Geospatial analysis of the association between bedrock fractures and vegetation in an arid environment

• Published in: International journal of remote sensing 2008-12, Vol.29 (23), p.6937-6955
• Main Authors: Aich, S., Gross, M. R.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Teledetection and vegetation maps
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160802220185

Remote sensing and GIS techniques were applied to a high resolution air photograph from Arches National Park, Utah in order to quantify the spatial correlation between bedrock fractures and the distribution of surface vegetation. Field surveys conducted on the north-east limb of Salt Valley anticline reveal four distinct fracture sets in massive sandstone beds of the Curtis Formation. The most pervasive fractures belong to two sets of mega-scale joints (J1 and J2) that trend NW-SE. Over 10 000 joint traces were digitized from the rectified air photographs encompassing an area of 0.72 km 2 . Joint orientations were extracted in the GIS, allowing for their division into discrete sets and the calculation of mean orientations. A raster map of vegetation was derived from unsupervised classification of the air photograph. Clusters of vegetation, enhanced by filtering, are preferentially aligned in linear trends that closely correspond to the NW-SE joints. Further, a buffer analysis applied to the J1 and J2 joint sets indicates a systematic decrease in vegetation with increasing distance from the mega-scale joints. Strong correlations in orientation and proximity demonstrate that bedrock fractures may strongly influence the distribution of vegetation in arid environments, especially where bedrock constitutes the majority of land cover and soils are thin. †Present address: Photo Science Geospatial Solutions, St. Petersburg, Florida 33716, USA.