{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T01:44:55Z","timestamp":1782179095156,"version":"3.54.5"},"reference-count":63,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T00:00:00Z","timestamp":1648598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"David H. Smith Conservation Research Fellowship","award":["Fellowship Awardee: Dr. Mallika Nocco"],"award-info":[{"award-number":["Fellowship Awardee: Dr. Mallika Nocco"]}]},{"name":"Wisconsin Potato and Vegetable Grower Association Water Task Force","award":["Grant Awardee: Dr. Mallika Nocco"],"award-info":[{"award-number":["Grant Awardee: Dr. Mallika Nocco"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recent advancements in remotely piloted aircrafts (RPAs) have made frequent, low-flying imagery collection more economical and feasible than ever before. The goal of this work was to create, compare, and quantify uncertainty associated with evapotranspiration (ET) maps generated from different conditions and image capture elevations. We collected optical and thermal data from a commercially irrigated potato (Solanum tuberosum) field in the Wisconsin Central Sands using a quadcopter RPA system and combined multispectral\/thermal camera. We conducted eight mission sets (24 total missions) during the 2019 growing season. Each mission set included flights at 90, 60, and 30 m above ground level. Ground reference measurements of surface temperature and soil moisture were collected throughout the domain within 15 min of each RPA mission set. Evapotranspiration values were modeled from the flight data using the High-Resolution Mapping of Evapotranspiration (HRMET) model. We compared HRMET-derived ET estimates to an Eddy Covariance system within the flight domain. Additionally, we assessed uncertainty for each flight using a Monte Carlo approach. Results indicate that the primary source of uncertainty in ET estimates was the optical and thermal data. Despite some additional detectable features at low elevation, we conclude that the tradeoff in resources and computation does not currently justify low elevation flights for annual vegetable crop management in the Midwest USA.<\/jats:p>","DOI":"10.3390\/rs14071660","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T21:28:39Z","timestamp":1648675719000},"page":"1660","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["How High to Fly? Mapping Evapotranspiration from Remotely Piloted Aircrafts at Different Elevations"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4685-7419","authenticated-orcid":false,"given":"Logan A.","family":"Ebert","sequence":"first","affiliation":[{"name":"Department of Land, Air, and Water Resources, University of California-Davis, One Shields Ave., Davis, CA 95616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ammara","family":"Talib","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Wisconsin\u2013Madison, 1415 Engineering Dr., Madison, WI 53706, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8735-5757","authenticated-orcid":false,"given":"Samuel C.","family":"Zipper","sequence":"additional","affiliation":[{"name":"Kansas Geological Survey, Department of Geology, University of Kansas, 1930 Constant Ave., Lawrence, KS 66047, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5226-6041","authenticated-orcid":false,"given":"Ankur R.","family":"Desai","sequence":"additional","affiliation":[{"name":"Department of Atmospheric and Ocean Sciences, University of Wisconsin\u2013Madison, 1225 W Dayton St., Madison, WI 53706, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyaw Tha","family":"Paw U","sequence":"additional","affiliation":[{"name":"Department of Land, Air, and Water Resources, University of California-Davis, One Shields Ave., Davis, CA 95616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex J.","family":"Chisholm","sequence":"additional","affiliation":[{"name":"Wysocki Farm Company, 6320 Third Ave., Plainfield, WI 54966, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob","family":"Prater","sequence":"additional","affiliation":[{"name":"Department of Soils and Water Resources, University of Wisconsin\u2013Stevens Point, 800 Reserve St., Stevens Point, WI 54481, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6067-8759","authenticated-orcid":false,"given":"Mallika A.","family":"Nocco","sequence":"additional","affiliation":[{"name":"Department of Land, Air, and Water Resources, University of California-Davis, One Shields Ave., Davis, CA 95616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,30]]},"reference":[{"key":"ref_1","unstructured":"US Geological Survey (2015). Estimated Use of Water in the United States in 2015."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1023\/A:1009808118692","article-title":"Fertilizers and the environment","volume":"55","author":"Park","year":"1999","journal-title":"Nutr. Cycl. Agroecosyst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bai, Y.-C., Chang, Y.