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Berkeley Indices Trajectory Extractor (BITE)

version 1.13 (1.23 MB) by Yanlei
BITE derives disturbance maps from satellite image stacks


Updated 30 Apr 2015

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Berkeley Indices Trajectory Extractor (BITE) is an algorithm to derive disturbance maps from multi-temporal remote sensing image stacks. Particularly, BITE can distinguish persistent forest, slow-onset disturbances and rapid-onset disturbances. Slow-onset disturbances are usually caused by diseases and insects, which result in forest loss over a long period. Rapid-onset disturbances are abrupt loss of canopies that are usually caused by clearcut, logging, prescribed fires, wildfires and other natural disasters. BITE features a distinctive processing flow that requires almost no parameters for tuning but a training dataset to fit statistical learning models. The models are used to predict the features extracted from the trajectories, which are derived from segmenting time-series for multiple spectral indices. For each spectral index, a disturbance map can be derived, and by integrating these maps a final integrated disturbance map is produced via a plurality voting, thus is more accurate than any disturbance map of a single spectral index. BITE algorithm was tested to be resistant to data gaps (clouds/shadow/snow) and noises (haze, temporal fluctuation, minor misregistrations).
The algorithm is introduced in,
Chen, Y., Liang, L., Hawbaker, T.J., Gong, P., Biging, G.S., Zhu, Z., BITE: An algorithm for mapping slow-onset forest disturbances caused by mountain pine beetles with Landsat image stacks. Remote Sensing of Environment, submitted.
Read BITE_UserGuideV1.1.pdf for instructions.

Cite As

Yanlei (2020). Berkeley Indices Trajectory Extractor (BITE) (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (1)



Will now automatically update forest mask to include nodata pixels in Module_Trajectory.m.

Add a space after '=' for some char strings in writeenvi.m.

Fixed a bug that may cause mismatched observations in Module_FittingModels.m.

Fixed a description. The input images for Module_TimeSeriesStack.m end with 'c' instead of 's'.

Fixed an error that can be caused by 0 division when calculating R-squared in Segmentation.m.

Fixed an error in Function Module_TimeSeriesStack.m of mismatched image size.

Fixed an error in Function Module_Subsetimg(). It should work as intended now.
A potential conflict between multithreading and undefined variables was fixed.

Add models folder for the default CART and SVM models. Add LIBSVM folder for the LIBSVM files for matlab.

Changed the Screenshot.

Update the User Guide BITE_UserGuideV1.pdf and convert into pdf.

Updates some introductions in the functions and guides.



MATLAB Release Compatibility
Created with R2013a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired by: Label connected components in 2-D array