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MS - 04 (RS&GIS), Term Project
COMPARISON OF PIXEL BASED & OBJECT BASED
CLASSIFICATION TECHNIQUES FOR GLACIER CHANGE
DETECTION
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 Group Members
 Amir Javaid
 Sher Muhammad
 Chaman Gul
 Supervisor
 Mr. Mirza Muhammad Waqar (IST, Karachi)
Contents
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 Introduction
 Literature Review
 Purpose of the study
 Objectives
 Study Area
 Data Required
 Methodology
 Results
 Conclusion

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Introduction
 Glaciers are important indicators of sustainable life on the globe by
various means and provide good motivation for continuous
monitoring (Bishop et al., 2000; Kargel et al., 2005).
 Glaciers are vital and big resource of freshwater which is used by the
people in the form of agriculture and energy (Knight, 1999).
 Glaciers accumulate in winters and ablate in summers. The normal
accumulation and melting phenomena of the glaciers is affected by the
changing climate which in turn seriously impact human life and
economy.
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 Mountain Glaciers
 These glaciers develop in high mountainous regions, often flowing
out of ice fields that span several peaks or even a mountain range.
The largest mountain glaciers are found in Arctic Canada, Alaska,
the Andes in South America, the Himalayas in Asia, and on
Antarctica.
 Valley Glaciers
 Commonly originating from mountain glaciers or ice fields, these
glaciers spill down valleys, looking much like giant tongues. Valley
glaciers tend to be very long, often flowing down beyond the snow
line, sometimes reaching sea level (study area glaciers are valley
glaciers).
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Glacier Types

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 Piedmont Glaciers
 Piedmont glaciers occur when steep valley glaciers spill into
relatively flat plains, where they spread out into bulb-like lobes. The
Malaspina Glacier in Alaska, covering over 5,000 square kilometers
is one of the most famous examples of this type of glacier.
 Cirque Glaciers
 Cirque Glaciers are named for the bowl-like hollows they occupy,
which are called cirques. Typically, they are found high on
mountainsides and tend to be wide rather than long.
 Hanging Glaciers
 Also called ice aprons, these glaciers cling to steep mountainsides.
Like cirque glaciers, they are wider than they are long. Hanging
glaciers are common in the Alps, where they often cause avalanches
due to the steep inclines they occupy.
Land covers Classified
 Snow
 Precipitation in the form of solid, usually occurs when the temperature
is below 0 Centigrade.
 Debris
 As glaciers creep along the landscape, they often pick up pieces of
rock and transport them as the glacier advances. When the glacier
melts, these pieces of rock are left behind as glacial debris.
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Literature Review
 In January 2012 research published “Pixel-based and
Object-oriented Classification of High Resolution Satellite Images”
by Y. Aruna Suhasini Devi and Dr.I.V.Murali Krishna, they concluded that
 The results show that object-oriented classification can produce satisfying
results when compared with pixel-based method.
 The overall accuracy was 87.5% by object-oriented method, while that of
pixel-based method gave an overall accuracy of 78.1%.
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Literature Review
 In 2011 work published on “COMPARISON OF PIXEL-BASED AND
OBJECT-ORIENTED CLASSIFICATION APPROACHES USING
LANDSAT-7 ETM SPECTRAL BANDS” by M. Oruc he Found that.
 The result of the accuracy assessment shows that object oriented
image analysis attain higher overall accuracy and higher individual
producer’s and user’s accuracy for each classified land cover class.
 In object base method smaller scale increases the dimensionality and
dividing the object into the sub-groups, while the larger scale
combines the multi segments into one.
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Literature Review
 In 2007, paper published on “Study of Glaciers in Northern Pakistan” by
M.Haq, R.Jilani they found
 Area of Batura & Biafo glaciers decreased from 1992-2000
 Decreasing trend of water in Indus river system.
 In 2012 a study on “Climate Change Effect on Glacier Behavior” By
Pandey and Venkataraman
 Glacier will happily advancing in a healthy climate and retreating in
response to a warmer climate.
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 In 2012, a research had been launched on, “Spatiotemporal
distribution of snow in eastern Tibet and the response to climate
change” by Jie Gao and found that
 Duration of the snow-free period was inversely correlated with
elevation" at lower elevation sites the length of the snow-free
season increased, in contrast, at higher elevation, it decreased.
 Analysis of local temperature and precipitation, snow-free period
changes with elevation however median date of the snow free
period is quite stable.
Literature Review

