- [Instructor] Hi,
and welcome to module three of Advanced GIS.
This sequence of lectures differentiates
between overlay and data aggregation strategies
and identifies approaches for developing composite datasets,
both Vector and Raster.
We'll focus on both Vector and Raster data
in this lecture sequence,
and look at alternative Geoprocessing operations
for putting data together.
On the Vector side,
we have options including Merge or append.
I include Union in this list of options
to highlight the fact that it is not
the correct tool for the job.
Hopefully, this will be born out in the examples,
but if not,
let's keep that conversation going on (indistinct).
As far as Raster data are concerned,
our options are a bit more limited.
We can create a Mosaic dataset and add Rasters to it,
or we can append data to an existing Raster dataset,
those are the options.
Note the append tool
can accommodate both Vector and Raster datasets.
Let's start with Vector data.
And a quick review of the Union Geoprocessing operation.
Union tool computes a geometric Union of the input features
and creates a new feature class of the resulting feature,
plus; and this is important here,
all the input attributes.
The Union tool can only use polygon data
and only requires a single dataset to Run,
that last part might be a bit confusing.
But think of the case where you have a polygon dataset
that has overlapping polygons.
If you want to break those overlaps down,
the Union tool would be the correct approach.
Most important to consider here
is that this is an overlay operation,
it's meant to be used on data that overlap one another.
So how does it work?
It's a four-step process.
First, the algorithm determines the spatial reference
to be used in the analysis.
This comes from the first input
in the list of input datasets.
Then it cracks and clusters the features.
Cracking means that anywhere two lines
from different polygons intersect,
it's going to break those polygons
at those intersection points.
Then those point locations are evaluated
against the cluster-tolerance parameter.
And if they're too close,
fall within a certain threshold,
they're closer to a single point.
Next, the overlaps are identified,
in other words,
ArcGIS discovers the geometric relationships
between or among the different input data.
Lastly, the new features are written to an output dataset.
We've heard the what and the how,
now let's identify what a Union operation does not do.
It doesn't provide you a means
for efficiently assembling multiple datasets
into a single dataset.
For one thing,
it does not let you map fields to one another,
instead, assembling all the attributes
from all the input datasets
and presenting them individually.
We'll look at the power of field mapping
here in a few minutes.
Additionally, the Union tool cannot accommodate Raster data.
It's a Vector only Geoprocessing operation.
One of the parameters of the Union tool
I did not introduce previously
is the gaps allowed.
Gaps are areas that are completely enclosed by the polygons
resulting from a Union operation.
Let's look at the two examples here to our right.
We have two polygon data sets as our inputs
one shaded in green, one outlined in blue.
If we leave the default setting
for the gaps allowed parameter,
no additional features are created to fill those gaps.
We started with two polygons
and we ended up with four
as our output from the Union operation.
If however you uncheck that parameter option,
the opposite happens, the gaps are filled.
In this case, starting with two
but ending up with five polygons in the output dataset.
Important to note here that the FID values
of these polygons will be set to negative one.
So if you wanted to have the gaps filled
but later also want it to be able to
identify those polygons that represent those filled gaps,
you could perform a select
by attributes operation to identify features
with an FID value of negative one.
A Merge operation combines multiple input data sets
into a single output data set using points,
lines or polygons as inputs.
The output geometry type
as well as the data types for each attribute
are determined by the first input dataset.
You've heard twice now the effect
of first input data set has on the output data set.
It's always important to think about that first
input data set that you enter
because a lot of information for the output
is reliant on that input data information.
So what doesn't Merge do ?
well, unlike the Union tool
the Merge tool will not split or alter the geometry.
It does not affect the individual features
even if they overlap one another.
It also does not accommodate Raster data.
I can't stress enough how important it is
to understand the difference
between a Union and Merge operation.
A Union cracks features
and creates new ones based on the spatial relationships
between input datasets,
the Merge tool lumps the input data sets
together without looking more closely
at the geometry of the individual features themselves.
Permit me a brief aside here about field mapping,
a parameterization you can specify
for a limited set of Geoprocessing tools,
I provide a short list here of the most common.
Field mapping controls,
how and whether fields or attributes
are processed and mapped to an output data set.
Like we've heard before,
the first input data set in the list
is the one from which that list of attributes is drawn,
and it's the list of attributes
to which every subsequent data set
needs to have their fields mapped
in order to be written to the output.
If all the tables scheme match,
meaning they all have the same list of attributes
and data types,
but not necessarily attribute values,
ArcGIS will map the fields automatically.
Again, this only happens when the attribute
definitions are the same.
Otherwise it's up to you to manually map the fields
of the various input datasets
to the fields of the first input dataset.
You can also add and delete fields set data types
and even define Merge rules,
if you're trying to combine multiple input fields
into a single output field;
not unlike a concatenation operation.
Moving on, the last of the three Vector tools ,
we'll look at is Append
What does this tool do?
It adds or appends data to an existing dataset.
Imagine you're writing a book,
you saved the first three chapters in one file
and the next three in a separate file.
How do you resolve this?
You paste or append the final three chapters
to the initial three ,
same basic idea with facial data.
You're adding more data to an existing
or target dataset.
Both the Union and Merge operations result in a new dataset,
the Append tool modifies the target data.
The append tool can also accommodate most data types
Vector, Raster, tabular, and more.
It sounds great.
What can't it do?
Well like the Merge operation,
it doesn't split or alter the geometries
even if the inputs overlap one another.
It also does not allow new attributes
to be created using the field mapping interface.
Remember you're adding data to an existing data set here,
a dataset with its own table specification.
Any data you want to append should match that specification.
