{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T06:49:22Z","timestamp":1782370162269,"version":"3.54.5"},"reference-count":82,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"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":["31672484"],"award-info":[{"award-number":["31672484"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31702175"],"award-info":[{"award-number":["31702175"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018621","name":"Program for Changjiang Scholars and Innovative Research Team in University","doi-asserted-by":"publisher","award":["IRT_17R50"],"award-info":[{"award-number":["IRT_17R50"]}],"id":[{"id":"10.13039\/501100018621","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China project","award":["2017YFC0504801"],"award-info":[{"award-number":["2017YFC0504801"]}]},{"DOI":"10.13039\/501100013314","name":"111 Project","doi-asserted-by":"publisher","award":["B12002"],"award-info":[{"award-number":["B12002"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Nondestructive and accurate estimating of the forage nitrogen\u2013phosphorus (N:P) ratio is conducive to the real-time diagnosis of nutrient limitation and the formulation of a management scheme during the growth and development of forage. New-generation high-resolution remote sensors equipped with strategic red-edge wavebands offer opportunities and challenges for estimating and mapping forage N:P ratio in support of the sustainable utilization of alpine grassland resources. This study aims to detect the forage N:P ratio as an ecological indicator of grassland nutrient content by employing Sentinel-2 multispectral instrument (MSI) data and a random forest (RF) algorithm. The results showed that the estimation accuracy (R2) of the forage N:P ratio model established by combining the optimized spectral bands and vegetation indices (VIs) is 0.49 and 0.59 in the vigorous growth period (July) and the senescing period (November) of forage, respectively. Moreover, Sentinel-2 MSI B9 and B12 bands contributed greatly to the estimation of the forage N:P ratio, and the VIs (RECI2) constructed by B5 and B8A bands performed well in the estimation of the forage N:P ratio. Overall, it is promising to map the spatial distribution of the forage N:P ratio in alpine grassland using Sentinel-2 MSI data at regional scales. This study will be potentially beneficial in implementing precise positioning of vegetation nutrient deficiency and scientific fertilization management of grassland.<\/jats:p>","DOI":"10.3390\/rs12182929","type":"journal-article","created":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T09:10:09Z","timestamp":1599729009000},"page":"2929","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Mapping the Forage Nitrogen-Phosphorus Ratio Based on Sentinel-2 MSI Data and a Random Forest Algorithm in an Alpine Grassland Ecosystem of the Tibetan Plateau"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1188-8271","authenticated-orcid":false,"given":"Jinlong","family":"Gao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiangang","family":"Liang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8588-8026","authenticated-orcid":false,"given":"Mengjing","family":"Hou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Ge","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qisheng","family":"Feng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caixia","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenlong","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1080\/014311698215919","article-title":"Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves","volume":"19","author":"Blackburn","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","first-page":"196","article-title":"Estimation of grassland biomass and nitrogen using MERIS data","volume":"19","author":"Ullah","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/0034-4257(83)90021-4","article-title":"Radiometric estimation of biomass and nitrogen content of alicia grass","volume":"13","author":"Richardson","year":"1983","journal-title":"Remote Sens. Environ."},{"key":"ref_4","first-page":"43","article-title":"Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data","volume":"43","author":"Ramoelo","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3218","DOI":"10.1002\/ece3.1173","article-title":"The relationship of leaf photosynthetic traits\u2013vcmax and Jmax\u2013to leaf nitrogen, leaf phosphorus, and specific leaf area: A meta-analysis and modeling study","volume":"4","author":"Walker","year":"2014","journal-title":"Ecol. Evol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.isprsjprs.2018.11.015","article-title":"Modeling alpine grassland forage phosphorus based on hyperspectral remote sensing and a multi-factor machine learning algorithm in the east of Tibetan Plateau. China","volume":"147","author":"Gao","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.2307\/2404783","article-title":"The vegetation N:P ratio: A new tool to detect the nature of nutrient limitation","volume":"33","author":"Koerselman","year":"1996","journal-title":"J. Appl. Ecol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2191","DOI":"10.1890\/01-0639","article-title":"Species richness-productivity patterns differ between N-, P-, and K-limited wetlands","volume":"84","author":"Wassen","year":"2003","journal-title":"Ecology"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s00442-007-0912-y","article-title":"Leaf nitrogen:phosphorus stoichiometry across Chinese grassland biomes","volume":"155","author":"He","year":"2008","journal-title":"Oecologia"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1046\/j.1365-2664.2003.00820.x","article-title":"Use of nitrogen to phosphorus ratios in plant tissue as an indicator of nutrient limitation and nitrogen saturation","volume":"40","author":"Tessier","year":"2003","journal-title":"J. Appl. Ecol."