ArticleSensors (Basel, Switzerland)2020
Hyperspectral Inversion of Soil Organic Matter Content Based on a Combined Spectral Index Model.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- A lightweight hybrid transformer approach for hyperspectral imaging-based drought tolerance evaluation in tea plants.Plant methods · 2025Article
- Article
- Comparison of Performance of Predicting the Wear Amount of Tire Tread Depending on Sensing Information.Sensors (Basel, Switzerland) · 2023Article
- Improved multivariate modeling for soil organic matter content estimation using hyperspectral indexes and characteristic bands.PloS one · 2023Article
- Inversion of Soil Organic Matter Content Based on Improved Convolutional Neural Network.Sensors (Basel, Switzerland) · 2022Article
- Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm.Sensors (Basel, Switzerland) · 2022Article
- Deep Learning and Hyperspectral Images Based Tomato Soluble Solids Content and Firmness Estimation.Frontiers in plant science · 2022Article
- Hyperspectral band selection and modeling of soil organic matter content in a forest using the Ranger algorithm.PloS one · 2021Article
- ASAMS: An Adaptive Sequential Sampling and Automatic Model Selection for Artificial Intelligence Surrogate Modeling.Sensors (Basel, Switzerland) · 2020Article
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7 authors.
Funding
Abstract
Soil organic matter (SOM) refers to all carbon-containing organic matter in soil and is oneof the most important indicators of soil fertility. The hyperspectral inversion analysis of SOMtraditionally relies on laboratory chemical testing methods, which have the disadvantages of beinginefficient and time-consuming. In this study, 69 soil samples were collected from the Honghufarmland area and a mining area in northwest China. After pretreatment, 10 spectral indicators wereobtained. Ridge regression, kernel ridge regression, Bayesian ridge regression, and AdaBoostalgorithms were then used to construct the SOM hyperspectral inversion model based on thecharacteristic bands, and the accuracy of the models was compared. The results showed that theAdaBoost algorithm based on a grid search had the best accuracy in the different regions. For themining area in northwest China [...].
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