Detection of open-pit mining zones by implementing spectral indices and image fusion techniques
This article aims to present the results of the application of different proposed spectral indices and image fusion techniques for the detection of open-pit mining zones, located to the north-east of Antioquia, Colombia; having as reference mining and no mining zones samples obtained from visual cha...
- Autores:
-
Castellanos-Quiroz, Henry Omar A.
Ramírez-Daza, Héctor Mauricio
Ivanova, Yulia
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60406
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60406
http://bdigital.unal.edu.co/58738/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Open-pit mining
spectral indices
images fusion
Fisher discriminant function analysis
Minería a cielo abierto
índices espectrales
fusión de imágenes
relación discriminante Fisher
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | This article aims to present the results of the application of different proposed spectral indices and image fusion techniques for the detection of open-pit mining zones, located to the north-east of Antioquia, Colombia; having as reference mining and no mining zones samples obtained from visual characterization of pictorial-morphological properties of the open-pit mining zones in the study area. This research used high resolution (UltraCam-D y RapidEye) and medium resolution (Landsat 8 LDCM) imagery, where the latter was defined as the main input for the application of the spectral indices and image fusion techniques. The development of the proposed methodological design and the statistical analysis of the images, presented the Brovey transformed image fusion technique -on its band 2-as the one with the highest discriminant potential for open-pit mining zone; the classification of the results were determined between the thresholds of pixel values from 0.3225 -defined as the discriminant breakpoint-to the maximum value of the mining group samples, corresponding to 0.5237. |
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