},{"key":"ref_11","first-page":"334","article-title":"Savanna grass nitrogen to phosphorous ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy","volume":"23","author":"Ramoelo","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1038\/nature03950","article-title":"Endangered plants persist under phosphorus limitation","volume":"437","author":"Wassen","year":"2005","journal-title":"Nature"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1038\/nature12733","article-title":"Low investment in sexual reproduction threatens plants adapted to phosphorus limitation","volume":"505","author":"Fujita","year":"2014","journal-title":"Nature"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1080\/03736245.2016.1208586","article-title":"Progress in remote sensing: Vegetation monitoring in South Africa","volume":"98","author":"Mutanga","year":"2016","journal-title":"S. Afr. Geogr. J."},{"key":"ref_15","first-page":"25","article-title":"Progress on grassland chlorophyll content estimation by hyperspectral analysis","volume":"35","author":"Ma","year":"2016","journal-title":"Prog. Geogr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Skidmore, A.K. (2002). Taxonomy of environmental models in the spatial sciences. Environmental Modelling with GIS and Remote Sensing, Taylor and Francis.","DOI":"10.1201\/9780203302217"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.rse.2015.07.007","article-title":"Applicability of the PROSPECT model for estimating protein and cellulose + lignin in fresh leaves","volume":"168","author":"Wang","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/0034-4257(94)90136-8","article-title":"Reflectance indices associated with physiological changes in nitrogen and water-limited sunflower leaves","volume":"48","author":"Penuelas","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_19","unstructured":"Mutanga, O. (2004). Hyperspectral Remote Sensing of Tropical Grass Quality and Quantity. [Ph.D. Thesis, International Institute for Geoinformation Science and Earth Observation and Wageningen University]."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1080\/01431169408954177","article-title":"The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status","volume":"15","author":"Filella","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1080\/01431169508954387","article-title":"Red edge response to forest leaf area index","volume":"16","author":"Danson","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/0034-4257(91)90066-F","article-title":"The effect of a Red leaf pigment on the relationship between red edge and chlorophyll concentration","volume":"35","author":"Curran","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Ramoelo, A. (2012). Savanna Grass Quality-Remote Sensing Estimation from Local to Regional Scale. [Ph.D. Thesis, University of Twente]."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.isprsjprs.2020.03.017","article-title":"Potential of hyperspectral data and machine learning algorithms to estimate the forage carbon-nitrogen ratio in an alpine grassland ecosystem of the Tibetan Plateau","volume":"163","author":"Gao","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1111\/avsc.12122","article-title":"Mapping continuous forest type variation by means of correlating remotely sensed metrics to canopy N:P ratio in a boreal mixed wood forest","volume":"18","author":"Thomas","year":"2015","journal-title":"Appl. Veg. Sci."},{"key":"ref_26","first-page":"1","article-title":"Exploring the use of vegetation indices to sense canopy nitrogen to phosphorous ratio in grasses","volume":"75","author":"Loozen","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/JSTARS.2013.2267204","article-title":"Progress in hyperspectral remote sensing science and technology in China over the past three decades","volume":"7","author":"Tong","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.rse.2015.04.020","article-title":"Retrieval of grassland plant coverage on the Tibetan Plateau based on a multiscale, multi-sensor and multi-method approach","volume":"164","author":"Lehnert","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1016\/j.rse.2017.10.011","article-title":"Modeling grassland above-ground biomass based on artificial neural network and remote sensing in the Three-River Headwaters Region","volume":"204","author":"Yang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Meng, B.P., Gao, J.L., Liang, T.G., Cui, X., Ge, J., Yin, J.P., Feng, Q.S., and Xie, H.J. (2018). Modeling of alpine grassland cover based on unmanned aerial vehicle technology and multi-factor methods: A case study in the east of Tibetan Plateau, China. Remote Sens., 10.","DOI":"10.3390\/rs10020320"},{"key":"ref_31","first-page":"151","article-title":"Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor","volume":"19","author":"Ramoelo","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.isprsjprs.2017.04.016","article-title":"Examining the strength of the newly-launched Sentinel 2 MSI sensor in detecting and discriminating subtle differences between C3 and C4 grass species","volume":"129","author":"Shoko","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","first-page":"47","article-title":"Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels","volume":"25","author":"Schlemmer","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2018.02.004","article-title":"Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data","volume":"138","author":"Chemura","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1080\/14498596.2017.1341352","article-title":"Multispectral mapping of key grassland nutrients in KwaZulu-Natal","volume":"63","author":"Singh","year":"2018","journal-title":"S. Afr. J. Spat. Sci."