APPLICATION OF REMOTE SENSING IN THE ANALYSIS OF LANDSCAPE FRAGMENTATION IN CUCHILLAS DE LA ZARCA, MEXICO
We analyzed the structure and composition of the landscape of the Priority Area for Grasslands Conservation (APCP) Cuchillas de la Zarca, determining their involvement by fragmentation processes. It generated a supervised classification and analysis of fragmentation in the period from 2008 to 2011....
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | México |
| Institución: | UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO |
| Repositorio: | Investigaciones Geográficas |
| Idioma: | español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/36568 |
| Acceso en línea: | https://www.investigacionesgeograficas.unam.mx/index.php/rig/article/view/36568 |
| Access Level: | acceso abierto |
| Palabra clave: | Fragmentación Paisaje Clasificación supervisada Landsat TM kappa Índice de diversidad Fragmentation Landscape Supervised classification diversity index |
| Sumario: | We analyzed the structure and composition of the landscape of the Priority Area for Grasslands Conservation (APCP) Cuchillas de la Zarca, determining their involvement by fragmentation processes. It generated a supervised classification and analysis of fragmentation in the period from 2008 to 2011. Spectral analysis allowed to clearly define six classes, where the ecosystem is represented mostly natural grassland with 41.6% of the total area. The fragmentation analysis of landscape metrics generated shows a gradual process of fragmentation. An increase in the total number of fragments confirms the function of time in the process of fragmentation zone, whereas the average size of the patches is a decrease, indicating that large patches were fragmented or broken. In addition to this, the Shannon and Simpson indices show a rising trend (0.66 to 0.89), (0.68 to 0.82), indicating fragments increasing in time. The overall accuracy of classification evaluated in the period 2008 - 2011 shows high accuracy that ranged from 91 to 94%, while the discrete multivariate Kappa index showed a variation of 0.90 to 0.93. |
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