1. Doctor of Engineering (Urban Engineering) from The University of Tokyo, Japan (awarded on September 27, 2010)

2. Masters of Engineering (Urban Engineering) from The University of Tokyo, Japan (awarded on March 22, 2007) (Result: CGPA was 4.00 out of 4.00)

3. Bachelor of Urban and Rural Planning (BURP) from Khulna University, Bangladesh (Awarded on January 15, 2003) (Result: CGPA was 3.78 out of 4.00)

My general interests are in the area of application of quantitative geospatial methods in broader urban complexity. I am also interested about

• Geographic Information System
• Remote Sensing
• Photogrammetry
• Machine Learning in LULC modeling
• Land use planning

Current Research Project/Collaboration

ACADEMIC CAREER

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1.  Professor of Urban and Rural Planning Discipline, Khulna University (June 2015-on going)

2. Head of Urban and Rural Planning Discipline, Khulna University (April 2019-Dec. 2020)

3. Associate Professor of Urban and Rural Planning Discipline, Khulna University (March 2011-June 2015)

4. Lecturer, Center for Spatial Information Science (CSIS), University of Tokyo (2011-2012)

5. Assistant Professor of Urban and Rural Planning Discipline, Khulna University (Dec. 2006-Mar. 2011)

6. Assistant Proctor, Khulna University (June 2004-March 2005)

7. Lecturer of Urban and Rural Planning Discipline, Khulna University (Dec. 2003-Dec. 2006)

SELECTED CONSULTANCY EXPERIENCE

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Senior Urban Planner (November 2012)

Client: Khulna Development Authority (KDA), Khulna, Bangladesh

Brief of the project:  Preparation of Detailed Area Development Plan (DADP) for Khulna Master Plan (2001) Area funded by Khulna Development Authority and Government of the People’s Republic of Bangladesh.

GIS Expert (April, 2015)

Client: Capital Development Authority (RAJUK), Bangladesh

Brief of the project:  Preparation of Detailed Area Development Plan (2016-2035) for DMDP Area funded by RAJUK and Government of the People’s Republic of Bangladesh.

No Data Available

Supervision

No Data Available

coming soon...

Best paper award

Islam, K.S. and Karim, M. R. (2004), 'Small Scale Private Real Estate Business- Challenges to the Sustainable Development: a case study of Khulna City, Bangladesh', paper presented at the “9th Annual Asian Real Estate Conference, New Delhi, India, August 9-12, 2004.

 

 

Books and Book chapters

Islam, K. S. (2022). Environmental Sensitivity of Planning Practices in Bangladesh vis-à-vis Evolution of Planning Theories: A Case Study on a Thermal Power Plant at Rampal, Bangladesh. In A. Hussain, K. Tiwari, & A. Gupta (Eds.), Addressing Environmental Challenges Through Spatial Planning (pp. 55-74). IGI Global. http://doi:10.4018/978-1-7998-8331-9.ch004

 

 

Published Papers [Sorted by year]

Rahman, M. A., Islam, K. S., Siam, S. I., and Islam, S. (2022) Spatiotemporal Change of Land Use Land Cover: A case Study of Narayanganj Sadar Upazila, Bangladesh, Khulna University Studies., pp. 233–243, https://doi.org/10.53808/KUS.2022.ICSTEM4IR.0017-se

Rakibuzzaman, M. and Islam, K. S. (2022) A Narrative Review of the use of Fractal Geometry in Various Aspects of Urban Planning, Khulna University Studies., pp.  219–232, https://doi.org/10.53808/KUS.2022.ICSTEM4IR.0011-se

Hasan, M. Z., Leya, R. S. and Islam, K. S. (2022) Comparative Assessment of Machine Learning Algorithms for Land Use and Land Cover Classification Using Multispectral Remote Sensing Image, Khulna University Studies., pp.  33–46, https://doi.org/10.53808/KUS.2022.ICSTEM4IR.0124-se

Mia, M.R., Islam, K.S., Islam, M.D. (2021) Automatic Building Footprint Extraction from High-Resolution stereo Satellite image,  Planplus: a Journal of Planning, Development, Urbanization and Environment, Vol. 11, pp. 17-28. https://doi.org/10.54470/planplus.v11i1.2

Islam, M.D., Li, B., Islam, K. S., Ahsan, R., Mia, R., Haque, M.D. (2022) Airbnb rental price modeling based on Latent Dirichlet Allocation and MESF-XGBoost composite model, Machine Learning with Applications, 7, https://doi.org/10.1016/j.mlwa.2021.100208

