A review of spectral feature extraction and multi-feature fusion methods in predicting soil organic carbon
Author:
Affiliation:
1. School of Data Science, Qingdao University of Science and Technology, Qingdao, China
2. Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, China
Funder
the Natural Science Foundation of Shandong Province
National Natural Science Foundation of China
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/05704928.2024.2369570
Reference127 articles.
1. Assessing the effects of deforestation and intensive agriculture on the soil quality through digital soil mapping
2. UAS-based soil carbon mapping using VIS-NIR (480–1000 nm) multi-spectral imaging: Potential and limitations
3. Improving the Accuracy of Soil Organic Carbon Content Prediction Based on Visible and near-Infrared Spectroscopy and Machine Learning;Xu M. X.;Environ. Earth Sci.,2021
4. Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data
5. Soil carbon change and its responses to agricultural practices in Australian agro-ecosystems: A review and synthesis
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