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- [Instructor] Hi,

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and welcome to module
three of Advanced GIS.

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This sequence of lectures differentiates

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between overlay and data
aggregation strategies

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and identifies approaches for
developing composite datasets,

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both Vector and Raster.

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We'll focus on both Vector and Raster data

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in this lecture sequence,

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and look at alternative
Geoprocessing operations

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for putting data together.

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On the Vector side,

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we have options including Merge or append.

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I include Union in this list of options

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to highlight the fact that it is not

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the correct tool for the job.

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Hopefully, this will be
born out in the examples,

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but if not,

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let's keep that conversation
going on (indistinct).

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As far as Raster data are concerned,

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our options are a bit more limited.

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We can create a Mosaic
dataset and add Rasters to it,

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or we can append data to
an existing Raster dataset,

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those are the options.

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Note the append tool

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can accommodate both
Vector and Raster datasets.

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Let's start with Vector data.

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And a quick review of the
Union Geoprocessing operation.

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Union tool computes a geometric
Union of the input features

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and creates a new feature
class of the resulting feature,

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plus; and this is important here,

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all the input attributes.

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The Union tool can only use polygon data

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and only requires a single dataset to Run,

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that last part might be a bit confusing.

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But think of the case where
you have a polygon dataset

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that has overlapping polygons.

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If you want to break those overlaps down,

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the Union tool would be
the correct approach.

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Most important to consider here

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is that this is an overlay operation,

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it's meant to be used on data
that overlap one another.

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So how does it work?

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It's a four-step process.

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First, the algorithm determines
the spatial reference

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to be used in the analysis.

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This comes from the first input

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in the list of input datasets.

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Then it cracks and clusters the features.

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Cracking means that anywhere two lines

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from different polygons intersect,

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it's going to break those polygons

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at those intersection points.

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Then those point locations are evaluated

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against the cluster-tolerance parameter.

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And if they're too close,

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fall within a certain threshold,

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they're closer to a single point.

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Next, the overlaps are identified,

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in other words,

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ArcGIS discovers the
geometric relationships

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between or among the different input data.

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Lastly, the new features are
written to an output dataset.

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We've heard the what and the how,

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now let's identify what a
Union operation does not do.

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It doesn't provide you a means

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for efficiently assembling
multiple datasets

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into a single dataset.

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For one thing,

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it does not let you map
fields to one another,

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instead, assembling all the attributes

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from all the input datasets

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and presenting them individually.

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We'll look at the power of field mapping

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here in a few minutes.

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Additionally, the Union tool
cannot accommodate Raster data.

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It's a Vector only
Geoprocessing operation.

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One of the parameters of the Union tool

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I did not introduce previously

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is the gaps allowed.

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Gaps are areas that are completely
enclosed by the polygons

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resulting from a Union operation.

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Let's look at the two
examples here to our right.

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We have two polygon
data sets as our inputs

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one shaded in green, one outlined in blue.

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If we leave the default setting

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for the gaps allowed parameter,

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no additional features are
created to fill those gaps.

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We started with two polygons

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and we ended up with four

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as our output from the Union operation.

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If however you uncheck
that parameter option,

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the opposite happens, the gaps are filled.

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In this case, starting with two

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but ending up with five
polygons in the output dataset.

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Important to note here that the FID values

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of these polygons will
be set to negative one.

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So if you wanted to have the gaps filled

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but later also want it to be able to

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identify those polygons that
represent those filled gaps,

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you could perform a select

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by attributes operation
to identify features

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with an FID value of negative one.

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A Merge operation combines
multiple input data sets

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into a single output
data set using points,

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lines or polygons as inputs.

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The output geometry type

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as well as the data
types for each attribute

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are determined by the first input dataset.

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You've heard twice now the effect

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of first input data set
has on the output data set.

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It's always important to
think about that first

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input data set that you enter

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because a lot of
information for the output

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is reliant on that input data information.

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So what doesn't Merge do ?

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well, unlike the Union tool

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the Merge tool will not
split or alter the geometry.

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It does not affect the individual features

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even if they overlap one another.

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It also does not accommodate Raster data.

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I can't stress enough how important it is

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to understand the difference

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between a Union and Merge operation.

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A Union cracks features

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and creates new ones based
on the spatial relationships

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between input datasets,

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the Merge tool lumps the input data sets

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together without looking more closely

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at the geometry of the
individual features themselves.

