Optimising three-band spectral indices to assess aerial N concentration,N uptake and aboveground biomass of winter wheat remotely in China and Germany |
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| Institution: | 1. College of Ecology & Environmental Science, Inner Mongolia Agricultural University, 010019 Hohhot, China;2. Chair of Plant Nutrition, Department of Plant Sciences, Technische Universität München, Emil-Ramann-Str. 2, D-85350 Freising-Weihenstephan, Germany;3. College of Resources & Environmental Sciences, China Agricultural University, 100094 Beijing, China;1. College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China;2. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China;3. College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China;4. Agricultural Product Quality Safety and Standards Institute, Jiangxi Academy of Agricultural Sciences, Nanchang 330013, China;1. College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 800017, China;2. Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China;3. Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China;4. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China;5. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;6. School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China;7. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China;2. Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China;3. Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China;4. College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China;5. School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China;1. Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and Geo-information & Shenzhen Key Laboratory of Spatial-temporal Smart Sensing and Services, Shenzhen University, 518060 Shenzhen, China;2. College of Life and Marine Sciences, Shenzhen University, 518060 Shenzhen, China |
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| Abstract: | Remotely and accurately quantifying the canopy nitrogen status in crops is essential for regional studies of N budgets and N balances. In this study, we optimised three-band spectral algorithms to estimate the N status of winter wheat. This study extends previous work to optimise the band combinations further and identifies the optimised central bands and suitable bandwidths of the three-band nitrogen planar domain index (NPDI) for estimating the aerial N uptake, N concentration and aboveground biomass. Analysis of the influence of bandwidth change on the accuracy of estimating the canopy N status and aboveground biomass indicated that the suitable bandwidths for optimised central bands were 37 nm at 846 nm, 13 nm at 738 nm and 57 nm at 560 nm for assessing the aerial N uptake and were 37 nm at 958 nm, 21 nm at 696 nm and 73 nm at 578 nm for the assessment of the aerial N concentration and were 49 nm at 806 nm, 17 nm at 738 nm and 57 nm at 560 nm for the estimation of aboveground biomass. The optimised three-band NPDI could consistently and stably estimate the aerial N uptake and aboveground biomass of winter wheat in the vegetative stage and the aerial N concentration in the reproductive stage compared to the fixed band combinations. With suitable bandwidths, the broadband NPDI demonstrated excellent performance in estimating the aerial N concentration, N uptake and biomass. We conclude that the band-optimised algorithm represents a promising tool to measure the improved performance of the NPDI in estimating the aerial N uptake and biomass in the vegetative stage and the aerial N concentration in the reproductive stage, which will be useful for designing improved nitrogen diagnosis systems and for enhancing the applications of ground- and satellite-based sensors. |
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| Keywords: | Band selection Nitrogen N status Hyperspectral indices Remote sensing Precision Farming |
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