{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T23:00:52Z","timestamp":1784934052169,"version":"3.55.0"},"reference-count":72,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T00:00:00Z","timestamp":1574985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R &amp; D plan from the MOST of China","award":["2017YFC0403203"],"award-info":[{"award-number":["2017YFC0403203"]}]},{"name":"the Synergetic Innovation of Industry-University-Research Cooperation Project plan from Yangling","award":["2018CXY-23"],"award-info":[{"award-number":["2018CXY-23"]}]},{"name":"the 111 Project","award":["No.B12007"],"award-info":[{"award-number":["No.B12007"]}]},{"name":"the Key Discipline Construction Project of Northwest Agriculture and Forestry University","award":["2017-C03"],"award-info":[{"award-number":["2017-C03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The rapid, accurate, and real-time estimation of crop coefficients at the farm scale is one of the key prerequisites in precision agricultural water management. This study aimed to map the maize crop coefficient (Kc) with improved accuracy under different levels of deficit irrigation. The proposed method for estimating the Kc is based on multispectral images of high spatial resolution taken using an unmanned aerial vehicle (UAV). The analysis was performed on five experimental plots using Kc values measured from the daily soil water balance in Ordos, Inner Mongolia, China. To accurately estimate the Kc, the fraction of vegetation cover (fc) derived from the normalized difference vegetation index (NDVI) was used to compare with field measurements, and the stress coefficients (Ks) calculated from two vegetation index (VI) regression models were compared. The results showed that the NDVI values under different levels of deficit irrigation had no significant difference in the reproductive stage but changed significantly in the maturation stage, with a decrease of 0.09 with 72% water applied difference. The fc calculated from the NDVI had a high correlation with field measurement data, with a coefficient of determination (R2) of 0.93. The ratios of transformed chlorophyll absorption in reflectance index (TCARI) to renormalized difference vegetation index (RDVI) and TCARI to soil-adjusted vegetation index (SAVI) were used, respectively, to establish two types of Ks regression models to retrieve Kc. Compared to the TCARI\/SAVI model, the TCARI\/RDVI model under different levels of deficit irrigation had better correlation with Kc, with R2 and root-mean-square error (RMSE) values ranging from 0.68 to 0.80 and from 0.140 to 0.232, respectively. Compared to Kc calculated from on-site measurements, the Kc values retrieved from the VI regression models established in this study had greater ability to assess the field variability of soil and crops. Overall, use of the UAV-measured multispectral vegetation index approach could improve water management at the farm scale.<\/jats:p>","DOI":"10.3390\/s19235250","type":"journal-article","created":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T10:58:21Z","timestamp":1575025101000},"page":"5250","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9316-9670","authenticated-orcid":false,"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenting","family":"Han","sequence":"additional","affiliation":[{"name":"Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China"},{"name":"Institute of Soil and Water Conservation, Northwest A&amp;F University, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaotao","family":"Niu","sequence":"additional","affiliation":[{"name":"Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.scitotenv.2018.06.028","article-title":"Effects of water stress on water use efficiency of irrigated and rainfed wheat in the Loess Plateau, China","volume":"642","author":"Jin","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"307","DOI":"10.21273\/JASHS.106.3.307","article-title":"Control of peach tree growth and productivity by regulated water supply, tree density, and summer pruning","volume":"106","author":"Chalmers","year":"1981","journal-title":"J. Am. Soc. Hortic. Sci."},{"key":"ref_3","unstructured":"Molden, D. (2007). Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture, Earthscan, and Colombo: International Water Management Institute."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.5194\/hess-14-1863-2010","article-title":"Groundwater use for irrigation\u2014A global inventory","volume":"14","author":"Siebert","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_5","unstructured":"Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements, FAO\u2014Food and Agriculture Organization of the United Nations. FAO Irrigation and Drainage Paper 56."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2373","DOI":"10.3390\/rs70302373","article-title":"Estimation of actual crop coefficients using remotely sensed vegetation indices and soil water balance modelled data","volume":"7","author":"Paredes","year":"2015","journal-title":"Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.agwat.2014.07.031","article-title":"Crop evapotranspiration estimation with FAO56: Past and future","volume":"147","author":"Pereira","year":"2015","journal-title":"Agric. Water Manag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1061\/JRCEA4.0001372","article-title":"New evapotranspiration crop coefficients","volume":"108","author":"Wright","year":"1982","journal-title":"ASCE J. Irrig. Drain. Div."