{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T08:46:51Z","timestamp":1743065211597,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030061784"},{"type":"electronic","value":"9783030061791"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-06179-1_15","type":"book-chapter","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T05:24:08Z","timestamp":1547011448000},"page":"139-153","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Estimation of Leaf Nitrogen Concentration of Winter Wheat Using UAV-Based RGB Imagery"],"prefix":"10.1007","author":[{"given":"Qinglin","family":"Niu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haikuan","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changchun","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guijun","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhai","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haojie","family":"Pei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,9]]},"reference":[{"key":"15_CR1","first-page":"664","volume":"69","author":"P Scheromm","year":"1993","unstructured":"Scheromm, P., Martin, G., Bergoin, A., et al.: Influence of nitrogen fertilization on the potential bread-baking quality of two wheat cultivars differing in their responses to increasing nitrogen supplies. Cereal Chem. 69, 664\u2013670 (1993)","journal-title":"Cereal Chem."},{"issue":"4","key":"15_CR2","first-page":"745","volume":"4","author":"SL Guo","year":"2005","unstructured":"Guo, S.L., Dang, T.H., Hao, M.D.: Effects of fertilization on wheat yield, NO_3--N accumulation and soil water content in semi-arid area of China. Scientia Agricultura Sinica 4(4), 745\u2013751 (2005)","journal-title":"Scientia Agricultura Sinica"},{"issue":"6","key":"15_CR3","doi-asserted-by":"publisher","first-page":"647","DOI":"10.14358\/PERS.69.6.647","volume":"69","author":"P Pjjr","year":"2003","unstructured":"Pjjr, P., Hatfield, J.L., Schepers, J.S., et al.: Remote sensing for crop management. Photogram. Eng. Remote Sens. 69(6), 647\u2013664 (2003)","journal-title":"Photogram. Eng. Remote Sens."},{"issue":"2","key":"15_CR4","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s11119-013-9339-0","volume":"15","author":"XG Xu","year":"2014","unstructured":"Xu, X.G., Zhao, C.J., Wang, J.H., et al.: Using optimal combination method and in situ hyperspectral measurements to estimate leaf nitrogen concentration in barley. Precision Agric. 15(2), 227\u2013240 (2014)","journal-title":"Precision Agric."},{"key":"15_CR5","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.rse.2017.06.007","volume":"198","author":"X Jin","year":"2017","unstructured":"Jin, X., Liu, S., Baret, F., et al.: Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery. Remote Sens. Environ. 198, 105\u2013114 (2017)","journal-title":"Remote Sens. Environ."},{"key":"15_CR6","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.isprsjprs.2016.09.002","volume":"122","author":"S Moharana","year":"2016","unstructured":"Moharana, S., Dutta, S.: Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery. ISPRS J. Photogram. Remote Sens. 122, 17\u201329 (2016)","journal-title":"ISPRS J. Photogram. Remote Sens."},{"issue":"12","key":"15_CR7","first-page":"277","volume":"45","author":"CJ Zhao","year":"2014","unstructured":"Zhao, C.J.: Advances of research and application in remote sensing for agriculture. Trans. Chin. Soc. Agric. Mach. 45(12), 277\u2013293 (2014)","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"issue":"4","key":"15_CR8","first-page":"539","volume":"19","author":"WT Zhou","year":"2015","unstructured":"Zhou, W.T., Wu, B.F., Zhang, M., et al.: Comprehensive monitoring of crop growth \u2013 take India as an example. J. Remote Sens. 19(4), 539\u2013549 (2015)","journal-title":"J. Remote Sens."},{"issue":"5","key":"15_CR9","first-page":"1351","volume":"35","author":"JM Tang","year":"2015","unstructured":"Tang, J.M., Liao, Q.H., Liu, Y.Q., et al.: Estimating leaf area index of crops based on hyperspectral compact airborne spectrographic imager (CASI) data. Spectrosc. Spectral Anal. 35(5), 1351\u20131356 (2015)","journal-title":"Spectrosc. Spectral Anal."