TransWikia.com

Redrawing slow in ArcMap

Geographic Information Systems Asked by user18173 on February 8, 2021

I just updated ArcGIS Desktop (ArcMap) to 10.1 and it is so slow. When I load my template mxds they can take 30 plus seconds and if I have to change the view it’s another 30 seconds.

Does anyone have any ideas or methods to speed up the loading and redrawing purpose?

6 Answers

If you are re-using templates and documents from a previous version of ArcGIS, then I've found these often cause slow performance (even if they have been 'updated').

Try copying and pasting your data from the existing template into a new map document and see if that makes a difference.

Answered by user2375955 on February 8, 2021

In addition to @user2375955 answer here are some usefull tips to enhance performance:

  1. Make sure latest service packs are installed
  2. Make sure data is in geodatabase and not file based (e.g. shapefiles)
  3. Only leave layers on in map document that are needed during simple panning and editing tasks
  4. Online basemaps should get faster as they re-cache when users zoom and pan around
  5. Use the Analyze Map tool to figure out what else might be slowing the map performance
  6. When running geoprocessing tools on large datasets you may want to copy your input/output data locally for these tasks

Here are some additional links that may be helpful:

Tips on improving map display performance

ArcGIS Desktop System Requirments

Answered by artwork21 on February 8, 2021

I found the reason and solution:

  • Reason: Basemap layer doesn't have same projection as other layer(s) in one Data Frame! Transformation on the fly takes time.
  • Solution: Use only one projection throughout one Data Frame for all layers!

Answered by RollingDonut on February 8, 2021

When using basemaps from ArcGIS online through the "Add Data" toolbar, always change the map coordinate system to match the basemaps. ArcMap has an easier time projecting your shapefiles on the fly than it does projecting the large raster basemap images.

Answered by Andy Bartell on February 8, 2021

This is the one thing that I always do for large rasters, including image services.

  1. Go to your area of interest
  2. Draw (using draw toolbar) a box around your area of interest
  3. With that box selected, go to data frame properties>Data Frame>Clip options
  4. Choose clip to shape and specify shape as outline of selected graphics (this way only works if you only have that box graphic selected, if you need multiple graphics selected convert the graphic to feature and choose it as shape to clip by)
  5. Choose which layers to clip to, this way it doesn't try and always draw the entire massive raster, just your area and it will function way faster.

Like others have said, matching projections is key as well.

Answered by sparky on February 8, 2021

For raster data, systems with ample RAM capacity will generally benefit* from storing a raster dataset in a RAM virtual drive. The concept is that a sizeable partition of RAM memory acts as a scratch disk or temp workspace. "RAMDisk" and "Ram drive" are good search terms for more information.

Additionally, ArcGIS 10.3+ provides an option to store vector data in an "In-memory Workspace". There are caveats to it implementation including limited use for only geodatabase vector/tablular data.

BE AWARE: the data stored on RAM drives is non-persistent. That data is destroyed if the system is powered down, OS reboots, crashes, etc., and in the case of In-memory Workspaces, when ArcGIS closes. You must essentially load and unload items into memory manually.

RAM drives can also work well with other programs where hard drive transfer speeds are significant bottlenecks. I would suggest the practice if you tend to have >10GB and >50% of unused memory while working (as of 2018).

*I speak from experience but have not benchmarked it quantitatively.

Answered by CrystallineEntity on February 8, 2021

Add your own answers!

Ask a Question

Get help from others!

© 2024 TransWikia.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP