Cropping intensity mapping in Sentinel-2 and Landsat-8/9 remote sensing data using temporal transfer of a stacked ensemble machine learning model within google earth engine
Author:
Affiliation:
1. Department of Photogrammetry and Remote Sensing, K. N. Toosi University of Technology, Tehran, Iran
2. Department of Earth Sciences & CERI Research Center, Sapienza University of Rome, Rome, Italy
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2024.2387786
Reference74 articles.
1. A Parallel-Cascaded Ensemble of Machine Learning Models for Crop Type Classification in Google Earth Engine Using Multi-Temporal Sentinel-1/2 and Landsat-8/9 Remote Sensing Data
2. Code smell detection using feature selection and stacking ensemble: An empirical investigation
3. Detecting and Assessing the Spatio-Temporal Land Use Land Cover Changes of Bahrain Island During 1986–2020 Using Remote Sensing and GIS
4. Past and future land use/land cover, and climate change impacts on environmental sustainability in Vea catchment, Ghana
5. Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques
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