Maxwell
Center for Environmental Policy and Administration

Spatial Analyses of Logging Impacts in Amazonia Using Remotely Sensed Data.

Author:Jane M. Read
Date: March 2003
Publication:Photogrammetric Engineering and Remote Sensing, 69(3), pp. 275-282

Performances of selected spatial methods are investigated for characterizing canopy disturbgance in a reduced-impact logging operation in central Amazonia using Landsat-7 ETM+ and Ikonos visible, near-infrared, and normalized difference vegetation index data. Texture, fractal dimension (D), and Moran's I index of spatial autocorrelation were calculated for (1) 10-ha plots representing logged (LF), logged excluding major roads and patios (L), and old-growth (OG) forest; and (2) 335-ha plots representing LF and OG. Ikonos data were sensitive to roads, patios and some logging gaps, whereas ETM+ data were only sensitive to major logging features. The spatial methods were effective at characterizing the different logging feature treatments at both plot sizes; D-TPSA and Moran's I were most sensitive to fine-scale surface details. The spatial methods show potential for monitoring and management of logging activities over landscape scales. The importance of scale, given the ever-increasing choice of remotely sensed data, is emphasized.

Contacts

Jane Read
URL: http://cepa.maxwell.syr.edu/papers/21.html
Center for Environmental Policy and Administration
The Maxwell School, Syracuse University
Revised 06/14/2006 13:06:05