Islam, M.D., Islam, K.S., Ahsan, R., Mia, R. Haque, M.D. (2021) A data-driven Machine Learning-based approach for urban land cover change modeling: A case of Khulna City Corporation area, Remote Sensing Applications: Society and Environment, 24, https://doi.org/10.1016/j.rsase.2021.100634

 

Hussain, F., Islam, K.S. (2020, published in 2021) Classification of Cities Based on Land Use Land Cover Heterogeneity: A Case Study of Bangladesh, Journal of Bangladesh Institute of Planners, Vol. 13, pp. 1-16

 

Saha, A., Islam, K. S., (2020) Assessing the Impact of Cyclone Sidr and Aila on the Sundarbans and Its Current Recovery Status Using Remotely Sensed Imagery, Khulna University Studies, Vol. 16 (1 & 2), pp. 1-16 (KUS: 18/10: 250918) https://doi.org/10.53808/KUS.2019.16.1&2.6.1810-E&T

 

Tabassum, F., Morshed, M.M., Sydunnaher, S. and Islam, K.S. (2019) Are We Undercounting Poverty? Targeting Poor for Development Intervention in Khulna City,  Planplus: a Journal of Planning, Development, Urbanization and Environment, Vol. 9, pp. 1-16

 

Hosen, K. and Islam, K.S. (2019) Simulating the Impact of Setback, Floor Area Ratio (FAR) and Maximum Ground Coverage (MGC) Rules on Urban Living Environment: An Airflow Modelling Perspective, Proceedings of the First International Conference on Urban and Regional Planning, Bangladesh, Bangladesh Institute of Planners, Dhaka, Bangladesh, October 5-6, 2019 pp. 53-62

 

Saikat, S.S., Islam, K.S. (2019) Modeling Land Use Land Cover (LULC) Change Using Cellular Automata-Markov Model: A case of Khulna City, Bangladesh. Jahangirnagar University Planning Review, Vol. 17, pp. 17-31

 

Howlader, A.S, m, K. S., (2018, printed in 2020)   Nexus between Light Pollution and Air Temperature: A Study of Bangladesh, Journal of Bangladesh Institute of Planners, Vol. 11, pp. 1-9

 

Siddque, M. N. I., Islam K. S. and Habib, M. (2018) Practice of Higher Education Pedagogy in Bangladesh: Opportunities and Challenges, Bangladesh Journal of Extension Education, Volume 30 (2), pp. 71-78 

 

Sydunnaher, S., Islam, K. S., & Morshed, M. M. (2018). Spatiality of a multidimensional poverty index: a case study of Khulna City, Bangladesh. GeoJournal, Vol. 84, 1403–1416. https://doi.org/10.1007/s10708-018-9941-9

 

Sydunnaher, S., Islam, K.S. and Jebunnessa (2015, printed in 2018) Slum Dweller’s Understanding of Their Rights and Accessibility to Public Services: A Case Study of Khulna City, The Jahangirnagar Review; Part II: Social Science Vol. XXXIX, pp. 159-167

 

Rehan, S.M.T.I, Islam, K.S. (2015) Analysis of Building Shadow in Urban Planning: A Review, Jahangirnagar University Planning Review, Vol. 16, pp. 11-22

 

Islam, M.S., Islam, K.S. (2013) Application of Thermal Infrared Remote Sensing to Explore the Relationship between Land Use-Land Cover Changes and Urban Heat Island Effect: A Case Study of Khulna City, Journal of Bangladesh Institute of Planners, Vol. 6, p. 49-60

 

Siddque, N.I., Islam, K.S. (2013) Enrollment Trend of Khulna University: Regionalization? An Analysis based on Students’ Place of Origin, published in the Proceedings of the International Conference on Academic Enhancement, June 18, 2013, pp. 43-54

 

Islam, K.S., and Swapan, S.H., (2013) Impact of Volatile Industrialization on Urbanization and Internal City Structure: A Study of Khulna City, Bangladesh” Planplus: A Journal of Planning, Development, Urbanization and Environment, Vol. 6, pp. 81-96

 

Islam, K.S., Asami, Y., (2012) Influence of Poverty on Internal Household Mobility Pattern of a City: A Case Study of Khulna City: a case study of Khulna city, Bangladesh, Journal of Bangladesh Institute of Planners, Vol. 5, pp. 37-57.