The assumption here is that the existing dataset
already has the schema or table structure you need.
Okay, the bottom line ,
Union.
Great for computing
or understanding the spatial relationships
between or among input features
but it's not the right tool for assembling discrete pieces
of data into a single dataset.
This tool is an overlay analysis use
for understanding the relationship or between
or among the geometries of the input features.
The append tool is used to add data
to an existing data set with limited field mapping options;
I think making the book longer here.
Lastly,
Merge gives us the ability to combine multiple inputs
into a new output
with significantly more field mapping capabilities.
Now, one more thing to think about ,the dissolve tool.
What role might dissolve play as a followup
to a Union Merge or append operation.
Dissolve the Union output on an attribute,
common to your inputs
or a new attribute you create to derive new geometries.
Following a Merge or append operation,
the dissolve tool could be used
to eliminate overlapping polygons
and the input datasets.
You'll typically find these along the edges
of the tile data .
You could of course manually edit the offending polygons
but oftentimes the dissolve operation will go much quicker.
Okay
Let's move on and talk about some approaches
to assembling tiled Raster data;
the corollary to the Merge
and append operations we just discussed.
The nice thing about Raster data in this regard
is that there are really only two options ,
create Mosaic dataset and append,
and one of them won't work to create a new dataset.
That's right,
the same append tool from the Vector section of the lecture.
We already know that adds to a target dataset,
which means create Mosaic dataset
seems like the appropriate place to start.
Mosaic dataset is used to manage display,
serve and share Raster data.
It consists of many parts.
Key to understand, at least initially are the catalog,
the source of information that defines the Raster values
and their spatial extents.
A polygon feature class of the Mosaic boundary
rules for data handling.
Don't worry.
We'll use the defaults for now.
Lastly, a color correction
that supplies the color ramp for each Raster
in the Mosaic dataset could also be included.
Just like with regular old Vector and Raster datasets,
you can access a property's interface
for the Mosaic dataset.
The interface includes three sections of information,
general, default and multi-dimensional.
There's only one way to create a new Mosaic dataset
but there are two ways to get there,
either right click the geo database
where you want to store the Mosaic dataset
in the catalog pane
and choose new new Mosaic dataset
from the list of options
or search for the tool in the Geoprocessing pane,
like we've done many times before,
either way you end up in the same place;
the create Mosaic data set Dialog box.
As for Parameters,
We see that we need to specify a Mosaic data set name,
that's the empty container to be created
and a coordinate system.
If you access the Dialog box
from the Geoprocessing pane,
you will also need to specify
the geo database to store the Mosaic in.
Once you click Run,
the Mosaic dataset is added to the geo database
then right click the Mosaic data set
and select add Rasters
from the list of options.
Next, specify Which Rasters to add
and what format they are in to complete the specification.
Think of the Mosaic dataset you just created
as an empty container.
same basic idea when we create a new feature class
on the Vector side of things.
we create an empty container and digitize features.
With the Mosaic,
you create the container and add the Raster data
in lieu of digitizing ,
click Run to complete the process.
Now we see a snapshot of the Mosaic dataset components
in the contents pane of my project.
We've got the boundary;
remember that's the outer bounds
of the entire Mosaic dataset,
there's a footprint feature class,
polygons representing the individual Raster boundaries.
Lastly, there's the image itself,
the Mosaic we just created.
Look at the value range here,
it doesn't make much sense
unless you specify a color ramp,
this is likely to happen to you too.
If we look at the help documentation associated
with data types and ArcGIS,
we see the maximum and minimum value
that can be stored in a floating point
single precision number ;
looks pretty similar to what we saw in the legend
and that's not a coincidence.
It simply means that the statistics
of the Raster table have not been calculated,
which in turn means that the software
is displaying your data without having read it.
It knows it's there,
but doesn't know what's in it.
What's a geo processor to do!
Well ,you can force GIS
to compute the statistics of your dataset,
this doesn't have happen automatically
for floating point Rasters.
And while it may seem a bit counterintuitive,
imagine if you had a very large ;
from a file size perspective,
high resolution over a broad spatial extent for example,
a very large Raster file
that might take a long time to compute statistics.
And it might not be necessary
if you already know the value ranges.
You either need to know that
or allow the statistics to be computed
to generate a proper display.
You have options here
for controlling the calculations .
For large data sets,
you can skip cells, skip specific values
or even skip areas where statistics
have already been computed ;
likely at a different time.
You can also simply specify an area of interest
and only compute statistics for that region.
Once that's done,
we see that in my case,
the value range between zero and just under 4,400 meters.
One other thing here,
the data Lock icon ,
this appears when dataset alterations are underway.
For example,
you'll see this with something like
the add X, Y coordinates
or even when computing statistics on a Raster dataset.
That's because ArcGIS is actually
updating some aspect of the dataset,
which means that you can not use that data for anything
while the Lock icon is present;
it disappears once the operation has been completed.
Okay, last thing here,
a short reminder that the append tools
is an options as well,
and that it is to be used to expand the coverage
of an existing Raster dataset,
not to create a new one.
This is the one Geoprocessing operation
out of all that have been discussed in the segment
that works for both Vector and Raster data.
So hopefully that provides a clear picture
of the distinctions between Union and Merge
and the correct workflows
for assembling tile data,
whether they're Vector or Raster.
In the next segment,
I'll provide brief demonstration
of the tools we just discussed here.
We'll follow that up with
a look at summarizing one dataset
based on boundaries in another dataset.
That said,
if you think you've got the gist of this
feel free to skip the demonstration video
and move right into the summarizing data lecture.
I look forward to seeing you there.