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Article

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

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
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Remote Sens. 2020, 12(18), 2929; https://doi.org/10.3390/rs12182929
Received: 6 August 2020 / Revised: 6 September 2020 / Accepted: 7 September 2020 / Published: 10 September 2020
(This article belongs to the Collection Sentinel-2: Science and Applications)
Nondestructive and accurate estimating of the forage nitrogen–phosphorus (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. View Full-Text
Keywords: forage nutrition; spectral bands; red-edge; vegetation indices; multispectral forage nutrition; spectral bands; red-edge; vegetation indices; multispectral
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MDPI and ACS Style

Gao, J.; Liu, J.; Liang, T.; Hou, M.; Ge, J.; Feng, Q.; Wu, C.; Li, W. 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. Remote Sens. 2020, 12, 2929. https://doi.org/10.3390/rs12182929

AMA Style

Gao J, Liu J, Liang T, Hou M, Ge J, Feng Q, Wu C, Li W. 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. Remote Sensing. 2020; 12(18):2929. https://doi.org/10.3390/rs12182929

Chicago/Turabian Style

Gao, Jinlong, Jie Liu, Tiangang Liang, Mengjing Hou, Jing Ge, Qisheng Feng, Caixia Wu, and Wenlong Li. 2020. "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" Remote Sensing 12, no. 18: 2929. https://doi.org/10.3390/rs12182929

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