[article] | 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 |
|
Forest type mapping using object-based classification method in Kapilvastu district, Nepal in BANKO JANAKARI - वनको जानकारी : A Journal of Forestry Information for Nepal, 26: 1 (2016)