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1061\/(ASCE)0733-9437(2005)131:1(2)","article-title":"FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions","volume":"131","author":"Allen","year":"2005","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s00271-011-0267-3","article-title":"The dual crop coefficient approach using a density factor to simulate the evapotranspiration of a peach orchard: SIMDualKc model versus eddy covariance measurements","volume":"30","author":"Ferreira","year":"2012","journal-title":"Irrig. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.agwat.2012.11.008","article-title":"Dual crop coefficient modelling applied to the winter wheat-summer maize crop sequence in North China Plain: Basal crop coefficients and soil evaporation component","volume":"117","author":"Zhao","year":"2013","journal-title":"Agric. Water Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.agwat.2013.05.018","article-title":"Partitioning evapotranspiration into soil evaporation and transpiration using a modified dual crop coefficient model in irrigated maize field with ground-mulching","volume":"127","author":"Ding","year":"2013","journal-title":"Agric. Water Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.agwat.2014.05.004","article-title":"Modelling transpiration, soil evaporation and yield prediction of soybean in North China Plain","volume":"147","author":"Wei","year":"2015","journal-title":"Agric. Water Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.agwat.2006.04.008","article-title":"Effects of irrigation on water balance, yield and WUE of winter wheat in the North China Plain","volume":"85","author":"Sun","year":"2006","journal-title":"Agric. Water Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.agwat.2018.06.013","article-title":"Estimating net irrigation requirement of winter wheat using model- and satellite-based single and basal crop coefficients","volume":"208","author":"Mokhtari","year":"2018","journal-title":"Agric. Water Manag."},{"key":"ref_16","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_17","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1061\/(ASCE)IR.1943-4774.0000484","article-title":"Estimating water requirements of an irrigated mediterranean vineyard using a satellite-based approach","volume":"138","author":"Consoli","year":"2012","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.agwat.2017.04.018","article-title":"Modeling water needs and total irrigation depths of maize crop in the south west of France using high spatial and temporal resolution satellite imagery","volume":"189","author":"Battude","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhang, H., Niu, Y., and Han, W. (2019). Mapping Maize Water Stress Based on UAV Multispectral Remote Sensing. Remote Sens., 11.","DOI":"10.3390\/rs11060605"},{"key":"ref_20","unstructured":"Rouse, W., Haas, R., Scheel, J., and Deering, W. (1973, January 10\u201314). Monitoring Vegetation Systems in Great Plains with ERTS. Proceedings of the Third ERTS Symposium, NASA SP-351, Washington, DC, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.agwat.2012.11.005","article-title":"Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation","volume":"125","author":"Mateos","year":"2013","journal-title":"Agric. Water Manag."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.agwat.2010.07.011","article-title":"Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.)","volume":"98","author":"Campos","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.agwat.2017.07.010","article-title":"Evapotranspiration of winter wheat estimated with the FAO 56 approach and NDVI measurements in a temperate humid climate of NW Europe","volume":"192","author":"Drerup","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_24","first-page":"235","article-title":"Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops","volume":"34","author":"Kross","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3468","DOI":"10.1016\/j.rse.2011.08.010","article-title":"Comparison of different vegetation indices for the remote assessment of green leaf area index of crops","volume":"115","author":"Gitelson","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"967","DOI":"10.2134\/agronj1982.00021962007400060010x","article-title":"Evaluating the Crop Coefficient Using Spectral Reflectance1","volume":"74","author":"Heilman","year":"1982","journal-title":"Agron. J."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0167-5877(05)80004-2","article-title":"Interpreting vegetation indices","volume":"11","author":"Jackson","year":"1991","journal-title":"Prev. Vet. Med."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1080\/02757259509532290","article-title":"Combining remote sensing and modeling for estimating surface evaporation and biomass production","volume":"12","author":"Moran","year":"1995","journal-title":"Remote Sens. Rev."