},{"key":"ref_36","first-page":"344","article-title":"Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on sentinel-2 and-3","volume":"23","author":"Clevers","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4612809","DOI":"10.1155\/2016\/4612809","article-title":"Remote sensing of grassland biophysical parameters in the context of the Sentinel-2 satellite mission","volume":"2016","author":"Sakowska","year":"2016","journal-title":"J. Sens."},{"key":"ref_38","unstructured":"Rouse, J., Haas, R.H., Schell, J.A., and Deering, D.W. (1973, January 10\u201314). Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the Third Earth Resources Technology Satellite-1 Symposium, Greenbelt, MD, USA."},{"key":"ref_39","first-page":"77","article-title":"The influences of soil salinity, growth form, and leaf moisture on the spectral reflectance of spartina alterniflora canopies","volume":"49","author":"Hardisky","year":"1983","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/S0034-4257(02)00010-X","article-title":"Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages","volume":"81","author":"Sims","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_42","unstructured":"Barnes, E.M., Clarke, T.R., Richards, S.E., Colaizzi, P.D., Haberland, J., Kostrzewski, M., Waller, P., Choi, C., Riley, E., and Thompson, T. (2000, January 16\u201319). Coincident detection of crop water stress, nitrogen status and canopy density using ground-based multispectral data. Proceedings of the Fifth International Conference on Precision Agriculture, Bloomington, MN, USA."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/1011-1344(93)06963-4","article-title":"Quantitative estimation of chlorophyll using reflectance spectra","volume":"22","author":"Gitelson","year":"1994","journal-title":"J. Photochem. Photobiol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOSMODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.isprsjprs.2013.04.007","article-title":"Evaluating the capabilities of Sentinel-2 for quantitative estimation of biophysical variables in vegetation","volume":"82","author":"Frampton","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","unstructured":"Guyot, G., and Baret, F. (1988, January 18\u201322). Utilisation de la haute resolution spectrale pour suivre l\u2019etat des couverts vegetaux. Proceedings of the 4th International Colloquium Spectral Signatures of Objects in Remote Sensing, Aussois, France."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5403","DOI":"10.1080\/0143116042000274015","article-title":"The MERIS terrestrial chlorophyll index","volume":"25","author":"Dash","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"L08403","DOI":"10.1029\/2005GL022688","article-title":"Remote estimation of canopy chlorophyll content in crops","volume":"32","author":"Gitelson","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1078\/0176-1617-00887","article-title":"Relationships between leaf chlorophyll content and spectral reflectance and algorithms for nondestructive chlorophyll assessment in higher plant leaves","volume":"160","author":"Gitelson","year":"2003","journal-title":"J. Plant Physiol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1078\/0176-1617-01176","article-title":"Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation","volume":"161","author":"Gitelson","year":"2004","journal-title":"J. Plant Physiol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.nicl.2014.08.023","article-title":"Random Forest ensembles for detection and prediction of Alzheimer\u2019s disease with a good between-cohort robustness","volume":"6","author":"Lebedev","year":"2014","journal-title":"NeuroImage Clin."},{"key":"ref_54","unstructured":"Kohavi, R. (1995, January 20\u201325). A study of cross-validation and bootstrap for accuracy estimation and model selection. Proceedings of the 14th International Joint Conference on Artificial Intelligence, Montreal, QC, Canada."},{"key":"ref_55","unstructured":"Akademiai, K. (1973). Information theory and an extension of the maximum likelihood principle. International Symposium on Information Theory, Springer."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","article-title":"Estimating the dimension of a model","volume":"6","author":"Schwarz","year":"1978","journal-title":"Ann. Statist."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"19336","DOI":"10.1073\/pnas.0810021105","article-title":"Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks","volume":"105","author":"Ollinger","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.rse.2015.11.028","article-title":"Examining spectral reflectance features related to foliar nitrogen in forests: Implications for broadscale nitrogen mapping","volume":"173","author":"Lepine","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"4897","DOI":"10.1080\/01431160701253253","article-title":"Estimating and mapping grass phosphorus concentration in an African savanna using hyperspectral image data","volume":"28","author":"Mutanga","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/0034-4257(89)90069-2","article-title":"Remote sensing of foliar chemistry","volume":"30","author":"Curran","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_61","unstructured":"Knox, N. (2010). Observing Temporal and Spatial Variability of Forage Quality. [Ph.D. Thesis, Faculty Geo-Information Science and Earth Observation and Twente University]."