| 000 -LEADER |
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| fixed length control field |
a |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20221230120958.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
221230b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
AIKTC-KRRC |
| Transcribing agency |
AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| 9 (RLIN) |
19472 |
| Author |
Kulkarni, Keerti |
| 245 ## - TITLE STATEMENT |
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| Title |
Mapping Forests Using an Imbalanced Dataset |
| 250 ## - EDITION STATEMENT |
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| Volume, Issue number |
Vol,103(6), Dec |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
New York |
| Name of publisher, distributor, etc. |
Springer |
| Year |
2022 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Pagination |
1987–1994p |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Forests play a major role in maintaining the ecological stability of the region. In recent years, rampant tourism and other human activities have resulted in the decline of the area covered by forests. Many of the times, it becomes difficult to keep a track of the forest land lost, by regular land surveying. Machine learning classifiers applied to remotely sensed images can map the land cover of the region. The challenge in this experiment is that the classes are imbalanced, and hence the classifiers tend to be more biased toward the class which has a greater number of training samples. The novelty of the work is handling this imbalance at the training data level. This is done by using the area-proportionally sampled training samples for training the parameter tuned Random Forest Classifier. The results of this study revealed that, after the classifier is tuned, area-proportional allocation of training samples per class achieved the best classification results. The overall accuracy obtained is 90.5% and 94.6%, with a kappa of 0.85 and 0.92, respectively, for uniform sampling and area-proportional sampling methods. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| 9 (RLIN) |
4623 |
| Topical term or geographic name entry element |
Electrical Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| 9 (RLIN) |
19473 |
| Co-Author |
Vijaya, P. A. |
| 773 0# - HOST ITEM ENTRY |
|---|
| International Standard Serial Number |
2250-2106 |
| Title |
Journal of the institution of engineers (India): Series B |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| URL |
https://link.springer.com/article/10.1007/s40031-022-00790-y |
| Link text |
Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
|
| Koha item type |
Articles Abstract Database |
