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Digital Mapping Techniques '02 -- Workshop Proceedings
U.S. Geological Survey Open-File Report 02-370

A Scalable, Digital Map Database of Bedrock Geology for Canada: A Progress Report

By Peter Davenport,1 Eric Boisvert,2 Marianne Quat,3 Andy Okulitch,4 Boyan Brodaric,5 Stephen Colman-Sadd,6 Larry Nolan,7 Bert Struik,8 Don MacIntyre,9 Ping Tzeng,10 David Scott,11 Celine Gilbert,12 Grant Abbott,13 Andrea Bassan,14 Murray Journeay,15 Jodie Francis,16 and Terry Houlahan17

1Geological Survey of Canada
3303 33rd St NW
Calgary, AB, Canada, T2L 2A7
Telephone: (403) 292-7141
Fax: (403) 292-7071

2Geological Survey of Canada; email:
3 Survey of Canada; email:
4Geological Survey of Canada; email:
5Geological Survey of Canada; email:
6Geological Survey of Newfoundland and Labrador; email:
7Geological Survey of Canada; email:
8Geological Survey of Canada; email:
9Geological Survey Branch, British Columbia; email:
10Geological Survey of Canada; email:
11Canada-Nunavut Geoscience Office; email:
12Canada-Nunavut Geoscience Office; email:
13Yukon Geology Program; email:
14Geological Survey of Newfoundland and Labrador; email:
15Geological Survey of Canada; email:
16ESS Info, Natural Resources Canada; email:
17ESS Info, Natural Resources Canada; email:


Canadian geological surveys at the federal and provincial/territorial levels are collaborating to make their collective holdings of geoscience data and information accessible through the Internet, under the umbrella of the Canadian Geoscience Knowledge Network at As part of this collaboration, work has started on organizing sets of existing digital geological maps (Figure 1) as a database that can be searched and reclassified consistently to prepare customized maps to meet various user needs. This project has adopted a variant of the North American Data Model ( and is adapting and developing the software tools, standards, and protocols that are required to deliver bedrock-geological map data from several geological surveys in a nationally consistent form. The current partners are the geological surveys of British Columbia and Newfoundland and Labrador, the Canada-Nunavut Geoscience Program office, the Yukon Geology Program, and Natural Resources Canada (Geological Survey of Canada and Earth Sciences Sector).

Figure 1. Location and geological setting of map sets used in project to develop a bedrock geology map database for Canada.


The ultimate goal of the project is to produce from a collection of the most recent geological maps available for the various parts of Canada a composite geological map "layer" in a database from which elements can be selected by area, age, and lithological properties to produce "new" maps to meet specific user requirements. This map database also will allow generalizations of the geological information using the classifications from regional compilations at various resolutions, permitting its display at scales ranging from that of the original mapping to broad regional maps at 1:5,000,000 or less. This first phase of the project will produce a working example of a distributed geological-map database and a system to access it that will form the foundation for bedrock geology in CGKN. At first, it will have limited functionality and will certainly be incomplete, but its design will be both extensible and adaptable.


Several digital maps sets from different agencies and a variety of geological domains are being used, each representing some of the "best and most current" published information for bedrock geology that is available for each region (Figure 1). Scale of mapping is mainly 1:250,000 or more detailed, from mostly provincial, territorial, and federal survey publications, but with contributions from academic and industry sources. There are some differences in the way these digital map sets were created, reflecting differing approaches adopted by individual agencies. These differences have to be accommodated in building the national geological database, and their salient features are described below.

Set 1. This map set comprises 88 map tiles compiled by the Geological Survey of British Columbia (BCGS) at a scale of 1:250,000 as a base for a mineral potential assessment of the entire province. Map sheets have been edge-matched, and a provincewide legend applied to the whole set.

Set 2. The Yukon map set includes approximately 90 maps whose original line work was digitized and synthesized into a digital compilation that was released on CD-ROM for the whole territory by Gordey and Makepeace (1999). In contrast to set 1, map features remain linked to their original map sources, and scale of mapping ranged from 1:250,000 (or less in a few cases) to 1:50,000. The compilers concentrated on fitting individual source legends into a regional legend for the whole area, and adjusting some map features across map boundaries. The varying resolution of the source maps resulted in variable levels of detail in the final compilation. Little original information has been lost in the compilation process, and the compilers' changes are identified as such. Together, map sets 1 and 2 cover the entire Canadian Cordillera and the western margin of the Interior Platform.

Set 3. This map set consists of nine 1:50,000 digital geological maps and one 1:250,000 map that was digitized and released by the Geological Survey of Canada in GIS (ArcView) format as part of the ongoing Central Forelands NATMAP project ( The 1:50,000 maps are the most recent detailed mapping for this part of northern British Columbia and Yukon and will be used to update the BCGS and Yukon map sets.

Sets 4.1 and 4.2. There are two map sets for Nunavut, all for Baffin Island, which lies within the Churchill Province and Arctic Platform. Set 4.1 is being digitized by the Nunavut Geoscience Office. These 36 existing 1:250,000 paper maps were published by the Geological Survey of Canada as part of a project to create a digital geological map for the new territory. In addition, seven contiguous 1:100,000 maps (set 4.2) have been prepared by ESS Info (the Earth Science Sector information agency for the Geological Survey of Canada) in ArcInfo format in a pilot project to create a data warehouse of its published geological maps.

Sets 5.1 and 5.2. The final two map sets are from the geological-map database system Geolegend (Colman-Sadd and others, 1997) developed and maintained by the Geological Survey of Newfoundland and Labrador (Colman-Sadd and Crisby-Whittle, 2001). These map sets were digitized from the original source maps at their original scales. Set 5.1 comprises 82 maps for the Island of Newfoundland at scales ranging from 1:15,000 to 1:250,000. These lie within the Appalachian Orogen. Set 5.2 comprises 15 maps for Labrador at scales ranging from 1:50,000 to 1:500,000, covering parts of the Churchill and Nain Geological Provinces. For any particular area, the most detailed and recent information has been used, and the goal is to have provincewide coverage. The database also is maintained to reflect the results of new mapping and other research (such as radiometric dating) as they are published.


