Assessing land-use changes driven by river dynamics in chronically flood affected Upper Brahmaputra plains, India, using RS-GIS techniques

Hazarika, Nabajit; Das, Apurba Kumar; Borah, Suranjana Bhaswati

doi:10.1016/j.ejrs.2015.02.001

Cited by 66 publications

(38 citation statements)

References 39 publications

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“…Indiscriminate dumping of municipal solid wastes into the water bodies was observed in our study. This could probably be another reason for decreased water area, increase floodplain and sand deposit since the wastes obstruct water flow [64]. Furthermore, the reclamation of the rivers and streams promoted an overflow especially during the wet seasons.…”

Section: Overall Landuse-landcover (Lulc) Changesmentioning

confidence: 99%

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

Nwaogu

Okeke²,

Fadipe

et al. 2017

Open Geosciences

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Onitsha is one of the largest commercial cities in Africa with its population growth rate increasing arithmetically for the past two decades. This situation has direct and indirect effects on the natural resources including vegetation and water. The study aimed at assessing land use-land cover (LULC) change and its effects on the vegetation and landscape from 1987 to 2015 using geoinformatics. Supervised and unsupervised classifications including maximum likelihood algorithm were performed using ENVI 4.7 and ArcGIS 10.1 versions. The LULC was classified into 7 classes: built-up areas (settlement), waterbody, thick vegetation, light vegetation, riparian vegetation, sand deposit (bare soil) and floodplain. The result revealed that all the three vegetation types decreased in areas throughout the study period while, settlement, sand deposit and floodplain areas have remarkable increase of about 100% in 2015 when compared with the total in 1987. Number of dominant plant species decreased continuously during the study. The overall classification accuracies in 1987, 2002 and 2015 was 90.7%, 92.9% and 95.5% respectively. The overall kappa coefficient of the image classification for 1987, 2002 and 2015 was 0.98, 0.93 and 0.96 respectively. In general, the average classification was above 90%, a proof that the classification was reliable and acceptable.

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Section: Overall Landuse-landcover (Lulc) Changesmentioning

confidence: 99%

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

Nwaogu

Okeke²,

Fadipe

et al. 2017

Open Geosciences

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“…2007, Sarkar et al 2012. With yearly occurring floods these islands keep on changing in shape, sizes and orientation (Lahiri-Dutta 2014, Hazarika et al 2015. Many of such chars remain stable for long period of time allowing vegetation to grow up and settlement to establish (Rahman et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Study of Brahmaputra River Islands (Chars) for Agriculture Expansion in Assam, India

Prashnani

Qadir

Goswami

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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The present paper aims to understand the spatio-temporal dynamics of the Brahmaputra river islands locally known as chars in Assam for agriculture crop expansion using long term multispectral satellite data and Google Earth Engine. This study also provides information on existing agriculture lands on these chars. For the study Landsat data is analysed to find the long term stable islands and the present status of these islands for seasonal crop expansion. Validation of results was performed by using highresolution satellite data. It is found that total area of vegetative chars has increased in past three decades and approximately 146 thousand hectares area of char is stable from past ten years. This study also reveals that the major crop cultivation is in Lower Brahmaputra Valley (LBV). In Upper Brahmaputra Valley (UBV), the crop cultivation is almost negligible compared to the large islands size. It can be inferred that less stable chars which are mostly located in upper Assam has negligible agriculture. It is also observed that at many places in lower Assam, double cropping system is followed. This study can be further extended by including factors like soil type, soil texture, rainfall, socio-economic etc. to study suitability for different crops. Proper facilities and incentives are to be provided to farmers of this region for better food security.

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“…The ASAR wave mode creates 5 km x 5 km sketch spaced with 100 km of azimuth resolution (VV-polarization), whereas the ASAR swath mode provides 400 km of swath coverage with 150 m resolution. The Radarsat satellite is most leading surveillance system developed by Canada centre for mapping, and earth observation is used to track atmospheric changes of flood (Hazarika, Apurba, & Borah, 2015), oil spill, earthquake, land use (Hadjimitsis et al, 2010) and change map (Ban & Yousif, 2012) applications. The Radarsat also provides high-quality multitemporal images with a steerable beam and single frequency to offer fine image scale and resolution.…”

Section: Introductionmentioning

confidence: 99%

Laplacian pyramid-based change detection in multitemporal SAR images

Geetha

Kalaivani

2019

European Journal of Remote Sensing

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The Synthetic Aperture Radar (SAR) has many attractive and desired features to cope with uncertain weather conditions and also provides superlative resolution in images. In this paper, a unique multiscale approach of change detection (CD) that integrates the preprocessing and CD technique of SAR imagery is discussed. Condensed anisotropic diffusion method is employed as a preprocessing tool for despeckling, and the resultant image is processed by multiscale approach in the Laplacian pyramid (LP) domain. In each layer of LP, the difference between the pyramid coefficient of two images of the same area obtained at different periods is estimated through log ratio operation. Each layer of pyramid coefficient has explicit features at particular scale. Fine scale related to a band pass layer localizes edges of the change area and the coarse scale related to a low pass layer preserves more detail information of the change region. Reconstruction of LP provides exact difference image with perfect boundary. Otsu's algorithm is used to generate binary change map to distinguish changed and unchanged pixels. The efficiency of the proposed method is tested by using simulated and real SAR image datasets. The confusion matrix parameters are used to prove competence of the proposed CD method.

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Assessing land-use changes driven by river dynamics in chronically flood affected Upper Brahmaputra plains, India, using RS-GIS techniques

Cited by 66 publications

References 39 publications

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

Spatio-Temporal Study of Brahmaputra River Islands (Chars) for Agriculture Expansion in Assam, India

Laplacian pyramid-based change detection in multitemporal SAR images

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