462 related articles for article (PubMed ID: 33059134)
1. Prediction of soil organic carbon and the C:N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and Landsat-8 images.
Zhou T; Geng Y; Ji C; Xu X; Wang H; Pan J; Bumberger J; Haase D; Lausch A
Sci Total Environ; 2021 Feb; 755(Pt 2):142661. PubMed ID: 33059134
[TBL] [Abstract][Full Text] [Related]
2. High-resolution digital mapping of soil organic carbon and soil total nitrogen using DEM derivatives, Sentinel-1 and Sentinel-2 data based on machine learning algorithms.
Zhou T; Geng Y; Chen J; Pan J; Haase D; Lausch A
Sci Total Environ; 2020 Aug; 729():138244. PubMed ID: 32498148
[TBL] [Abstract][Full Text] [Related]
3. Estimation of Soil Organic Carbon Content in the Ebinur Lake Wetland, Xinjiang, China, Based on Multisource Remote Sensing Data and Ensemble Learning Algorithms.
Xie B; Ding J; Ge X; Li X; Han L; Wang Z
Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408299
[TBL] [Abstract][Full Text] [Related]
4. High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.
Forkuor G; Hounkpatin OK; Welp G; Thiel M
PLoS One; 2017; 12(1):e0170478. PubMed ID: 28114334
[TBL] [Abstract][Full Text] [Related]
5. A novel intelligence approach based active and ensemble learning for agricultural soil organic carbon prediction using multispectral and SAR data fusion.
Nguyen TT; Pham TD; Nguyen CT; Delfos J; Archibald R; Dang KB; Hoang NB; Guo W; Ngo HH
Sci Total Environ; 2022 Jan; 804():150187. PubMed ID: 34517328
[TBL] [Abstract][Full Text] [Related]
6. Effects of optical and radar satellite observations within Google Earth Engine on soil organic carbon prediction models in Spain.
Zhou T; Geng Y; Lv W; Xiao S; Zhang P; Xu X; Chen J; Wu Z; Pan J; Si B; Lausch A
J Environ Manage; 2023 Jul; 338():117810. PubMed ID: 37003220
[TBL] [Abstract][Full Text] [Related]
7. High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.
Wang B; Waters C; Orgill S; Gray J; Cowie A; Clark A; Liu L
Sci Total Environ; 2018 Jul; 630():367-378. PubMed ID: 29482145
[TBL] [Abstract][Full Text] [Related]
8. Predictive Mapping of Topsoil Organic Carbon in an Alpine Environment Aided by Landsat TM.
Yang R; Rossiter DG; Liu F; Lu Y; Yang F; Yang F; Zhao Y; Li D; Zhang G
PLoS One; 2015; 10(10):e0139042. PubMed ID: 26473739
[TBL] [Abstract][Full Text] [Related]
9. Large-scale digital mapping of topsoil total nitrogen using machine learning models and associated uncertainty map.
Parsaie F; Farrokhian Firouzi A; Mousavi SR; Rahmani A; Sedri MH; Homaee M
Environ Monit Assess; 2021 Mar; 193(4):162. PubMed ID: 33665671
[TBL] [Abstract][Full Text] [Related]
10. Machine learning-based detection of soil salinity in an arid desert region, Northwest China: A comparison between Landsat-8 OLI and Sentinel-2 MSI.
Wang J; Ding J; Yu D; Teng D; He B; Chen X; Ge X; Zhang Z; Wang Y; Yang X; Shi T; Su F
Sci Total Environ; 2020 Mar; 707():136092. PubMed ID: 31972911
[TBL] [Abstract][Full Text] [Related]
11. Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.
Ließ M; Schmidt J; Glaser B
PLoS One; 2016; 11(4):e0153673. PubMed ID: 27128736
[TBL] [Abstract][Full Text] [Related]
12. Digital soil mapping of soil total nitrogen based on Landsat 8, Sentinel 2, and WorldView-2 images in smallholder farms in Yellow River Basin, China.
Xu Y; Li B; Shen X; Li K; Cao X; Cui G; Yao Z
Environ Monit Assess; 2022 Mar; 194(4):282. PubMed ID: 35294667
[TBL] [Abstract][Full Text] [Related]
13. Ensemble Machine Learning Approach Improves Predicted Spatial Variation of Surface Soil Organic Carbon Stocks in Data-Limited Northern Circumpolar Region.
Mishra U; Gautam S; Riley WJ; Hoffman FM
Front Big Data; 2020; 3():528441. PubMed ID: 33693410
[TBL] [Abstract][Full Text] [Related]
14. Inversion of soil organic carbon content based on the two-point machine learning method.
Wang C; Gao B; Yang K; Wang Y; Sukhbaatar C; Yin Y; Feng Q; Yao X; Zhang Z; Yang J
Sci Total Environ; 2024 Sep; 943():173608. PubMed ID: 38848920
[TBL] [Abstract][Full Text] [Related]
15. Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra.
Peng Y; Xiong X; Adhikari K; Knadel M; Grunwald S; Greve MH
PLoS One; 2015; 10(11):e0142295. PubMed ID: 26555071
[TBL] [Abstract][Full Text] [Related]
16. Estimation of dissolved organic carbon from inland waters at a large scale using satellite data and machine learning methods.
Harkort L; Duan Z
Water Res; 2023 Feb; 229():119478. PubMed ID: 36527868
[TBL] [Abstract][Full Text] [Related]
17. Remote sensing-based prediction of organic carbon in agricultural and natural soils influenced by salt and sand mining using machine learning.
Zhang T; Li Y; Wang M
J Environ Manage; 2024 Feb; 352():120107. PubMed ID: 38237334
[TBL] [Abstract][Full Text] [Related]
18. Tracking changes in soil organic carbon across the heterogeneous agricultural landscape of the Lower Fraser Valley of British Columbia.
Paul SS; Dowell L; Coops NC; Johnson MS; Krzic M; Geesing D; Smukler SM
Sci Total Environ; 2020 Aug; 732():138994. PubMed ID: 32438157
[TBL] [Abstract][Full Text] [Related]
19. Digital Mapping of Soil Organic Carbon Based on Machine Learning and Regression Kriging.
Zhu C; Wei Y; Zhu F; Lu W; Fang Z; Li Z; Pan J
Sensors (Basel); 2022 Nov; 22(22):. PubMed ID: 36433592
[TBL] [Abstract][Full Text] [Related]
20. Mapping soil organic carbon stocks and trends with satellite-driven high resolution maps over South Africa.
Venter ZS; Hawkins HJ; Cramer MD; Mills AJ
Sci Total Environ; 2021 Jun; 771():145384. PubMed ID: 33540160
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