-Y., Hussain, M., Lu, B., Zhang, J.-P., Song, X.-B., Lei, X.-S., and Pei, D. (2020). Soil Chemical and Microbiological Properties Are Changed by Long-Term Chemical Fertilizers That limit Ecosystems Functioning. Microorganisms, 8.","DOI":"10.3390\/microorganisms8050694"},{"key":"ref_4","first-page":"43","article-title":"Precision irrigation and its prospect analysis","volume":"43","author":"Liu","year":"2006","journal-title":"Water Sav. Irrig."},{"key":"ref_5","first-page":"371","article-title":"Opportunities for conservation with precision irrigation","volume":"60","author":"Sadler","year":"2005","journal-title":"J. Soil Water Conserv."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s10705-017-9853-y","article-title":"Irrigation and nitrogen managements affect nitrogen leaching and root yield of sugar beet","volume":"108","author":"Barzegari","year":"2017","journal-title":"Nutr. Cycl. Agroecosyst."},{"key":"ref_7","unstructured":"Hedley, C., Yule, I., and Bradbury, S. (2010, January 6\u20139). Analysis of potential benefits of precision irrigation for variable soils at five pastoral and arable production sites in New Zealand. Proceedings of the 19th World Soil Congress, Brisbane, Australia."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Liang, Z., Liu, X., Xiong, J., and Xiao, J. (2020). Water Allocation and Integrative Management of Precision Irrigation: A Systematic Review. Water, 12.","DOI":"10.3390\/w12113135"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Nocco, M.A., Zipper, S.C., Booth, E.G., Cummings, C.R., Ii, S.P.L., and Kucharik, C.J. (2019). Combining Evapotranspiration and Soil Apparent Electrical Conductivity Mapping to Identify Potential Precision Irrigation Benefits. Remote Sens., 11.","DOI":"10.3390\/rs11212460"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"677","DOI":"10.13031\/2013.22000","article-title":"Comparison of site-specific and conventional uniform irrigation management for potatoes","volume":"22","author":"King","year":"2006","journal-title":"Appl. Eng. Agric."},{"key":"ref_11","first-page":"250","article-title":"Soil salinity modeling and mapping using remote sensing and GIS: The case of Wonji sugar cane irrigation farm, Ethiopia","volume":"17","author":"Asfaw","year":"2016","journal-title":"J. Saudi Soc. Agric. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"697","DOI":"10.5194\/hess-20-697-2016","article-title":"Estimating evaporation with thermal UAV data and two-source energy balance models","volume":"20","author":"Hoffmann","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s11119-014-9351-z","article-title":"Crop water stress index derived from multi-year ground and aerial thermal images as an indicator of potato water status","volume":"15","author":"Rud","year":"2014","journal-title":"Precis. Agric."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.compag.2017.05.001","article-title":"An overview of current and potential applications of thermal remote sensing in precision agriculture","volume":"139","author":"Khanal","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Barbedo, J.G.A. (2019). A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses. Drones, 3.","DOI":"10.3390\/drones3020040"},{"key":"ref_16","unstructured":"Cazaurang, F., Cohen, K., and Kumar, M. (2020). Multi-Rotor Platform-Based UAV Systems, Elsevier."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Calera, A., Campos, I., Osann, A., D\u2019Urso, G., and Menenti, M. (2017). Remote sensing for crop water management: From ET modelling to services for the end users. Sensors, 17.","DOI":"10.3390\/s17051104"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1080\/02626669609491522","article-title":"Use of remote sensing for evapotranspiration monitoring over land surfaces","volume":"41","author":"Kustas","year":"1996","journal-title":"Hydrol. Sci. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"106228","DOI":"10.1016\/j.agwat.2020.106228","article-title":"Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize","volume":"238","author":"Xue","year":"2020","journal-title":"Agric. Water Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"197","DOI":"10.5194\/hess-21-197-2017","article-title":"Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: An artificial neural network approach","volume":"21","author":"Wandera","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/0168-1923(95)02265-Y","article-title":"Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature","volume":"77","author":"Norman","year":"1995","journal-title":"Agric. For. Meteorol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2284","DOI":"10.1002\/jgrd.50259","article-title":"A hybrid dual-source scheme and trapezoid framework-based evapotranspiration model (HTEM) using satellite images: Algorithm and model test","volume":"118","author":"Yang","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S0022-1694(98)00253-4","article-title":"A remote sensing surface energy balance algorithm