Multitemporal analysis using satellite remote sensing and GIS land cover change in the municipality of Danli, El Paraiso, in the years 1987 -2011

Authors

  • Alicia Maricela Cárcamo Universidad Autónoma Nacional de Honduras, UNAH.
  • Juan Gregorio Rejas Ayuga Universidad Politécnica de Madrid, UPM

DOI:

https://doi.org/10.5377/ce.v8i2.2081

Keywords:

GIS, Digital Classification, Multitemporal Analysis, Change Detection, Development

Abstract

Danlí town is located in the eastern of Honduras. It has an area of approximately 2500 km2, has 37 villages and a projected population of 181.500 inhabitants. It consists of urban, snuff producing areas, basic grains, cattle and also has vegetation areas mainly conifer forests and mixed forest. Despite being one of the most important cities of the region has well established development plans so it has experienced urban sprawl and agricultural zoning without careful management to ensure sustainable development.

The remote sensing allows the availability of satellite images, which can be analyzed using GIS to establish an automated changes in the territory in an extended period of time. This article outlines the multitemporal analysis of Landsat and evaluation of land cover changes occurred in a 11-year period between 1987 and 2011. This classification was developed digital image that has been monitored in the study area. Thematic mapping presents the results generated and indicative of the dynamic soil uses in the region. Finally we analyze the methodology applied in relation to its impact as an important diagnostic tool, and trends that will be useful for better decision-making for development and welfare of the area and its inhabitants.

Revista Ciencias Espaciales, Volumen 8, Número 2 Otoño, 2015; 259-271

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Published

2015-08-30

How to Cite

Maricela Cárcamo, A., & Rejas Ayuga, J. G. (2015). Multitemporal analysis using satellite remote sensing and GIS land cover change in the municipality of Danli, El Paraiso, in the years 1987 -2011. Ciencias Espaciales, 8(2), 259–271. https://doi.org/10.5377/ce.v8i2.2081

Issue

Section

Analysis methods with Geographic Information Technologies