FEMA Floodplain GIS Data Download Automation

Local governments need to work with relevant data from many different sources and stay apprised of changes to that data.  One large municipal government that we serve employs an ArcGIS enterprise geodatabase to store their in-house geographic data as well as select datasets from third parties.  To make floodplain data readily available within their organization, they maintain a copy of FEMA’s National Flood Hazard Layers within their database.  However, their version of that data had become outdated.

Our Approach

At dymaptic, we know well how keeping up with data from disparate sources can be a moving target.  So rather than manually import this data into our client’s database once, only to repeat those steps periodically, we sought to automate the process to ensure this important dataset remains up to date without our client needing to dedicate any manpower toward doing so.

Our Solution

Our deep knowledge of software development and GIS analysis led us to conclude that regularly scheduled execution of Python script would be an ideally-suited solution for our client’s need.  We knew that, without any programming, GIS software could not be configured to take care of this work in an automated fashion.  But we also knew that it would only take a small amount of narrowly targeted code to perform this task and that Esri’s ArcPy Python library offered everything that was needed to programmatically manipulate the municipality’s database.  Moreover, we understand well that Esri provides world-class support for executing and authoring Python scripts, and that maintaining these is within the skillset of many analysts and technicians who work with GIS but are not software developers.

With the solution defined, we implemented a Python script that retrieved the data from the FEMA download location and then leveraged ArcPy to connect to the municipality’s geodatabase, empty the feature class containing the National Flood Hazard data, and populate it with the newly downloaded data.   We then configured Task Scheduler on our client’s infrastructure to execute the script weekly and, in the event the script unexpectedly fails, automatically send an email to the relevant points of contact. 

The Bottom Line

With our knowledgeable and proactive approach, we at dymaptic were able to not only address our client’s immediate need, but to efficiently deliver an automated process to ensure that need is handled continuously into the future.  This right-sized solution has operated maintenance-free since its deployment, effectively removing this task from the always-full plates of the city’s staff.



Local Government Entity


April 2020


Python, ArcPy

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