{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T22:14:51Z","timestamp":1762640091953,"version":"build-2065373602"},"reference-count":71,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T00:00:00Z","timestamp":1647561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41901368"],"award-info":[{"award-number":["41901368"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Science &amp; Technology Projects","award":["Guike AD21220085","Guike AD20238059"],"award-info":[{"award-number":["Guike AD21220085","Guike AD20238059"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Plant water use is an important function reflecting vegetation physiological status and affects plant growth, productivity, and crop\/fruit quality. Although hyperspectral vegetation indices have recently been proposed to assess plant water use, limited sample sizes for established models greatly astricts their wide applications. In this study, we have managed to gather a large volume of continuous measurements of canopy spectra through proximally set spectroradiometers over the canopy, enabling us to investigate the feasibility of using continuous narrow-band indices to trace canopy-scale water use indicated by the stem sap flux density measured with sap flow sensors. The results proved that the newly developed D (520, 560) index was optimal to capture the variation of sap flux density under clear sky conditions (R2 = 0.53), while the best index identified for non-clear sky conditions was the D (530, 575) (R2 = 0.32). Furthermore, the bands used in these indices agreed with the reported sensitive bands for estimating leaf stomatal conductance which has a critical role in transpiration rate regulation over a short time period. Our results should point a way towards using proximal hyperspectral indices to trace tree water use directly.<\/jats:p>","DOI":"10.3390\/rs14061483","type":"journal-article","created":{"date-parts":[[2022,3,20]],"date-time":"2022-03-20T21:37:17Z","timestamp":1647812237000},"page":"1483","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Proximal Remote Sensing-Based Vegetation Indices for Monitoring Mango Tree Stem Sap Flux Density"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9917-4881","authenticated-orcid":false,"given":"Jia","family":"Jin","sequence":"first","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqing","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Yan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengjuan","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecoinf.2016.06.004","article-title":"Hyperspectral indices based on first derivative spectra closely trace canopy transpiration in a desert plant","volume":"35","author":"Jin","year":"2016","journal-title":"Ecol. Inform."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Weksler, S., Rozenstein, O., Haish, N., Moshelion, M., Wallach, R., and Ben-Dor, E. (2021). Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting. Sensors, 21.","DOI":"10.3390\/s21030958"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1002\/eco.20","article-title":"Transpiration and stomatal conductance across a steep climate gradient in the southern Rocky Mountains","volume":"1","author":"McDowell","year":"2008","journal-title":"Ecohydrology"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Nordey, T., Lechaudel, M., Saudreau, M., Joas, J., and Genard, M. (2014). Model-assisted analysis of spatial and temporal variations in fruit temperature and transpiration highlighting the role of fruit development. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0092532"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1016\/j.agrformet.2010.04.004","article-title":"A comparison of sap flux density using thermal dissipation, heat pulse velocity and heat field deformation methods","volume":"150","author":"Steppe","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S0168-1923(99)00151-3","article-title":"Water balance, transpiration and canopy conductance in two beech stands","volume":"100","author":"Granier","year":"2000","journal-title":"Agric. For. Meteorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"70","DOI":"10.3390\/s8010070","article-title":"Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation","volume":"8","author":"Verstraeten","year":"2008","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e2019WR026058","DOI":"10.1029\/2019WR026058","article-title":"ECOSTRESS: NASA\u2019s next generation mission to measure evapotranspiration from the International Space Station","volume":"56","author":"Fisher","year":"2020","journal-title":"Water Resour. Res."},{"key":"ref_9","first-page":"307","article-title":"Remote sensing and its use in detection and monitoring plant diseases: A review","volume":"39","author":"Gogoi","year":"2018","journal-title":"Agric. Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1007\/s10712-010-9102-2","article-title":"Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing","volume":"31","author":"Glenn","year":"2010","journal-title":"Surv. Geophys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"RG2005","DOI":"10.1029\/2011RG000373","article-title":"A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability","volume":"50","author":"Wang","year":"2012","journal-title":"Rev. Geophys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/s10795-005-5186-0","article-title":"Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches","volume":"19","author":"Courault","year":"2005","journal-title":"Irrig. Drain. