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Author A. K. Chaudhary |
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Add the result to your basket Make a suggestion Refine your search Apply to external sourcesForest type mapping using object-based classification method in Kapilvastu district, Nepal / A. K. Chaudhary in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal, 26: 1 (2016)
Title : Forest type mapping using object-based classification method in Kapilvastu district, Nepal Material Type: printed text Authors: A. K. Chaudhary, Author ; A. K. Acharya, Author ; S. Khanal, Author Publication Date: 2016 Article on page: 38-44 p. Languages : English (eng) Keywords: Landsat, machine learning algorithm, object-based classification Abstract: In the recent years, object-based image analysis (OBIA) approach has emerged with
an attempt to overcome limitations inherited in conventional pixel-based approaches.
OBIA was performed using Landsat 8 image to map the forest types in Kapilvastu
district of Nepal. Systematic sampling design was adopted to establish sample points
in the field, and 70% samples were used for classification and 30% samples for
accuracy assessment. Landsat image was pre-processed, and the slope and aspect
derived from the ASTER DEM were used as additional predictors for classification.
Segmentation was done using eCognition v8.0 with the scale parameter of 20, ratios
of 0.1 and 0.9 for shape and color, respectively. Classification and Regression Tree
(CART) and nearest neighbor classifier (k-NN) methods were used for object-based
classification. The major forest types observed in the district were KS (Acacia catechu/
Dalbergia sissoo), Sal (Shorea robusta) and Tropical Mixed Hardwood. The k-NN
classification technique showed higher overall accuracy than the CART method. The
classification approach used in this study can also be applied to classify forest types
in other districts. Improvement in classification accuracy can be potentially obtained
through inclusion of sufficient samples from all classes.Link for e-copy: http://lib.frtc.gov.np/elibrary/?r=577
in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal > 26: 1 (2016) . - 38-44 p.[article] Forest type mapping using object-based classification method in Kapilvastu district, Nepal [printed text] / A. K. Chaudhary, Author ; A. K. Acharya, Author ; S. Khanal, Author . - 2016 . - 38-44 p.
Languages : English (eng)
in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal > 26: 1 (2016) . - 38-44 p.
Keywords: Landsat, machine learning algorithm, object-based classification Abstract: In the recent years, object-based image analysis (OBIA) approach has emerged with
an attempt to overcome limitations inherited in conventional pixel-based approaches.
OBIA was performed using Landsat 8 image to map the forest types in Kapilvastu
district of Nepal. Systematic sampling design was adopted to establish sample points
in the field, and 70% samples were used for classification and 30% samples for
accuracy assessment. Landsat image was pre-processed, and the slope and aspect
derived from the ASTER DEM were used as additional predictors for classification.
Segmentation was done using eCognition v8.0 with the scale parameter of 20, ratios
of 0.1 and 0.9 for shape and color, respectively. Classification and Regression Tree
(CART) and nearest neighbor classifier (k-NN) methods were used for object-based
classification. The major forest types observed in the district were KS (Acacia catechu/
Dalbergia sissoo), Sal (Shorea robusta) and Tropical Mixed Hardwood. The k-NN
classification technique showed higher overall accuracy than the CART method. The
classification approach used in this study can also be applied to classify forest types
in other districts. Improvement in classification accuracy can be potentially obtained
through inclusion of sufficient samples from all classes.Link for e-copy: http://lib.frtc.gov.np/elibrary/?r=577
Title : Identification of land reclamation area and potential plantation area on Bagmati river-basin in the Terai region of Nepal Material Type: printed text Authors: A. K. Acharya, Author ; A. K. Chaudhary, Author ; S. Khanal, Author Publication Date: 2016 Article on page: 53-59 p. Languages : English (eng) Keywords: Bagmati river basin, land reclamation, object-based image classification,potential plantation area, Terai Abstract: Utilization of land reclamation area offers the potentiality of increasing greenery as
well as providing forest products. This study refers to the identification of the land
