Paper
7 October 2011 Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape
Sandra Carolina Ramírez-Forero, Alejandra López-Caloca, José Luis Silván-Cárdenas
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Abstract
The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sandra Carolina Ramírez-Forero, Alejandra López-Caloca, and José Luis Silván-Cárdenas "Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81741S (7 October 2011); https://doi.org/10.1117/12.897925
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KEYWORDS
Earth observing sensors

Landsat

Image classification

Agriculture

Detection and tracking algorithms

Satellite imaging

Satellites

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