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/S0034-4257(99)00025-5","article-title":"A Remote Sensing Study of the NDVI\u2013Ts Relationship and the Transpiration from Sparse Vegetation in the Sahel Based on High-Resolution Satellite Data","volume":"69","author":"Boegh","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"85","DOI":"10.5194\/hess-6-85-2002","article-title":"The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes","volume":"6","author":"Su","year":"2002","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1061\/(ASCE)0733-9437(2007)133:4(380)","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_16","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). 1. Formulation","volume":"212\u2013213","author":"Bastiaanssen","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.agrformet.2018.02.023","article-title":"Spatiotemporal dynamics of leaf transpiration quantified with time-series thermal imaging","volume":"256-257","author":"Page","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/s00271-007-0088-6","article-title":"ET mapping for agricultural water management: Present status and challenges","volume":"26","author":"Gowda","year":"2008","journal-title":"Irrig. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.agrformet.2015.12.025","article-title":"Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)","volume":"218\u2013219","author":"Marshall","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1038\/nature11983","article-title":"Terrestrial water fluxes dominated by transpiration","volume":"496","author":"Jasechko","year":"2013","journal-title":"Nature"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/07352680701402503","article-title":"Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration","volume":"26","author":"Glenn","year":"2007","journal-title":"Crit. Rev. Plant Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.agwat.2003.10.001","article-title":"Estimation of evapotranspiration, transpiration ratio and water-use efficiency from a sparse canopy using a compartment model","volume":"65","author":"Kato","year":"2004","journal-title":"Agric. Water Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1023\/A:1026530522612","article-title":"Effects of long-term rainfall variability on evapotranspiration and soil water distribution in the Chihuahuan Desert: A modeling analysis","volume":"150","author":"Reynolds","year":"2000","journal-title":"Plant Ecol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.envexpbot.2013.10.008","article-title":"Assessing gas exchange, sap flow and water relations using tree canopy spectral reflectance indices in irrigated and rainfed Olea europaea L.","volume":"99","author":"Marino","year":"2014","journal-title":"Environ. Exp. Bot."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"El-Hendawy, S., Al-Suhaibani, N., Hassan, W., Tahir, M., and Schmidhalter, U. (2017). Hyperspectral reflectance sensing to assess the growth and photosynthetic properties of wheat cultivars exposed to different irrigation rates in an irrigated arid region. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0183262"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1007\/s12665-012-1989-0","article-title":"Multiscale remote-sensing retrieval in the evapotranspiration of Haloxylon ammodendron in the Gurbantunggut desert, China","volume":"69","author":"Cao","year":"2013","journal-title":"Environ. Earth Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s10661-018-7140-2","article-title":"Combing both simulated and field-measured data to develop robust hyperspectral indices for tracing canopy transpiration in drought-tolerant plant","volume":"191","author":"Jin","year":"2019","journal-title":"Environ. Monit. Assess."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3846","DOI":"10.1016\/j.rse.2008.06.005","article-title":"Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass","volume":"112","author":"Soudani","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jfoodeng.2014.02.021","article-title":"The potential use of visible\/near infrared spectroscopy and hyperspectral imaging to predict processing-related constituents of potatoes","volume":"135","author":"Rady","year":"2014","journal-title":"J. Food Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.compag.2003.12.001","article-title":"Detecting drought status and LAI of two Quercus species canopies using derivative spectra","volume":"43","author":"Imanishi","year":"2004","journal-title":"Comput. Electron. Agric."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/s11120-021-00873-9","article-title":"Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data","volume":"151","author":"Jin","year":"2021","journal-title":"Photosynth. Res."