R Studio’s Spatial Capabilities going 3D! - Revision history

Smitchs: /* Using a Lattice (Wireframe) */

2018-10-29T23:20:47Z

Using a Lattice (Wireframe)

Timothy Kebbel: /* Creating Composites */

2018-10-09T02:44:49Z

Creating Composites

Timothy Kebbel: /* 3D Mapping in a Myriad of Ways */

2018-10-09T02:43:00Z

3D Mapping in a Myriad of Ways

Timothy Kebbel: /* Conclusion */

2018-10-09T02:42:35Z

Conclusion

Timothy Kebbel: /* Creating Composites */

2018-10-09T02:36:22Z

Creating Composites

Timothy Kebbel: /* Creating 3D interactive maps with the RGL package */

2018-10-09T02:35:15Z

Creating 3D interactive maps with the RGL package

Timothy Kebbel: /* Using image2D and persp3D */

2018-10-09T02:29:42Z

Using image2D and persp3D

Timothy Kebbel: /* Using a Lattice (Wireframe) */

2018-10-09T02:20:29Z

Using a Lattice (Wireframe)

Timothy Kebbel: /* 3D Mapping in a Myriad of Ways */

2018-10-09T02:13:18Z

3D Mapping in a Myriad of Ways

Timothy Kebbel: /* Software Introduction */

2018-10-09T02:10:17Z

Software Introduction

@@ Line 123: / Line 123: @@
 === Using a Lattice (Wireframe) ===
-A straight forward method of creating a 3D image on R can be done using the Lattice package. This creates powerful and elegant graphics with minimum tuning.
+A straightforward method of creating a 3D image on R can be done using the Lattice package. This creates powerful and elegant graphics with minimum tuning.
 At its most basic level this package has the ability to create a 3D scatter plot (using x, y, z) and draw wires across all the points, creating a 3D image.

@@ Line 293: / Line 293: @@
            col = "black", plot = TRUE)
-You can see how we're using '''persp3D''', '''image3D''' and '''contour3D'''.
+You can see how '''persp3D''', '''image3D''' and '''contour3D''' are combined to create this model.
 '''The end result should resemble the following:'''

@@ Line 70: / Line 70: @@
  library(plot3D)
  library(rgl)
 ==== Using Basic Contours ====

@@ Line 328: / Line 328: @@
 == Conclusion ==
-As demonstrated RStudio offers more than just stats but can be used of mapping and 3D modelling.
+As demonstrated, RStudio offers more than just statistical analysis but can also be used to perform mapping and 3D modelling.
-This tutorial is a basic introduction in how to conceptualize and do some basic 3D mapping. Users are encouraged to experiment and explore the software to get a better understanding on the full capabilities that RStudio has to offer.
+This tutorial is a basic introduction on how to conceptualize and do some basic 3D mapping. Users are encouraged to experiment and explore the software to get a better understanding on the full capabilities that RStudio has to offer.
-Using RStudio isn't a replacement for ArcMap, as there are many capabilities that Arc can do much easier and smoother. RStudio has the advantage that it gets users to write code and thinking through steps on how to construct their map/images.
+Using RStudio isn't a replacement for other GIS software, as there are many functions that other software perform better. RStudio has the advantage that it gets users to write code and think through steps required to construct their map/models in a comprehensible manner.

@@ Line 296: / Line 296: @@
 You can see how we're using '''persp3D''', '''image3D''' and '''contour3D'''.
-'''The end result should look like this.'''
+'''The end result should resemble the following:'''
 [[file:CompositesExample.png]]
@@ Line 324: / Line 324: @@
-Try changing some of the parameters to produce a different plot.
+Try changing some of the parameters to produce a modified plot.
 == Conclusion ==

