Education:

South Dakota State University-Brookings, SD, USA.

MS in Geographic Information Science

Research: A Method for Evaluating Light Pollution in the Brookings Area: A Local Study (Link)

Major Coursework: Geographic Information System, Remote Sensing, GIS Raster & Vector Modeling, Aerial Remote Sensing, Spatial Data Creation & Integration, Web GIS Programming, Statistical Methods, Big Data Analytics, Machine Learning in GIS and RS, Deep Learning in Remote Sensing, etc.

University of Dhaka-Dhaka, Bangladesh.

MS in Physical Geography and Environmental Science

Research: Spatial Analysis of the Inequality Pattern of Health Facilities in Bangladesh: with a special focus on Mymensingh, Bangladesh.

Major Coursework: Biodiversity and Conservation, Hydrology, Resource Management, Population-Environment & Sustainable Development, Research Methods, Fluvial Geomorphology, etc.

University of Dhaka-Dhaka, Bangladesh.

BS in Geography and Environmental Science

Research: Land Use, Socio-Economic and Environmental Condition of North Sonaichari Union, Chittagong, Bangladesh.

Major Coursework: Biogeography, Climatology, Geomorphology, Transport Geography, Population Geography, Urban Geography, Human Geography, Environmental Management, Environmental Analysis, GIS, RS, Land-use Planning, Sustainable Development, Economics, etc.

IBM AI Engineering Professional Certificate (Coursera)     

Field of Study: - Machine Learning and Deep Learning.

Skills: AI | Apache Spark | Data Science | Deep Learning | Machine Learning | Neural Network.

Project Management Professional (PMP)®- (PMI) in progress 2023.

Skills: Team| People | Project |Goal | Agile | Hybrid | Leadership

Primary responsibilities:

• Designs, implements, and performs data management activities such as modifying elements and assigning privileges.
• Performs GIS/ programming activities such as design, development, testing, debugging, documentation, and modification of geospatial applications.
• Analyzes data from various sources to produce data sets, cartographic layouts, and reports in accordance with specifications and standards.
• Practice business process analysis, develops alternatives, and makes recommendations.
• Communicates and interfaces with members of the Caltrans-HQ, vendor, and user communities.

Primary responsibilities as a scientist at USGS-EROS.

•  Active participant in the NLCD strategies team, which leads and development of overall products.

• Integrated people-environment and spatial study in research that can build better sustainability.

• Integrating and implementing models for developing the spatial framework that will support NLCD, CoNED, and RCMAP projects.

• Automated manual tasks in research and education, such as sensor/image data extraction and analysis, reduce time consumption by 80% and the need for the person involved.

• Collaborate with center-wise various projects to find synergy between two projects/ with other federal government projects. 

• Several project papers were co-authored, which include topics such as change detection to overall product description papers.

• 131 Lab: Introduction to Physical Geography Weather and Climate
• 372 Lab: Introduction to Geographic Information System (GIS)

• Identification, analysis, and resolution of Geospatial problems
• Interpretation of complex design drawings, property plats, maps, and other related information
• Working with Landsat 8, Sentinel 2, NAIP, DEM, and CLU data
• Maintain accurate records and files
• Collaboration with a team to plan and solve complex geospatial problems.

• Collecting nighttime light data with Sky Quality Meter (SQM) and Light Meter (LUX).

• Advising on the formulation and local adaptation of both quantitative and qualitative fieldwork tools (questionnaire, interview guidelines, and questions).
• Carrying out a questionnaire survey (random sampling of interview partners and conducting interviews, advice on possible partners for qualitative interviews).
• Advising on the design of a multi-site fieldwork strategy (family members of the village households living in Dhaka).

• Baseline, Knowledge Aptitude and Practice (KAP) and GPS survey, GIS Mapping.
• Project: Implementation of Mangroves for the Future (MFF) outreach activities in Bangladesh.

Current Work:

Caltrans Vegetation and Wildfire Management , more coming soon. . . 

Previous Work:

National Land Cover Database Project:

NLCD: https://www.mrlc.gov/

[The U.S. Geological Survey (USGS) has released a new generation of National Land Cover Database (NLCD) products named NLCD 2019 for the conterminous U.S. NLCD 2019 contains 34 different land cover products characterizing land cover and land cover change across 8 epochs from 2001-2019. Products include urban imperviousness and urban imperviousness change updated to match all landcover epochs; tree canopy and tree canopy change across 2 epochs from 2011-2016, with a 2019 and 2021 canopy suite set to be released in the next year; and RCMAP rangeland fractional component data including a 1985-2020 time-series, projections of future component cover through the 2080s, and Ecological Potential component cover. Data are available on this website either as prepackaged products or custom product areas can be interactively chosen using the viewer. NLCD 2019 represents the most comprehensive land cover database ever produced by the USGS and was specifically developed to meet the rapidly growing demand for land cover change data. NLCD is coordinated through the 10-member Multi Resolution Land Characteristics Consortium (MRLC), a two decades-long interagency federal government collaboration that has proved an exemplary model of cooperation among federal agencies to combine resources to provide digital land cover information for the Nation.

NLCD 2019 now offers land cover for years 2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019, and impervious surface and impervious descriptor products now updated to match each date of land cover. These products update all previously released versions of landcover and impervious products for CONUS (NLCD 2001, NLCD 2006, NLCD 2011, NLCD 2016) and are not directly comparable to previous products. NLCD 2019 land cover and impervious surface product versions of previous dates must be downloaded for proper comparison. Also included with thelLand cover is the NLCD Land Cover Change Index. This index provides a simple and comprehensive way to visualize change from all 8 dates of land cover in a single layer. The change index was designed to assist NLCD users to understand complex land cover change with a single product. NLCD 2019 also offers an impervious surface descriptor product that identifies the type of each impervious surface pixel. This product identifies types of roads, wind tower sites, building locations, and energy production sites to allow deeper analysis of developed features. mrlc.gov]

CONUS Land Cover CONUS Imperviousness Interactive Viewer MRLC NLCD EVA Tool

Coastal National Elevation Database (CoNED) Applications Project:

CoNED: https://www.usgs.gov/special-topics/coastal-national-elevation-database-applications-project

[ The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research and Earth science applications.]

CoNED Peoject Viewer

Rangeland Condition Monitoring Assessment and Projection Project:

RCMAP: 

https://www.usgs.gov/news/usgs-eros-mapping-products-be-renamed-rangeland-condition-monitoring-assessment-and-projection

[The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas and times identified as having no spectral change relative to the base year across all years in the time-series and used a series of procedures to remove the most spatially and temporally common values. We also used composite Landsat Analysis Ready Data (ARD) in seven regions instead of using individual images by path and row. An automated method to identify change in spectral conditions between each year in the Landsat archive and the circa 2016 base map, resulted in a robust and sensitivity of subtle changes. Yearly fractional component cover outputs were inserted in the changed area while the base year values were maintained in the unchanged area. Processing efficiency has been increased through use of open-source software and High-Performance Computing (HPC) resources. The mapping area included seven regions which were subsequently mosaicked for all eight components. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices. Component products can be downloaded from www.mrlc.gov. ]

MRLC Rangeland Viewer

Recent Class Project:

 Impervious_ML NLCD_Impervious     Light_Pollution   RS_SDSU

Professional skills and software:

• Esri Software: ArcGIS (Desktop 10.8x, Pro, Enterprise, Online, Cloud), Field Maps, 123 Survey, etc.

• Image Processing Software: ERDAS Imagine, ENVI, SNAP, QGIS, Pix4D, Agisoft.

• Operating System: Windows, Linux, Mac.

• Other Platforms: Anaconda, Colab, AWS, PyCharm, RStudio, MS Office suite.

• Fieldworks: Field Survey, Field Sampling, Ground Truth via GPS.

• Physical Geography Techniques: Particle size analysis, Suspended Sediment Sampling, Pollen & Diatom analyses.

• Human Geography Techniques: Questionnaire, FGD, RRA, PRA.