 

Islam, Kazi Saiful and Asami, Yasushi (2011) “Addressing Structural Instability in Housing Market Segmentation of the used houses of Tokyo, Japan” Procedia - Social and Behavioral Sciences (21) 33-42 doi:10.1016/j.sbspro.2011.07.021

 

Islam, K.S. (2009) “Housing Market Segmentation: Spatial Variable Search perspective” paper presented at S4 International Conference on Emergence in Geographical Space: Concepts, Methods and Models, Paris, France, November 23-25, 2009

 

Islam, K.S (2009) “Urban Sustainability in Declining era: Challenges and Response” paper presented at CIB-W101 & The University of Tokyo GCOE co-hosted Workshop, Tokyo, Japan, June 21, 2009 

 

Islam, K.S., Asami, Y., (2009) “Housing market segmentation: a review” Review of Urban and Regional Development Studies 21(2-3), pp. 93-109,  (DOI: 10.1111/j.1467-940X.2009.00161.x)

 

Islam, K.S., (2009) “Challenges of urban planning at the face of counter urbanization” Theoretical and empirical research in urban management, 2(11)

 

Islam, K.S., Asami, Y., (2008), “Neighborhood Mobility due to Poverty: a Threshold Perspective” paper presented at ACSP-AESOP Joint Congress, Chicago, Illinois, July 6-11, 2008

 

Islam, K.S., Asami, Y., (2008), Review of Literature and Future Research Direction: Housing Market Segmentation Perspective', paper presented at 10th Summer Institute of Pacific Regional Science Conference Organization (PRSCO) Dhaka, Bangladesh, May 15-16, 2008.

 

Islam, K.S., Hasan, M.U., (2007) ‘Addressing the issue of Rural Landuse in disaster management policy or programme: a case study of Southwestern coastal areas of Bangladesh’ paper presented at First international conference of Bangladesh Regional Science Association, Dhaka, Bangladesh, March 17-18, 2007.

 

Islam, K.S., Asami, Y., (2007), 'Neighborhood mobility due to poverty: a threshold perspective', paper given at The Seventh International Urban Planning and Environment conference (UPE 7) Bangkok, Thailand, January 3-5.

 

Swapan, S.H., Islam, K.S. and Ahmed, S., (2006), 'Spatial dimension of urban poverty ', Planplus: a Journal of Planning, Development, Urbanization and Environment, Vol. 4, pp. 119-135.

 

Islam, K.S., Akther, M.S. (2006), 'City structure models and location of lower-income settlements: the context of Khulna city, Bangladesh', International Symposium on Urban Planning 2006 (Taipei, Taiwan), 13-30

 

Islam, K.S and Karim, R. (2006), The Impact of the small scale real estate business on the urbanization patterns of third world cities, ed. Stephen Brown,  (RICS Research Paper Series, London: Royal Institute of Chartered Surveyors) Vol. 6(3).

 

Islam, K.S., Rahman, K.R. (2003), 'Effects of the increase of the two-stroke three-wheelers on the urbanization pattern of Khulna City, Bangladesh', JPWK, Jurnal Perencanaan WIlayahdan Kota or Journal of Urban and Regional Planning, 14 (2), 39-48.

 

Karim, R., Islam, K.S (2003), 'Shrimp culture around the Sundarbans and its effects on land agriculture, livestock and poultry: a case study of some selected villages of Rampal Thana ', The Sundarbans, the largest mangrove forest of the earth: A world heritage site (Khulna University, Khulna, Bangladesh), 18-24.

Urban Analysis Technique Planning is all about analyzing data to extract information for decision-making. This course will pave the way to enable students to analyze landuse, land value, urban character, demography etc.

Urban Analysis Technique (FW/Studio) This is the sessional part of URP 2221.

Geographic Information System Planning involves data collection, analysis, and decision-making. Since “physical determinism” is still considered as one of the major determinants of planning, geospatial data plays a vital role in physical planning.  For production, analysis and decision making, planners need to know about Geographic Information System (GIS). The course is designed to familiarize students with the concept of geographic data and GIS, process of inputting geo-data, storage and management of data and modelling, application of GIS in the real-world studies. Lectures cover the basics of GIS, vector and raster data models, geographic data analysis, visualization techniques and geographic overlay. Importantly, the focus of this course is in the application of GIS to solving real world problems.

Geographic Information System (Lab/Studio) This is the sessional part of URP 2261.

Remote sensing and Photogrammetry Modern planners need to deal with huge amount of spatial data. Production of these data is often expensive and time consuming. Using remotely sensed images we can acquire data of large areas. Therefore this course offers remote sensing techniques and photogrammetry as the part of decision support system for planning. This course will be conducted simultaneously with the sessional part.

Remote sensing and Photogrammetry (Lab/Studio) This is the sessional part of URP 3261.