@@ Line 212: / Line 212: @@
 === Creating 3D interactive maps with the RGL package  ===
-Utilizing the '''rgl package''' will allow you to create 3D maps that can be rotated 360 degrees outside of the RStudio.
+Utilizing the '''rgl package''' will allow you to create 3D maps that can be rotated 360 degrees independent of RStudios' GUI.
-RStudio doesn't have the interface to move the map's perspective on the fly (with your mouse) so it creates an external window to display the model.
+RStudio doesn't have the capability to move the map's perspective in real time, so it creates an external window to display the model.
+The following script creates a 3D model of Mount Eden:
-A basic script that looks at the '''volcano''' dataset looks like this:
  #Create a 3D model of Mount Eden
@@ Line 236: / Line 236: @@
  rgl.surface(x, y, z, color = col, alpha = 1, back = "lines")
-This code utilizes the '''volcano''' dataset but exaggerates the z values in order to produce a model that better demonstrates the change in elevation.
+This code utilizes the '''volcano''' dataset and exaggerates the z values in order to produce a model that better demonstrates the variance in elevation.
 Running this code will generate a 3D model of the selected AOI within another window.
@@ Line 242: / Line 242: @@
 This model can be manipulated by clicking and dragging the cursor across the screen.
-From above you can see a color gradient shifting from low on the periphery and high near the peak. Looking from the underside you can see how the 'mountain' was rendered by R.
+You can see the color gradient shifting from low on the periphery to high near the peak. From observing the underside of the model you can see how the 'mountain' was rendered by R.
 [[File:3dmodel.gif]]
@@ Line 264: / Line 264: @@
 [[File:3dand2d.gif]]
-If you look closely you can see how the 2D images corresponds with the changes in elevation. The brighter areas representing areas with higher elevation than those along the edge.
+If you look closely you can see how the 2D images corresponds with the changes in elevation. The brighter areas represent areas with higher elevation than those along the edge.
-You can now create 3D images that can be interacted with outside of RStudio.
 === Creating Composites  ===

@@ Line 161: / Line 161: @@
 === Using image2D and  persp3D ===
-Using the '''image2D''' and '''persp3D''' extension from R's '''image''' and '''persp''' function you can create 3D segments of maps, but you won't be using the scatter plot method as seen in utilizing a wireframe. First a 2D image will get generated using a default dataset and then you'll create a 3D segment from this 2D image.
+Using the '''image2D''' and '''persp3D''' extension from R's '''image''' and '''persp''' function you can create 3D segments of maps, but you won't be using the scatter plot method seen previously in the wireframe function. First a 2D image will be generated using a default dataset, a 3D segment will then be created from this 2D image.
-Ensure that you have the necessary packages installed. Make sure you have '''plot3D''' and '''misc3d''' as they'll allow you to plot with multi-dimensional data. You can click on them in the package pane (bottom left) to get a better description.
+Ensure that you have the necessary packages installed. Make sure you have '''plot3D''' and '''misc3d''' as they will allow you to plot with multi-dimensional data. You can click on them in the package pane (bottom left) to get a better description of their capabilities.
-Let's create our basic map. For this you'll use the hypsometry data that R has built in. '''Hypsometry''' is the measurement of land elevation relative to sea level. So along that line of thought the 2D image you'll create will illustrate areas above and below sea level.
+For this map you will use the hypsometry dataset that is pre-loaded within R Studio. '''Hypsometry''' is the measurement of land elevation relative to sea level. The 2D image will be created will illustrate areas above and below sea level.
  #Create a 2 dimensional map of land elevation
@@ Line 174: / Line 174: @@
  rect(-50, 10, -20, 40, lwd = 3)
-Just like creating a graph you set the parameters and labels as you see fit. The Hypsometry data is first, then we set the axis labels,explained how the contours would be set, gave it a title and a simple bar explaining the differences in the colors.
+Similar to creating a graph the user has the ability to set the parameters and labels as they see fit. The Hypsometry data is assigned as the input data, then we set the axis labels, determine how the contours will be set, finally we give it a title and a key to explain the color gradient.
 This results in the following:
@@ Line 180: / Line 180: @@
 [[File:Hypsometrydataset.PNG|frame|left|none|2D map depicting land elevation, with designated AOI]]
 <br clear=all>
-This should look a bit familiar as most elevation maps have a similar color gradient. Try googling some of the areas that are red and see if they correspond with geographical phenomenon.
+This should look familiar as most elevation maps have a similar color gradient. Try googling some of the areas that are red and see if they correspond with geographical phenomenon.
+From here we'll create a 3D image using AOI within the Hypsometric map '''(the black square)'''. Creating a 3D image of all the globe would use up a lot of visual space and sacrifices detail for coverage.
-From here we'll create a 3D image using a segment of the Hypsometric data '''(the black square)'''. Creating a 3D image of all the globe would use up a lot of visual space and you'd be sacrificing detail for coverage.
  #Create the Area of Interest within the bounds of the previously stated rectangle
  #
@@ Line 201: / Line 202: @@
 Looking at the '''alongLat''' & '''alongLong''' variables you can see that '''hypsometry$_''' coincide with the Latitude and Longitude columns of '''Hypsometry'''.
+These first two lines are used to store the AOI within variables, which will be used within the '''persp3D( )''' function.
-From this you're segmenting your AOI from the larger 2D image.
-The variable '''Seabed''' becomes the upper and lower limits that will be depicted on the scale.
+The variable '''Seabed''' becomes the upper and lower limits of elevation that will be depicted on the scale.
 [[file:LookingBelowtheSea.png]]
-This 3D image illustrates a ridge/trench that runs along the sea. Where else could you apply this kind of 3D image?
+This 3D image illustrates a ridge/trench that runs along the sea.
 === Creating 3D interactive maps with the RGL package  ===