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Literature Review
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 In 2009, worked on “Monitoring of Mountain Glacial Variations in
Northern Pakistan using Landsat and ALOS Data “ by M. Haq, R. Jilani
et. al found that
 Temporal loss in snow cover area of Yazghil, Jutmau and Passu
Glaciers.
 Glaciated areas of the glaciers have decreased near their terminus.
Literature Review
 Bayr et al., 1994; Gratton et al., 1990; Paul et al., 2002; Sidjak and
Wheate, 1999, found that
 Remote Sensing experts have been developing a number of methods to
assess variation in area and volume of the glaciers.
 Several methods such as supervised classification or thresholding of
ratio images are available to delineate the glacier ice.
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Literature Review
 Related study by Benn and Evans, in 1998 stated that
 The ice of glaciers is either clean or debris covered. The source of
debris on the glaciers may vary from place to place. Mainly the
activities which cause debris cover on glaciers are
 a) mass movements from adjacent mountain slopes.
 b) wind-blown dust.
 c) pollutants.
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Objectives
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 Objective of the study was to detect temporal changes and find
suitable classification technique for clean and debris cover ice.
 Monitoring of glaciers is difficult by direct field methods whereas,
Remote sensing offers an efficient technique for glaciological studies.
 Long term study in short period of time.
 To analyze changes and map study area Glaciers.

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Objective of the study
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 Glaciers variation is an important indicator of Climate change.
 Observation of Glaciers retreat and advancement to support Hazards
management.
 For scientific investigation of climate change, the glaciers retreat and
advance study by using satellite data.
Study Area18

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Data and software Required
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Data Type/ Software Specification Source
LANDSAT satellite data dataset (1972-2011) http://earthexplorer.usgs.gov
http://glovis.usgs.gov
DEM Aster 30m Resolution http://earthexplorer.usgs.gov
ERDAS Imagine Image Processing Leica
Arc GIS Mapping ESRI
eCognition Image Processing Definien

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Methodology
Flow Chart
Data Acquisition
Raster: LANDSAT (MSS, TM) Imagery (1972 – 2011), ASTER DEM,
Google Earth
Landsat Data
Layer Stacking
Geometric Correction
Atmospheric Correction
Google EarthDEM
Extraction of Glacier Boundary
Glacier Boundary Overlay
Operation
Subset Image
Supervised
Classification
Define Training Sits
Evaluate Signatures
Classification
Area Estimation
Knowledge Based
Classification
Spectral Signatures
B4 NDSI
Making Decision
Rules
Classification
Area Estimation
Multi -Resolution
image segmentation
Define training sites
NDSI
Making Decision Rules
Classification
Area Estimation
Accuracy Assessment with Reference Classification
Object Oriented
Classification
Output Statistics/ Charts/ Map Layouts
Results and Discussions
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 Due to climate change glaciers vary according to its location and
weather condition.
 Multi-temporal analysis on glacier extent using satellite imagery is an
important and valuable tool to understand climate variability, since
glaciers respond very fast to climate change.
 Variation occurs near terminus of the glaciers
 Valley Glaciers exposed to South retreats and to North are stable or
advances

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Results and Discussions
 Different Classification techniques based on thresholds of optical
images (LANDSAT, or Equivalent) is a valuable tool for multitemporal
analyses of glacier and snow-cover changes.
 Debris-covered ice is difficult to map with different classifications
without manual supervision, since it could be misclassified with
recently deglaciated terrain at high altitude.
 Object based classification is best technique to study temporal changes
of glaciers
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0
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1972 1998 2010 1972 1998 2010 1972 1998 2010
Ice Debris Rocks
Area(sq.km)
Change Detection of Sachen Glacier by Different Classification Techniques
Knowledge Based
Supervised
Object Based
Reference
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0
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1972 1998 2010 1972 1998 2010 1972 1998 2010
Ice Debris Rocks
Area(sq.km)
Change Detection of Rupal Glacier by Different Classification Techniques
Knowledge Based
Supervised
Object Based
Reference