for land (SEBAL)","volume":"212\u2013213","author":"Bastiaanssen","year":"1998","journal-title":"Hydrology"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1080\/01431161.2012.748990","article-title":"A satellite-based energy balance algorithm with reference dry and wet limits","volume":"34","author":"Feng","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture","volume":"90","author":"Haboudane","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Espinoza, C.Z., Khot, L.R., Sankaran, S., and Jacoby, P.W. (2017). High resolution multispectral and thermal remote sensing-based water stress assessment in subsurface irrigated grapevines. Remote Sens., 9.","DOI":"10.3390\/rs9090961"},{"key":"ref_27","first-page":"27","article-title":"Water stress detection in potato plants using leaf temperature, emissivity, and reflectance","volume":"53","author":"Gerhards","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"170008","DOI":"10.2136\/vzj2017.01.0008","article-title":"Drivers of Potential Recharge from Irrigated Agroecosystems in the Wisconsin Central Sands","volume":"17","author":"Nocco","year":"2018","journal-title":"Vadose Zone J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1061\/(ASCE)0733-9437(2007)133:4(395)","article-title":"Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)\u2014Model","volume":"133","author":"Allen","year":"2007","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.agrformet.2018.05.010","article-title":"Partitioning of evapotranspiration in remote sensing-based models","volume":"260\u2013261","author":"Talsma","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107187","DOI":"10.1016\/j.agwat.2021.107187","article-title":"Remotely-sensed water budgets for agriculture in the upper midwestern United States","volume":"258","author":"Smail","year":"2021","journal-title":"Agric. Water Manag."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Nassar, A., Torres-Rua, A., Kustas, W., Nieto, H., McKee, M., Hipps, L., Stevens, D., Alfieri, J., Prueger, J., and Alsina, M.M. (2020). Influence of model grid size on the estimation of surface fluxes using the two source energy balance model and sUAS imagery in vineyards. Remote Sens., 12.","DOI":"10.3390\/rs12030342"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.5194\/hess-20-1523-2016","article-title":"Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one-and two-source modeling schemes","volume":"20","author":"Xia","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Mokhtari, A., Ahmadi, A., Daccache, A., and Dreschsler, K. (2021). Actual Evapotranspiration from UAV Images: A Multi-Sensor Data Fusion Approach. Remote Sens., 13.","DOI":"10.3390\/rs13122315"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Nassar, A., Torres-Rua, A., Hipps, L., Kustas, W., McKee, M., Stevens, D., Nieto, H., Keller, D., Gowing, I., and Coopmans, C. (2022). Using Remote Sensing to Estimate Scales of Spatial Heterogeneity to Analyze Evapotranspiration Modeling in a Natural Ecosystem. Remote Sens., 14.","DOI":"10.3390\/rs14020372"},{"key":"ref_36","unstructured":"USDA (2019). United States Summary and State Data, 2017 Census of Agriculture."},{"key":"ref_37","unstructured":"USDA (2020). Wisconsin Ag News\u2014Potatoes."},{"key":"ref_38","unstructured":"WI-DNR (2014). Central Sand Plains Ecological Landscape, The Ecological Landscapes of Wisconsin: An Assessment of Ecological Resources and a Guide to Planning Sustainable Management."},{"key":"ref_39","unstructured":"Kraft, G.J., and Mechenich, D.J. (2010). Groundwater Pumping Effects on Groundwater Levels, Lake Levels, and Streamflows in the Wisconsin Central Sands, Center for Watershed Science and Education College of Natural Resources."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1111\/gwat.12536","article-title":"Depletion Mapping and Constrained Optimization to Support Managing Groundwater Extraction","volume":"56","author":"Fienen","year":"2018","journal-title":"Groundwater"},{"key":"ref_41","unstructured":"Tempfli, K., Huurneman, G., Bakker, W., Janssen, L.L., Feringa, W.F., Gieske, A.S.M., Grabmaier, K.A., Hecker, C.A., Horn, J.A., and Kerle, N. (2009). Principles of Remote Sensing, International Institute for Geo-Information Science and Earth Observation."},{"key":"ref_42","unstructured":"Allen, R., Pereira, L., Raes, D., and Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirments, Food and Agriculture Organization of the United Nations."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.agrformet.2014.06.009","article-title":"Using evapotranspiration to assess drought sensitivity on a subfield scale with HRMET, a high resolution surface energy balance model","volume":"197","author":"Zipper","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_44","unstructured":"Hammersley, J., and Handscomb, D. (1979). Monte Carlo Methods, Chapman and Hall."},{"key":"ref_45","unstructured":"Desai, A.R. (2020). AmeriFlux US-CS3 Central Sands Irrigated Agricultural Field."