APPLYING RANDOM FOREST CLASSIFICATION TO MAP LAND USE/LAND COVER USING LANDSAT 8 OLI

22 citations as recorded by crossref.

1. Multi-Temporal Passive and Active Remote Sensing for Agricultural Mapping and Acreage Estimation in Context of Small Farm Holds in Ethiopia T. Mengesha et al. 10.3390/land13030335
2. Spatiotemporal pattern of water hyacinth (Pontederia crassipes) distribution in Lake Tana, Ethiopia, using a random forest machine learning model M. Belayhun et al. 10.3389/fenvs.2024.1476014
3. Detailed and automated classification of land use/land cover using machine learning algorithms in Google Earth Engine X. Pan et al. 10.1080/10106049.2021.1917005
4. Land Use and Land Cover Scenarios for Optimum Water Yield and Sediment Retention Ecosystem Services in Klong U-Tapao Watershed, Songkhla, Thailand J. Srichaichana et al. 10.3390/su11102895
5. Relative performance evaluation of machine learning algorithms for land use classification using multispectral moderate resolution data T. Ramachandra et al. 10.1007/s42452-023-05496-4
6. Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms U. Ali et al. 10.3390/ijgi11060333
7. Extent of Lake Tana’s Papyrus Swamps (1985–2020), North Ethiopia A. Kahsay et al. 10.1007/s13157-022-01651-6
8. Assessment of Systematic Errors in Mapping Electricity Access Using Night-Time Lights: A Case Study of Rwanda and Kenya T. Raji et al. 10.3390/rs16193561
9. Estimating maize lethal necrosis (MLN) severity in Kenya using multispectral high-resolution data K. Richard et al. 10.1007/s12518-021-00357-4
10. “Human elephant conflict in changing land-use land-cover scenario in and adjoining region of Buxa tiger reserve, India” C. Nad et al. 10.1016/j.envc.2021.100384
11. Predicting priority management areas for land use/cover change in the transboundary Okavango basin based on machine learning B. Kavhu et al. 10.1016/j.heliyon.2023.e22762
12. Geospatial urban heat mapping with interpretable machine learning and deep learning: a case study in Hue City, Vietnam N. Hoang et al. 10.1007/s12145-024-01582-2
13. Urban Ecosystem Services Quantification through Remote Sensing Approach: A Systematic Review P. Tavares et al. 10.3390/environments6050051
14. Time-Series Monitoring of Dust-Proof Nets Covering Urban Construction Waste by Multispectral Images in Zhengzhou, China Z. Li et al. 10.3390/rs14153805
15. Comparing global and local maps of the Caribbean pine forests of Andros, home of the critically endangered Bahama Oriole J. Antalffy et al. 10.1007/s10661-021-09560-7
16. Provision of land use and forest density maps in semi-arid areas of Iran using Sentinel-2 satellite images and vegetation indices S. Eskandari & S. Bordbar 10.1016/j.asr.2024.10.060
17. LULC changes to riverine flooding: A case study on the Jamuna River, Bangladesh using the multilayer perceptron model M. Hasan et al. 10.1016/j.rineng.2023.101079
18. Adoption of Machine Learning Technique in Nile River Islands Classification N. Kamal et al. 10.2166/hydro.2022.154
19. The use of Landsat-8 and Sentinel-2 imageries in detecting and mapping rubber trees N. Yusof et al. 10.1007/s42464-020-00078-0
20. Landscape context importance for predicting forest transition success in central Panama G. Bardino et al. 10.1007/s10980-023-01694-y
21. Classification of land use/land cover using artificial intelligence (ANN-RF) E. Alshari et al. 10.3389/frai.2022.964279
22. Multilayer perceptron and Markov Chain analysis based hybrid-approach for predicting land use land cover change dynamics with Sentinel-2 imagery H. Abbas et al. 10.1080/10106049.2023.2256297