23 results on '"Gao, Bingbo"'
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2. A Segment Anything Model based weakly supervised learning method for crop mapping using Sentinel-2 time series images
3. Crop residue burning in China (2019–2021): Spatiotemporal patterns, environmental impact, and emission dynamics
4. Mapping urban construction sites in China through geospatial data fusion: Methods and applications
5. Priority areas identification for arable soil pollution prevention based on the accumulative risk of heavy metals
6. Deep learning in cropland field identification: A review
7. TSANet: A deep learning framework for the delineation of agricultural fields utilizing satellite image time series
8. Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach
9. Land use/cover and land degradation across the Eurasian steppe: Dynamics, patterns and driving factors
10. The spatiotemporal variation of PM2.5-O3 association and its influencing factors across China: Dynamic Simil-Hu lines
11. The division of PM2.5-O3 composite airborne pollution across China based on spatiotemporal clustering
12. Multi-objective optimization sampling based on Pareto optimality for soil mapping
13. Optimization of the sampling design for multiobjective soil mapping using the multiple path SSA (MP-SSA) method
14. Causal inference in spatial statistics
15. Multi-modal fusion of satellite and street-view images for urban village classification based on a dual-branch deep neural network
16. A two-point machine learning method for the spatial prediction of soil pollution
17. Large-scale crop mapping from multi-source optical satellite imageries using machine learning with discrete grids
18. Phenology-based classification of crop species and rotation types using fused MODIS and Landsat data: The comparison of a random-forest-based model and a decision-rule-based model
19. Improving prediction of soil organic carbon content in croplands using phenological parameters extracted from NDVI time series data
20. Understanding the causal influence of major meteorological factors on ground ozone concentrations across China
21. Ground ozone variations at an urban and a rural station in Beijing from 2006 to 2017: Trend, meteorological influences and formation regimes
22. Understanding temporal patterns and characteristics of air quality in Beijing: A local and regional perspective
23. Upward-fusion urban DTM generating method using airborne Lidar data
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