Çimtay, Y. Estimating Plant Nitrogen by Developing an Accurate Correlation between VNIR-Only Vegetation Indexes and the Normalized Difference Nitrogen Index. Remote Sens.2023, 15, 3898.
Çimtay, Y. Estimating Plant Nitrogen by Developing an Accurate Correlation between VNIR-Only Vegetation Indexes and the Normalized Difference Nitrogen Index. Remote Sens. 2023, 15, 3898.
Çimtay, Y. Estimating Plant Nitrogen by Developing an Accurate Correlation between VNIR-Only Vegetation Indexes and the Normalized Difference Nitrogen Index. Remote Sens.2023, 15, 3898.
Çimtay, Y. Estimating Plant Nitrogen by Developing an Accurate Correlation between VNIR-Only Vegetation Indexes and the Normalized Difference Nitrogen Index. Remote Sens. 2023, 15, 3898.
Abstract
Nitrogen is crucial for plant physiology due to the fact that plants consume a significant amount of nitrogen during the development period. Nitrogen supports the root, leaf, stem, branch, shoot and fruit development of plants. At the same time, it also increases flowering. To monitor the vegetation nitrogen concentration, one of the best indicator developed in the literature is Normalized Difference Nitrogen Index (NDNI) which is based on the usage of the spectral bands: 1510 and 1680 nm. from Short-Wave Infrared (SWIR) region of electromagnetic spectrum. However, majority of the remote sensing sensors like cameras and/or satellites do not have a SWIR sensor due to the high costs. Many vegetation indexes like NDVI, EVI, MNLI, have been developed in also VNIR region to monitor the greenness and healthy of the crops. However these indexes are not very correlated to the nitrogen content. Therefore, in this study, a novel method is developed which transforms the estimated VNIR band indexes to NDNI by using a regression method between a group of VNIR indexes and NDNI. Training is employed by using VNIR band indexes as input and NDNI as output which are both calculated from the same location. After training, 0.93 correlation is achieved. Therefore, by using only VNIR band sensors, it is possible to estimate the nitrogen content of the plant with high accuracy.
Keywords
agriculture; land cover; remote sensing; fertilizer; yield
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
