ASSESSING THE ACCURACY OF LAND USE LAND COVER (LULC) MAPS USING CLASS PROPORTIONS IN THE REFERENCE DATA

11 citations as recorded by crossref.

1. Analyzing Land Use/Land Cover Changes Using Google Earth Engine and Random Forest Algorithm and Their Implications to the Management of Land Degradation in the Upper Tekeze Basin, Ethiopia A. Fentaw et al. https://doi.org/10.1155/2024/3937558
2. Predicting spatio-temporal land use / land cover changes and their drivers forces based on a cellular automated Markov model in Ibb City, Yemen A. Dammag et al. https://doi.org/10.1080/10106049.2023.2268059
3. A Comparative Assessment of UGS Changes and Accessibility Using Per Capita Metrics: A Case Study of Budapest and Vienna Y. Hassan https://doi.org/10.2139/ssrn.4864401
4. Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings S. Mantey et al. https://doi.org/10.4236/ars.2026.151001
5. Analysing the inconsistencies of CORINE status layers (CLC) and layers of changes (CHA) (1990-2018) for a Spanish case study D. García Álvarez & M. Camacho Olmedo https://doi.org/10.1080/19475683.2023.2166583
6. Automated road surface classification in OpenStreetMap using MaskCNN and aerial imagery R. Parvathi et al. https://doi.org/10.3389/fdata.2025.1657320
7. Spatiotemporal analysis of Urban Heat Island and land use land cover changes using Landsat images and CA-ANN machine learning techniques: a case study of Dakahlia government, Egypt S. Sameh et al. https://doi.org/10.1080/14498596.2023.2257619
8. 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. https://doi.org/10.3390/land13030335
9. Evaluation of Different Classification Algorithms for Land Use Land Cover Mapping K. Chomani & S. Pshdari https://doi.org/10.24017/science.2024.2.2
10. Accuracy Assessment and Comparison of National, European and Global Land Use Land Cover Maps at the National Scale—Case Study: Portugal C. Fonte et al. https://doi.org/10.3390/rs16091504
11. The land use and land cover changes, 1994–2024: implications for livelihood options and employment opportunities in Dhanbad, India A. Ranjan et al. https://doi.org/10.1007/s41324-025-00605-4