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Jin, J., Arief Pratama, B., and Wang, Q. (2020). Tracing Leaf Photosynthetic Parameters Using Hyperspectral Indices in an Alpine Deciduous Forest. Remote Sens., 12.","DOI":"10.3390\/rs12071124"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1002\/eco.1321","article-title":"Water-use response to climate factors at whole tree and branch scale for a dominant desert species in central Asia: Haloxylon ammodendron","volume":"7","author":"Zheng","year":"2014","journal-title":"Ecohydrology"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1051\/forest:19850204","article-title":"A new method of sap flow measurement in tree stems","volume":"42","author":"Granier","year":"1985","journal-title":"Ann. Sci. For."},{"key":"ref_35","first-page":"631","article-title":"Granier\u2019s thermal dissipation probe (TDP) method for measuring sap flow in trees: Theory and practice","volume":"46","author":"Lu","year":"2004","journal-title":"Acta Bot. Sin."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5194\/asr-13-1-2016","article-title":"On the effective solar zenith and azimuth angles to use with measurements of hourly irradiation","volume":"13","author":"Blanc","year":"2016","journal-title":"Adv. Sci. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0034-4257(85)90040-9","article-title":"View azimuth and zenith, and solar angle effects on wheat canopy reflectance","volume":"18","author":"Shibayama","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.solener.2003.12.003","article-title":"Solar position algorithm for solar radiation applications","volume":"76","author":"Reda","year":"2004","journal-title":"Solar Energy"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0038-092X(60)90062-1","article-title":"The interrelationship and characteristic distribution of direct, diffuse and total solar radiation","volume":"4","author":"Liu","year":"1960","journal-title":"Solar Energy"},{"key":"ref_40","unstructured":"Clough, S., Brown, P., Liljegren, J., Shippert, T., Turner, D., Knuteson, R., Revercomb, H., and Smith, W. (1996, January 4\u20137). Implications for atmospheric state specification from the AERI\/LBLRTM quality measurement experiment and the MWR\/LBLRTM quality measurement experiment. Proceedings of the 6th ARM Science Team Meeting, San Antonio, TX, USA."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1007\/s00376-008-0885-8","article-title":"Influences of the clearness index on UV solar radiation for two locations in the Tibetan Plateau-Lhasa and Haibei","volume":"25","author":"Hu","year":"2008","journal-title":"Adv. Atmos. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"4759","DOI":"10.1029\/1999JD901106","article-title":"Influences of the clearness index for the whole spectrum and of the relative optical air mass on UV solar irradiance for two locations in the Mediterranean area, Valencia and Cordoba","volume":"105","year":"2000","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"30","DOI":"10.3832\/ifor1634-008","article-title":"Leaf transpiration of drought tolerant plant can be captured by hyperspectral reflectance using PLSR analysis","volume":"9","author":"Wang","year":"2015","journal-title":"iForest\u2014Biogeosciences For."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/S0034-4257(98)00032-7","article-title":"Derivative Analysis of Hyperspectral Data","volume":"66","author":"Tsai","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_45","unstructured":"Chapra, S.C., and Canale, R.P. (1988). Numerical Methods for Engineers, McGraw-Hill."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Thenkabail, P.S., Lyon, J.G., and Huete, A. (2018). Derivative hyperspectral vegetation indices in characterizing forest biophysical and biochemical quantities. Hyperspectral Indices and Image Classifications for Agriculture and Vegetation, CRC Press.","DOI":"10.1201\/9781315159331"},{"key":"ref_47","unstructured":"Williams, P., and Norris, K. (1987). Variable affecting near infrared reflectance spectroscopic analysis. Near-Infrared Technology in the Agriculture and Food Industries, American Association of Cereal Chemists Inc."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"16473","DOI":"10.1038\/s41598-019-52802-5","article-title":"Estimating growth and photosynthetic properties of wheat grown in simulated saline field conditions using hyperspectral reflectance sensing and multivariate analysis","volume":"9","author":"Alotaibi","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Sun, P., Wahbi, S., Tsonev, T., Haworth, M., Liu, S., and Centritto, M. (2014). On the Use of Leaf Spectral Indices to Assess Water Status and Photosynthetic Limitations in Olea europaea L. during Water-Stress and Recovery. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0105165"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Zhou, J.-J., Zhang, Y.-H., Han, Z.-M., Liu, X.-Y., Jian, Y.-F., Hu, C.-G., and Dian, Y.