Multi-scale spatial and spectral feature fusion for soil carbon content prediction based on hyperspectral images-Reference-Cited by-同舟云学术

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Multi-scale spatial and spectral feature fusion for soil carbon content prediction based on hyperspectral images

Published:2024-03 Issue: Volume:160 Page:111843
ISSN:1470-160X
Container-title:Ecological Indicators
language:en
Short-container-title:Ecological Indicators

Author:

Li Xueying,Li Zongmin,Qiu Huimin,Chen Guangyuan,Fan Pingping,Liu Yan

Funder

Natural Science Foundation of Shandong Province

Shandong Academy of Sciences

Natural Science Foundation of Qingdao Municipality

National Natural Science Foundation of China

Key Technology Research and Development Program of Shandong Province

Publisher

Elsevier BV

Reference41 articles.

1. Vis-SWIR spectral prediction model for soil organic matter with different grouping strategies;Bao;Catena,2020

2. Using a global VNIR soil-spectral library for local soil characterization and landscape modeling in a 2nd-order Uganda watershed;Brown;Geoderma,2007

3. Evaluating the capability of the sentinel 2 data for soil organic carbon prediction in croplands;Castaldi;ISPRS J. Photogramm. Remote Sens.,2018

4. Hyperspectral texture metrology based on joint probability of spectral and spatial distribution;Chu;IEEE Trans. Image Process.,2021

5. Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models;Dristi;Sensors,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A critical systematic review on spectral-based soil nutrient prediction using machine learning;Environmental Monitoring and Assessment;2024-07-04

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