Mukherjee, A and Ramachandran, P (2022) Development of New Index Based Supervised Algorithm for Separation of Built-Up and River Sand Pixels from Landsat7 Imagery: Comparison of Performance with SVM. In: 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, 17 - 22 July 2022, Kuala Lumpur, pp. 3183-3186.
|
PDF
IGARSS_2022.pdf - Published Version Download (555kB) | Preview |
Abstract
While extracting 'built-up' pixels from satellite imagery, supervised classification algorithms often misclassify 'river sand' pixels as 'built-up' ones due to the similarity in their spectral profiles. With the help of the spectral reflectance information in BLUE & GREEN bands of Landsat satellite imagery, this study has introduced a new index BRSSI (Built-Up & River Sand Separation Index) that efficiently reduce the misclassification between these two classes. The results shows that average overall accuracy, F1 score and kappa (kappa) coefficient for the developed index corresponding to selected 3 study regions across India are 0.9763, 0.9767 & 0.9527 respectively.
Item Type: | Conference Paper |
---|---|
Publication: | International Geoscience and Remote Sensing Symposium (IGARSS) |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to the Authors. |
Keywords: | Pixels; Remote sensing; Rivers; Sand; Satellite imagery; Support vector machines, Build-up & river sand separation; Classification algorithm; Comparison of performance; Index based methodology; LandSat 7; Machine-learning; River sands; Supervised algorithm; Supervised classification; Support vectors machine, Separation |
Department/Centre: | Division of Interdisciplinary Sciences > Management Studies |
Date Deposited: | 04 Jan 2023 06:51 |
Last Modified: | 04 Jan 2023 06:51 |
URI: | https://eprints.iisc.ac.in/id/eprint/78719 |
Actions (login required)
View Item |