The variant of the North American Data Model (NADM 5.2) used in the CORDLink digital library is the starting point for this project. Minor modifications have been made as the project progressed to accommodate specific requirements. Ways are being explored to use the COA tree (Compound Object Archive, perhaps more easily understood as Concept tree Archive) and attribute tables together to organize map-unit descriptors in several logical and linkable hierarchies. A combination of COA architecture and logical science language will be the key to producing customized geological maps that can be displayed not only using a "conventional" legend format (i.e., map units ordered by age and identified as lithostratigraphic/lithodemic entities), but also other classifications based on different combinations of concepts (e.g., composition, age, genesis, tectonic association, etc.). Initial databases were assembled in Microsoft Access, which allowed easier testing of ideas on table design. As the design has stabilized the databases have being moved to Oracle 8.17 implementations.

Geomatter II (Boisvert and others, 2001) has been used as a graphical user interface for populating and organizing the NADM tables. Some tables are also loaded directly from spreadsheets, but Geomatter is used to verify the results of the bulk loading and to make any minor corrections. Geomatter II has been modified during the project as the database structure has evolved and works with both the Access and Oracle versions of NADM.

The multi-agency nature of CGKN dictates that the data and information of each participating survey is maintained locally, while the need to deliver consistent information across agencies requires the adoption of common standards and protocols for coordinating the way it is organized. This distributed nature of the project poses problems in coordinating concept trees between several databases, especially since there will be differences in the details of the information to be stored in each. A way to allow local diversity while maintaining overall consistency has been proposed (Boisvert and others, 2001) through a central database (or registry) of concepts that are identified as being nationally important. This central concept registry will mediate between clients and the distributed databases to present a nationally consistent interface. The distributed databases will be able to accommodate local needs with a minimum of external constraints and allow them to be accessed directly.


In tackling these issues, the Yukon map set (Gordey and Makepeace, 1999) has been used extensively for both designing the approaches to the problem and testing the results of the designs. The other maps sets have been used to test the general applicability and effectiveness of these designs, and this testing process is continuing.

Scalability (Varying Map Resolution)

The initial plan was to use a map-unit hierarchy as depicted in Table 1 to allow the aggregation of detailed source units into progressively more general groupings.

Table 1. Map-unit levels as an idealized hierarchy,
and appropriate display scales for each level.

Map-unit type     Approximate
display scale
Geological Province     ≤1:25,000,000
Tectonic Terrane (Cordillera)
≅ Tectonic Zone (Appalachians)
Tectonic Assemblage     1:1,000,000
Supergroup (Super Suite)     ≥ 1:250,000
Group (Suite, Complex)     ≥ 1:250,000
Formation (Lithodeme)     ≥ 1:250,000
Member     ≥ 1:250,000
Source-map unit (informal)     variable

There are fundamental problems with this idealized hierarchy as an entity, however, in particular between the upper part (Geological Province, Tectonic Terrane) and the lower part (the Lithostratigraphic/Lithodemic hierarchy). "Geological province" is defined as "an extensive region characterized throughout by similar geologic history or by similar structural, petrographic, or physiographic features" (Jackson, 1997). A lithostratigraphic unit is "a defined body of sedimentary, extrusive igneous, metasedimentary, or metavolcanic strata that is distinguished and delimited on the basis of lithic characteristics and stratigraphic position" (Jackson, 1997), while a lithodemic unit is "a defined body of predominantly intrusive, highly deformed, and/or metamorphosed rock, distinguished and delimited on the basis of rock characteristics" (North American Commission on Stratigraphic Nomeclature, 1980). Thus, Geological Provinces are defined and distinguished not only by the bodies of rock they contain, but also by their structural history.

Tectonic Terranes, like Geological Provinces, "are parts of the earth's crust which preserve a geological record different from those of neighbouring terranes" (Gabrielse and others, 1992), and are thus defined on more than one criterion. Tectonic Assemblages are comparable in most respects to lithostratigraphic/lithodemic units. A Tectonic Assemblage is defined as a grouping of lithostratigraphic units that is "commonly bounded by regional unconformities or by faults [and] represents a specific depositional or volcanic setting and/or response to one or more tectonic events"; "each tectonic assemblage reflects a specific tectonic and/or depositional environment regardless of its place of origin." A specific assemblage may belong to two or more Terranes that differ in their history of deformation. Some source units in the Yukon map set also have been split among two or more assemblages.

The variation in criteria used for each classification type leads inevitably to multiple inheritance problems when one attempts to impose a simple hierarchy. Instead of defining a hierarchy for the map-unit types as a COA tree, the spatial classification, classification object, and classification scheme tables are used to classify the source-map units into the various levels by individual spatial feature (polygon). Specifically, each source-map polygon must be individually assigned to each of the higher levels in the spatial classification table (as Gordey and Makepeace, 1999, had done in their compilation). For other maps, this will entail more work during loading because with a simple hierarchy, each unit at the lowest level (i.e., the original units on the source maps) has only to be related to its immediate parent to be placed correctly in the hierarchy.

The above discussion applies mainly to the stratified rocks that form the lithotectonic framework of a region. Plutonic rocks, which are typically considered apart from the stratified rocks, generally can be grouped into major pulses of magmatism. Metamorphic rocks may either be included in the lithostratigraphic units, or, in some cases where they are of uncertain affinity, they may be grouped into an "unassigned" category. Finally, postorogenic lithostratigraphic units commonly may be grouped into larger assemblages based on criteria such as regional unconformities. These groupings of plutonic, metamorphic, and postorogenic lithostratigraphic units provide ways to aggregate them into more general categories that serve as the equivalents to Tectonic Assemblages and Tectonic Terranes for the purpose of map scaling.

Test of Map-Unit Hierarchy

One problem encountered very quickly was the asymmetry of the lithostratigraphic/ lithodemic hierarchy, as illustrated for the northeastern Yukon in Table 2. The Supergroup/Supersuite and Group/Suite/Complex levels are seldom used, and in fact for the Yukon map set, almost 60% of the units were informal. Furthermore, these informal units vary in their apparent rank equivalency from Group to Formation to Member. To overcome this problem, for the Yukon compilation Gordey and Makepeace (1999) developed a set of "regional compilation" units 1 and subunits that they used to better group the source-map units for display at different resolutions, as illustrated for a single quadrangle in Figure 2. In Figure 2a, all of the 58 source-map units were informal, with no name assigned. In the database, for these unnamed units, a provisional name has been created by concatenating its label with the name of the regional compilation unit to which they have been assigned by Gordey and Makepeace (1999). In Figure 2b, some of the units are represented by small polygons even at the Tectonic Assemblage and Terrane levels, and GIS functions will be required to dissolve these to allow a satisfactory display at small scales.

Table 2. Hierarchy developed for map units in the portion
of the Yukon map set northeast of the Tintina Fault. "Source
units" are original map units that are uniquely identified by their
original label and a source-map ID. "Regional unit" and "Regional
subunit" are groupings of source units developed by Gordey and
Makepeace (1999).

COA_Name (map unit type)     Number
of classes
Geological Province     2
   Tectonic Terrane     17
     Tectonic Assemblage     42
       "Regional unit"     99
         (Supergroup, Supersuite)     2
           "Regional subunit"     159
             Group, Suite, Complex     43
               Formation, Lithodeme
               (+ informal equivalents)
                 Member (+ informal equivalents)     21
"Source unit"     2082

Examples of changing map resolution based on map-unit level for NTS sheet 105A, NE of Tintina Fault. Original units from source maps, and index map

Figure 2a. Examples of changing map resolution based on map-unit level for NTS sheet 105A, NE of Tintina Fault. Original units from source maps, and index map (see Figure 1, map set 2 for location). b. Terranes.

Examples of changing map resolution based on map-unit level for NTS sheet 105A, NE of Tintina Fault. The 58 source-map units have been reclassified into 16 regional compilation units, 11 Tectonic Assemblages, and 8 Tectonic Terranes

Figure 2b. Examples of changing map resolution based on map-unit level for NTS sheet 105A, NE of Tintina Fault. Top to bottom, the 58 source-map units have been reclassified into 16 regional compilation units, 11 Tectonic Assemblages, and 8 Tectonic Terranes.

Interoperability at the Map-Unit Level

Legend entries for units on bedrock geology maps are almost always characterized by a chronostratigraphic age (or age range) and a lithological description. Together these provide the common elements for associating related units from different maps. The way both age and lithology are described is quite variable, however, and usage is seldom explicitly defined, making it difficult to correlate map units from one map source to another from legend information alone. A less rigorous approach is proposed to define "related" map units that exhibit varying degrees of similarity based on these characteristics (cf. lithodemic units). Ultimately, the user will need to review the original map-unit descriptions to decide whether the units identified as related do indeed have the association needed for the task at hand.

The chronostratigraphic interval assigned to a map unit may be from one of a number of regional systems, and the particular system used in map legends is rarely, if ever, specifically referenced. Despite this uncertainty, map-unit ages can be reconciled in a general way by reference to their currently accepted absolute age ranges. For this purpose in Canada, the geologic time scale compiled and updated periodically by Okulitch (2002) is being employed.

Lithological nomenclature presents similar, but more complex challenges for correlating map units from different sources. There are two main problems. Firstly, rock names are based on one or more of the following properties: genesis, composition, texture, fabric and degree of consolidation or induration; that is, rock names are "multidimensional." Secondly, several common rock names imply different rock properties to different geological communities, and as in the case of chronostratigraphy, usage of these names is rarely defined explicitly. For both these reasons, rock names themselves do not provide a reliable basis for either querying or defining relationships among map units on geological maps from different sources.

The issue of the multidimensionality of rock names has been addressed by attempting to break down each rock name into its implicit properties, building on the proposals of Weisenfluh (2001) and Struik and others (2002). A single rock name such as "siltstone" implies a genesis (a clastic, sedimentary rock), a texture (a sorted rock composed of silt- and clay-sized grains), and an indurated material. A "shale" likewise implies a similar genesis, texture, and degree of induration, but also a fabric, as a shale is implicitly a rock with planar laminations that impart fissility. In some cases, additional information about rock properties is provided by qualifiers; for example, "marine siltstone" provides more information about the rock's genesis, "foliated sandstone" provides information about fabric that is not implicit in the rock name itself.

Classifications for Lithological Characteristics

Initially, each of the four characteristics--genesis, composition, texture, and fabric--was considered as a single, simple theme. For each, a single hierarchical classification was attempted to allow the rock name and associated qualifiers to be indexed with a degree of precision appropriate to the information in the map legend. It became apparent that several of these themes are in fact composite, and these have been further broken down so that the classifications are both independent and simpler. In most cases, they are shallow hierarchies (2-3 levels) to allow characterization with different levels of precision and to allow searching at various levels of generalization. In addition, "mechanical" properties such as degree of induration and parting characteristics have been added to the set of parameters used for classification. In some cases, a rock name may imply more than one genesis, composition, fabric, etc.; multiple values are allowed as required. The purpose of these rock-property classifications is to provide an effective mechanism for searching inconsistent and loosely defined information, to be used as sets of controlled keywords. Furthermore, an attempt has been made to make the terms generic and descriptive, avoiding specialized jargon as much as possible.

Mechanical Properties

Degree of induration is a primary criterion used to distinguish "bedrock" geology from "surficial" deposits. The Science Language Technical Team of NADM is working on a definition to separate "consolidated" from "unconsolidated" for sedimentary rocks (Matti, 2002). For this project, all igneous and metamorphic rocks are classified as consolidated, and a simple, qualitative, threefold classification is used for sedimentary rocks: (1) unconsolidated,(2) poorly consolidated, and (3) consolidated (Table 3).

