The Land-cover Change Mapper (LCM) and its application to timber harvest monitoring in Western Canada.

We introduce an automated change detection and delineation tool for remote sensing images: the Land-cover Change Mapper (LCM). LCM rapidly generates a polygon vector layer (shapefile) of regions deemed to have undergone significant change in land-cover. In its simplest usage, LCM requires two single band or multi-band co-registered images of the same scene acquired at different dates, and as the only user-defined parameter, the minimum size for change regions. The main advantages of this tool are that (a) it is fully unsupervised, (b) it is exceptionally fast, (c) it is robust to geometric misregistration errors and variations in illumination, and (d) it produces visually pleasing outlines that resemble those obtained through manual digitization. We describe how the tool works, illustrate its application to monitoring forest clear-cuts on a 1,000 km 2 area in Western Canada using SPOT imagery, compare it to a commercial tool, and report on its thematic and spatial accuracy. A freeware LCM version is available on the Internet.

[1]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[2]  Ashbindu Singh,et al.  Review Article Digital change detection techniques using remotely-sensed data , 1989 .

[3]  Peng Gong,et al.  Registration-noise reduction in difference images for change detection , 1992 .

[4]  Michael F. Goodchild,et al.  Integrating GIS and remote sensing for vegetation analysis and modeling: methodological issues , 1994 .

[5]  Xiaoping Yuan,et al.  COMPUTER-ASSISTED PHOTOINTERPRETATION AIDS TO FOREST INVENTORY MAPPING: SOME POSSIBLE APPROACHES , 1999 .

[6]  G. Hay,et al.  A Multiscale Object-Specific Approach to Digital Change Detection , 2003 .

[7]  D. Flanders,et al.  Preliminary evaluation of eCognition object-based software for cut block delineation and feature extraction , 2003 .

[8]  Lorenzo Bruzzone,et al.  An adaptive approach to reducing registration noise effects in unsupervised change detection , 2003, IEEE Trans. Geosci. Remote. Sens..

[9]  Volker Walter,et al.  Object-based classification of remote sensing data for change detection , 2004 .

[10]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[11]  D. Lu,et al.  Change detection techniques , 2004 .

[12]  Pol Coppin,et al.  Review ArticleDigital change detection methods in ecosystem monitoring: a review , 2004 .

[13]  John R. Jensen,et al.  A change detection model based on neighborhood correlation image analysis and decision tree classification , 2005 .

[14]  T. Blaschke TOWARDS A FRAMEWORK FOR CHANGE DETECTION BASED ON IMAGE OBJECTS , 2005 .

[15]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[16]  Patrick Bogaert,et al.  Forest change detection by statistical object-based method , 2006 .

[17]  G. Hay,et al.  Size-constrained Region Merging (SCRM): An Automated Delineation Tool for Assisted Photointerpretation , 2008 .

[18]  G. Hay,et al.  Pixels to objects to information: Spatial context to aid in forest characterization with remote sensing , 2008 .

[19]  John R. Jensen,et al.  Object‐based change detection using correlation image analysis and image segmentation , 2008 .

[20]  Michael E. Hodgson,et al.  Optimizing the binary discriminant function in change detection applications , 2008 .

[21]  R. Guthrie,et al.  Denudation and landslides in coastal mountain watersheds: 10,000 years of erosion , 2008 .