• Geospatial Library: GDAL, rasterio, shapely, Fiona, geopandas, etc.

• Programming Languages: Python, R, C++, SQL.

• Web Development: HTML, CSS, PHP, JavaScript. 

• Data Science: Python programming with excellent efficiency in NumPy, Pandas, Matplotlib, and Seaborn

• AI/ML/DL: Supervised, unsupervised, cluster, and reinforcement learning using Sci-kit learn, Tensor Flow, Keras, PyTorch etc.

• Miscellaneous: Object-Oriented Programming, Regular Expressions, FastAPI for python web servers, Optical Character Recognition (OCR), 3D Visualization, etc.

Google Scholar Link

• "Topobathymetric Model of the Coastal Georgia, 1851 to 2020: U.S. Geological Survey data release, July 2022. (Link)

• "Topobathymetric Model of the Coastal Carolinas, 1851 to 2020: U.S. Geological Survey data release, March 2022. (Link)

• "A Comprehensive Comparison of Machine Learning and Deep Learning Methods for Wheat Biomass Estimation Using UAS Multispectral Images." (in progress).

• "National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance product.” (In progress from NLCD project). [2022] (Link)

• “Exploring spatial and temporal patterns of Visceral Leishmaniasis in endemic areas of Bangladesh.” Tropical Medicine and Health; Publisher: BioMed Central. [2017] (Link)

• “Environmental factors associated with the distribution of visceral leishmaniasis in endemic areas of Bangladesh: modeling the ecological niche.” Tropical Medicine and Health. [2017] (Link)

• “Environmental change and kala-azar with particular reference to Bangladesh”. Springer International Publishing. [2016] (Link)

• “Analysis of Temperature Change in Capital City of Bangladesh”.  J. Environ. Treat. Tech. [2015] (Link)

Conference Paper:

• “National Land Cover Database 2019: A comprehensive strategy for creating the 1986-2019 forest disturbance date product”

American Geophysical Union (December 13-17, 2021) Annual Meeting at New Orleans, LA & Online Everywhere.

• “Identifying Influential Factors Affecting Visceral Leishmaniasis in Endemic Areas of Bangladesh with Geospatial Techniques”

American Association of Geographers (April 10-14, 2018) Annual Meeting at New Orleans, USA.

• “Mapping Light Pollution Brookings, South Dakota”

American Association of Geographers (April 03-07, 2019) Annual Meeting at Washington DC, USA.

Poster Presentations:

• "Urban Impervious Surfaces Mapping using Multisource Satellite Imagery and Machine Learning" at 53rd Annual South Dakota State Geography Convention March 2022, Brookings, SD.

• “Light Pollution: why is it and why is it important” at 49th Annual South Dakota State Geography Convention, March 2018, Brookings, SD.

Awards:

2021 National Land Cover Database (NLCD) Team Awards.

2018-2019 Scholarship: EROS Scholarship, United States Geological Survey.

2019 Grant: Graduate Mini-Grant, South Dakota View, South Dakota.

2015 The Duke of Edinburgh’s International Award (Bronze & Silver standard). (Link) 

Affiliations:

• Member, American Association of Geographers (AAG)

• Member, American Geophysical Union (AGU)

• Member, American Society for Photogrammetry and Remote Sensing (ASPRS)

• Member, International Dark-Sky Association (IDSA) 

• Member, California Geographical Society (CGS)

• Member, California URISA (CalURISA)

In media/news:

2018 The End of Night (MS Thesis work) (Link)

Community Service: 

2017  The 48th Annual South Dakota State Geography Convention, South Dakota State University, Brookings, SD, USA

2018 Vise-President, Bangladesh Student Association, South Dakota State University, Brookings, SD, USA.

2018 Conference-Volunteer American Association of Geographers (AAG), New Orleans, USA.

2019 Conference-Volunteer American Association of Geographers (AAG), Washington, D.C., USA.

Interests: Anything outdoors, exploring new places and foods, badminton, and iPhone photography.

Language: Fluent in English and Bengali (native), with basic Spanish.

THANK YOU! 😀