Lab 2 Review


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Lab 2 Review…

First step is to prepare your input data for analysis.

Your inputs are:

  • landcover: polygon shapefile in NAD_1927_Hotine_Oblique_Mercator_Azimuth_Natural_Origin coordinate system (projected coordinate system)
  • owl_nest_locs.csv: tabular file containing latitude/longitude coordinates (geographic coordinate system) of nest locations

Before you proceed, you must ensure all of your inputs are cast in the same projected coordinate system.

Use the PROJECT tool to convert from one coordinate system to another.

Combine information in layers based on location

We have land cover in one layer and nest locations represented in another layer.  We need to answer the question “Which land cover types do our owls prefer?”  To answer this question, we must determine the land cover type in which nest is located.

Use the SPATIAL JOIN to join information from one layer to another based on location.

Summarize table based on a categorical variable

Recall our nest attribute table.  At this point in the lab, its attribute table contains the nest’s latitude, longitude, and the land cover in which it is located – 47 total entries.  We need to figure out how many of the points fall within aspen stands, how many are in northern hardwoodoak, etc.  You could manually count the points in each type but this would take a long time.  There is a better way.

Use the SUMMARIZE command to count, find the average, minimum, maximum and several other statistics for entries within each category.

Selecting records (and shapes) based on an attribute

There are many uses for attribute queries.  You might need to know “where are all of the pine stands located”, or you may need to “find all of the second order streams”, or all of the points “within a sandy loam soil.”  If your attribute table contains the information, then you can query it.

The query syntax is <FIELD NAME> <OPERATOR> <VALUE>

On pages 16 and 17, you submitted an attribute query to select all of the herbaceous openland polygons that are >= 0.405 hectares in size.  This is the foraging habitat the experts have identified as important to our owls.

Calculate distance among features

In the Proximity section of Lab 2, you are asked to determine the distance from each nesting point to the closest foraging habitat polygon.  You must use your projected point layer as the input.  Your near input is your land cover layer.  Only a subset of these polygons will be considered since the herbaceous openland polygons >= 0.405 ha are still selected.

Use the NEAR tool to determine the distance from the features in one layer to the nearest features in another.

Answering the within a distance of’ question

Many times you need to answer the ‘within a distance of’ question – “How many acres are within 200′ of a river?”  or “Determine the percentage of cover types within our nest buffer.”  “Within a distance of” is a phrase you should key in on.  It suggests you will perform a buffer operation.

Use the BUFFER command to create a buffer around your point, line, or polygon features.

Keep in mind, if present, only selected features will be buffered.

Clip, the ‘cookie cutter process’

On page 20, you have a polygon layer that you created when you buffered each point 176m.  You also have a land cover polygon layer with selected features.  If you proceed (on page 20, step 1)  without unselecting these polygons, the next steps will only operate this small set of land cover polygons.

Use the CLEAR SELECTED FEATURES entry under the Selection pull-down menu to unselect everything.

Use the CLIP tool to crop land cover within each buffer.

Every time you perform a clip, you must recalculate area or length using the CALCULATE GEOMETRY command.