Santonu Sarker Santo
I am a professional Urban Planner with 3 years of experience delivering 100+ national and international projects, specializing in GIS & remote sensing, social research, housing, feasibility studies, baseline and endline studies, and data-driven urban decision-making.
I hold a Bachelor’s degree in Urban and Rural Planning (BURP) from Khulna University, Bangladesh. I began my professional career as a town planner at Geo Smart Planning, a Khulna-based urban planning consulting firm, where I developed expertise in research, spatial analysis, and applied urban planning solutions.
My research interests focus on data-driven and real-time decision-making in urban planning, with an emphasis on quantitative and spatial analysis methods. My recent work, “Predicting Land Use/Land Cover Change Using Random Forest and ArcGIS Python API,” reflects my dedication to integrating machine learning with GIS to model urban dynamics, identify emerging trends, and inform evidence-based planning strategies. I am particularly passionate about leveraging GIS and machine learning to conduct map-based research that models land use and urban change, strengthening technical expertise while supporting evidence-based urban planning decisions.
Overview of Research Domains and Application Areas
Spatial Analysis
Digitization and georeferencing, spatial data editing, DEM and contour analysis, watershed delineation, hotspot and hazard mapping, drainage density and hillshade analysis, flood risk mapping, land use/land cover (LULC) mapping, vegetation and built-up indices (NDVI, NDBI, NDWI), land suitability assessment, participatory GIS mapping, network and accessibility analysis, community action plan mapping, choropleth visualization, and machine learning applications for land use prediction, urban change modeling, and spatial pattern analysis
Decision Making Project
Feasibility studies, housing development planning, social and environmental impact assessments (SIA, EIA/ESIA), land acquisition planning, land use zoning, land area demarcation using RTK, topographic survey design, longitudinal profile creation, urban landscaping, right-of-way (RoW) demarcation over cadastral and mouza maps, and machine learning applications including object detection, spatial prediction, and urban change modeling
Mixed Method Research
Qualitative and quantitative research methods, including focus group discussions (FGD), key informant interviews (KII), in-depth interviews (IDI), thematic analysis and coding, inferential statistics, and data triangulation; climate and environmental vulnerability assessments, including livelihood vulnerability index (LVI) and climate risk analysis; survey design using KOBO Toolbox; analytic hierarchy process (AHP) and knowledge-attitude-practice (KAP) analysis; and baseline, midline, and endline assessments for land use, urban change, and climate impact studies
Research Outputs from Field and Planning Projects
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Work Experiences
GEO SMART PLANNING | PROJECT MANAGER
June 2024 – Present
- Leading 3 project teams, completing 100+ projects, including baseline, endline, feasibility studies, EIA, ESIA, GIS, remote sensing, housing, and land acquisition planning, with a 98% on-delivery rate.
- Directed a team of 25 GIS and AutoCAD professionals to digitise and georeferenced 400+ Mouza maps, integrating a semi-automated CAD-GIS process, saving 50% of the digitisation, edge matching, and attribute creation time.
- Improved overall project/grant proposal content quality, increasing the probability of shortlisting by 80% through strategic structuring, clarity, and alignment with donor requirements.
- Managed 10.3M budgets across multiple projects, ensuring 100% compliance with financial targets.
GEO SMART PLANNING | JUNIOR TOWN PLANNER
July 2022 – May 2024
- Pioneered the use of ArcGIS Pro, Python, and Power BI, winning 15+ new feasibility study projects.
- Established KOBO toolbox for household surveys in 15 research projects with advanced skip logic, reducing overall project timelines by 30% through improved data collection and cleaning efficiency.
- Cleaned and analysed 5000+ quantitative data in 3 research projects, improving overall project efficiency by 18%.
Education
Bachelor of Urban and Rural Planning (URP)
Khulna University, Bangladesh | 2017 – 2023
CGPA: 3.22
BURP Dissertation: Problems of Urban Water Supply and Sanitation Facilities in Lower-Income Communities, A Case Study on Khalishpur, Khulna City
- Collected spatial data and created 3 locational distribution maps of drinking water sources.
- Accomplished network analysis to calculate each supply system’s service area and closest facilities using ArcGIS Pro.
- Analyzed and visualized 100 household survey data through R-Studio (R Programming).
Ongoing Research Paper
Title of Research Paper: Predicting Land Use/Land Cover Change Using Random Forest and ArcGIS Python API
Methodology: The study collected and preprocessed historical land use/land cover (LULC) and satellite datasets, deriving key spatial features and indices such as NDVI, NDBI, NDWI, and DEM-based metrics. A Random Forest model was trained to predict future LULC changes, and the results were integrated and visualized using the ArcGIS Python API. The model’s predictions were validated using accuracy metrics, and the spatial trends were analyzed to inform urban planning and climate adaptation strategies.
Planning, GIS & Analytical Tools
ArcGIS Pro | ArcGIS Desktop | SuperMap GIS | QGIS | Grass GIS | Survey 123 | Margin App | Erdas Imagine | Blender | Google Earth Pro | OSM | AutoCAD 2D
Python (NumPy, Pandas, GeoPandas, Matplotlib, Seaborn) | Jupyter Notebook | RStudio (ggplot2, plotly, dplyr, R-shiny) | Machiine Learning | Excel | SPSS | Power BI | Adobe Illustrator | Photoshop | Google Sketchup Pro | Lumion
MS Office Applications | Overleaf (LaTex) | MS Project | Grammarly | Turnitin Student | Quilbot | Mendeley | Zotero | EndNote | KoBoToolbox | ODK | mWater