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0
10
20
30
40
50
60
70
80
1978 1998 2011 1978 1998 2011 1978 1998 2011
Ice Debris Rocks
Area(sq.km)
Change Detection of Apsara Glacier by selected Classification Techniques
Knowledge Based
Supervised
Object Based
Reference
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0
10
20
30
40
50
60
70
80
90
1978 1998 2011 1978 1998 2011 1978 1998 2011
Ice Debris Rocks
Area(SqKm)
Change Detection of Singhi Glacier by Different Classification Techniques
Knowledge Based
Supervised
Object Based
Reference

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Accuracy Assessment (%)
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Overall Accuracy
Results and conclusions
 Throughout the study period, it was observed that, about 9% of area is
lost by Rupal and Sachen glaciers whereas, Apsara and Singhi have lost
3% of its snow cover area.
 Object based classification provide best results with comparison of
other classification techniques.
 After object based, Supervised classification provide better results to
classify land-covers.
 Knowledge base is not suitable for mixed pixel and to differentiate
debris and rocks.
 80% to 90% results are matching and having more than 90% overall
accuracy in the study area.
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Recommendations
 Field visit is required for accuracy assessment
 Use and search for freely available software's to do object based
classification
 More strong technological software are required for image processing
 Use object based techniques for land-cover classification rather than
other techniques.
 Knowledge based and objects based is depended on rules so define
these rules carefully
 Familiarization with image is necessary to differentiate land-covers for
better results
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Bibliography
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 Bayr, Klaus J., D. K. Hall, and W. M. Kovalick. "Observations on glaciers
in the eastern Austrian Alps using satellite data." International Journal
of Remote Sensing, vol. 15, no. 9, pp. 1733-1742, 1994.
 Bishop, M. P., Kargel, J. S., Kieffer, H., Machinnin, D. J., Raup., B. And
Shroder, J. F., “Remote Sensing Science and Technology for Studying
Glacier Processes in High Asia”, Annals Glaciology, vol. 31, pp. 164-170,
2000.
 Gratton, D. J., Howarth, P. J. and Marceau, D.J., “Combining DEM
parameters with Landsat MSS and TM imagery in a GIS for mountain
glacier characterization”, IEEE Trans. Geosci. Remote Sens., vol. 28, pp.
766-769, 1990.
 Haeberli, Wilfred, and Martin Hölzle, "Application of inventory data for
estimating characteristics of and regional climate-change effects on
mountain glaciers: a pilot study with the European Alps." Annals
Glaciology, vol. 21, pp. 206-212, 1995.

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Bibliography
 Paul, F., Huggel, C. and Kääb, A. “Combining satellite multispectral
image data and a digital elevation model for mapping of debris-
covered glaciers”, Remote Sensing Envr., vol. 89, pp. 510-518, 2004.
 Sidjak, R. W. And Wheate, R. D., “Glacier mapping of the Illecillewaet
Icefield, British Columbia, Canada, using Landsat TM and digital
elevation data”, International Journal Remote Sens., vol. 20, pp. 273-
284, 1999.
 Jie Gao, “Spatiotemporal distribution of snow in eastern Tibet and the
response to climate change”, 2012.
 M. Haq, R. Jilani, “Study of Glaciers in Northern Pakistan”, 2007 .
 Panday and Venkataraman, “Climate Change Effect on Glacier
Behavior: A Case Study from the Himalayas”, 2012 .
 M. Haq, R. Jilani, Monitoring of Mountain Glacial Variations in Northern
Pakistan using Landsat and ALOS Data” 2009.
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 Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I. and Heynen, M.
2003. “Multi-resolution, object-oriented fuzzy analysis of remote
sensing data for GIS-ready information, ISPRS Journal of
Photogrammetry & Remote Sensing”, 58 (2004) pp. 239-258v.
 S. Shataee, T. Kellenberger, A.A. Darvishsefat, “Forest types
classification using ETM+ data in the north of Iran/ Comparison of
Object-oriented with Pixel-based classification techniques”.
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Bibliography

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Questions - Discussion