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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprsarchives-XL-8-943-2014</article-id>
<title-group>
<article-title>Land Use and Land Cover Classification from ETM Sensor Data : A Case Study from Tamakoshi River Basin of Nepal</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shrestha</surname>
<given-names>U. S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>PK Campus, Tribhuwan University, Kathmandu, Nepal</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>11</month>
<year>2014</year>
</pub-date>
<volume>XL-8</volume>
<fpage>943</fpage>
<lpage>948</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2014 U. S. Shrestha</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-8/943/2014/isprs-archives-XL-8-943-2014.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-8/943/2014/isprs-archives-XL-8-943-2014.pdf</self-uri>
<abstract>
<p>The mountain watershed of Nepal is highly rugged, inaccessible and difficult for
acquiring field data. The application of ETM sensor Data Sat satellite image of 30 meter pixel
resolutions has been used for land use and land cover classification of Tamakoshi River Basin (TRB)
of Nepal. The paper tries to examine the strength of image classification methods in derivation of land
use and land classification. Supervised digital image classification techniques was used for
examination the thematic classification. Field verification, Google earth image, aerial photographs,
topographical sheet and GPS locations were used for land use and land cover type classification,
selecting training samples and assessing accuracy of classification results. Six major land use and land
cover types: forest land, water bodies, bush/grass land, barren land, snow land and agricultural land
was extracted using the method. Moreover, there is spatial variation of statistics of classified land uses
and land cover types depending upon the classification methods.
&lt;br&gt;&lt;br&gt;
The image data revealed that the major portion of the surface area is covered by unclassified bush and
grass land covering 34.62 per cent followed by barren land (28 per cent). The knowledge derived from
supervised classification was applied for the study. The result based on the field survey of the area
during July 2014 also verifies the same result. So image classification is found more reliable in land
use and land cover classification of mountain watershed of Nepal.</p>
</abstract>
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