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, F., and Zhou, G. (2019). Estimation of vegetation water content using hyperspectral vegetation indices: A comparison of crop water indicators in response to water stress treatments for summer maize. BMC Ecol., 19.","DOI":"10.1186\/s12898-019-0233-0"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"15203","DOI":"10.3390\/rs71115203","article-title":"Estimation of canopy water content by means of hyperspectral indices based on drought stress gradient experiments of maize in the north plain China","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S0034-4257(02)00018-4","article-title":"Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture","volume":"81","author":"Haboudane","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.tplants.2018.11.007","article-title":"Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture","volume":"24","author":"Maes","year":"2019","journal-title":"Trends Plant Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1080\/0143116031000115319","article-title":"Monitoring barley and corn growth from remote sensing data at field scale","volume":"25","author":"Calera","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4050","DOI":"10.1002\/hyp.8392","article-title":"Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems","volume":"25","author":"Glenn","year":"2011","journal-title":"Hydrol. Process."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.biosystemseng.2012.08.009","article-title":"Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps","volume":"114","author":"Mulla","year":"2013","journal-title":"Biosyst. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, C., Walters, D., and Kovacs, J.M. (2014). Applications of low altitude remote sensing in agriculture upon farmers\u2019 requests-A case study in northeastern Ontario, Canada. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0112894"},{"key":"ref_37","first-page":"81","article-title":"Remote Sensing of Vegetation Characteristics for Farm Management","volume":"Volume 475","author":"Jackson","year":"1984","journal-title":"Remote Sensing: Critical Review of Technology"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"647","DOI":"10.14358\/PERS.69.6.647","article-title":"Remote Sensing for Crop Management","volume":"69","author":"Pinter","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: A review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.agwat.2016.07.007","article-title":"Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients","volume":"179","author":"Kullberg","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s11119-013-9334-5","article-title":"Mapping crop water stress index in a \u2018Pinot-noir\u2019 vineyard: Comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle","volume":"15","author":"Bellvert","year":"2014","journal-title":"Precis. Agric."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"11","DOI":"10.13031\/2013.39320","article-title":"Performance characteristics of self-propelled center-pivot sprinkler irrigation system","volume":"11","author":"Heermann","year":"1968","journal-title":"Trans. ASAE"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.agwat.2009.09.011","article-title":"Water requirements of maize in the middle Heihe River basin, China","volume":"97","author":"Zhao","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1007\/s00704-016-1841-7","article-title":"Effective crop evapotranspiration measurement using time-domain reflectometry technique in a sub-humid region","volume":"129","author":"Srivastava","year":"2017","journal-title":"Theor. Appl. Climatol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.agwat.2018.02.021","article-title":"Comparison of actual evapotranspiration of irrigated maize in a sub-humid region using four different canopy resistance based approaches","volume":"202","author":"Srivastava","year":"2018","journal-title":"Agric. Water Manag."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Ridolfi, L., D\u2019Odorico, P., Laio, F., Tamea, S., and Rodriguez-Iturbe, I. (2008). Coupled stochastic dynamics of water table and soil moisture in bare soil conditions. Water Resour. Res., 44.","DOI":"10.1029\/2007WR006707"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.agwat.2011.10.013","article-title":"Implementing the dual crop coefficient approach in interactive software. 1. Background and computational strategy","volume":"103","author":"Rosa","year":"2012","journal-title":"Agric. Water Manag."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.agwat.2011.10.018","article-title":"Implementing the dual crop coefficient approach in interactive software: 2. Model testing","volume":"103","author":"Rosa","year":"2012","journal-title":"Agric. Water Manag."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.agwat.2006.02.004","article-title":"Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region","volume":"87","author":"Chehbouni","year":"2007","journal-title":"Agric. Water Manag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"439","DOI":"10.3390\/rs4020439","article-title":"Satellite NDVI assisted monitoring of vegetable crop evapotranspiration in california\u2019s san Joaquin Valley","volume":"4","author":"Johnson","year":"2012","journal-title":"Remote Sens."},{"key":"ref_51","unstructured":"Gonz\u00e1lez, J. (2006). Evapotranspiraci\u00f3n de la cubierta vegetal mediante la determinaci\u00f3n del coeficiente de cultivo por teledetecci\u00f3n. Extensi\u00f3n a escala regional: Acu\u00edfero 08.29 Mancha Oriental. [Ph.D. Thesis, Universidad de Valencia]."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1029\/WR017i004p01133","article-title":"Canopy Temperature as a Crop Water Stress Indicator","volume":"17","author":"Jackson","year":"1981","journal-title":"Water Resour. