PIXEL-BASED CLASSIFICATION ANALYSIS OF LAND USE LAND COVER USING SENTINEL-2 AND LANDSAT-8 DATA

35 citations as recorded by crossref.

1. Analysis of Changes in Forest Structure using Point Clouds from Historical Aerial Photographs P. Bożek et al. 10.3390/rs11192259
2. Modelling and evaluation of land use changes through satellite images in a multifunctional catchment: Social, economic and environmental implications C. Acuña-Alonso et al. 10.1016/j.ecoinf.2022.101777
3. Accuracy Assessment of land use maps classification based on remote sensing and GIS techniques H. Abdullah Abbas et al. 10.1051/bioconf/20249700063
4. Movement and dispersal of a habitat specialist in human-dominated landscapes: a case study of the red panda D. Bista et al. 10.1186/s40462-021-00297-z
5. Fusing Sentinel-2 Imagery and ALS Point Clouds for Defining LULC Changes on Reclaimed Areas by Afforestation M. Szostak et al. 10.3390/su11051251
6. Land use mapping from sentinel satellite imagery using remote sensing and GIS techniques H. Abdullah Abbas et al. 10.1088/1755-1315/1374/1/012042
7. Monitoring Effect of Spatial Growth on Land Surface Temperature in Dhaka M. Rahman et al. 10.3390/rs12071191
8. Evaluation and comparison of the earth observing sensors in land cover/land use studies using machine learning algorithms P. Prasad et al. 10.1016/j.ecoinf.2021.101522
9. Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation C. Pande et al. 10.1186/s12302-024-00901-0
10. Efficient Argan Tree Deforestation Detection Using Sentinel-2 Time Series and Machine Learning Y. Karmoude et al. 10.3390/app15063231
11. Land use/land cover and change detection mapping in Rahuri watershed area (MS), India using the google earth engine and machine learning approach C. Pande 10.1080/10106049.2022.2086622
12. Sentinel-2 Data for Land Use/Land Cover Mapping: A Meta-analysis and Review A. Kumari & S. Karthikeyan 10.1007/s42979-023-02214-0
13. Temporal dynamics change of land use/land cover in Jhansi district of Uttar Pradesh over past 20 years using LANDSAT TM, ETM+ and OLI sensors P. Kumar et al. 10.1016/j.rsase.2021.100579
14. Sentinel-2 Data for Land Cover/Use Mapping: A Review D. Phiri et al. 10.3390/rs12142291
15. Land Cover Mapping and Change Analysis Using Optimized Random Forest Classifier Incorporating Fusion of Texture and Gabor Features A. Kumar & R. Garg 10.1007/s42979-023-02111-6
16. Dynamic Land Degradation Assessment: Integrating Machine Learning with Landsat 8 OLI/TIRS for Enhanced Spectral, Terrain, and Land Cover Indices P. Badapalli et al. 10.1007/s41748-024-00442-9
17. Geo-spatial approach for land-use and land-cover changes and deforestation mapping: a case study of Ankasha Guagusa, Northwestern, Ethiopia S. Mekasha et al. 10.1007/s42965-020-00113-6
18. Overview of Recent Developments in Flood Mitigation Techniques with Respect to Indian Subcontinent P. Pusdekar & S. Dudul 10.32628/IJSRST218356
19. Extracting built-up areas from Sentinel-1 imagery using land-cover classification and texture analysis I. Holobâcă et al. 10.1080/01431161.2019.1608391
20. Comparing Sentinel-2 and Landsat 9 for land use and land cover mapping assessment in the north of Congo Republic: a case study in Sangha region L. Bill Donatien et al. 10.1080/01431161.2024.2394238
21. Land degradation assessment using AHP and GIS-based modelling in Duhok District, Kurdistan Region, Iraq R. Mzuri et al. 10.1080/10106049.2021.1987534
22. Urban Expansion and Land Use Transformations in Midnapore City (2003–2024): Implications for Sustainable Development R. Thakur et al. 10.3390/earth6020050
23. Vegetation Classification and Extraction of Urban Green Spaces Within the Fifth Ring Road of Beijing Based on YOLO v8 B. Li et al. 10.3390/land14102005
24. PlanetScope Imageries and LiDAR Point Clouds Processing for Automation Land Cover Mapping and Vegetation Assessment of a Reclaimed Sulfur Mine M. Szostak et al. 10.3390/rs13142717
25. A comparative evaluation of state-of-the-art ensemble learning algorithms for land cover classification using WorldView-2, Sentinel-2 and ROSIS imagery I. Colkesen & M. Ozturk 10.1007/s12517-022-10243-x
26. Land Use Classification of the Deep Convolutional Neural Network Method Reducing the Loss of Spatial Features X. Yao et al. 10.3390/s19122792
27. Land cover change analysis between 1990 and 2021 using Landsat images and object-based classification: A case study in Bodrum peninsula, Aegean Region, Turkey B. USTAOĞLU 10.51800/ecd.1087278
28. Usage PlanetScope Images and LiDAR Point Clouds for Characterizing the Forest Succession Process in Post-Agricultural Areas M. Szostak 10.3390/su142114110
29. Assessing the Influence of Land Use/Land Cover Alteration on Climate Variability: An Analysis in the Aurangabad District of Maharashtra State, India M. Masroor et al. 10.3390/su14020642
30. Land use and land cover classification from satellite images based on ensemble machine learning and crowdsourcing data verification S. Puttinaovarat et al. 10.1080/23729333.2023.2166252
31. Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India P. Mishra et al. 10.1016/j.ejrs.2019.02.001
32. Effect of disturbances and habitat fragmentation on an arboreal habitat specialist mammal using GPS telemetry: a case of the red panda D. Bista et al. 10.1007/s10980-021-01357-w
33. Land Use/Cover Classification of Large Conservation Areas Using a Ground-Linked High-Resolution Unmanned Aerial Vehicle L. Mangewa et al. 10.3390/resources13080113
34. Reclaimed Area Land Cover Mapping Using Sentinel-2 Imagery and LiDAR Point Clouds M. Szostak et al. 10.3390/rs12020261
35. Analysis of Land Cover Change Detection in Gozamin District, Ethiopia: From Remote Sensing and DPSIR Perspectives A. Gedefaw et al. 10.3390/su12114534