ASSESSMENT OF MULTIRESOLUTION SEGMENTATION FOR EXTRACTING GREENHOUSES FROM WORLDVIEW-2 IMAGERY

12 citations as recorded by crossref.

1. AssesSeg—A Command Line Tool to Quantify Image Segmentation Quality: A Test Carried Out in Southern Spain from Satellite Imagery A. Novelli et al. https://doi.org/10.3390/rs9010040
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3. Effects of Atmospheric Correction and Image Enhancement on Effective Plastic Greenhouse Segments Based on a Semi-Automatic Extraction Method Y. Yao & S. Wang https://doi.org/10.3390/ijgi11120585
4. A GeOBIA-assisted framework for canopy height estimation using airborne lidar scanning: a city-scale approach T. Jones et al. https://doi.org/10.1080/10106049.2025.2515270
5. Object-Based Plastic-Mulched Landcover Extraction Using Integrated Sentinel-1 and Sentinel-2 Data L. Lu et al. https://doi.org/10.3390/rs10111820
6. Geographic Object-Oriented Analysis of UAV Multispectral Images for Tree Distribution Mapping in Mangroves L. Conti et al. https://doi.org/10.3390/rs17091500
7. Mapping Urban Green Spaces Based on an Object-Oriented Approach D. GÜLÇİN & A. AKPINAR https://doi.org/10.30516/bilgesci.486893
8. Emerging methodologies in waterbody delineation: an In-depth review S. Rajeswari & P. Rathika https://doi.org/10.1080/01431161.2024.2379518
9. A Green Infrastructure Prioritization Index Combining Woody Vegetation Deficits and Social Vulnerability in Temuco, Chile G. Catalán et al. https://doi.org/10.3390/land15040574
10. Mask R-CNN and OBIA Fusion Improves the Segmentation of Scattered Vegetation in Very High-Resolution Optical Sensors E. Guirado et al. https://doi.org/10.3390/s21010320
11. Exploring the synergy between Landsat and ASAR towards improving thematic mapping accuracy of optical EO data A. Cass et al. https://doi.org/10.1007/s12518-019-00258-7
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