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.isprsjprs.2011.01.008","article-title":"Water removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations","volume":"66","author":"Ramoelo","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1046\/j.1461-0248.2001.00210.x","article-title":"Plant\u2013herbivore interactions and ecological stoichiometry: When do herbivores determine plant nutrient limitation","volume":"4","author":"Daufresne","year":"2001","journal-title":"Ecol. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"674","DOI":"10.2307\/1312897","article-title":"Organism size, life history, and N:P stoichiometry","volume":"46","author":"Elser","year":"1996","journal-title":"BioScience"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"597","DOI":"10.2307\/2261481","article-title":"Nutrients resorption from senescing leaves of perennials: Are these general patterns?","volume":"84","author":"Aerts","year":"1996","journal-title":"J. Ecol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"257","DOI":"10.3724\/SP.J.1148.2010.00257","article-title":"The seasonal dynamics of nutrient contents and the nutrition balanced values in the eight forage species in the Alxa desert grassland","volume":"2","author":"Wu","year":"2010","journal-title":"Arid Zone Res."},{"key":"ref_67","unstructured":"Chen, J.X. (2007). Alpine Meadow Soil Nitrogen Seasonal Dynamics in Eastern Qinghai-Tibetan Plateau. [Ph.D. Thesis, Sichuan Normal University]."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Gao, J.L., Liang, T.G., Yin, J.P., Ge, J., Feng, Q.S., Wu, C.X., Hou, M.J., Liu, J., and Xie, H.J. (2019). Estimation of alpine grassland forage nitrogen coupled with hyperspectral characteristics during different growth periods on the Tibetan Plateau. Remote Sens., 11.","DOI":"10.3390\/rs11182085"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1007\/s11434-012-5493-4","article-title":"Large scale patterns of forage yield and quality across Chinese grasslands","volume":"58","author":"Shi","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_70","first-page":"509","article-title":"The nitrogen cycle in an alpine meadow ecosystem","volume":"19","author":"Zhang","year":"1999","journal-title":"Acta Ecol. Sin."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"4289","DOI":"10.3390\/rs6054289","article-title":"Quantifying responses of spectral vegetation indices to dead materials in mixed grasslands","volume":"6","author":"Yang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.ecocom.2013.11.005","article-title":"The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures","volume":"17","author":"Croft","year":"2014","journal-title":"Ecol. Complex."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3421","DOI":"10.1080\/01431160152609245","article-title":"Exploring spectral discrimination of grass species in African rangelands","volume":"22","author":"Schmidt","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.rse.2005.12.011","article-title":"A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method","volume":"101","author":"Cho","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.1080\/01431161.2015.1024893","article-title":"Predicting C3 and C4 grass nutrient variability using in situ canopy reflectance and partial least squares regression","volume":"36","author":"Adjorlolo","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_76","first-page":"85","article-title":"Potential utility of the spectral red-edge region of SumbandilaSat imagery for assessing indigenous forest structure and health","volume":"16","author":"Cho","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_77","first-page":"178","article-title":"Evaluating the robustness of models developed from field spectral data in predicting African grass foliar nitrogen concentration using WorldView-2 image as an independent test dataset","volume":"34","author":"Mutanga","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"439","DOI":"10.2111\/1551-5028(2005)058[0439:AUAVFR]2.0.CO;2","article-title":"An unmanned aerial vehicle for rangeland photography","volume":"58","author":"Hardin","year":"2005","journal-title":"Rangel. Ecol. Manag."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1017\/S1466046606060224","article-title":"Using unmanned aerial vehicles for rangelands: Current applications and future potentials","volume":"8","author":"Rango","year":"2006","journal-title":"Environ. Pract."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.rse.2006.07.016","article-title":"Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data","volume":"106","author":"Houborg","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2003.09.004","article-title":"Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements","volume":"89","author":"Francois","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"2592","DOI":"10.1016\/j.rse.2007.12.003","article-title":"Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland","volume":"112","author":"Darvishzadeh","year":"2008","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/18\/2929\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:08:35Z","timestamp":1760177315000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/18\/2929"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,10]]},"references-count":82,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["rs12182929"],"URL":"https:\/\/doi.org\/10.3390\/rs12182929","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,10]]}}}