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About Land Records / GIS

Land Records / GIS is responsible for maintaining property information used in public inquiry and legal research. Land Records / GIS uses public documents to create and maintain the official index of property ownership in the County. Land Records / GIS handles the geographic information systems for Orange County.

With the Punic Wars Content pack, Rome has a unique set of 9 mission trees primarily focusing on its conquests during the time period, including the unification of Italy, the struggle with Carthage over Africa and the Western Mediterranean, conquering the tribes of Gaul and Hispania, and incursions into the east to gain control of the Hellenistic states of Greece and Asia. Creative plots is a flatworld separated into 64×64 plots for people to claim as their own to work on Server projects, Arenas for mini-games, Personal projects, test redstone, test ship designs etc! Plots can be merged into mega plots, friends added and plenty of settings, with Worldedit and VoxelSniper being limited to each plot or megaplot!

Addressing

Survival of unowned cats was considered to be density-dependent with respect to the carrying capacity of free-roaming and feral cats (Fig 5). The carrying capacity, and hence strength of density-dependent survival, of unowned cats is thought to be dependent upon food availability. Eco Update 9.1 releases on November 3rd! Wed, 28 October 2020 We’ve got a launch date for Eco 9.1, coming November 3rd! With Eco 9 a year in development, it came with a long list of new features. 1.7.x 1.8.x Raiding Cannons Plots Plotworld Creative Tnt Build Redstone Google Ads TOPG.ORG 2020 - 2021 Trademarks are the property of their respective owners, all sites and servers are added by users.

Addresses are obtained by contacting the addressing authority for each address jurisdiction. In the County jurisdiction your new address is assigned when you apply for a building permit or when your road name changes. You can call the following numbers to obtain information on new or existing addresses:

Orange County: 919-245-2100
Carrboro: 919-918-7328
Chapel Hill: 919-969-5089
Hillsborough: 919-296-9471
Mebane: 919-563-9990

Road Naming and Addressing Ordinance Information
Road Naming and Addressing Ordinance (PDF)

Interactive Services

Property Ownership and History Inquiry (PIN App): Search tool to provide ownership information for properties. Tool also includes history of property and ownership. Can be used in conjunction with Register of Deeds Document Inquiry to conduct detailed research on property and history. Formerly known as Property Information Search Page.
Orange County Interactive GIS Mapping Systems: Interactive mapping system with options for viewing all of Orange County or zooming down to specific parcels.
Orange Address Database Search: The address search offers search by PIN, TMBL, Street Name (with a selection list of all Orange County streets), or Place (with a selection list of subdivisions, condominiums, and common area names).
Cross Reference Tool for TMBL and Tract: This tool is provided to assist the public in finding Parcel Identification Numbers (PIN) based on TMBLs or Tracts. Orange County uses the PIN as the official tracking mechanism for all parcels. As of October 1, 2010, Orange County no longer assigns TMBL or Tract numbers to parcels.
Download GIS Data: Download Orange County GIS data files and aerial photos.
Search Address Related Information (ARIES): Search for services and public information related to your address (ARIES).

There are a variety of ways to combine ggplot2 plots with a single shared axis. However, things can get tricky if you want a lot of control over all plot elements.

I demonstrate four different approaches for this:
1. Using facets, which is built in to ggplot2 but doesn’t allow much control over the non-shared axes.
2. Using package cowplot, which has a lot of nice features but the plot spacing doesn’t play well with a single shared axis.
3. Using package egg.
4. Using package patchwork.

The last two packages allow nice spacing for plots with a shared axis.

Using egg to combine plots
Using patchwork to combine plots

I’ll be plotting with ggplot2, reshaping with tidyr, and combining plots with packages egg and patchwork.

I’ll also be using package cowplot version 0.9.4 to combine individual plots into one, but will use the package functions via cowplot:: instead of loading the package. (I believe the next version of cowplot will not be so opinionated about the theme.)

Here’s the scenario: we have one response variable (resp) that we want to plot against three other variables and combine them into a single “small multiples” plot.

I’ll call the three variables elev, grad, and slp. You’ll note that I created these variables to have very different scales.

One good option when we want to make a similar plot for different groups (in this case, different variables) is to use faceting to make different panels within the same plot.

Since the three variables are currently in separate columns we’ll need to reshape the dataset prior to plotting. I’ll use gather() from tidyr for this.

Now I can use facet_wrap() to make a separate scatterplot of resp vs each variable. The argument scales = 'free_x' allows the x axis scales to differ for each variable but leaves a single y axis.

I can use the facet strips to give the appearance of axis labels, as shown in this Stack Overflow answer.

That’s a pretty nice plot to start with. However, controlling the axis breaks in the individual panels can be complicated, which is something we’d commonly want to do.

In that case, it may make more sense to create separate plots and then combine them into a small multiples plot with an add-on package.

Package cowplot is a really nice package for combining plots, and has lots of bells and whistles along with some pretty thorough vignettes.

The first step is to make each of the three plots separately. If doing lots of these we’d want to use some sort of loop to make a list of plots as I’ve demonstrated previously. Today I’m going to make the three plots manually.

The function plot_grid() in cowplot is for combining plots. To make a single row of plots I use nrow = 1.

The labels argument puts separate labels on each panel for captioning.

But we want a single shared y axis, not a separate y axis on each plot. I’ll remake the combined plot, this time removing the y axis elements from all but the first plot.

This makes panels different sizes, though, which isn’t ideal. To have all the plots the same width I need to align them vertically with align = 'v'.

But, unfortunately, this puts the axis space back between the plots to make them all the same width. It turns out that cowplot isn’t really made for plots with a single shared axis. The cowplot package author points us to package egg for this in this Stack Overflow answer.

Package egg is another nice alternative for combining plots into a small multiples plot. The function in this package for combining plots is called ggarrange().

Here are the three plots again.

The ggarrange() function has an nrow argument so I can keep the plots in a single row.

The panel spacing is automagically the same here after I remove the y axis elements, and things look pretty nice right out of the box.

We can bring panes closer by removing some of the space around the plot margins with the plot.margin in theme(). I’ll set the spacing for right margin of the first plot, both left and right margins of the second, and the left margin of the third.

Adding plot labels with tag_facet()

You’ll see there is a labels argument in ggarrange() documentation, but it didn’t work well for me out of the box with only one plot with a y axis. However, we can get tricky with egg::tag_facet() if we add a facet strip to each of the individual plots.

It’d make sense to build these plots outside of ggarrange() and then add the tags and combine them instead of nesting everything like I did here, since the code is now a little hard to follow.

We might want to add a right y axis to the right-most plot. In this case we’d want to change the axis ticks length to 0 via theme() elements. This can be done separately per axis in the development version of ggplot2, and will be included in version 3.2.0.

The patchwork package is another one that is great for combining plots, and is now on CRAN (as of December 2019) 🎉. It has nice vignettes here to help you get started.

In patchwork the + operator is used to add plots together. Here’s an example, combining my three original plots.

If we give the resulting combined plot a name, we can remove the titles from the last two subplots using double-bracket indexing. (Of course, I also could have built the plots how I wanted them in the first place. 😜)

The result has nice spacing for a single, shared y axis. Margins can be controlled the same was as in the egg example above.

Adding plots labels with plot_annotation()

There are many annotation options in patchwork. I’ll focus on adding tags, but see the annotation vignette.