-Y. (2021). Hyperspectral sensing of photosynthesis, stomatal conductance, and transpiration for citrus tree under drought condition. bioRxiv.","DOI":"10.1101\/2021.02.26.433135"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.foreco.2006.03.027","article-title":"Suitability of existing and novel spectral indices to remotely detect water stress in Populus spp.","volume":"229","author":"Eitel","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/0168-1923(91)90002-8","article-title":"Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: A model that includes a laminar boundary layer","volume":"54","author":"Collatz","year":"1991","journal-title":"Agric. For. Meteorol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1093\/treephys\/18.8-9.633","article-title":"Regulation of stomatal conductance and transpiration in forest canopies","volume":"18","author":"Whitehead","year":"1998","journal-title":"Tree Physiol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/S0034-4257(97)00110-7","article-title":"Reflectance Wavebands and Indices for Remote Estimation of Photosynthesis and Stomatal Conductance in Pine Canopies","volume":"63","author":"Carter","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/0034-4257(93)90106-8","article-title":"Photosynthesis and stomatal conductance related to reflectance on the canopy scale","volume":"44","author":"Verma","year":"1993","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/0034-4257(92)90103-Q","article-title":"Remote sensing of vegetation canopy photosynthetic and stomatal conductance efficiencies","volume":"42","author":"Myneni","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Maimaitiyiming, M., Ghulam, A., Bozzolo, A., Wilkins, J.L., and Kwasniewski, M.T. (2017). Early Detection of Plant Physiological Responses to Different Levels of Water Stress Using Reflectance Spectroscopy. Remote Sens., 9.","DOI":"10.3390\/rs9070745"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.cropro.2018.02.022","article-title":"Proximal hyperspectral sensing of stomatal conductance to monitor the efficacy of exogenous abscisic acid applications in apple trees","volume":"109","author":"Jarolmasjed","year":"2018","journal-title":"Crop Protect."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Sukhova, E., and Sukhov, V. (2020). Relation of Photochemical Reflectance Indices Based on Different Wavelengths to the Parameters of Light Reactions in Photosystems I and II in Pea Plants. Remote Sens., 12.","DOI":"10.3390\/rs12081312"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.rse.2004.03.012","article-title":"A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence","volume":"91","author":"Evain","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_61","first-page":"114","article-title":"Detecting leaf nitrogen content in wheat with canopy hyperspectrum under different soil backgrounds","volume":"32","author":"Yao","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/0034-4257(90)90055-Q","article-title":"High resolution derivative spectra in remote sensing","volume":"33","author":"Steven","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/S0034-4257(02)00113-X","article-title":"Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects","volume":"84","author":"Pushnik","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"107608","DOI":"10.1016\/j.agrformet.2019.06.007","article-title":"Improvement of sap flow estimation by including phenological index and time-lag effect in back-propagation neural network models","volume":"276\u2013277","author":"Tu","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1093\/treephys\/17.8-9.511","article-title":"Transpiration of a boreal pine forest measured by branch bag, sap flow and micrometeorological methods","volume":"17","author":"Saugier","year":"1997","journal-title":"Tree Physiol."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Haagsma, M., Page, G.F.M., Johnson, J.S., Still, C., Waring, K.M., Sniezko, R.A., and Selker, J.S. (2021). Model selection and timing of acquisition date impacts classification accuracy: A case study using hyperspectral imaging to detect white pine blister rust over time. Comput. Electron. Agric., 191.","DOI":"10.1016\/j.compag.2021.106555"},{"key":"ref_67","unstructured":"Darmawan, A., Nadirah, A.W., Evri, M., Mulyono, S., Nugroho, A., Sadly, M., Hendiarti, N., Kashimura, O., Kobayashi, C., and Uchida, A. (2009, January 18\u201323). Quantitative analysis from unifying field and airborne hyperspectral in prediction biophysical parameters by using partial least square (PLSR) and Normalized Difference Spectral Index (NDSI). Proceedings of the 30th Asian Conference on Remote Sensing (ACRS), Beijing, China. TS10-02."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"729","DOI":"10.13031\/2013.24370","article-title":"Yield Estimation from Hyperspectral Imagery Using Spectral Angle Mapper (SAM)","volume":"51","author":"Yang","year":"2008","journal-title":"Trans. ASABE"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2011.10.007","article-title":"Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera","volume":"117","author":"Berni","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Thenkabail, P.S., Lyon, J.G., and Huete, A. (2012). Hyperspectral Remote Sensing of Vegetation, CRC Press.","DOI":"10.1201\/b11222-41"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2136","DOI":"10.3390\/s8042136","article-title":"Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape","volume":"8","author":"Glenn","year":"2008","journal-title":"Sensors"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/6\/1483\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:39:25Z","timestamp":1760135965000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/6\/1483"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,18]]},"references-count":71,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14061483"],"URL":"https:\/\/doi.org\/10.3390\/rs14061483","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,3,18]]}}}