Hybrid modelling approach for water body change detection at Chalan Beel area in northern Bangladesh
- PDF / 11,673,987 Bytes
- 18 Pages / 595.276 x 790.866 pts Page_size
- 19 Downloads / 177 Views
ORIGINAL ARTICLE
Hybrid modelling approach for water body change detection at Chalan Beel area in northern Bangladesh Riad Arefin1 · Sarita Gajbhiye Meshram2,3 · Celso Augusto Guimarães Santos4 · Richarde Marques da Silva5 · Jagalingam Pushparaj6 Received: 29 January 2020 / Accepted: 9 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Water is a strategic resource for both socio-economic development and human life. The current study has been carried out for spatio-temporal change detection of surface water bodies during winter period using hybrid modelling approach. The study area has fallen in the northern part of Bangladesh and is locally called Chalan Beel with 5 million of in habitants, a prominent intensive crop production, surface and groundwater irrigation, high evapotranspiration, and water scarcity. For the detection of water body changes, satellite images of 1999 and 2011 were used, and the following image fusion techniques were applied: (a) Gram-Schmidt (GS), (b) modified intensity hue saturation (IHS), (c) high-pass filter (HPF), and (d) wavelet. Landsat 7/ETM + panchromatic (PAN) band of 15 m × 15 m resolution in 1999 and Landsat 5/TM multispectral (MS) bands of 30 m × 30 m resolution in 2011 were allied each other to generate high-resolution image that contains information of two different years. The fused images were classified to extract the water bodies using four classification methods: (a) artificial neural network (ANN), (b) support vector machine (SVM) and (c) maximum likelihood (ML). To analyze the quality of the fused images, statistical calculation (quantitatively) and Laplacian edge detection (qualitatively) were used. To validate the fused image classification results, the multispectral images from 1999 and 2011 were again individually classified using principal component analysis (PCA), normalized difference water index (NDWI), and image differencing (ID) processes and compared with the previous classification. Surprisingly, the results showed that two-third of the areas dried up in 10 years. Keywords Landsat image · Remote sensing · Image fusion · Surface water · Change detection · Chalan beel · Bangladesh
Introduction
* Sarita Gajbhiye Meshram [email protected] 1
Department of Geology and Mining, University of Rajshahi, P.O. Box 6205, Rajshahi, Bangladesh
2
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
3
Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam
4
Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, PB 58051‑900, Brazil
5
Department of Geosciences, Federal University of Paraíba, João Pessoa, PB 58051‑900, Brazil
6
School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Water body change detection in humid climatic areas is essential for biodiversity, ecological environment and regional food security, because help in ma
Data Loading...
