If your organization participates in LARIAC, then you probably know that right now you have Early Access to the 2017 imagery (both orthos and obliques) in Pictometry’s online CONNECTExplorer application. Keep in mind the Early Access imagery still has work to be done on it, but at least you can take a look at the new stuff while they are working on it.
One thing you can do is bring some of the ortho imagery into your ArcGIS Desktop environment. Here are the simple steps to do so:
- Login to ConnectExplorer and zoom to the area you are interested in. Make sure to set the imagery date to “Early Access”.
- Next, set your Export Image preferences to output a GeoTIFF and turn off scale image, north pointer, and image date if you want. You do not need a world file for a GeoTIFF.
- Next, bring up the ortho view of the area you want. Make sure to zoom in quite a bit to get the higher resolution.
- In the lower-right corner, click on the export icon and select Export Entire Image.
- Now bring the GeoTIFF into ArcGIS Desktop. Here I have the new 2017 ortho displayed on top of the 2014 ortho.
- Your image might look a little choppy. To fix that, open the layer properties, select the Display tab, and change the “Resample during display” setting to “Bilinear Interpolation”. The “Nearest Neighbor” setting will make your image too choppy looking. Bilinear does a great job smoothing it out.
The GeoTIFF images are actually using geographic coordinates (WGS84), but they reproject very well into State Plane.
This is a very quick way to bring in the new 2017 Early Access imagery into your maps if you need to. As the imagery is cleaned up and worked on to create preliminary images, there will be map services setup for you to consume in your applications. But for now, you can use these steps. Enjoy! -mike
If you have converted your ArcGIS Pro licenses from Online to Concurrent Use, you must upgrade your ArcGIS Licenses Manager to 10.5.1 to use ArcGIS Pro 2.0. There is a GeoNet article on how to do it. Enjoy!
Looking to do a little prediction mapping using logistic regression in ArcGIS and the R environment … I thought so! This stuff makes my head ache, however if you are interested there is a series of videos that will step you through it. Check it out!
Also, check out this article about ESRI and R support.
Back in December 2013 I posted about using the field calculator in ArcMap to calc a field to the third word from another field. Since then, the comments section has been pretty active with questions and answers. I thought it would be a great time to expand on that with other nifty field calculator tricks that I have used over the years.
Split Up Data
This one I use a lot. I have a field that contains parcel number data. In LA County, parcel numbers are 10 digit numbers that represent the assessor book (first 4 numbers), page (next 3 numbers), and lot number (last 3 numbers). I want to split them out into their own fields. Here is how I do it.
Here is an interesting article about using a drawing option in ArcMap called Match To Symbols. By naming a feature attribute with the same symbol name that is in a style, you can quickly symbolize them for feature categories. Click below to read.
This is just like when us old school GIS types used a field to store a symbol number to symbolize our points, lines, and polygons!
Recently I had a need to generate a spider diagram for my map. Spider diagrams, also called desire lines for business scenarios, are a series of rays drawn from a central point to related points. The result shows you the actual area of influence for each central point.
Some good examples would be store locations and customers that visit them, library locations and patrons’ home locations, or in my case fire station locations and incidents they responded to. Continue reading
We currently have a business need to get at parcel center points using parcel numbers. If some of our business systems can communicate using HTTP, I thought using the ArcGIS Server REST API with our map service would be ideal. But first I needed to figure out how to do it. What better way to test the concept by building a Python script! Continue reading