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Fire Insurance Maps at the Library of Congress: A Resource Guide

Downloading Sanborn Maps

Maps that have been digitized and placed on the Library's website are in the public domain and can be downloaded directly to a computer or flash drive. If you look underneath the thumbnail image in the individual catalog record, you will see a download menu with various scans available to download at no cost. The TIFF file is the highest resolution scan.

Depending on the age of your computer and default programs, it can be difficult to download TIFF files without a TIFF viewer. A search of the internet will provide links to many free TIFF viewers. The Library of Congress uses Irfanview on its computers for this purpose.

Downloading in Bulk

The Geography and Map Division is beginning a series of Jupyter Notebooks exploring how to computationally access, retrieve, and analyze cartographic materials in the digitized collections. These notebooks include instructions and demonstration Python code that lead you through the process of downloading and analyzing images and metadata in bulk from the Library's website, specifically geared towards maps. These notebooks are designed to be downloaded to your computer and opened with Jupyter Notebook, an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

GitHub Access to the Jupyter Notebooks

The first two of the notebooks are now available on the Library’s GitHub page External:

  1. Querying and downloading cartographic material from
  2. Analyzing and visualizing cartographic metadata from

These notebooks use the Sanborn Fire Insurance Map collection to show you how to do things like download map image files in bulk.

Using the Notebooks

If this is your first time using Jupyter Notebooks, there are many online tutorials to help you install the software and get started, including instructions for installing Jupyter via Anaconda. To download the two Jupyter notebooks, head to the Library’s GitHub page External and download the individual files. Or, if you are comfortable with it, you can clone the repository.

Inside that repository and at LC for Robots, you will find other notebook tutorials and example code. In particular, be sure to check out accessing images for image analysis External (which the maps notebooks build on) and extracting location data from the API for geovisualization External.