The way a rock parts is quite commonly described in map legends, such as rock's fissility or blockiness, as well as more specific jointing characteristics. For this preliminary scheme, a simple set of categories has been set up that distinguishes partings along one set of planar surfaces from rocks with two or more sets, and lithologies that are explicitly stated to be structureless.

Resistance to weathering is another mechanical property that commonly is used in map-unit descriptions. Its performance as a standard rock-property index has yet to be tested.

Table 3. Classification of mechanical properties as
implied by rock names used to describe map units. This
scheme is extensible based on the properties of actual map

Property     Category     Subcategory
1 unconsolidated
2 poorly consolidated
3 consolidated
1 resistant
2 recessive
1 multiplanar
2 fissile (single plane)
1.1 columnar
1.2 blocky
2.1 platy
2.2 flaggy
2.3 slaty


The information about the composition of map units is almost always descriptive and qualitative, so these attributes are reflected in the classification proposed here. For composition, a simple two-level system is suggested (Table 4). The primary grouping is based mainly on the main anion type for each lithology: silicate, oxide (nonsilicate), carbonate, sulphate, sulphide, halide, phosphate, nitrate, and borate, as well as a native element class and a carbonaceous class for rocks that are predominantly hydrocarbon. The second level is based in a general way on the dominant cation or cation group. For silicates, the terms high silica (felsic or acidic), intermediate silica (intermediate), low silica (mafic or basic), and very low silica (ultramafic or ultrabasic) are usually applied to igneous rocks, but they can in some cases be applied in a descriptive way to sedimentary and metamorphic rocks if the rock name contains sufficient information (e.g., an orthoquartzite would be classified as "silicate, high silica"). The numeric ranges for silica content are only an indication of the typical values for each category and should not be used for quantitative modeling.

As assemblages of earth materials, rocks commonly comprise two or more of the first-level compositional groupings (e.g., a calcareous quartz sandstone is predominantly a high-silica silicate rock, but has a lesser, but noteworthy, carbonate component). Thus, a rock can be assigned to one dominant and one or more subordinate compositional categories, all based on a single, simple, qualitative classification.

Table 4. Simple two-level classification of composition as
implied by rock names used to describe map units. This
scheme is extensible based on the properties of actual map

1 Silicate     1.1 high silica > 65% SiO2
1.2 intermediate silica 53-65% SiO2
1.3 low silica 44-53% SiO2
1.4 very low silica < 44% SiO2
2 Oxide (nonsilicate)     2.1 ferruginous
2.2 manganiferous
3 Carbonate     3.1 calcic
3.2 magnesian
3.3 barium
3.4 iron
4 Sulphate     (subcategories by major cation)
5 Sulphide     (subcategories by major cation)
6 Halide     (subcategories by major cation)
7 Phosphate     (subcategories by major cation)
8 Nitrate     (subcategories by major cation)
9 Borate     (subcategories by major cation)
10 Native element     (subcategories by element/polymorph)
11 Carbonaceous      


Initially, a single classification for the "genesis" of each rock was attempted, but it became apparent that two main themes, genetic process and site of formation, were commonly used in genetic classifications. These two themes are therefore used as separate classifiers named "Genetic Process" and "Environment of Formation."

Genetic Process: The primary level of subdivision for this classifier (Table 5) recognizes the traditional categories Igneous, Sedimentary, and Metamorphic, although the term "metamorphic" is used in its most general sense to mean a protolith that has undergone a mineralogical and/or compositional change, including metasomatism and pedogenesis. This sense follows the preliminary approach of the metamorphic subgroup of the Science Language Technical Team of NADM (Richard, 2002). The second level allows further description of the process in a very general way. The third level has been developed only partially, but other equivalent categories may be added to accommodate the lithological information to be classified in actual map legends.

Table 5. Simple three-level classification of genetic
process as implied by rock names used to describe map
units. This scheme is extensible based on the properties of
actual map legends.
Category     Subcategory     Sub-subcategory
1 Igneous     1.1 explosive
1.2 passive
2 Sedimentary     2.1 clastic
2.2 chemical precipitation  
2.3 biogenic
2.2.1 evaporitic
2.2.2 nonevaporitic
3 Metamorphic     3.1 dynamic (high strain)
3.2 regional (dynamothermal)
3.3 contact
3.4 metasomatic
3.5 pedogenic
3.6 impact
3.4.1 hydrothermal
3.4.2 deuteric
3.4.3 pyrometasomatic

Environment of Formation: The other information about a rock's genesis that is commonly implicit is its place of formation relative to the upper surface of the crust. This information is indexed using the three-level classification in Table 6. The first level distinguishes rocks formed on or above the surface of the crust--"supracrustal"--from those formed below--"crust" or "mantle" (it could also be extended to other astronomical bodies using a level above this). The second and third levels provide more detail where this is available. As in other classifications, the third level is not completely developed at present.

Rock names may imply a genetic history rather than a single genesis, so a rock name may be classified against more than one genetic process, each of which may have an associated environment of formation. Thus, a slate would be classified as both "sedimentary, clastic" and "metamorphic, dynamothermal" in terms of genetic process, and "supracrustal, subaqueous" and "crust" as the environments of formation associated with each respective genetic process. No attempt has been made to capture the order of the genetic events.

Table 6. Simple three-level classification of environment
of formation as implied by rock names used to describe
map units. This scheme is extensible based on the properties
of actual map legends.

