Desarrollo de un modelo para caracterizar el cambio de las coberturas del suelo por causas de la explotación minera a cielo abierto utilizando imágenes satelitales Landsat 8
This research project is based on the spatial and multitemporal analysis of the last 7 years of the Área of influence of the La Esmeralda mine of the Multinational CEMEX, using LANDSAT 8 images identifying the influence that the mining project has generated on the vegetation cover. The main object...
- Autores:
-
Andrade Ordoñez, Yonhson Power
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad de San Buenaventura
- Repositorio:
- Repositorio USB
- Idioma:
- spa
- OAI Identifier:
- oai:bibliotecadigital.usb.edu.co:10819/8038
- Acceso en línea:
- http://hdl.handle.net/10819/8038
- Palabra clave:
- Clasificación supervisada
Analisis cobertura
Teledetección
Landsat 8
Supervised classification
Coverage analysis
Remote sensing
Landsat 8
Sistemas de información geográfica
- Rights
- License
- Atribución-NoComercial-SinDerivadas 2.5 Colombia
Summary: | This research project is based on the spatial and multitemporal analysis of the last 7 years of the Área of influence of the La Esmeralda mine of the Multinational CEMEX, using LANDSAT 8 images identifying the influence that the mining project has generated on the vegetation cover. The main objective of the aggregates mining plant of the multinational CEMEX, located in the town of Payandé, belonging to the municipality of San Luis; It is the exploration and exploitation of sand, stone, coal, gypsum, limestone and limestone mines. This makes the study Área a site of mass removal of the soil and subsoil, changing the characteristics of the terrain surface. Through the hypothesis chosen for the study and through the use of ArcGIS, 2 multispectral images from the periods 2013 and 2020 are analyzed. The classification supervised by maximum probability (maximum likelihood) allows the characterization of the coverage present in each of the images satellite by identifying the spectral signature of the object on the surface of the earth. The maximum likelihood classification allows visualizing the change in coverage in the Área of interest, validating the intervened or affected Áreas, as well as those recovered around the exploitation |
---|