},{"key":"15_CR10","doi-asserted-by":"publisher","first-page":"1111","DOI":"10.3389\/fpls.2017.01111","volume":"8","author":"G Yang","year":"2017","unstructured":"Yang, G., Liu, J., Zhao, C., et al.: Unmanned aerial vehicle remote sensing for field-based crop phenotyping: current status and perspectives. Front. Plant Sci. 8, 1111 (2017)","journal-title":"Front. Plant Sci."},{"issue":"6","key":"15_CR11","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","volume":"13","author":"C Zhang","year":"2012","unstructured":"Zhang, C., Kovacs, J.M.: The application of small unmanned aerial systems for precision agriculture: a review. Precision Agric. 13(6), 693\u2013712 (2012)","journal-title":"Precision Agric."},{"issue":"7","key":"15_CR12","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1016\/S2095-3119(14)60818-2","volume":"13","author":"S Shao","year":"2014","unstructured":"Shao, S., Wei, X., et al.: Framework of SAGI agriculture remote sensing and its perspectives in supporting national food security. J. Integr. Agric. 13(7), 1443\u20131450 (2014)","journal-title":"J. Integr. Agric."},{"issue":"4","key":"15_CR13","doi-asserted-by":"publisher","first-page":"4026","DOI":"10.3390\/rs70404026","volume":"7","author":"S Candiago","year":"2015","unstructured":"Candiago, S., Remondino, F., De Giglio, M., et al.: Evaluating multispectral images and vegetation indices for precision farming applications from UAV images. Remote Sens. 7(4), 4026\u20134047 (2015)","journal-title":"Remote Sens."},{"issue":"11","key":"15_CR14","doi-asserted-by":"publisher","first-page":"11013","DOI":"10.3390\/rs61111013","volume":"6","author":"J Suomalainen","year":"2014","unstructured":"Suomalainen, J., Anders, N., Iqbal, S., et al.: A lightweight hyperspectral mapping system and photogrammetric processing chain for unmanned aerial vehicles. Remote Sens. 6(11), 11013\u201311030 (2014)","journal-title":"Remote Sens."},{"issue":"1","key":"15_CR15","first-page":"110","volume":"33","author":"XQ Zhao","year":"2017","unstructured":"Zhao, X.Q., Yang, G.J., Liu, J.G., et al.: Estimation of soybean breeding yield based on optimization of spatial scale of UAV hyperspectral image. Trans. CSAE 33(1), 110\u2013116 (2017)","journal-title":"Trans. CSAE"},{"issue":"7","key":"15_CR16","first-page":"3259","volume":"9","author":"S Nie","year":"2016","unstructured":"Nie, S., Wang, C., Dong, P., et al.: Estimating leaf area index of maize using airborne discrete-return LiDAR Data. Remote Sens. Lett. 9(7), 3259\u20133266 (2016)","journal-title":"Remote Sens. Lett."},{"key":"15_CR17","first-page":"666","volume":"7","author":"O Vergarad\u00edaz","year":"2016","unstructured":"Vergarad\u00edaz, O., Zamanallah, M.A., Masuka, B., et al.: A novel remote sensing approach for prediction of maize yield under different conditions of nitrogen fertilization. Front. Plant Sci. 7, 666 (2016)","journal-title":"Front. Plant Sci."},{"key":"15_CR18","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1016\/j.ecolind.2016.03.036","volume":"67","author":"W Li","year":"2016","unstructured":"Li, W., Niu, Z., Chen, H., et al.: Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system. Ecol. Ind. 67, 637\u2013648 (2016)","journal-title":"Ecol. Ind."},{"key":"15_CR19","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.jag.2015.02.012","volume":"39","author":"J Bendig","year":"2015","unstructured":"Bendig, J., Yu, K., Aasen, H., et al.: Combining UAV-based plant height from crop surface models, visible, and near-infrared vegetation indices for biomass monitoring in barley. Int. J. Appl. Earth Obs. Geoinf. 39, 79\u201387 (2015)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"9","key":"15_CR20","doi-asserted-by":"publisher","first-page":"706","DOI":"10.3390\/rs8090706","volume":"8","author":"M Schirrmann","year":"2016","unstructured":"Schirrmann, M., Giebel, A., Gleiniger, F., et al.: Monitoring agronomic parameters of winter wheat crops with low-cost UAV imagery. Remote Sens. 8(9), 706 (2016)","journal-title":"Remote Sens."},{"issue":"10","key":"15_CR21","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.jag.2014.03.018","volume":"32","author":"MM Saberioon","year":"2014","unstructured":"Saberioon, M.M., Amin, M.S.M., Anuar, A.R., et al.: Assessment of rice leaf chlorophyll content using visible bands at different growth stages at both the leaf and canopy scale. Int. J. Appl. Earth Obs. Geoinf. 