Category     Subcategory     Sub-subcategory
1 Supracrustal      
1.1 subaerial
1.2 subglacial
1.3 subaqueous
1.3.1 marine
1.3.2 freshwater
1.3.3 intertidal
2 Crust      
2.1 shallow
2.2 deep
3 Mantle            

Physical Properties: Texture, Fabric, and Structure

Initially two classifications, one based on texture and a second on fabric were tried until it was realized that both are multidimensional concepts (especially texture), and also somewhat overlapping in the way they are used. For example, texture is defined by Bates and Jackson (1980) as "the general physical appearance or character of a rock, including the geometric aspects of, and the mutual relationships among, its component particles or crystals, e.g. the size, shape, and arrangement of the constituent elements of a sedimentary rock, or the crystallinity, granularity, and fabric of the constituent elements of an igneous rock". The definition of fabric for deformed rocks from the same source includes textural properties as well as the orientation of their constituent physical elements. Even if the properties to be included under each heading are decided, the concepts of both texture and fabric remain multidimensional. Structure as a theme presents similar problems. For this reason, rather than attempting to construct two or three hierarchies, two sets of categorical classes have been established: Texture and Physical Form. Texture includes five classifications based on properties of the particles that constitute a rock (Table 7), and Physical Form includes two classificaitions based on the spatial orientation of a rock's constituent physical elements (Tables 8a, b).

Table 7. Five categories for texture as implied by rock names used to describe map units. This scheme is extensible based on the properties of actual map legends.

Textural Property     Category     Subcategory     Sub-subcategory
Grain intergrowth      
1 crystalline
1 granular
Grain-size variability      
1 homogeneous
2 heterogeneous
3 gradational
Grain size      
1 size class 1 <0.05 mm
2 size class 2 0.05-0.2mm
3 size class 3 >0.2 mm
3.1 size class 3.1 0.2-2 mm
3.2 size class 3.2 2-4 mm
3.3 size class 3.3 4-64 mm
3.4 size class 3.4 64-256 mm
3.5 size class 3.5 >256 mm
3.3.1 size class 3.3.1 4-16 mm
3.3.2 size class 3.3.2 16-64 mm
Grain morphology      
1 rounded
2 subrounded
3 angular
4 irregular
Large particle to
matrix proportions
(heterogeneous rocks only)
1 matrix dominant
2 matrix subordinate

The classification for texture is:

grain intergrowth of a rock's component particles; crystalline is used for rocks where intergrowth is complete or nearly so; granular for rocks whose grains are not interlocking and, therefore, potentially have pore space.

grain-size variability; homogeneous, heterogeneous, and gradational.

grain size; three general categories are proposed: rocks whose grains are all microscopic (size class 1), rocks containing grains that are just discernable to the naked eye or by using a hand lens (size class 2), and rocks that contain clearly visible grains (size class 3). Size class 3 is further subdivided to accommodate size ranges commonly implicit in rock names or qualifiers. Approximate size ranges in millimeters are given for each class (Table 7), together with commonly used equivalent terms for sedimentary and igneous/metamorphic rocks. The numeric ranges are only an indication of the typical values for each category and should not be used for quantitative modeling. The use of descriptive terms such as fine, medium, and coarse is avoided because they have been defined in a several conflicting ways. Many rocks exhibit a range in grain size that spans even these general size classes (i.e., heterogeneous or gradational rocks), so two grain-size fields are used; one for the matrix (or finer particles), and a second for the coarser grains or clasts. Grain size for homogeneous rocks is entered in the "matrix" field. Clearly this scheme cannot accommodate the full range of particle sizes found in some rocks, but it seems adequate for the qualitative information contained in most map unit descriptions.

grain morphology; based on the relative degree of rounding of grains or crystals.

proportions of coarser to finer elements; this category is for rocks with heterogeneous grain-size distributions, where the rocks can be classified as being either matrix/groundmass dominated, or matrix/groundmass subordinate.
Aspects of structure and fabric are treated under Physical form. External habit captures the overall form of the lithological entity in a very general way--features seen at outcrop and larger scales--whereas structures and fabrics at the outcrop and smaller scales are categorized under internal structures. External habit (Table 8a) is subdivided broadly on geometric rather than genetic criteria. Thus, tabular form includes beds, dykes, veins, and volcanic flows (except where the last are explicitly described as having a different shape such as a pillow). The other two forms recognized are lenticular (e.g., bioherms and pillows) and equant (roughly equidimensional rock bodies such as plugs, stocks, and pinnacle reefs).

Table 8a. Classification of physical form--external habit
as implied by rock names used to describe map units. This
scheme is extensible based on the properties of actual map
Category     Subcategory
1 Tabular
2 Lenticular
3 Equant
1.1 thin
1.2 medium
1.3 thick
1.4 very thick

Internal structures (Table 8b) are grouped under surfaces (both primary and secondary) and volumes (more equidimensional features). Some "lithology strings" may imply more than one surface type or volume type.

Table 8b. Classification of physical features--internal
structures as implied by rock names used to describe map
units. This scheme is extensible based on the properties of
actual map legends.

Category     Subcategory     Sub-subcategory
1 Surfaces      
1.1 laminated
1.2 cross-stratified
1.3 wavy
1.4 mudcracked
1.5 foliated
1.6 flaser
1.7 sheared
1.5.1 continuous (schistose)
1.5.2 discontinuous (gneissose)
2 Volumes      
2.1 amygdaloidal
2.2 boudinaged
2.3 concretionary
2.4 miarolitic
2.5 nodular
2.6 orbicular
2.7 vesicular
2.8 vuggy

Summary of Classifications

Although geological principles have been used in their design, the main purpose of these classifications is to allow effective selection of map units from a geological-map database based on consistent, thematically based lithological attributes. Each thematic classification is organized as a shallow hierarchy or simple set of categories, so that keywords may be selected at a level of detail that corresponds to the level of information available. Further, because the number and nature of themes that are implicit in any particular rock name are variable, the use of multiple keyword sets organized under thematic headings allows a rock name to be indexed by as many (or as few) as appropriate. The design is preliminary and has been tested against a digital map database derived from about 60 individual source maps, using both the original map-unit descriptions, and the more general regional legends. As the map database grows, the classifications will be extended and modified as necessary to accommodate new types of lithological information as required.