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.agrformet.2017.04.006","article-title":"Experimental validation of footprint models for eddy covariance CO2 flux measurements above grassland by means of natural and artificial tracers","volume":"242","author":"Arriga","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"5163","DOI":"10.5194\/amt-9-5163-2016","article-title":"Random uncertainties of flux measurements by the eddy covariance technique","volume":"9","author":"Rannik","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF00119817","article-title":"Footprint estimation for scalar flux measurements in the atmospheric surface layer","volume":"59","author":"Horst","year":"1992","journal-title":"Boundary-Layer Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s10546-020-00529-6","article-title":"Surface-Energy-Balance Closure over Land: A Review","volume":"177","author":"Mauder","year":"2020","journal-title":"Bound.-Layer Meteorol."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Nassar, A., Torres-Rua, A.F., Kustas, W.P., Nieto, H., McKee, M., Hipps, L.E., Alfieri, J.G., Prueger, J.H., Alsina, M.M., and McKee, L.G. (2020). To what extend does the Eddy Covariance footprint cutoff influence the estimation of surface energy fluxes using two source energy balance model and high-resolution imagery in commercial vineyards?. Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, International Society for Optics and Photonics.","DOI":"10.1117\/12.2558777"},{"key":"ref_51","first-page":"102282","article-title":"Leaf area index estimation using top-of-canopy airborne RGB images","volume":"96","author":"Raj","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_52","unstructured":"Haala, N. (2011). Multiray Photogrammetry and Dense Image Matching. Photogrammetric Week, VDE."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/S0168-1699(02)00096-0","article-title":"Precision agriculture\u2014A worldwide overview","volume":"36","author":"Zhang","year":"2002","journal-title":"Comput. Electron. Agric."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.agwat.2014.02.002","article-title":"Assessing crop coefficients of sunflower and canola using two-source energy balance and thermal radiometry","volume":"137","author":"Rubio","year":"2014","journal-title":"Agric. Water Manag."},{"key":"ref_55","unstructured":"(2021, September 15). Capturing from Low Altitudes and from a Fixed Point. Available online: https:\/\/support.micasense.com\/hc\/en-us\/articles\/360045449134-Capturing-from-low-altitudes-and-from-a-fixed-point."},{"key":"ref_56","first-page":"539","article-title":"Using high resolution UAV thermal imagery to assessthe variability in the water status of five fruit tree specieswithin a commercial orchard","volume":"388","author":"Nortes","year":"2018","journal-title":"Nature"},{"key":"ref_57","first-page":"244","article-title":"Remote sensing of spider mite damage in California peach orchards","volume":"11","author":"Luedeling","year":"2009","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_58","first-page":"500","article-title":"The use of low-altitude infrared remote sensing for estimating stress conditions in tree crops","volume":"91","author":"Fouche","year":"1995","journal-title":"S. Afr. J. Sci."},{"key":"ref_59","unstructured":"Gallego, J., Carfagna, E., and Baruth, B. (2008). Accuracy, Objectivity and Efficiency of Remote Sensing for Agricultural Statistics. Agricultural Survey Methods, Wiley."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.3390\/rs2092274","article-title":"Remote Sensing of Irrigated Agriculture: Opportunities and Challenges","volume":"2","author":"Ozdogan","year":"2010","journal-title":"Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.3390\/s90503801","article-title":"A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data","volume":"9","author":"Li","year":"2009","journal-title":"Sensors"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Simpson, J., Holman, F., Nieto, H., Voelksch, I., Mauder, M., Klatt, J., Fiener, P., and Kaplan, J. (2021). High spatial and temporal resolution energy flux mapping of different land covers using an off-the-shelf unmanned aerial system. Remote Sens., 13.","DOI":"10.3390\/rs13071286"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1002\/eco.1586","article-title":"Evapotranspiration comparisons between eddy covariance measurements and meteorological and remote-sensing-based models in disturbed ponderosa pine forests","volume":"8","author":"Ha","year":"2014","journal-title":"Ecohydrology"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1660\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:46:38Z","timestamp":1760136398000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,30]]},"references-count":63,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071660"],"URL":"https:\/\/doi.org\/10.3390\/rs14071660","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,30]]}}}