@@ Line 126: / Line 126: @@
 A straight forward method of creating a 3D image on R can be done using the Lattice package. This creates powerful and elegant graphics with minimum tuning.
-At its most basic level what this package will do is create a 3D scatter plot (using x, y, z) and draw wires across all the points creating a 3D image.
+At its most basic level this package has the ability to create a 3D scatter plot (using x, y, z) and draw wires across all the points, creating a 3D image.
 [[file:DOTS.png]]   [[file:DRAPPED.png]]
-In the context of mapping it involves using variables like the latitude, longitude and elevation to create a 3D image, akin to a '''Digital Elevation Model'''. Within this tutorial we are going to use a stored dataset '''volcano''' to illustrate the lattice method.
+In the context of mapping this involves using variables like the latitude, longitude, and elevation to create a 3D image, akin to a '''Digital Elevation Model'''. Within this tutorial we are going to use a stored dataset '''volcano''' to illustrate the lattice method.
-Before writing any code the '''lattice package''' needs to be installed.
+Before writing any code, the '''lattice package''' needs to be installed.
-Clicking on the '''Tools''' tab and clicking '''Install Packages''' brings up the Install Packages Window. In the blank '''Packages''' box type in the desired package and click '''Install'''.
+Clicking on the '''Tools''' tab, then clicking '''Install Packages''' will bring up the Install Packages Window. In the blank '''Packages''' box, type in the desired package and click '''Install'''.
-This will take a few seconds to install but will allow provide full access to the functions within the package.
+This will take a few seconds to install but will allow provide full access to the functions.
-A metaphor for what you're doing by installing this package is that you've taken the lattice tool out of your 'tool shed' (R's various packages) and put them on your 'tool belt' for access.
 Here's what the code looks like.
@@ Line 149: / Line 147: @@
+The first two lines bring in the '''volcano''' dataset and assign the data into a matrix called '''cano'''.
+The last line will create the fictional scatter plot and drape wires across the points to create the 3D image.
-The '''library'''(lattice); line is telling R that I'll be using some of the lattice tools from my 'belt' in this script.
-The following two lines involve bring in the '''volcano''' dataset and putting the data into a matrix called '''cano'''.
-The last line will do the work of creating the fictional scatter plot (you won't see it) and drap wires across the points to create the 3D imaged.
-The parameters that are set will use an unclassified matrix called '''cano''', shading the wires, telling it the aspect you want to look at it from, whether there's a title, labeling the 3 axes, and how you want to scales depicted.
+The parameters that are set will use an unclassified matrix called '''cano''', shade the wires, tell it the aspect angle, determine a title, label the axis, and determine how the scales are depicted.
 This code will create the following image:
@@ Line 162: / Line 157: @@
 [[file:Ssmounteden.PNG]]
-Try other parameters and see what happens. Maybe change '''shade = F''' or '''draw = TRUE'''? Changing the '''aspect''' will also change the image.
+Try other parameters and see what happens. Maybe change '''shade = F''' or '''draw = TRUE'''? Changing the '''aspect''' will also change orientation of the image.
 === Using image2D and  persp3D ===

