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The National Inventory and Monitoring Applications Center (NIMAC) is a program with national scope, based at the headquarters office of the US Forest Service’s Northern Research Station in Newtown Square, Pennsylvania.

Recommended Resources

Webb, Jeremy; Brewer, C. Kenneth; Daniels, Nicholas; Maderia, Chris; Hamilton, Randy; Finco, Mark; Megown, Kevin A.; Lister, Andrew J. 2012. Image-based change estimation for land cover and land use monitoring.


Lister, Tonya; Lister, Andrew; Alexander, Eunice. 2009. Estimating Fine-Scale Land Use Change Dynamics Using An Expedient Photointerpretation-Based Method.

Rapid Photo Interpretation Tool

Andrew Lister, Thomas Weber and James Westfall

[image:] Example subplot

Large area resource assessments with remotely sensed data are conducted in a variety of ways, however, these methods are often flawed. Most of these problems can be mitigated by creating new classifications with multitemporal high resolution imagery, LiDAR and object based image analysis procedures, but these advanced products require high levels of skill, specialized software, and significant hardware investments. Ocular photointerpretation (PI) from high resolution aerial imagery is a direct observation approach that is a cost-effective and accurate way to conduct large area resource assessments. The primary advantages of ocular PI are that the technology is generally accessible to resource agencies that use GIS, it is easily teachable, land use or cover classes can be chosen to meet detailed user needs, and imagery is often served freely over the internet and updated frequently. 

To increase ocular PI efficiency, an automated method was developed whereby an ArcGIS tool is used to extract a subset of imagery. In other words “snapshots” of imagery are generated, with each image centered on a point. These snapshots are then stored locally and displayed using a Microsoft Access form (available for download below). This preassembling of images allows users to move through each image quickly and efficiently while assigning a land use category. The form was designed to minimize the number of mouse clicks, wait time for images to load, and data entry time. Internet is not required to use this form and all the images are self-contained. The visual basic code behind this template can be edited, the names of the buttons can be changed, and the types of information that the buttons load into the form can be changed. Overall, this form allows for an efficient photointerpretation-based change detection method that automates the work of gathering and loading images. Please contact us with any questions.   

Video Tutorial

More Information

Downloads and Documentation
Rapid Photointerpretation Tool Template zip file 48 kb
Land use change monitoring in Maryland using a probabilistic sample
and rapid photointerpretation
Python script txt  


Last Modified: February 22, 2017