EXPLORING SENTINEL-2 FOR LAND COVER AND CROP MAPPING IN PORTUGAL

14 citations as recorded by crossref.

1. Leveraging ground truth data and GIS technologies for reliable crop analysis and agricultural production optimization J. Shah et al. https://doi.org/10.1007/s41870-024-02101-8
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3. Vegetation Mapping with Random Forest Using Sentinel 2 and GLCM Texture Feature—A Case Study for Lousã Region, Portugal P. Mohammadpour et al. https://doi.org/10.3390/rs14184585
4. Addressing sample imbalance in deep learning based multi-temporal crop classification: a study in Jhansi, India M. Antony Ravi et al. https://doi.org/10.1080/01431161.2026.2654095
5. Forest Land Resource Information Acquisition with Sentinel-2 Image Utilizing Support Vector Machine, K-Nearest Neighbor, Random Forest, Decision Trees and Multi-Layer Perceptron C. Zhang et al. https://doi.org/10.3390/f14020254
6. Refining European Crop Mapping Classification Through the Integration of Permanent Crops: A Case Study in Rapidly Transitioning Irrigated Landscapes Induced by Dam Construction M. Quintela et al. https://doi.org/10.3390/rs17243979
7. Mapping Crop Types of Germany by Combining Temporal Statistical Metrics of Sentinel-1 and Sentinel-2 Time Series with LPIS Data S. Asam et al. https://doi.org/10.3390/rs14132981
8. Crop Type Mapping and Winter Wheat Yield Prediction Utilizing Sentinel-2: A Case Study from Upper Thracian Lowland, Bulgaria I. Kamenova et al. https://doi.org/10.3390/rs16071144
9. Mapping of Forest Species Using Sentinel-2A Images in the Alentejo and Algarve Regions, Portugal C. Isbaex et al. https://doi.org/10.3390/land13122184
10. Rapid and Automated Approach for Early Crop Mapping Using Sentinel-1 and Sentinel-2 on Google Earth Engine; A Case of a Highly Heterogeneous and Fragmented Agricultural Region H. Saad El Imanni et al. https://doi.org/10.3390/jimaging8120316
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12. Adaptive Capacity of Machine Learning Approaches for Leaf Area Estimation in Faba Bean Under Diverse Agro-environmental Conditions M. Kaya et al. https://doi.org/10.15832/ankutbd.1782340
13. Spatially Stratified and Multi-Stage Approach for National Land Cover Mapping Based on Sentinel-2 Data and Expert Knowledge H. Costa et al. https://doi.org/10.3390/rs14081865
14. Sentinel-2 and AISA Airborne Hyperspectral Images for Mediterranean Shrubland Mapping in Catalonia M. Kycko et al. https://doi.org/10.3390/rs14215531