EXTRACTION OF BUILT-UP AREA BY COMBINING TEXTURAL FEATURES AND SPECTRAL INDICES FROM LANDSAT-8 MULTISPECTRAL IMAGE

10 citations as recorded by crossref.

1. Evaluation Of The Relationship Between Spatial-Temporal Changes Of Land Use/Land Cover (Lulc) And Land Surface Temperature (Lst): A Case Study Of Nilüfer, Bursa T. ÜSTÜN TOPAL 10.51552/peyad.1346845
2. Spatio-Temporal Evolution Features and Impact Factors of Urban Expansion in Underdeveloped Cities: A Case Study of Nanchang, China K. Liao et al. 10.3390/land11101799
3. The use of bands ratio derived from Sentinel-2 imagery to detect built-up area in the dry period (North-East Algeria) K. Rouibah 10.1007/s12518-023-00513-y
4. The urban areas classification methodology according to multi-zone images of Sentinel 2 and Landsat 8 (on the example of the city of Thanh Hoa, Vietnam) L. Trinh et al. 10.22389/0016-7126-2020-956-2-40-49
5. Applying Multi-Index approach from Sentinel-2 Imagery to Extract Urban Area in dry season (Semi-Arid Land in North East Algeria) K. Rouibah & M. Belabbas 10.4995/raet.2020.13787
6. Exploring the Use of Orthophotos in Google Earth Engine for Very High-Resolution Mapping of Impervious Surfaces: A Data Fusion Approach in Wuppertal, Germany J. Langenkamp & A. Rienow 10.3390/rs15071818
7. Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020) F. Dubertret et al. 10.3390/rs14092127
8. Building Extraction Using Orthophotos and Dense Point Cloud Derived from Visual Band Aerial Imagery Based on Machine Learning and Segmentation A. Schlosser et al. 10.3390/rs12152397
9. Temporal and Spatial Changes in Vegetation Ecological Quality and Driving Mechanism in Kökyar Project Area from 2000 to 2021 Z. Wang et al. 10.3390/su14137668
10. Automated Built-Up Infrastructure Land Cover Extraction Using Index Ensembles with Machine Learning, Automated Training Data, and Red Band Texture Layers M. Maloney et al. 10.3390/rs16050868