کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8867867 | 1621787 | 2018 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Improved nitrogen retrievals with airborne-derived fluorescence and plant traits quantified from VNIR-SWIR hyperspectral imagery in the context of precision agriculture
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
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چکیده انگلیسی
In semi-arid conditions, nitrogen (N) is the main limiting factor of crop yield after water, and its accurate quantification remains essential. Recent studies have demonstrated that solar-induced chlorophyll fluorescence (SIF) quantified from hyperspectral imagery is a reliable indicator of photosynthetic activity in the context of precision agriculture and for early stress detection purposes. The role of fluorescence might be critical to our understanding of N levels due to its link with photosynthesis and the maximum rate of carboxylation (Vcmax) under stress. The research presented here aimed to assess the contribution played by airborne-retrieved solar-induced chlorophyll fluorescence (SIF) to the retrieval of N under irrigated and rainfed Mediterranean conditions. The study was carried out at three field sites used for wheat phenotyping purposes in Southern Spain during the 2015 and 2016 growing seasons. Airborne campaigns acquired imagery with two hyperspectral cameras covering the 400-850â¯nm (20â¯cm resolution) and 950-1750â¯nm (50â¯cm resolution) spectral regions. The performance of multiple regression models built for N quantification with and without including the airborne-retrieved SIF was compared with the performance of models built with plant traits estimated by model inversion, and also with standard approaches based on single spectral indices. Results showed that the accuracy of the models for N retrieval increased when chlorophyll fluorescence was included (r2LOOCVâ¯â¥â¯0.92; pâ¯<â¯0.0005) as compared to models only built with chlorophyll aâ¯+â¯b (Cab), dry matter (Cm) and equivalent water thickness (Cw) plant traits (r2LOOCV ranged from 0.68 to 0.77; pâ¯<â¯0.005). Moreover, nitrogen indices (NIs) centered at 1510â¯nm yielded more reliable agreements with N concentration (r2â¯=â¯0.69) than traditional chlorophyll indices (TCARI/OSAVI r2â¯=â¯0.45) and structural indices (NDVI r2â¯=â¯0.57) calculated in the VNIR region. This work demonstrates that under irrigated and non-irrigated conditions, indicators directly linked with photosynthesis such as chlorophyll fluorescence improves predictions of N concentration.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 70, August 2018, Pages 105-117
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 70, August 2018, Pages 105-117
نویسندگان
Carlos Camino, Victoria González-Dugo, Pilar Hernández, J.C. Sillero, Pablo J. ZarcoâTejada,