Procedure of Indexing Lithological Information from the Map Legend

The classification schemes described above were developed to use as much information as possible from "typical" map-unit descriptions. These initial schemes were developed and tested on 2,082 map-unit descriptions from the Yukon Geology CD (NE of the Tintina Fault) that were taken by Gordey and Makepeace (1999) directly from the source maps. To these were added the map-unit descriptions from the 223 regional compilation units, the 41 Tectonic Assemblages, and the 19 Tectonic Terranes to determine how the lithological indexes would work with these more generalized descriptions. The first step was to parse the unit descriptions from the map legends to identify a set of specific rock names for each map unit (here termed the "root lithology"), together with any associated qualifiers that may influence the way each instance of that rock name is classified, their relative proportions (Table 9), and rock colour(s) if given. Colour and proportion were captured only at the source-unit and regional-unit levels, because there was very little information for these attributes at the Tectonic Terrane and Assemblage levels. In this initial trial, information about weathering characteristics was not captured, although it is common (especially weathering colours). The authors' rock names are retained as far as possible (e.g., dolomite was not renamed dolostone), although the order of the rock names and their associated qualifiers was standardized, so that in general the rock name is first (a "root" lithology), followed by modifiers for composition, texture, fabric, and genesis, in that order, to create a "lithology string." The reason for this ordering is to facilitate their subsequent classification as efficiently and consistently as possible, not to try to develop a set of "preferred" rock names (or qualifiers).

Table 9. Qualitative classification of the proportions of
ithologies in map units from legend descriptions of map
Proportion label     Description
All:     map unit contains only a single lithology
Major:     lithologies explicitly described as the main
component, or implied to be major where the
all other components are stated to be minor
Significant:     lithologies are named in the main part of the text
without qualification as to their importance
Minor:     lithologies explicitly described as minor (or rare)
components of the map unit

In addition to the qualifiers explicitly expressed in the map legend, in some cases an additional qualifier may be inferred from the context of the map unit. For example, the rock name "quartzite" may refer to either a sedimentary or a metamorphic rock, and it is commonly possible to determine which applies from the associated lithologies within the same map unit. The aim is to make each "rock name and associated qualifier" contain all the information that will be needed to classify it as precisely as possible against the generic classifications without further reference to the map-unit description. This speeds up the classification process and ensures that similar strings from different sources are classified identically.

Extracting lithological information from the legend in this way is the slowest step of the process and requires geological knowledge and experience. It is critical to the success of the whole exercise and probably cannot be automated. Although the classifications will be refined over time, if this step is done well, it should not have to be repeated.

When the list of rock names and associated qualifiers was complete for a map set, a list of all the unique combinations was compiled, spelling errors corrected, and "trivial synonyms" caused by variations in spelling or order of qualifiers removed. This edited list was then classified against the thematic indexes, and these classifications related back to the map units. The legend of the next map set was taken through the same process, and the list of unique rock names and qualifiers compared to the first, edited as before, and any new strings added to the set to build up a master list. This list grew rapidly at first, but more slowly as more map sets were processed. This list also allowed an analysis of historical usage of rock names that can be used to suggest a better approach to the process of describing map units for geological map databases in the future.

Results of Legend Parsing, Yukon Test Data Set

From the 2,311 map-unit descriptions, 1,947 unique "lithology strings" were parsed out. These consist of about 160 "root names" (Table 10), and combinations of some 640 qualifying words or phrases (each "root name" having between 0 and 8 distinct qualifiers). The "root names" for lithology can be subdivided into three broad categories; 125 common names that are quite specific (e.g., andesite, metaquartzite), 28 more general "rock class" names (e.g., igneous rocks, organic deposits), and 8 mineral names that are used to label a significant, monomineralic component of a map unit. One approach to standardizing the diversity of language would be to map the actual usage to a "standard" rock-classification scheme. This task would be very time consuming and would involve many assumptions. Furthermore, it would have to be done both for the "root names" and their qualifiers. Two further drawbacks are the current lack of a "standard" for rock nomenclature that is well accepted by Canadian geologists, and the multidimensionality that persists in most of the draft rock-naming schemes that have been proposed or are in preparation. This feature of rock names will continue to hamper the construction of simple queries for map units based on lithology and the production of simple, derivative maps based on a single theme.

Table 10. "Root" rock names extracted from 2,311 NE Yukon map-unit descriptions.

Common rock names
Mineral names
Rock class names
calc-silicate rocks
carbonate rocks
clastic rocks
glacial drift
igneous rocks
intrusive rocks
lime-silicate rocks
metacarbonate rocks
metamorphic rocks
    metasedimentary rocks
metavolcanic rocks
organic deposits
phosphate rocks
plutonic rocks
pyroclastic rocks
quartz-carbonate rocks
quartzose rocks
sedimentary rocks
siliciclastic laminates
ultramafic rocks
volcanic rocks
volcaniclastic rocks

The colour of each lithology also was captured for the legends of the source maps and regional compilation units (colour is little used as a descriptor at the Tectonic Assemblage and Terrane levels). The frequency of association of colours with lithologies decreased from 28% for the source map units to 24% and 17% for the compilers' regional subunits and units, respectively. On closer examination, there are 321 unique colour combinations, ranging from single, simple names (e.g., black, red, white), to those with little specific meaning (e.g., dark or varicoloured), to multi-hued assemblages to describe a single lithology (e.g., light grey to black, greenish grey to turquoise). In short, the descriptions of colours as used in this test map set are too varied to organize in a single database field, although in retrospect some could have been captured in the "lithology string" as they provide information on genesis or composition (e.g., red sandstone, black shale). Weathering colours are more frequently described than the colour of fresh surfaces but suffer from similar inconsistencies.