reclamation areas and potential plantation areas on the Bagmati river-basin in the
Terai region of Nepal, and recommends appropriate species for plantation in order
to rehabilitate such areas. Multi-temporal Landsat Satellite Images (Landsat 7 and
Landsat 8) were acquired for 2002 and 2014. Object-based Image Classification
method was used to classify the land cover classes into four broad categories: i) Water,
ii) Sand and gravel, iii) Plantation potential (open areas suitable for plantation) and
iii) Others (forest, agriculture, built-up areas etc.). The Mean Normalized Difference
Water Index (NDWI) values and Mean Brightness values were found to be helpful in
identifying the water and sand & gravel areas from the other land cover classes. The
overall classification accuracy was 0.97 with a kappa coefficient of 0.89 in the case of
the 2014 Image classification. In this study, the land reclamation area referred to the
areas occupied by water, sand & gravel on the river-beds that were converted into
plantation potential and other classes between 2002 and 2014. Similarly, the potential
plantation area referred to the summation of the area of reclaimed land, the area of
‘Others’ class converted into ‘Plantation potential’ class and the area that remained
to be plantation potential on the bed of the Bagmati River and its tributaries between
2002 and 2014. Altogether, 4,819.10 ha land was reclaimed in the study area, and a
total of 5,395.10 ha land was found to be potential for plantation within the study area.Link for e-copy: http://lib.frtc.gov.np/elibrary/?r=579
in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal > 26: 1 (2016) . - 53-59 p.[article] Identification of land reclamation area and potential plantation area on Bagmati river-basin in the Terai region of Nepal [printed text] / A. K. Acharya, Author ; A. K. Chaudhary, Author ; S. Khanal, Author . - 2016 . - 53-59 p.
Languages : English (eng)
in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal > 26: 1 (2016) . - 53-59 p.
Keywords: Bagmati river basin, land reclamation, object-based image classification,potential plantation area, Terai Abstract: Utilization of land reclamation area offers the potentiality of increasing greenery as
well as providing forest products. This study refers to the identification of the land
reclamation areas and potential plantation areas on the Bagmati river-basin in the
Terai region of Nepal, and recommends appropriate species for plantation in order
to rehabilitate such areas. Multi-temporal Landsat Satellite Images (Landsat 7 and
Landsat 8) were acquired for 2002 and 2014. Object-based Image Classification
method was used to classify the land cover classes into four broad categories: i) Water,
ii) Sand and gravel, iii) Plantation potential (open areas suitable for plantation) and
iii) Others (forest, agriculture, built-up areas etc.). The Mean Normalized Difference
Water Index (NDWI) values and Mean Brightness values were found to be helpful in
identifying the water and sand & gravel areas from the other land cover classes. The
overall classification accuracy was 0.97 with a kappa coefficient of 0.89 in the case of
the 2014 Image classification. In this study, the land reclamation area referred to the
areas occupied by water, sand & gravel on the river-beds that were converted into
plantation potential and other classes between 2002 and 2014. Similarly, the potential
plantation area referred to the summation of the area of reclaimed land, the area of
‘Others’ class converted into ‘Plantation potential’ class and the area that remained
to be plantation potential on the bed of the Bagmati River and its tributaries between
2002 and 2014. Altogether, 4,819.10 ha land was reclaimed in the study area, and a
total of 5,395.10 ha land was found to be potential for plantation within the study area.Link for e-copy: http://lib.frtc.gov.np/elibrary/?r=579
Title : Statistical Methods MBS, MPA, MBA & M. Ed., M.H.M Material Type: printed text Authors: Pushkar Kumar Sharma, Author ; A. K. Chaudhary, Author Publisher: Khanal Publication Publication Date: 2073 Pagination: 518 ISBN (or other code): 978-99946-751-5-9 Price: 555 Languages : English (eng) Statistical Methods MBS, MPA, MBA & M. Ed., M.H.M [printed text] / Pushkar Kumar Sharma, Author ; A. K. Chaudhary, Author . - Kathmandu : Khanal Publication, 2073 . - 518.
ISBN : 978-99946-751-5-9 : 555
Languages : English (eng)Copies (1)
Barcode Call number Media type Location Section Status 7726 519.50 SHA Books CFL Documents Available