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Permit me a brief aside
here about field mapping,

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a parameterization you can specify

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for a limited set of Geoprocessing tools,

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I provide a short list
here of the most common.

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Field mapping controls,

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how and whether fields or attributes

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are processed and mapped
to an output data set.

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Like we've heard before,

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the first input data set in the list

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is the one from which that
list of attributes is drawn,

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and it's the list of attributes

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to which every subsequent data set

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needs to have their fields mapped

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in order to be written to the output.

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If all the tables scheme match,

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meaning they all have the
same list of attributes

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and data types,

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but not necessarily attribute values,

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ArcGIS will map the fields automatically.

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Again, this only happens
when the attribute

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definitions are the same.

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Otherwise it's up to you
to manually map the fields

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of the various input datasets

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to the fields of the first input dataset.

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You can also add and delete
fields set data types

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and even define Merge rules,

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if you're trying to combine
multiple input fields

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into a single output field;

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not unlike a concatenation operation.

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Moving on, the last of
the three Vector tools ,

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we'll look at is Append

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What does this tool do?

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It adds or appends data
to an existing dataset.

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Imagine you're writing a book,

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you saved the first three
chapters in one file

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and the next three in a separate file.

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How do you resolve this?

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You paste or append the
final three chapters

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to the initial three ,

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same basic idea with facial data.

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You're adding more data to an existing

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or target dataset.

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Both the Union and Merge
operations result in a new dataset,

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the Append tool modifies the target data.

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The append tool can also
accommodate most data types

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Vector, Raster, tabular, and more.

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It sounds great.

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What can't it do?

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Well like the Merge operation,

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it doesn't split or alter the geometries

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even if the inputs overlap one another.

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It also does not allow new attributes

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to be created using the
field mapping interface.

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Remember you're adding data
to an existing data set here,

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a dataset with its own
table specification.

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Any data you want to append
should match that specification.

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The assumption here is
that the existing dataset

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already has the schema or
table structure you need.

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Okay, the bottom line ,

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Union.

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Great for computing

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or understanding the spatial relationships

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between or among input features

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but it's not the right tool
for assembling discrete pieces

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of data into a single dataset.

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This tool is an overlay analysis use

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for understanding the
relationship or between

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or among the geometries
of the input features.

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The append tool is used to add data

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to an existing data set with
limited field mapping options;

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I think making the book longer here.

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Lastly,

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Merge gives us the ability
to combine multiple inputs

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into a new output

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with significantly more
field mapping capabilities.

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Now, one more thing to think
about ,the dissolve tool.

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What role might dissolve
play as a followup

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to a Union Merge or append operation.

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Dissolve the Union output on an attribute,

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common to your inputs

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or a new attribute you create
to derive new geometries.

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Following a Merge or append operation,

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the dissolve tool could be used

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to eliminate overlapping polygons

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and the input datasets.

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You'll typically find
these along the edges

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of the tile data .

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You could of course manually
edit the offending polygons

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but oftentimes the dissolve
operation will go much quicker.

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Okay

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Let's move on and talk
about some approaches

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to assembling tiled Raster data;

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the corollary to the Merge

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and append operations we just discussed.

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The nice thing about
Raster data in this regard

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is that there are really
only two options ,

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create Mosaic dataset and append,

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and one of them won't work
to create a new dataset.

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That's right,

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the same append tool from the
Vector section of the lecture.

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We already know that
adds to a target dataset,

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which means create Mosaic dataset

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seems like the appropriate place to start.

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Mosaic dataset is used to manage display,

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serve and share Raster data.

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It consists of many parts.

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Key to understand, at least
initially are the catalog,

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the source of information
that defines the Raster values

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and their spatial extents.

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A polygon feature class
of the Mosaic boundary

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rules for data handling.

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Don't worry.

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We'll use the defaults for now.

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Lastly, a color correction

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that supplies the color
ramp for each Raster

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in the Mosaic dataset
could also be included.

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Just like with regular old
Vector and Raster datasets,

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you can access a property's interface

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for the Mosaic dataset.

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The interface includes three
sections of information,

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general, default and multi-dimensional.

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There's only one way to
create a new Mosaic dataset

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but there are two ways to get there,

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either right click the geo database

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where you want to store the Mosaic dataset

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in the catalog pane

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and choose new new Mosaic dataset

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from the list of options

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or search for the tool in
the Geoprocessing pane,

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like we've done many times before,

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either way you end up in the same place;

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the create Mosaic data set Dialog box.