Few map units at either the source or regional map-unit levels consist of a single lithology (5% and 3%, respectively); most include two or more distinct lithologies. Very few source-unit descriptions contain any quantitative information on the relative proportions of each rock type within the map unit as a whole. For this reason, a qualitative measure of proportions (Table 9) was used, and the results are summarized in Figure 3. The "significant" category really means no information could be gleaned about the proportion of a rock type in a map unit from the legend; this was the case for about 70% of the rock types named in map units at both levels. At the source-map level, a greater number of map units contain, or are dominated by, a single lithology than at the regional level, and the frequency of minor rock types is less. These changes are to be expected in the process of grouping source units into regional compilation units.

Frequency of occurrence of rock-type proportion categories     Figure 3. Frequency of occurrence of rock-type proportion categories (see Table 2). a. source-map descriptions. b. Regional-compilation-unit descriptions.

Analysis of the generic classification schemes

To be effective as criteria for querying map units on their lithological characteristics, each classification scheme should address the following: The number of classifiers associated with particular "lithology strings" is illustrated in Figure 4. The mode is 9 classifiers per unique "lithology string," and the number ranges from 2 to 15. An analysis of each group of classifications by theme shows that some are more effective discriminators than others.

Histogram showing the range and frequency of the number of generic classifications implicit in each unique 'lithology string.'     Figure 4. Histogram showing the range and frequency of the number of generic classifications implicit in each unique "lithology string."

The frequencies with which composition can be applied to the test set of lithologies is illustrated in Figure 5. A composition could be inferred for more than 99%, and there is a reasonably good breakdown among the 14 categories represented. The dominance of the undivided "silicate" category (32.4% of lithologies, Figure 5) is likely due to the predominance of terrigenous sedimentary rocks in this particular map set. Subordinate composition is associated with only 17% of lithologies, but 12 categories are represented.

Chart showing breakdown of lithologies by their implicit composition

Figure 5. Breakdown of lithologies by their implicit composition. a. dominant composition. b. subordinate composition.

The potential of genetic process as a discriminator is illustrated in Figure 6. Again, more than 99% of the test "lithology strings" could be assigned at least one genetic process, and about 17% a second process. Clastic (sedimentary) was the most common category, due to the particular map set used for this exercise, but, in total, 15 different values for genetic process were assigned in the first instance, and 11 for lithologies where a second process was implied.

Chart showing breakdown of lithologies by their implicit genetic process

Figure 6. Breakdown of lithologies by their implicit genetic process. a. at least one process. b. second process.

Environment of formation could be assigned to more than 98% of lithologies (Figure 7). For the 17% of "lithology strings" where a second genetic process was recognized, a corresponding environment of formation could be assigned in almost all instances. As in the case of composition and genetic process, the frequency of occurrence of the various processes reflects the nature of the geological terrane that forms the basis of this test map set.

Chart showing breakdown of lithologies by their implicit environment of formation

Figure 7. Breakdown of lithologies by their implicit environment of formation. a. first genetic process. b. second genetic process.

Texture was classified under five separate schemes. Over 92% of lithologies could be assigned to either a granular or crystalline style of grain intergrowth, with a somewhat even split between the two categories (Figure 8a). Grain-size variability (Figure 8b) could be classified for about half of the "lithology strings," and was evenly split between homogeneous and heterogeneous, with about 2% classified as gradational. Grain size for the matrix (or all particles for homogeneous rocks) could be classified for two-thirds of the "lithology strings" (Figure 8c), with roughly one-third each in size class 2 (0.05-0.2 mm) and size class 3 (>0.2 mm), and less than 3% assigned to size class 1 (<0.05 mm). Although 24% of the "lithology strings" imply that the rocks are heterogeneous in grain size (Figure 8b), for less than 8% could the size of the coarse clasts or crystals be classified (Figure 8d), and almost all of these fell into size class 3. Grain-size morphology (Figure 8e) could be classified for only about 13% of the "lithology strings," and the majority of these fell into the "rounded" category. Finally, the proportion of matrix or groundmass to coarse clasts or crystals (rocks with heterogeneous grain size only) could be assigned to less than 5% of "lithology strings" (Figure 8f).

Chart showing breakdown of lithologies by their textural charactersistics     Figure 8. Breakdown of lithologies by their textural charactersistics. a. grain intergrowth. b. grain-size variability. c. grain size, matrix. d. grain size, clasts/megacrysts. e. grain morphology. f. matrix abundance.

The last major category of indexes was based on physical form, both external habit and internal structure or fabric. External habit could be inferred for only about 25% of the "lithology strings" (Figure 9a), and nearly 23% of these were tabular, reflecting the predominance of stratified rocks in this map set. Internal structures were divided into two categories on the basis of their geometric dimensions: surfaces (2-D) and volumes (3-D). Because very few lithologies (less than 0.5%) were qualified by a linear (1-D) structure, this information has not been used. Almost 21% of "lithology strings" implied a planar fabric, either primary or secondary (Figure 9b), while less than 5% implied a 3-D internal structure (Figure 9c).

    Figure 9. Breakdown of lithologies by their physical form. a. external habit. b. internal structure (fabric), surfaces. c. internal structure, volumes.

The final property that influenced the power of these classification schemes to select map units on specific rock properties was how many are implicit in the "root" rock names themselves, so that queries such as "make a map of all the units that contain carbonate minerals" can be effectively and efficiently constructed. Table 11 contains the percentage of the 161 rock names from Table 10 that intrinsically contain information for each of the main classification schemes.

The results are not unexpected--composition, genetic process, and environment of formation, together with some textural properties, are implicit in most simple rock names. Similarly, a rough indication of the degree of consolidation can be inferred for most materials. Physical form was not very useful, and most of the textural classifications were useful for less than half of the simple rock names.

Table 11. Proportions of "root" rock names that implicitly
allow classification against 17 schemes developed to systematically
index lithological information from bedrock map units.