@@ Line 44: / Line 44: @@
 == 3D Mapping in a Myriad of Ways ==
-Before doing any coding in R you'll need to think about what 'tools' you'll need. What packages do you need to install to run any specialized functions?
+Before doing any coding in R you'll need to think about what 'tools' you'll need.
 Through this tutorial we'll focus on four specific packages;
@@ Line 56: / Line 56: @@
 '''lattice''' for more info look here -> https://cran.r-project.org/web/packages/lattice/lattice.pdf
-The following code will install each and 'unpack' them for use.
+The following code will install each and unpack them for use.
  #You can click on the packages in the package pane (bottom right) for a full description of their functions
@@ Line 71: / Line 71: @@
  library(rgl)
-The following examples will also illustrate how to install '''packages''' through the install window.
 ==== Using Basic Contours ====
-The easiest way of map visualization is the use of a simple contour map.
+The easiest way of map visualization is a contour map.
 Install the '''plotly''' package and load it using the command '''library(plotly)'''.
@@ Line 97: / Line 96: @@
 By utilizing the '''plot3D''' package we can take both of these contour map representations and merge them into a single map that demonstrates the elevation with a color gradient and contour lines simultaneously.
-We start by installing the '''plot3D''' package and installing it
+We start by installing the '''plot3D''' package
  #install the plot3D package
  install.packages("plot3D")
@@ Line 121: / Line 120: @@
-This example demonstrates the variability and flexibility of R Studio with respect to visualizing topographic data.
+This example demonstrates the flexibility of R Studio with respect to visualizing topographic data.
 === Using a Lattice (Wireframe) ===

@@ Line 27: / Line 27: @@
-This is an open software program that creates a user-friendly graphic user interface for accessing the R statistical analysis and scripting language.  R is often used for data analysis, statistics and graphing of very large datasets. It also has the ability to interface with the SAGA spatial analysis program, through the 69 modules shown below; users are able to use spatial data and manipulate and perform geoprocessing via special commands within this software. The more you explore and use the commands the more comfortable you will get. Initially everyone may face difficulty, however, if the basics are understood well, it eases the application of major geoprocessing tools. R studio is known for handling large datasets with efficiency and helps in optimizing results quicker in order to perform them multiple times at a time without the needs to run through the steps again and again. Also, R not only processes data but if users may want to visualize their spatial output of their data, R has a package called sp which has that feature.
+R Studio is an open software program that creates a user-friendly graphic interface for accessing the R statistical analysis and scripting language. R is often used for data analysis, statistics and graphing of very large datasets. It is also capable of interfacing with the SAGA spatial analysis program through the 69 modules shown below. Users are able to use spatial data and manipulate and perform geoprocessing via special commands within this software. Initially everyone may face difficulty utilizing the R language, however, if the basics are understood well, it eases the application of major geoprocessing tools. R studio is known for handling large datasets with efficiency, and helps in optimizing results quickly in order to perform them multiple times without the need to reiterate. R not only processes data, but can also visualize spatial output through the use of a package called sp.
 To download RStudio click the link --> https://www.rstudio.com/products/rstudio/download/
@@ Line 33: / Line 33: @@
 There's a great introduction on the R Studio layout and configuration found on [[ User: JuliaRiddick | Julia Riddick]]'s '''R Studio's Spatial Capabilities''' at http://gracilis.carleton.ca/CUOSGwiki/index.php/R_Studio%27s_Spatial_Capabilities, so take a look and become familiar with the software.
-Throughout this tutorial we will use datasets that are pre-installed in R, saving users time in tracking down data as well and to ensure that users can follow along with the tutorial.
+Throughout this tutorial we will use datasets that are pre-installed in R, saving time in tracking down data as well and to ensure that users can follow along with the tutorial.
-R studio has a great '''volcano''' dataset that represents Maunga Whau (Mt Eden). This mountain is one of about 50 volcanos in the Auckland volcanic field. This data set represents the topographic information for Maunga Whau on a
+R studio has a great '''volcano''' dataset that represents Maunga Whau (Mt Eden). This mountain is one of 50 volcanos in the Auckland volcanic field. This data set represents the topographic information for Maunga Whau on a 10x10 meter grid.
-x10 meter grid.
 [[file:MountEden.jpg|frame|left|none|Photograph of Mount Eden, Source: ''Antonia Baker'']]
 <br clear=all>
-The scripts that this tutorial will be using will be straight forward and simple, users will need to do some thinking on their own to wrap their heads around how to apply these techniques to different datasets.
+The scripts within this tutorial are straightforward and simple, so users will be allowed some creative freedom in how they wish to apply these functions.
 == 3D Mapping in a Myriad of Ways ==