THE EFFICIENCY OF RANDOM FOREST METHOD FOR SHORELINE EXTRACTION FROM LANDSAT-8 AND GOKTURK-2 IMAGERIES

12 citations as recorded by crossref.

1. A Proposal for Automatic Coastline Extraction from Landsat 8 OLI Images Combining Modified Optimum Index Factor (MOIF) and K-Means F. Figliomeni et al. 10.3390/rs15123181
2. Machine learning application in modelling marine and coastal phenomena: a critical review A. Pourzangbar et al. 10.3389/fenve.2023.1235557
3. VEdge_Detector: automated coastal vegetation edge detection using a convolutional neural network M. Rogers et al. 10.1080/01431161.2021.1897185
4. An Overview of Shoreline Mapping by Using Airborne LiDAR J. Wang et al. 10.3390/rs15010253
5. A Novel Approach for Instantaneous Waterline Extraction for Tidal Flats H. Yang et al. 10.3390/rs16020413
6. An Overview of Coastline Extraction from Remote Sensing Data X. Zhou et al. 10.3390/rs15194865
7. On the shoreline positioning via remote sensing imagery: an isoradiometric approach A. Maltese et al. 10.1117/1.JRS.18.014529
8. Coast type based accuracy assessment for coastline extraction from satellite image with machine learning classifiers O. Çelik & C. Gazioğlu 10.1016/j.ejrs.2022.01.010
9. Aktarımlı Öğrenme ile SENTINEL-2 Görüntülerinden Kıyı Çizgisi Bölütlemesi S. KARAGÖL et al. 10.51489/tuzal.830052
10. Edge Technologies for Disaster Management: A Survey of Social Media and Artificial Intelligence Integration M. Aboualola et al. 10.1109/ACCESS.2023.3293035
11. Semi-Automated Semantic Segmentation of Arctic Shorelines Using Very High-Resolution Airborne Imagery, Spectral Indices and Weakly Supervised Machine Learning Approaches B. Aryal et al. 10.3390/rs13224572
12. Quantifying shoreline dynamics in the Indian Sundarban delta with Google Earth Engine (GEE)-based automatic extraction approach M. Santra et al. 10.1007/s42965-023-00321-w