Classification scheme     Proportion
of classified
Composition, dominant     93%
Composition, subordinate     2%
Genetic process, at least one     97%
Genetic process, second     19%
Environment of formation, first genetic process     94%
Environment of formation, second genetic process     19%
Texture, grain intergrowth     86%
Texture, grain-size variability     32%
Texture, grain size, matrix     44%
Texture, grain size, clasts/megacrysts     <1%
Texture, grain morphology     11%
Matrix proportion     4%
Physical form, external habit     0%
Physical form, internal surfaces     7%
Physical form, internal volumes     0%
Mechanical properties, induration     99%
Mechanical properties, partings     1%


Example of a map produced from a simple query on lithological properties

The true test of these classifications is their effectiveness in constructing simple queries to return specific subsets of map units. A single example will be described, based on the Yukon map set. The goal was to make a map of all units that contained volcanic rocks at both the source-unit and regional-compilation-unit levels of resolution. The query was constructed around the statement that a unit contain a lithology whose "genetic process = igneous" and "environment of formation = supracrustal," for either the first or second genetic process. The query was run on the whole database, but the results (Figure 10) are shown only for the same area as in Figure 2 (i.e., NTS sheet 105A, NE of the Tintina Fault). Figure 10 shows the outlines of all map units at each level; those containing volcanic rocks are shaded. The legend descriptions for the selected units are listed, with the lithologies that triggered their selection capitalized. The variety of these rock names is quite striking even within this small area. It is important that the descriptions of the selected units be scrutinized to ensure that they meet the purpose of the initial query. If not, the query should be refined.

Results of a database query to select map units that contain volcanic rocks from the Yukon map set, shown for NTS sheet 105A only

Figure 10. Results of a database query to select map units that contain volcanic rocks from the Yukon map set, shown for NTS sheet 105A only (see Figure 2). Left, source-map units; right, regional map units. The outlines of all units are shown, with those containing "volcanic" lithologies shaded, and their legend descriptions listed ("volcanic" lithologies capitalized).

Indexing Map Units

The generic indexes for lithology not only aid in the creation of derivative thematic maps as above, but also allow lithologically equivalent map units to be selected. Each map unit has in effect a "profile" of these generic classifications that is the aggregate of the classifications of its component lithologies. This profile can be used to search for other map units with the same profile. Because the classifications are broken down into several independent themes, and many of these classifications are shallow hierarchies, we envision developing a tool that allows the user to selectively modify the search profile by dropping or adding search parameters, or relaxing or tightening classification criteria. For example, if a unit used as the basis for a search was described as a "calcareous marine sandstone with minor concretionary marine shale," this would be parsed as:

lithology     proportion
sandstone, calcareous, marine     major
shale, concretionary, marine     minor

and classified as in Table 12. The profile in Table 12 could be modified to relax or tighten the search constraints. For example, if the "Physical form, internal surfaces = laminated" and "Mechanical properties, partings = platy" criteria for the second lithology were dropped, then units with minor mudstone, siltstone, and other fine-grained marine, clastic, concretionary rocks would be selected. These lithological criteria can be combined with lithological proportions and the age range of the target map units.

Table 12. Generic lithological classification of a map unit described as "calcareous marine sandstone with minor concretionary
marine shale." The actual values for each category are stored in an attribute table as COA ID's from the conceptual classifications
in the COA table.

Classification scheme     sandstone, calcareous, marine     shale, concretionary, marine
Composition, dominant     silicate     silicate
Composition, subordinate
Genetic process     sedimentary>clastic     sedimentary>clastic
Genetic process, second
Environment of formation,
first genetic process
    supracrustal>subaqueous>marine     supracrustal>subaqueous>marine
Environment of formation,
second genetic process
Texture, grain intergrowth     granular     granular
Texture, grain-size variability     homogeneous     homogeneous
Texture, grain size, matrix     size class 3.1     size class 2
Texture, grain size, clasts/megacrysts     nul     nul
Texture, grain morphology
Matrix proportion
Physical form, external habit     nul     nul
Physical form, internal surfaces     nul     laminated
Physical form, internal volumes
Mechanical properties, induration     yes     yes
Mechanical properties, partings     nul     platy


Scalability of geological maps can be achieved by applying the map-unit classifications from the legends of regional compilations to group the map units on more detailed maps used for most practical geological applications (typically at scales 1:250,000). Apart from national compilations at scales 1:5,000,000 (Wheeler and others, 1997), there are at present no nationally applied Canadian regional legend schemes that can be used at intermediate scales (i.e., 1:2,000,000 to 1:1,000,000). The Tectonic Terrane (Wheeler and others, 1991) and Tectonic Assemblage (Wheeler and McFeely, 1991) classifications developed for the Cordilleran Orogen are suitable approaches to fill this gap, and equivalent classifications are being developed for the Newfoundland and Nunavut regions. The various levels of regional legend do not belong to a simple hierarchy of map units, which means that instances of detailed map units on each source map must be assigned to their correct regional group at each level of generalization by compilers who have a thorough knowledge of the geology of the various regions of Canada.

These generic classification schemes for map units based on their lithological characteristics are preliminary, but we believe it is the type of classification scheme needed for a functional geological-map database. They are informed by geological principles, but do not purport to be anything more than categorical classifications. If we can make them truly generic we can unbundle the multidimensional nature of geological nomenclature. Such a classification scheme will greatly assist in making "derivative" maps, and perhaps in making geological map information less cryptic to the nonspecialist. Further, by keeping the number of "concepts" in the COA table to a reasonable size, the task of documenting the concepts (and translating the documentation into other languages) can be kept to a manageable size. Finally, by placing much of the detail (i.e., instances of concepts) in attribute tables, these can be managed locally, making the task of coordinating the "global concepts" more tractable. These generic classifications can also co-exist with more interpretative, thematic classifications at a regional map unit level such as that proposed by Struik and Quat (2002) for Tectonic Assemblages.

The project so far has addressed the map units of existing geological maps the historical map information. For new maps, authors must be asked to place map units into predetermined higher levels, explicitly provide proportions of lithologies within map units, and complete the lithological indexing for map units. This last task will become much easier if geologists move toward the use of standard science language for rock names and qualifying information, as these standard terms would be already linked to generic keywords. Work on linear and point features from geological maps will be a task for the future.


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