A Comparison of Pixel- and Object-Based Glacier Classification With Optical Satellite Images

Precise information about the size and spatial distribution of glaciers is needed for many research applications, for example water resources evaluation, determination of glacier specific changes in area and volume, and for calculation of the past and future contribution of glaciers to sea-level change. However, mapping glacier outlines is challenging even under optimal conditions due to time consuming manual corrections of wrongly classified pixels. In the last decades, advantages in computer technologies have led to the development of object-based-image analysis (OBIA), an image classification technique that can be seen as an alternative to the common pixel-based image analysis (PBIA). In this study we compare the performance of OBIA with PBIA for glacier mapping in three test regions with challenging mapping conditions. In both approaches, a ratio image was created to map clean snow and ice while thermal and slope information was used to assist in the identification of debris-covered ice. The mapping results of OBIA have overall a ~ 3% higher quality than PBIA, in particular in the processing of debris-covered glaciers where OBIA has a 12% higher accuracy. The post-processing possibilities in OBIA (e.g., the application of a processing loop and neighborhood analysis) are especially powerful to improve the final classification. This leads also to a reduction of the workload for the manual corrections, which are still required to achieve a sufficient accuracy.

[1]  Josef Strobl,et al.  What’s wrong with pixels? Some recent developments interfacing remote sensing and GIS , 2001 .

[2]  T. Bolch,et al.  A new satellite-derived glacier inventory for western Alaska , 2010, Annals of Glaciology.

[3]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[4]  D. Tiede,et al.  Transferability of OBIA rulesets for IDP camp analysis in DARFUR , 2010 .

[5]  M. K. Arora,et al.  Delineation of debris-covered glacier boundaries using optical and thermal remote sensing data , 2010 .

[6]  Mark Cutler,et al.  Using ASTER satellite and ground-based surface temperature measurements to derive supraglacial debris cover and thickness patterns on Miage Glacier (Mont Blanc Massif, Italy) , 2008 .

[7]  Arno Schäpe,et al.  Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .

[8]  Tobias Bolch,et al.  Glacier fluctuations between 1975 and 2008 in the Greater Himalaya Range of Zanskar, southern Ladakh , 2011 .

[9]  Yong Zhang,et al.  Distribution of debris thickness and its effect on ice melt at Hailuogou glacier, southeastern Tibetan Plateau, using in situ surveys and ASTER imagery , 2011, Journal of Glaciology.

[10]  Mark W. Williams,et al.  Decision Tree and Texture Analysis for Mapping Debris-Covered Glaciers in the Kangchenjunga Area, Eastern Himalaya , 2012, Remote. Sens..

[11]  Nico Mölg,et al.  The first complete inventory of the local glaciers and ice caps on Greenland , 2012 .

[12]  Yves Arnaud,et al.  Decadal changes in glacier parameters in the Cordillera Blanca, Peru, derived from remote sensing , 2008, Journal of Glaciology.

[13]  Andreas Kääb,et al.  Landsat-derived glacier inventory for Jotunheimen, Norway, and deduced glacier changes since the 1930s , 2008 .

[14]  Fan Xia,et al.  Assessing object-based classification: advantages and limitations , 2009 .

[15]  Martin Volk,et al.  The comparison index: A tool for assessing the accuracy of image segmentation , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[16]  F. Paul,et al.  Compilation of a glacier inventory for the western Himalayas from satellite data: methods, challenges, and results , 2012 .

[17]  Jeffrey S. Kargel,et al.  ASTER measurement of supraglacial lakes in the Mount Everest region of the Himalaya , 2002, Annals of Glaciology.

[18]  A. Ohmura,et al.  Mass balance of glaciers and ice caps: Consensus estimates for 1961–2004 , 2006 .

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

[20]  J. Dozier.  Spectral Signature of Alpine Snow Cover from the Landsat Thematic Mapper , 1989 .

[21]  A. Malin Johansson,et al.  Adaptive Classification of Supra-Glacial Lakes on the West Greenland Ice Sheet , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[22]  W. Tangborn,et al.  Mass balance and runoff of the partially debris-covered Langtang Glacier, Nepal , 2000 .

[23]  J. VanLooy,et al.  Glacial changes of five southwest British Columbia icefields, Canada, mid-1980s to 1999 , 2008, Journal of Glaciology.

[24]  Siri Jodha Singh Khalsa,et al.  Challenges and recommendations in mapping of glacier parameters from space: results of the 2008 Global Land Ice Measurements from Space (GLIMS) workshop, Boulder, Colorado, USA , 2009, Annals of Glaciology.

[25]  T. Bolch,et al.  Planimetric and volumetric glacier changes in the Khumbu Himal, Nepal, since 1962 using Corona, Landsat TM and ASTER data , 2008 .

[26]  Aparna Shukla,et al.  Synergistic approach for mapping debris-covered glaciers using optical–thermal remote sensing data with inputs from geomorphometric parameters , 2010 .

[27]  Manfred F. Buchroithner,et al.  Identification of glacier motion and potentially dangerous glacial lakes in the Mt. Everest region/Nepal using spaceborne imagery , 2008 .

[28]  Manfred F. Buchroithner,et al.  Automated delineation of debris-covered glaciers based on ASTER data , 2007 .

[29]  Andreas Kääb,et al.  Combining satellite multispectral image data and a digital elevation model for mapping debris-covered glaciers , 2004 .

[30]  Tobias Bolch,et al.  Mapping of debris-covered glaciers in the Garhwal Himalayas using ASTER DEMs and thermal data , 2011 .

[31]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .

[32]  Tobias Bolch,et al.  Glacier mapping in high mountains using DEMs, Landsat and ASTER data , 2005 .

[33]  Sunil Narumalani,et al.  Utilizing geometric attributes of spatial information to improve digital image classification , 1998 .

[34]  Albert Rango,et al.  Temperature and emissivity separation from multispectral thermal infrared observations , 2002 .

[35]  M. Cutler,et al.  A physically based method for estimating supraglacial debris thickness from thermal band remote-sensing data , 2012, Journal of Glaciology.

[36]  Andreas Kääb,et al.  Perspectives on the production of a glacier inventory from multispectral satellite data in Arctic Canada: Cumberland Peninsula, Baffin Island , 2005, Annals of Glaciology.

[37]  Ute Beyer,et al.  Remote Sensing And Image Interpretation , 2016 .

[38]  B. Bookhagen,et al.  Spatially variable response of Himalayan glaciers to climate change affected by debris cover , 2011 .

[39]  T. Bolch,et al.  Landsat-based inventory of glaciers in western Canada, 1985-2005 , 2010 .

[40]  G. Willhauck,et al.  Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. , 2000 .