shrub currently under investigation as a viable commercial alternative to the Par\u00e1 rubber tree (Hevea brasiliensis), the traditional source of natural rubber. Previous studies on guayule have shown a close association between morphological traits or biomass and rubber content. We collected multispectral and RGB-derived Structure-from-motion (SfM) data using an unmanned aircraft system (UAS; drone) to determine if incorporating both high-resolution normalized difference vegetation index (NDVI; an indicator of plant health) and canopy height (CH) information could support model predictions of crop productivity. Ground-truth resource allocation in guayule was measured at four elevations (i.e., tiers) along the crop\u2019s vertical profile using both traditional biomass measurement techniques and a novel volumetric measurement technique. Multiple linear regression models estimating fresh weight (FW), dry weight (DW), fresh volume (FV), fresh-weight-density (FWD), and dry-weight-density (DWD) were developed and their performance compared. Of the crop productivity measures considered, a model predicting FWD (i.e., the fresh weight of plant material adjusted by its freshly harvested volume) and incorporating NDVI, CH, NDVI:CH interaction, and tier parameters reported the lowest mean absolute percentage error (MAPE) between field measurements and predictions, ranging from 9 to 13%. A reduced FWD model incorporating only NDVI and tier parameters was developed to explore the scalability of model predictions to medium spatial resolutions with Sentinel-2 satellite data. Across all UAS surveys and corresponding satellite imagery compared, MAPE between FWD model predictions for UAS and satellite data were below 3% irrespective of soil pixel influence.<\/jats:p>","DOI":"10.3390\/rs14122867","type":"journal-article","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T03:01:22Z","timestamp":1655348482000},"page":"2867","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Estimating Productivity Measures in Guayule Using UAS Imagery and Sentinel-2 Satellite Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2583-5149","authenticated-orcid":false,"given":"Truman P.","family":"Combs","sequence":"first","affiliation":[{"name":"Vegetation Index & Phenology (VIP) Laboratory, The University of Arizona, Tucson, AZ 85721, USA"},{"name":"Biosystems Engineering Department, University of Arizona, Tucson, AZ 85719, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kamel","family":"Didan","sequence":"additional","affiliation":[{"name":"Vegetation Index & Phenology (VIP) Laboratory, The University of Arizona, Tucson, AZ 85721, USA"},{"name":"Biosystems Engineering Department, University of Arizona, Tucson, AZ 85719, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Dierig","sequence":"additional","affiliation":[{"name":"Guayule Research Farm, Bridgestone Americas, Inc., Eloy, AZ 85131, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher J.","family":"Jarchow","sequence":"additional","affiliation":[{"name":"Biosystems Engineering Department, University of Arizona, Tucson, AZ 85719, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Armando","family":"Barreto-Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Vegetation Index & Phenology (VIP) Laboratory, The University of Arizona, Tucson, AZ 85721, USA"},{"name":"Biosystems Engineering Department, University of Arizona, Tucson, AZ 85719, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"012022","DOI":"10.1088\/1755-1315\/275\/1\/012022","article-title":"A Review on the Use of Drones for Precision Agriculture","volume":"275","author":"Daponte","year":"2019","journal-title":"IOP Conf. 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