{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T23:52:14Z","timestamp":1773100334139,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T00:00:00Z","timestamp":1544400000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The efficient use of nitrogen fertilizer is a crucial problem in modern agriculture. Fertilization has to be minimized to reduce environmental impacts but done so optimally without negatively affecting yield. In June 2017, a controlled experiment with eight different nitrogen treatments was applied to winter wheat plants and investigated with the UAV-based hyperspectral pushbroom camera Resonon Pika-L (400\u20131000 nm). The system, in combination with an accurate inertial measurement unit (IMU) and precise gimbal, was very stable and capable of acquiring hyperspectral imagery of high spectral and spatial quality. Additionally, in situ measurements of 48 samples (leaf area index (LAI), chlorophyll (CHL), and reflectance spectra) were taken in the field, which were equally distributed across the different nitrogen treatments. These measurements were used to predict grain yield, since the parameter itself had no direct effect on the spectral reflection of plants. Therefore, we present an indirect approach based on LAI and chlorophyll estimations from the acquired hyperspectral image data using partial least-squares regression (PLSR). The resulting models showed a reliable predictability for these parameters (R2LAI = 0.79, RMSELAI [m2m\u22122] = 0.18, R2CHL = 0.77, RMSECHL [\u00b5g cm\u22122] = 7.02). The LAI and CHL predictions were used afterwards to calibrate a multiple linear regression model to estimate grain yield (R2yield = 0.88, RMSEyield [dt ha\u22121] = 4.18). With this model, a pixel-wise prediction of the hyperspectral image was performed. The resulting yield estimates were validated and opposed to the different nitrogen treatments, which revealed that, above a certain amount of applied nitrogen, further fertilization does not necessarily lead to larger yield.<\/jats:p>","DOI":"10.3390\/rs10122000","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T11:31:16Z","timestamp":1544441476000},"page":"2000","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":144,"title":["High-Resolution UAV-Based Hyperspectral Imagery for LAI and Chlorophyll Estimations from Wheat for Yield Prediction"],"prefix":"10.3390","volume":"10","author":[{"given":"Martin","family":"Kanning","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Working Group, Remote Sensing and Digital Image Analysis, University of Osnabr\u00fcck, Wachsbleiche 27, D-49090 Osnabr\u00fcck, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2873-2425","authenticated-orcid":false,"given":"Insa","family":"K\u00fchling","sequence":"additional","affiliation":[{"name":"Institute of Agricultural and Nutritional Sciences, Department of Agronomy and Organic Farming, Martin Luther University Halle-Wittenberg, D-06120 Halle (Saale), Germany"}]},{"given":"Dieter","family":"Trautz","sequence":"additional","affiliation":[{"name":"Faculty of Agricultural Sciences and Landscape Architecture, Working Group Sustainable Agro-Ecosystems, Osnabr\u00fcck University of Applied Sciences, D-49090 Osnabr\u00fcck, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4652-1640","authenticated-orcid":false,"given":"Thomas","family":"Jarmer","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Working Group, Remote Sensing and Digital Image Analysis, University of Osnabr\u00fcck, Wachsbleiche 27, D-49090 Osnabr\u00fcck, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5995","DOI":"10.1073\/pnas.96.11.5995","article-title":"Global environmental impacts of agricultural expansion: The need for sustainable and efficient practices","volume":"96","author":"Tilman","year":"1999","journal-title":"Proc. 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