Resumen

PAREDES, Carlos; MATOS, Hector; VEGA, Rogelio de la  y  PARDO, Eulogio. Semiautomatic recognition of karstic depressions by analysis of aggregates in their morphometric distributions. Application to the karst of the State of Yucatán, Mexico. Rev. mex. cienc. geol [online]. 2019, vol.36, n.2, pp.270-288.  Epub 05-Dic-2025. ISSN 2007-2902.  https://doi.org/10.22201/cgeo.20072902e.2019.2.1017.

The Yucatán Peninsula, one of the regions in which the Republic of Mexico is physiographically divided, is mainly constituted by carbonate rocks of sedimentary origin, which, due to its geological, structural, climatic and hydrogeological conditions, hosts important dissolution processes, which configure surface and underground karst landscapes. Among these, karst depressions in the form of cenotes, sinkholes, uvalas and poljes, have been the subject of many studies, because they constitute important groundwater and historic sociocultural resources, very sensitive to the environmental alteration. Currently, there are about 3000 collected karst depressions in the State of Yucatán (EY), however, the thick vegetation cover usually hinders its location and / or classification, reducing the completeness of the inventory. This paper presents the procedure used to build a catalog in the EY, grouped by types of karstic depressions, using a k-means semi-automatic classification system, and the most relevant morphometric parameters of the depressions, identified by a hierarchical clustering. The inventories used here are: cenotes (from Secretaría de Desarrollo Urbano y Medio Ambiente, Yucatán), water bodies (from Instituto Nacional de Estadística y Geografía, INEGI), and hypsometric level curves from 1:50000 topographical maps (INEGI). They have been complemented with the depressions obtained by two algorithms: DEM (CEM 3.0, INEGI) filling and hierarchical, both implemented in ArcGis with 15 m of pixel resolution. For each inventory, once each has been corrected and rectified, the morphometric parameters have been calculated: area, perimeter, circularity, shape, width, length, and elongation, the first two (logarithmically transformed) and the third and fourth ones, have turned out to be more relevant, after the cluster hierarchical analysis. The k-means clustering method provide, after synthesis of each grouping on inventories, a total of6587small depressions, geographically around to the Chicxulub impact structure; 4428 uvalas, 89 large depressions, all of them outside to the Chicxulub edge, and 5176 cockpit karst depression, most of them spreaded over Sierra de Ticul. Finally, probabilistic distributions of most representative morphometric parameters have been determined, characterizing each karstic sink typology resulting clusters.

Palabras llave : karst; doline; cenote; uvala; polje; clustering; k-means; Yucatán; Mexico.

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