Deep-Learning-Based Approach for Estimation of Fractional Abundance of Nitrogen in Soil From Hyperspectral Data
One of the vital growth nutrient parameters of crops is soil Nitrogen (N) content. The ability to accurately grasp soil nutrient information is a prerequisite for scientific fertilization within the field of precision agriculture. Information pertaining to soil macronutrients, such as N, may be obta...
Main Authors: | Ajay Kumar Patel, Jayanta Kumar Ghosh, Shivam Pande, Sameer Usmangani Sayyad |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9266791/ |
Similar Items
-
Non-linear spectral unmixing of hyperspectral data using Modified PPNMM
by: Ankur Dixit, et al.
Published: (2021-03-01) -
Unmixing of Hyperspectral Data Using Spectral Libraries
by: Sefa Küçük, et al.
Published: (2020-04-01) -
Collaborative Coupled Hyperspectral Unmixing Based Subpixel Change Detection for Analyzing Coastal Wetlands
by: Minghui Chang, et al.
Published: (2021-01-01) -
Hierarchical Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing with Spectral Variability
by: Tatsumi Uezato, et al.
Published: (2020-07-01) -
Exploration of Planetary Hyperspectral Images with Unsupervised Spectral Unmixing: A Case Study of Planet Mars
by: Jun Liu, et al.
Published: (2018-05-01)