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PROJECTS

Presentation
Poster Presentation| Here is a poster that I presented in Chiba, Japan in 2019 at the SAKURA SCIENCE Exchange program.
"Climate Resilient Smart Housing"

Bangladesh is one of the most flood-prone countries in the world.

It is prone to flooding due to being situated on the Brahmaputra River Delta (also known as the Ganges Delta) and the many distributaries flowing into the Bay of Bengal. Coastal flooding, combined with the bursting of river banks, is common, and severely affects the landscape and society of Bangladesh.

Every year people lost their houses because of flooding.

If they can build a climate-resilient house, then it would lessen the suffering of people who are living under the poverty line. Moreover, on the riverbank people will have a better life.

 Click the pdf icon or check out my experience of Sakura Science Exchange Program

Petrel
Geophysics lab and Self Learning Projects

This includes figures that were created during lab work and self learn projects.

Petrophysical Analysis 2.JPG

Petrophysical Analysis with Petrel (Data: Udemy)

2068.JPG

Seismic Data interpretation in Geophysics Lab

Presentation
Applied
Sedimentology
| Lab Project|

This includes the analysis that was made during laboratory work.

Pleistocene Sandstone.jpg

Figure: A-CN-K ternary diagram with CIA values for the given Pleistocene sandstone sample

Interpretation: From the A-CN-K ternary diagram, it is determined that the value of all these parameters reflects the sample being weakly chemically weathered. The weakly weathered also indicate cold and arid paleoclimate condition of the source area of the sample.

Problem-2.jpg

Figure: Vertical litholog of Sonatila section

Vertical Litholog of  Xiejia Section.jpg

Figure: Vertical lithology of Xiejia Section 

ArcGIS
ArcGIS
| Coursera Project|  Research Society Project | Lab Project|

This includes the maps that were created during the above-mentioned training.

Dhaka City Covid_19 situation.jpg

A map presenting COVID'19 Situation in Dhaka Megacity. [ Updated on 31 May 2020]

It implies how much area of the capital of Bangladesh is affected.

A map of the Sylhet District mainly indicating the field sampling location and adjoining area.

Moreover, Buffer distance of the river as well as the Highway.

Gowainghat supervised classification.jpg

Supervised image classification of the Gowainghat area of the Sylhet District.


This Classification mainly includes five types of land. They are Farming land, Forest, Riverbank Sediment, River, and wetland.

NWDI Modelling.jpg

Normalized Difference Water Index (NDWI) modeling of Landsat 8 image of the interested area. 
It is derived using principles of the
comparison of differences of two bands, Green and near-infra-red (NIR).
The NDWI implies vegetation suppressed and the open water features enhanced.

NDVI Modelling.jpg

Normalized Difference Vegetation Index (NDVI) modeling of Landsat 8 image of the interested area.

It is a standardized index allowing to generate an image displaying greenness (relative biomass).
An NDVI is often used worldwide to monitor drought, monitor and predict agricultural production, assist in predicting hazardous fire zones, and map desert encroachment.

Geology Formation of Nilphamari.jpg

Geological Formation map of Nilphamari District.

An Inverse Distance Weighting (IDW) of minimum Temperature modeling of Bangladesh.
This a type of non-graded data.

NetCDF (Network Common Data Form) modeling of the Rainfall Distribution of Bangladesh.
Data Credit: https://www.unidata.ucar.edu/software/netcdf/

Georeferencing Image.jpg

Georeferenced Image of a drone image of the New-market area, a well-known shopping area of Dhaka City.

Electoral Politics Assignment.jpg

Precinct level Electoral Politics voting data analysis map.
It also shows the Yes vote to the total votes.

Image analysis via different color band combination 

Study area with 754 Band Combination

Study area with 321 (NCC) Band Combination

Study area with 432 Band Combination

Geology 
field report
| Field Project |
Here presented some of my geological field-related interpretations from my senior year academic field survey.

Stereonet Projection of dip direction and dipping amount of Jaintiapur and its adjoining area field survey.

Rose diagram based on the bedding strike orientation of Jaintiapur and its adjoining areas.

CM Diagram of jaintiapur.jpg

Here is the CM-Diagram of sieve analysis data from Jaintiapur and its adjoining areas sample.
It is assumed that the mode of transportation of sands of Jaintiapur and adjoining area were represented by the load type as rolling to suspension as well as minor graded suspension grains.

two component veriation diagram.jpg

The Two-Component Variation Diagram of sieve analysis data from Jaintiapur and its adjoining areas' sample.
It is assumed that the sands are mainly of river sand.

cross section.jpg

This map contains the location of the cross-sections of the studied field area.

Legends for Cross-section
A=Limestone

B=Kopili Shale
C= Barail Group
D=Bhuban
E=Tipam Sandstone
F= Girujan Clay
G=Dupitila Sandstone
H= Dihing Formation

A Schematic representation of stratigraphy of the Jaintiapur and its adjoining area.

Engineering Geology
| Lab Project|

This includes the analysis that was made during laboratory work.

Soil classification after after BS 5930-1981.jpg

Figure: Soil Classification after BS5930-(1981)

Plasticity chart of the studied clay soils.jpg

Figure: Plasticity chart of the studied clay soils after BS5930-(1981)

Interpretation: According to plasticity chart for the BSCS (after BS 5930: 1981) samples A, B, C, D, E and F lie above the ‘A’ line which indicate that they are inorganic clay. In case of the cone penetrometer method, all samples show intermediate (medium) plasticity range.

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