McElhanney MapInfo-Discover2 Course-Notes Surfaces

7/27/2019 McElhanney MapInfo-Discover2 Course-Notes Surfaces

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©McElhanney Consulting Services 2012

This is an excerpt from Exercise 7, “Surfaces”, of the course manual provided for

the McElhanney course MapInfo Professional and Encom Discover Mineral

Exploration Module 2.

Modify Grid DisplayWhen a grid is first created it may not have a satisfactory appearance. The grid created in the

previous exercise may be too dark, have strong shadows or might have the wrong colour scheme.

In this exercise you will use the Modify Grid Display utility to change the appearance of the grid.

Modify Sun-Shading

1. Click Surfaces >

Modify Grid Display (or click the Sun-shade

Grid button on theSurfaces toolbar).

2. Click the Sun tab and

check the box for Auto

Apply (Note that thismay cause long delays

when large data sets are

used).3. Modify the settings for

Saturation, Intensity

and Shadow. Observethe results in the map

window. The sun angle

can be modified by

dragging the sunsymbol to different

locations. Once a

suitable result isachieved, click the

Close button at the

bottom right.

Modify Grid Colors

1. If the Modify Grid

Display window is not

open, click Surfaces >Modify Grid Display (or click the Alter grid

colours button on the

Surfaces toolbar).

2. The default setting is alinear stretch using

Pseudocolour.lut (lut =

Move this to

interactivelychange the sunan le.

Step 4

Step 3

Acceptdefaults orclick tochange

colours orvalues.




‘look up table’). Change this to geochemistry.clr. Note that there are two file extension for

colour tables; *.clr and *.lut. Percentile breaks can only be created for the *.clr type.3. Experiment with the different method options; you will need to click the Apply button after

each change.

4. Select the Percentile Breaks

option, and then choosePercentile Breaks (10) from

the dropdown list underOptions. Accept the default

colours and percentile values,

or click in the rows to changethat values or colours. If you

then select the option to

Colour to Data Breaks, you

will see the actual values thatcorrespond to the percentile

values.

Create a Grid LegendThere is no setup procedure for

creating a grid legend, other than toto match grid colours to values, as

was done when grid colours were

modified. The appearance of thelegend is determined by how colours are matched to values.

1. From the Surfaces menu click Make Legend for Grid. Alternatively, you can click the Grid

Legend button on the Surfaces toolbar. If more than one grid files are open, you will be

asked to specify the grid.

Why are there Negative Values in the Grid?

Depending on the input data values and the method you used to create a grid, you might end upwith negative values in the grid. Negative values can occur for two reasons:

• There are actually negative values in the data. These values could indicate no data, lostsamples, samples not taken, etc. These should be dealt with through data conditioning on theInput page of the gridding tool. As you did earlier in the exercise (on the Input page of the

gridding tool), use the statistics explorer button to see if negative values exist in the sample

data. If negative values exist, use data conditioning to specify values less than or equal to

zero as invalid.

• Negative values can occur in a grid even if there are no negative values in the input datapoints, and even if data conditioning was used to exclude negative values. This is particularly

prevalent when using the minimum curvature method, but it does not happen when using the

triangulation method. Negative values are created when the gridding process projects adecreasing value trend into an area where there are no input samples points. For example,

suppose that along a constant direction the gridding tool encounters values of 100 ppm; then

50 metres away, 60 ppm; then another 50 metres away, 10 ppm; then another 50 metresfurther away, no sample. Given the trend of rapidly decreasing values and the fact that the

Notice negativevalues. See belowfor explanation.




last value encountered was close to zero, the gridding tool will likely create a negative value

in the area where no sample was encountered.

False Anomalies

Something important to note here is that false anomalies of high values can be created for the

exact same reason that negative values can be created. Reversing the trend (looking in theopposite direction) in the example on the previous page could result in the creation of values

much higher than 100 ppm in an area where possibly no samples exist. This is particularlycommon when using the minimum curvature method, though the effect can be reduced by

increasing the boundary tension value and by using a buffer to limit the maximum distance

from a sample that a value can be calculated. It does not happen when using the triangulationmethod.

Deriving Elevation Values from a Digital Elevation ModelIf you have a DEM (digital elevation model), you can use the Surfaces menu to update point

data, such as drillhole collars or sample locations, with elevation values derived from the DEM.

This can be useful if elevation values are not known for those points or if the DEM has moreaccurate elevation values than those currently stored for those locations. For example, initial

elevation values stored for drillholes may have been collected with a handheld GPS with ± 10

metre accuracy, but the DEM may have been generated using satellite imagery or LiDAR data

might have ± 1.5 m and ± 0.2 m respectively. Values derived from the DEM can be used toreplace those collected with the handheld GPS, or they can be added to an additional

ELEV_DEM column.