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As for Parameters,

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We see that we need to specify
a Mosaic data set name,

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that's the empty container to be created

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and a coordinate system.

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If you access the Dialog box

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from the Geoprocessing pane,

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you will also need to specify

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the geo database to store the Mosaic in.

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Once you click Run,

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the Mosaic dataset is
added to the geo database

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then right click the Mosaic data set

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and select add Rasters

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from the list of options.

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Next, specify Which Rasters to add

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and what format they are in
to complete the specification.

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Think of the Mosaic
dataset you just created

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as an empty container.

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same basic idea when we
create a new feature class

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on the Vector side of things.

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we create an empty container
and digitize features.

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With the Mosaic,

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you create the container
and add the Raster data

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in lieu of digitizing ,

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click Run to complete the process.

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Now we see a snapshot of the
Mosaic dataset components

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in the contents pane of my project.

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We've got the boundary;

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remember that's the outer bounds

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of the entire Mosaic dataset,

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there's a footprint feature class,

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polygons representing the
individual Raster boundaries.

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Lastly, there's the image itself,

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the Mosaic we just created.

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Look at the value range here,

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it doesn't make much sense

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unless you specify a color ramp,

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this is likely to happen to you too.

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If we look at the help
documentation associated

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with data types and ArcGIS,

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we see the maximum and minimum value

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that can be stored in a floating point

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single precision number ;

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looks pretty similar to
what we saw in the legend

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and that's not a coincidence.

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It simply means that the statistics

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of the Raster table have
not been calculated,

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which in turn means that the software

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is displaying your data
without having read it.

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It knows it's there,

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but doesn't know what's in it.

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What's a geo processor to do!

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Well ,you can force GIS

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to compute the statistics of your dataset,

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this doesn't have happen automatically

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for floating point Rasters.

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And while it may seem
a bit counterintuitive,

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imagine if you had a very large ;

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from a file size perspective,

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high resolution over a broad
spatial extent for example,

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a very large Raster file

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that might take a long
time to compute statistics.

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And it might not be necessary

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if you already know the value ranges.

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You either need to know that

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or allow the statistics to be computed

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to generate a proper display.

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You have options here

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for controlling the calculations .

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For large data sets,

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you can skip cells, skip specific values

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or even skip areas where statistics

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have already been computed ;

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likely at a different time.

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You can also simply
specify an area of interest

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and only compute
statistics for that region.

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Once that's done,

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we see that in my case,

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the value range between zero
and just under 4,400 meters.

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One other thing here,

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the data Lock icon ,

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this appears when dataset
alterations are underway.

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For example,

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you'll see this with something like

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the add X, Y coordinates

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or even when computing
statistics on a Raster dataset.

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That's because ArcGIS is actually

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updating some aspect of the dataset,

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which means that you can not
use that data for anything

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00:14:02,190 --> 00:14:04,240
while the Lock icon is present;

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it disappears once the
operation has been completed.

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Okay, last thing here,

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a short reminder that the append tools

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00:14:10,980 --> 00:14:12,170
is an options as well,

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00:14:12,170 --> 00:14:14,450
and that it is to be used
to expand the coverage

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00:14:14,450 --> 00:14:16,400
of an existing Raster dataset,

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00:14:16,400 --> 00:14:18,310
not to create a new one.

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This is the one Geoprocessing operation

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00:14:20,230 --> 00:14:22,120
out of all that have been
discussed in the segment

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that works for both
Vector and Raster data.

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So hopefully that provides a clear picture

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00:14:27,790 --> 00:14:30,090
of the distinctions
between Union and Merge

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00:14:30,090 --> 00:14:31,160
and the correct workflows

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00:14:31,160 --> 00:14:32,630
for assembling tile data,

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00:14:32,630 --> 00:14:34,870
whether they're Vector or Raster.

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In the next segment,

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I'll provide brief demonstration

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00:14:37,340 --> 00:14:39,370
of the tools we just discussed here.

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00:14:39,370 --> 00:14:40,210
We'll follow that up with

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a look at summarizing one dataset

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00:14:42,170 --> 00:14:44,120
based on boundaries in another dataset.

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That said,

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if you think you've got the gist of this

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feel free to skip the demonstration video

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00:14:49,890 --> 00:14:52,740
and move right into the
summarizing data lecture.

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I look forward to seeing you there.