Identification info

Metadata Language

English (en)

Character set

utf8

Dataset Reference Date ()

2022-05-25

Identifier

https://catalogue.ceh.ac.uk/id/f7aada06-7352-44c0-988e-2f4b31690189

Identifier

doi: / 10.5285/f7aada06-7352-44c0-988e-2f4b31690189

Other citation details

Beale, J.E.P., Grabowski, R.C., Vercruysse, K. (2022). River planform dynamics in the Beas and Sutlej catchments, India, 1847 and 1989-2018. NERC EDS Environmental Information Data Centre 10.5285/f7aada06-7352-44c0-988e-2f4b31690189

Keywords

• Fluvial geomorphology
• river planform
• Remote Sensing
• Landsat

Limitations on Public Access

otherRestrictions

Other constraints

no limitations

Use constraints

otherRestrictions

Other constraints

This resource is available under the terms of the Open Government Licence

Use constraints

otherRestrictions

Other constraints

If you reuse this data, you should cite: Beale, J.E.P., Grabowski, R.C., Vercruysse, K. (2022). River planform dynamics in the Beas and Sutlej catchments, India, 1847 and 1989-2018. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/f7aada06-7352-44c0-988e-2f4b31690189

Spatial representation type

vector

Spatial representation type

textTable

Topic category

• Imagery base maps earth cover

N

S

E

W

Begin date

1847-01-01

End date

1850-12-31

Begin date

1989-01-01

End date

2018-12-31

Code

WGS 84

Distribution Information

Data format

• Shapefile ()

• Comma-separated values (CSV) ()

Quality Scope

dataset

Other

dataset

Statement

Wet river area: The annual wet river area was extracted automatically from satellite imagery of Landsat 5 to 8 (1989 to 2018) using average post-monsoon season (October-December) values of the modified Normalized Difference Water Index (mDNWI) to differentiate water and land areas (Huang et al., 2018). The wet river area was extracted from the mNDWI raster images by the threshold mNDWI > 0.15. After manual editing to remove individual water pixels away from the river, the raster images were converted to polygon shapefiles). There is a feature for each year of measurement. The wet river area was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series. Active gravel bars: Visible red reflectance from Landsat 5 to 8 (1989 to 2018) was used to identify bare gravel bars showing high reflectance (> 0.16) using average post-monsoon season (October-December) values. Only pixels within a buffer defined by the maximum extent of the wet river area over the observed period were considered. After applying the reflectance threshold to raster images, shapefiles were created to define the active gravel bars as features. There is a feature for each year of measurement. Active Channel Area: The wet river area shapefiles from individual years 1989-2018 were aggregated together to produce a single feature that delineates areas that were wetted in the post-monsoon season in one or more years between 1989-2018, to estimate the extent of the active channel. Active channel width: The channel width was considered as the width of the wet area, including any gravel bars where that were surrounded by water. This width was automatically calculated every 2 km and was repeated for wet areas estimates derived from an historic map (“The Trans-Sutluj Division, comprising the districts of Jalundhur, Hoshyarpoor and Kangra”) (Revenue Survey of India, 1852) which was produced between 1847 and 1852. Width was measured perpendicular to the riverbank. The mean active channel width was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series. Anabranching Index (AI): The anabranching index reflects the number of active channels separated by bars or islands, measured in at least 10 cross sections (spaced the width of one braid plain apart). The AI was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series. Quality control: Landsat satellite data was used to collect information on spectral surface reflectance. These data are accompanied by quality assessment bands which were used to select data before processing, particularly with respect to obtaining cloud-free images. Processing was conducted by the project team, with using and spot validation against aerial satellite photography. Data were checked for errors at all stages by members of the project team at Cranfield University.

Metadata

File identifier

f7aada06-7352-44c0-988e-2f4b31690189 XML

Metadata Language

English (en)

Character set

ISO/IEC 8859-1 (also known as Latin 1)

Resource type

dataset

Hierarchy level name

dataset

Metadata Date

2023-05-02T07:46:12

Metadata standard name

UK GEMINI

Metadata standard version

2.3