1. If it is not already open, open the Soil_Samples.tab file from the Geochem folder.2. Open a browser for the soil samples table.

3. From the BaseMap folder, open the file DEM_1.tab. The tab file will open a digital

elevation model, saved in the Geosoft grid format. The DEM will need to be displayed in the

same map window as the soil samples table.4. In MapInfo, click Table > Maintenance > Table

Structure.

5. Select the Soil_Samples table and then add an

ELEV_DEM field (elevation derived from a DEM) to

the table. The field should be Float type. A safe place

to put the new column is at the end of existing columns. As drillhole projects and

workspace files may make reference to

columns by their order number, reorderingthose columns may lead to problems when

opening workspaces or drillhole projects.6. Select all points in the Soil Samples table -the fastest way to do this is to right click the

layer in the Enhanced Layer Control, and

from the resulting menu, click Select All.

7. Click Surfaces > Assign Values from

Grid. Note that you are not asked to choose

a table at this step, as the assigning of

Step 8




values depends on having selected points.

8. In the Assign Grid Values window, select the ELEV_DEM column. 9. Click OK. The Soil_Samples Elevation column will now show the elevation values assigned

from the DEM file.

Using a DEM to Check for Elevation Survey IssuesAt this point you should be aware that coordinates for a location are ambiguous unless they are

accompanied by projection and datum information. For example, given East-North or Latitude-Longitude coordinates for a drillhole, you won’t know where that drillhole is unless you know

whether the datum is NAD27 or NAD83. Did you know that similar issues arise with elevation

data? There are two common earth models used when surveyors report elevation data, the Geoid

model and the Ellipsoidal model. Problems arise when elevations measured in the two systems

(common on projects involving multiple stages/generations/eras of exploration) are used on the

same project, particularly when they are mixed in the same elevation column. Mixing elevation

models can lead to offsets of up to 25 metres or more (a typical difference between the twomodels at the same point). Imagine the problems that would be created in mineral deposit

resource calculation or drillhole planning if some of the drillholes had a 25 metre elevation offsetcompared to other drillholes.These problems can be found with the use of the Surfaces model and a sufficiently accurate

DEM. The following method outlines how it is done for a hypothetical drillhole collar table.

1. The collar table must already have a column containing elevation values (ELEV_SURV, for

example).

2. A new elevation column, called ELEV_DEM is added to the collar table. An Additional

column called ELEV_DIFF (elevation difference) is also created.3. A DEM with a known (and low) elevation error must be available for the drilling area.

Preferable DEM files would have been created using LiDAR (~± 20 cm) , high resolution

airphoto or satellite imagery (~± 1.5 to ± 2.5 metres). DEM files created from less accuratemethods (Geophysical RADAR, or government DEM files, for example) may have too much

error. SRTM (Space Shuttle) or ASTER DEM files are particularly unsuitable – the error is

just too high.4. The Surfaces > Assign Values tool is used to update the ELEV_DEM column with values

derived from the DEM.

5. Table > Update Column is used to update the ELEV_DIFF column with the difference

between the surveyed elevation column and the ELEV_DEM column. The expression wouldbe ELEV_DEM – ELEV_SURV, for example. The order of the expression does not matter.

The difference values will vary by several metres, according to the accuracy of the DEM, butwhat you are looking for is two distinct populations of differences – this can be accomplished by

creating a histogram of the difference values in Discover’s GraphMap module. If geoid and

ellipsoidal elevations have been mixed in the same elevation column, one population of differences will be within a few metres of zero and the other population is likely to be in the 15 –

30 metre range. Modern DEM files, such as those created with LiDAR, are often created using

the geoid model (though you will need to check with the data provider). This implies that anyelevations that are close to the DEM values created with the geoid model must also be geoid

elevations. Elevations that differ greatly from the DEM values might have been surveyed using




the ellipsoidal model, or they might be a result of poorly surveyed points or a data entry error. If

there is a large variation in elevation differences but there are not two distinct populations, thismight mean that you have a poor DEM, poorly surveyed points or both. If you have a DEM with

high accuracy, such as one created with LiDAR, elevations derived from that DEM may be used

to replace any suspect surveyed elevation values. For further discussion refer to the section at the

back of this manual titled “Using a DEM and Discover’s GraphMap Module to IdentifyElevation Survey Issues”.

McElhanney MapInfo-Discover2 Course-Notes Surfaces

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