Automating detection of clearcut areas in optical satellite imagery?
For a fantastic way to detect, visualize, and report your findings to the public, check out the Landtrendr (Landsat-based Detection of Trends in Disturbance and Recovery) program from OSU. The Landtrendr program is one of the most exciting recent developments in change detection research. There is very good documentation on the methods, and Landtrendr code is available from GitHub. Here is a link to a NASA video describing the process: Landsat Senses a Disturbance in the Forest.
Landsat 8 and/or Sentinel-2 will likely be the best available (free) data for detecting clearcuts at very large spatial extents. Additionally, there are plenty of data available from previous Landsat missions at Glovis and EarthExplorer.
More traditional approaches include digital processing of multispectral imagery through a variety of methods:
- Contrast thresholding (aka Density Slicing)
- Pixel based classification: ISODATA, Maximum Likelihood, Random Forests
- Object-oriented image anaysis (OBIA): Image Segmentation, Feature extraction
Landtrendr resources:
- Landtrendr code on GitHub
- Instructions for Landtrendr w/ GitHub
- How Landtrendr works
- Papers, Presentations and Other Documents
- An example: Forest harvest in Washington's Cascades Mountains
- Landtrendr and Timesync poster
It is hard to answer this without knowing what data you will be using and what software you have access to. I have done this using Landsat TM/ETM+ satellite imagery with Feature Analyst extension in ArcMap. You can build a signature file, which will allow you automatically classify other images that have a simular spectral signature.
You could use MODIS LAND imagery. The best resolution however is at 250m which may be a little bit coarse for you.
There is several tools provided that can be used such multispectral analysis and everything is free.
http://modis.gsfc.nasa.gov/
You can see Modis near real-time imagery here: http://rapidfire.sci.gsfc.nasa.gov/realtime/ but use these as demo only, you cant do analysis on those images because they are not gridded