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.1061\/(ASCE)WR.1943-5452.0001081","article-title":"Promise of UAV-Assisted Adaptive Management of Water Resources Systems","volume":"145","author":"Hill","year":"2019","journal-title":"J. Water Resour. Plan. Manag."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"48572","DOI":"10.1109\/ACCESS.2019.2909530","article-title":"Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges","volume":"7","author":"Shakhatreh","year":"2019","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1891","DOI":"10.13031\/2013.31240","article-title":"Development of reflectance-based crop coefficients for corn","volume":"32","author":"Neale","year":"1989","journal-title":"Trans. Am. Soc. Agric. Eng."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(94)90090-6","article-title":"Relations between evaporation coefficients and vegetation indices studied by model simulations","volume":"50","author":"Choudhury","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/0378-3774(95)01125-3","article-title":"Remote sensing of crop coefficients for improving the irrigation scheduling of corn","volume":"27","author":"Bausch","year":"1995","journal-title":"Agric. Water Manag."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1029\/2012WR012591","article-title":"AVHRR-NDVI-based crop coefficients for analyzing long-term trends in evapotranspiration in relation to changing climate in the U.S. High Plains","volume":"49","author":"Mutiibwa","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.3390\/rs5041588","article-title":"Estimating crop coefficients using remote sensing-based vegetation index","volume":"5","author":"Kamble","year":"2013","journal-title":"Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.agwat.2018.08.042","article-title":"Water use efficiency of corn among the irrigation districts across the Duero river basin (Spain): Estimation of local crop coefficients by satellite images","volume":"212","author":"Zubelzu","year":"2019","journal-title":"Agric. Water Manag."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.agwat.2016.02.010","article-title":"Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition","volume":"184","author":"Toureiro","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.13031\/2013.31241","article-title":"Spectral inputs improve Maize crop coefficients and irrigation scheduling","volume":"32","author":"Bausch","year":"1989","journal-title":"Trans. ASAE"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1016\/j.jhydrol.2014.09.075","article-title":"Evapotranspiration and crop coefficients for a super intensive olive orchard. An application of SIMDualKc and METRIC models using ground and satellite observations","volume":"519","author":"Cunha","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00271-005-0001-0","article-title":"Wheat basal crop coefficients determined by normalized difference vegetation index","volume":"24","author":"Hunsaker","year":"2005","journal-title":"Irrig. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"3267","DOI":"10.1007\/s11269-012-0071-8","article-title":"Aerodynamic Parameterization of the Satellite-Based Energy Balance (METRIC) Model for ET Estimation in Rainfed Olive Orchards of Andalusia, Spain","volume":"26","author":"Santos","year":"2012","journal-title":"Water Resour. Manag."},{"key":"ref_66","first-page":"212","article-title":"Metodolog\u00eda operativa para la obtenci\u00f3n del coeficiente de cultivo desde im\u00e1genes de sat\u00e9lite","volume":"101","author":"Cuesta","year":"2005","journal-title":"ITEA Inf. T\u00e9cnica Econ\u00f3mica Agrar."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.isprsjprs.2012.05.003","article-title":"Monitoring water stress and fruit quality in an orange orchard under regulated deficit irrigation using narrow-band structural and physiological remote sensing indices","volume":"71","author":"Stagakis","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/S0176-1617(96)80287-2","article-title":"Vegetation Stress: An Introduction to the Stress Concept in Plants","volume":"148","author":"Lichtenthaler","year":"1996","journal-title":"J. Plant Physiol."},{"key":"ref_69","first-page":"278","article-title":"Effect of Light and Water Stress on Photochemical Efficiency and Pigment Composition of Sabina vulgaris Seedlings","volume":"53","author":"Zhang","year":"2017","journal-title":"Chin. Bull. Bot."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1007\/s00271-012-0382-9","article-title":"Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV)","volume":"30","author":"Baluja","year":"2012","journal-title":"Irrig. Sci."},{"key":"ref_71","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_72","doi-asserted-by":"crossref","first-page":"289","DOI":"10.17660\/ActaHortic.2007.754.37","article-title":"Effects of drought stress on chlorophyll fluorescence and photosynthetic pigments in grapevine leaves (Vitis vinifera cv. \u2019White Riesling\u2019)","volume":"754","author":"Zulini","year":"2007","journal-title":"Acta Hortic."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5250\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:38:31Z","timestamp":1760189911000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5250"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,29]]},"references-count":72,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235250"],"URL":"https:\/\/doi.org\/10.3390\/s19235250","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,29]]}}}