Image segmentation and classification of Landsat Thematic Mapper data using a sampling approach for forest cover assessmentThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

Remote sensing surveys for estimating forest cover may be divided into two approaches: wall-to-wall and sampling. Sampling approaches offer a practical alternative to wall-to-wall mapping, but estimates of forest cover may be affected by the sampling rate of the estimation area. This study aimed to obtain stable estimates of forest cover from satellite data using object-oriented classification at the national level. We investigated a suitable value for the scale parameter in object-oriented classification using eCognition software to identify land cover types, and we evaluated the sampling rate for estimating forest cover at the national level. We used eight different scale parameters when applying object-oriented classification to Landsat data for a set of forty-six 10 km × 10 km sampling tiles centered at each degree of latitude and longitude in Japan. The scale parameter of 10 or less was found suitable for obtaining objects with areas of about 5 ha. Overall accuracy in classification was greater than ...

[1]  Piermaria Corona,et al.  Exploring forest structural complexity by multi-scale segmentation of VHR imagery , 2008 .

[2]  A. C. Seijmonsbergen,et al.  Improved landsat-based forest mapping in steep mountainous terrain , 2003 .

[3]  Frieke Van Coillie,et al.  Feature selection by genetic algorithms in object-based classification of IKONOS imagery for forest mapping in Flanders, Belgium , 2007 .

[4]  W. Kurz,et al.  Accounting of forest carbon sinks and sources under a future climate protocol—factoring out past disturbance and management effects on age–class structure , 2008 .

[5]  T. Dawson,et al.  Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol , 2005 .

[6]  Achard Frederic,et al.  The 2010 Global Forest Resource Assessment Remote Sensing Survey , 2009 .

[7]  P. Strobl,et al.  Pan-European Forest/Non-Forest Mapping with Landsat ETM+ and CORINE Land Cover 2000 Data , 2009 .

[8]  P. Mayaux,et al.  An object-based method for mapping and change analysis in mangrove ecosystems , 2008 .

[9]  J. Vogelmann,et al.  Monitoring forest changes in the southwestern United States using multitemporal Landsat data , 2009 .

[10]  Christian Töttrup,et al.  Improving tropical forest mapping using multi-date Landsat TM data and pre-classification image smoothing , 2004 .

[11]  P. Mayer.  Hot Spot: Forest policy in Europe: achievements of the MCPFE and challenges ahead , 2000 .

[12]  M. Lane,et al.  Converging global indicators for sustainable forest management , 2004 .

[13]  Jacek P. Siry,et al.  Sustainable forest management: global trends and opportunities , 2005 .

[14]  Michael A. Wulder,et al.  Landsat continuity: Issues and opportunities for land cover monitoring , 2008 .

[15]  L. Jansen,et al.  Analysis of land-cover/use change dynamics in Manica Province in Mozambique in a period of transition (1990–2004) , 2008 .

[16]  G. Hay,et al.  An automated object-based approach for the multiscale image segmentation of forest scenes , 2005 .

[17]  E. Tomppo,et al.  Potential for a remote-sensing-aided forest resource survey for the whole globe , 2002 .

[18]  J. Burger,et al.  Expanding site productivity research to sustain non-timber forest functions , 2006 .

[19]  R. Pirard,et al.  A methodology to estimate impacts of domestic policies on deforestation: Compensated Successful Efforts for “avoided deforestation” (REDD) , 2009 .

[20]  Geoffrey J. Hay,et al.  Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation , 2004, Landscape Ecology.

[21]  Stephen V. Stehman,et al.  An evaluation of sampling strategies to improve precision of estimates of gross change in land use and land cover , 2005 .

[22]  T. Schoennagel,et al.  An object-oriented approach to assessing changes in tree cover in the Colorado Front Range 1938–1999 , 2009 .

[23]  S. Stehman,et al.  Statistical sampling to characterize recent United States land-cover change , 2003 .

[24]  Tomoaki Miura,et al.  An assessment of Hawaiian dry forest condition with fine resolution remote sensing , 2008 .

[25]  Ben Gorte,et al.  A method for object-oriented land cover classification combining Landsat TM data and aerial photographs , 2003 .

[26]  Erwin Führer,et al.  Forest functions, ecosystem stability and management , 2000 .

[27]  J. Parviainen,et al.  Protected forests in Europe approaches-harmonising the definitions for international comparison and forest policy making. , 2003, Journal of environmental management.

[28]  Gregory Duveiller,et al.  Deforestation in Central Africa: Estimates at regional, national and landscape levels by advanced processing of systematically-distributed Landsat extracts , 2008 .