An integrated solar-induced chlorophyll fluorescence model for more accurate soil organic carbon content estimation in an Alpine agricultural area-Reference-Cited by-同舟云学术

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An integrated solar-induced chlorophyll fluorescence model for more accurate soil organic carbon content estimation in an Alpine agricultural area

Published:2023-01-07 Issue:1-2 Volume:486 Page:235-252
ISSN:0032-079X
Container-title:Plant and Soil
language:en
Short-container-title:Plant Soil

Author:

Yu Qing,Lu Hongwei,Yao Tianci,Feng Wei,Xue Yuxuan

Funder

Strategic Priority Research Program of the Chinese Academy of Sciences

Second Tibetan Plateau Scientific Expedition and Research Program

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Subject

Plant Science,Soil Science

Link

https://link.springer.com/content/pdf/10.1007/s11104-022-05863-x.pdf

Reference71 articles.

1. Ayala Izurieta JE, Jara Santillán CA, Márquez CO et al (2022) Improving the remote estimation of soil organic carbon in complex ecosystems with Sentinel-2 and GIS using gaussian processes regression. Plant Soil 479(1–2):159–183. https://doi.org/10.1007/s11104-022-05506-1

2. Ben-Dor E, Inbar Y, Chen Y et al (1997) The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400–2500 nm) during a controlled decomposition process. Remote Sens Environ 61:1–15. https://doi.org/10.1016/S0034-4257(96)00120-4

3. Breiman L (2001) Random forests. Mach Learn 45:5–32. https://doi.org/10.1023/A:1010933404324

4. Callies J, Corpaccioli E, Eisinger M (2000) GOME-2-Metop’s second-generation sensor for operational ozone monitoring. ESA Bull 102:28–37

5. Chen D, Chang N, Xiao J et al (2019) Mapping dynamics of soil organic matter in croplands with MODIS data and machine learning algorithms. Sci Total Environ 669:844–855. https://doi.org/10.1016/j.scitotenv.2019.03.151

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