32(10), 35\u201345 (2014)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"C","key":"15_CR22","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.compag.2015.03.019","volume":"114","author":"J Torres-S\u00e1nchez","year":"2015","unstructured":"Torres-S\u00e1nchez, J., L\u00f3pez-Granados, F., Pe\u00f1a, J.M.: An automatic object-based method for optimal thresholding in UAV images: application for vegetation detection in herbaceous crops. Comput. Electron. Agric. 114(C), 43\u201352 (2015)","journal-title":"Comput. Electron. Agric."},{"key":"15_CR23","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.isprsjprs.2017.05.003","volume":"130","author":"X Zhou","year":"2017","unstructured":"Zhou, X., Zheng, H.B., Xu, X.Q., et al.: Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery. ISPRS J. Photogram. Remote Sens. 130, 246\u2013255 (2017)","journal-title":"ISPRS J. Photogram. Remote Sens."},{"issue":"2","key":"15_CR24","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","volume":"8","author":"CJ Tucker","year":"1979","unstructured":"Tucker, C.J.: Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8(2), 127\u2013150 (1979)","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"15_CR25","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1080\/10106040108542184","volume":"16","author":"M Louhaichi","year":"2001","unstructured":"Louhaichi, M., Borman, M.M., Johnson, D.E.: Spatially located platform and aerial photography for documentation of grazing impacts on wheat. Geocarto Int. 16(1), 65\u201370 (2001)","journal-title":"Geocarto Int."},{"issue":"2","key":"15_CR26","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.compag.2008.03.009","volume":"63","author":"GE Meyer","year":"2008","unstructured":"Meyer, G.E., Neto, J.C.: Verification of color vegetation indices for automated crop imaging applications. Comput. Electron. Agric. 63(2), 282\u2013293 (2008)","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"15_CR27","doi-asserted-by":"publisher","first-page":"259","DOI":"10.13031\/2013.27838","volume":"38","author":"DM Woebbecke","year":"1995","unstructured":"Woebbecke, D.M., Meyer, G.E., Von Bargen, K., et al.: Color indices for weed identification under various soil, residue, and lighting conditions. Trans. ASAE 38(1), 259\u2013269 (1995)","journal-title":"Trans. ASAE"},{"key":"15_CR28","unstructured":"Kataoka, T., Kaneko, T., Okamoto, H., et al.: Crop growth estimation system using machine vision. In: Proceedings of 2003 IEEE\/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2003, vol. 2, pp. b1079\u2013b1083. IEEE (2003)"},{"issue":"5","key":"15_CR29","doi-asserted-by":"publisher","first-page":"n\/a-n\/a","DOI":"10.1029\/2002GL016450","volume":"30","author":"Anatoly A. Gitelson","year":"2003","unstructured":"Gitelson, A.A., Vi\u00f1a, A., Arkebauer, T.J., et al.: Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophys. Res. Lett. 30(5) (2003)","journal-title":"Geophysical Research Letters"}],"container-title":["IFIP Advances in Information and Communication Technology","Computer and Computing Technologies in Agriculture XI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-06179-1_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,8]],"date-time":"2023-01-08T01:07:43Z","timestamp":1673140063000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-06179-1_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030061784","9783030061791"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-06179-1_15","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"9 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CCTA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer and Computing Technologies in Agriculture","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jilin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 August 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 August 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccta2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iccta.cn","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}