Name, učo: Lenka Kociánová, 175417
Title: OATools: Orientation analysis of geological structures in GIS, case study on Svratka crystalline
complex, Bohemian massif, Czech rep
Type of the text: Introduction and the tools´ description section of a journal article
Abstract
In this paper we introduce the functionality of the OATools (Orientation Analysis Tools) Add-In for
ArcGIS® and show its practical usage on a case study of Svratka anticline (crystalline unit,
Bohemian massif, Czech Republic). We also discuss the tools usage together with GIS potential of
spatial data queries, storage and visualization.
1 Introduction
Geological mapping and structural investigation of deformed geological units give rise to
large datasets of oriented data. Structural data are captured and stored systematically to
enable the next GIS processing and map compilation.
Geological observations are bound to coordinates of control points, where structural
measurements and other descriptive data are taken. Localization of these control points
plays an important role in the map construction. Therefore, data are stored in a spatial
database and usage of GIS software is essential.
GIS software provides useful functionality for spatial analysis, but there is a lack of tools for
oriented data typical of structural geology (Alberti, 2005).
This work was initialized by a need to unify a workflow in a single software environment and
ensure a connection among the spatial database, analytical functionality and a visualization
application; to this purpose, Orientation Analysis Tools were created. This Add-In for ArcMap
brings a new functionality to the most extended software used in geological mapping –
ArcGIS® (ESRI) and has the potential to be used also in other fields of study.
1.2 Functions in combination with GIS tools
Tools presented here connect the GIS functionality with the orientation analysis tools. Data needs
to be processed in respect of regional geological settings, topographic position, e.g. area of interest,
or based on attributes stored in the spatial database. The GIS selection tool enables this selection by
location or by attributes, as well as selection by spatial and non-spatial relationships. To select and
investigate geodata by the means of query is an important functionality of GIS (Apel, 2006).
OATools offer methods of oriented data visualization – plotting of lines and planes in spherical
projections (equal-area), statistical analyses such as density distribution, mean vector and fold axis.
Other routine (‘other routine’ what? I think a word may be missing here.) estimates the spatial
distribution of lines and planes by plotting orientations in a rose diagram. For these tools, the input is
the selection from a dataset. Interpolation tools, the next functionality of OATools, are directly linked
to the map. Tools estimate the change of trends or dip directions of the rock fabric in 2D space.
Routines of Interpolation tools count spatial averaged map and map of fold axes.
Interactive work with the map and the equal-area projection facilitates to determine regions
(structural domains), where the geologic structures tend to have certain geometrical
characteristics (type of distribution). Foliations of that domain should share a common axis
(Vollmer, 1990). The subdivision of the geological map into structural domains is a useful
method for the analysis of complex structures (Ramsey and Huber, 1987; de Kemp, 1998).
A map of spatial averaged structural data can reveal the regional structure in context of the
geological setting.
2.4 Interpolation tools
Interpolation tools are the major benefit of the newly integrated functionality into GIS. These tools
analyze structural data in space and therefore, change in their direction can be observed and related
to other thematic map features. This helps in structural analysis, structural domains definition and
cross section construction.
2.2.1 Spatial averaged map and Map of fold axes
Spatial averaging and Map of fold axes are tools on the OATools toolbar. Both open an interactive
dialog box, where input data are set (Fig. 9). Selection from dataset is read after the input layer is
chosen. Fields for dip and dip direction are defined in the drop-down list or loaded from text file
(created in the last use). Two parameters can be modified by the user: interval of the grid of stations
and radius of influence (Fig. 10). Radius of influence is the distance within the structural data are
involved into the calculation (something missing from this sentences – see part highlighted in green).
The routine finds out the data extent and consequently, the width and the height are divided
by the interval to find the number of stations; therefore, the number of stations depends on
the extent of the data. This number, in both directions, and the width and the height of the
area are displayed in the tool dialog box when the input layer is selected. This information
helps to decide whether the interval is adequate. Interval is the same in both directions - the
squared grid prevents misrepresenting results.
Eigenvectors derived from the sum of orientation matrices weighed by distance from averaging
station are computed, Eq. (C.1). The lowest eigenvalue is used to get the axis of folding and the
highest one for the averaged orientation.
Result is a point geometry shapefile with identical coordinate system with the original data.
After the routine is performed, this shapefile is added to the ArcMap document. Symbols are rotated
according to dip direction. Attribute table of the shapefile contains information taken from the
original data (dip, dip direction, station ID, type of structure – if present).
This routine also incorporates a control of the data extent that prevents the extremely long
time of processing caused by mistake in coordinates in the original table.
Remember to place a comma after discourse markers
Note points where I’ve made comments – it’s difficult to know what you want to express
here, but something is not quite right with the sentence.
Overall Lenka, your written English is really good!