Statistics for Planners Description:  Basics of statistics, Qualitative and Quantitative methods of statistics, Sampling techniques, sample size and sample analysis, Basic concepts of probability, Normal probability distributions, Basics of Hypothesis Testing, Inferences from two samples, Goodness-of-Fit, Contingency tables, Chi-square tests, ANOVA, Correlation and Regression.   Rationale: Statistics is a basic tool of analysis able to effectively conduct research. It is concerned with the collection, analysis, and interpretation of data, as well as the effective communication and presentation of results relying on data. It is extremely important for a researcher to know what statistics they want to use before they collect their data. Otherwise data might be collected that is uninterruptable. To do well in statistics one must develop and use formal logical thinking abilities that are both high level and creative. To study statistics are to be able to effectively conduct research, to be able to read and evaluate journal articles, to further develop critical thinking and analytic skills.   Course Objectives: ·         Motivate in students an intrinsic interest in statistical thinking. ·         Instill the belief that Statistics is important for scientific research. ·         Provide a foundation and motivation for exposure to statistical ideas subsequent to the course. Learning outcomes: Demonstrate the ability to apply fundamental concepts in exploratory data analysis. Design studies for obtaining data whilst avoiding common design flaws that incur bias, inefficiency and confounding. Demonstrate an understanding of the basic concepts of probability and random variables  Interpret and analyze classical inference involving confidence intervals, hypothesis testing, data displayed in a two-way table, one-way analysis of variance (ANOVA). Apply and interpret basic of modeling techniques for bi-variate data and use inferential methods in the context of simple linear models with normally distributed errors.

Statistics for Planners Aims: This course aims to introduce the basics of Statistics. It discusses the importance of statistics in planning and urgency of statistics in every sphere of planning. This course mainly focuses on data collection methods, data processing, data analyzing tool and interpreting those data in order make decision.     Course Objectives The objectives of this course are as follows: ·         To understand the meaning of statistics, data, variable and information ·         To explain the division of statistics with respect to different kinds of data ·         To interpret ideas of population versus sample, random variables, and techniques of descriptive statistics ·         To calculate and interpret measures of central tendency and dispersion, including mean, median, standard deviation, and quartiles ·         To demonstrate skills in revealing the characteristics of normal distributions. ·         To describe and identify the characteristics of different numerical distributions. ·         To explain the relevance of statistics in different kinds of planning activities.   Intended Learning Outcomes (ILOs) At the end of the course the students will be able to- ·         Demonstrate the basic principles of describing and presenting data; ·         Explain the role of statistics in different brunches of urban planning; ·         Describe and compute different measures of central tendencies and dispersion.

Statistics for Planners -II Planners need statistics for decision making. Along with previous course (URP 1251: Statistics for Planners - I), this course is aimed at enabling students with greater quantitative decision making. The course is designed for the Second year students of Urban and Rural Planning Discipline. This course is designed to introduce student to the concepts of statistics and enable them with skills that they can use in their daily life.   Students should have basic knowledge about elementary mathematics. It is also assumed that the students have basic web browsing ability and should be able to deal with some softwares like MS Office suits.  Intended Learning Outcomes (ILOs) After completion of the course, students are expected - 1.     to recognize, examine, and interpret the basic principles of indexing multivariate data; 2.     to acquire critical thinking skills including analysis and application in the field of Urban and Rural Planning. 3.     to apply probability and hypothesis tests in solving planning related problems. 4.     to perform and interpret simple univariate, bivariate and multivariate statistical procedures using computer software. Running

Quantitative Methods, Analysis & Techniques Statistics is a major stream of knowledge that is used by planners to extract information from data and make decision out of it. Statistics is concerned with the collection, analysis, and interpretation of data, as well as the effective communication and presentation of results. To do well in statistics one must develop and use formal logical thinking abilities. . This course is developed assuming that the student have completed the MURP 5151 course. It is assumed that the students have prior knowledge about undergraduate level statistics. Students should also have basic knowledge about elementary mathematics. In reality, most of the data that we use are multivariate in nature. The course will introduce a number of techniques (including both generalization of univariate methods and continuous multivariate data) that the student will be able to use in decision-making. This course will introduce not only theoretical aspect of statistics but also its application. Learning Outcome Overall aim of the course is to familiarize students with the ideas and methodology of certain multivariate methods together with their application in data analysis. Upon completion of the course, the students will be able to - 1. Derive key properties of the multivariate normal distribution and apply these to the analysis of multivariate data. 2. Use contingency tables to test hypotheses and estimate effect sizes for a variety of multivariate models. 3. Apply planning statistical analysis in support of planning problem analysis. 4. Develop critical thinking skills necessary to compete in the planning profession.

• Urban Analysis Technique

• Urban Analysis Technique (FW/Studio)

• Geographic Information System

• Geographic Information System (Lab/Studio)

• Remote sensing and Photogrammetry

• Remote sensing and Photogrammetry (Lab/Studio)

• Statistics for Planners

• Statistics for Planners

• Statistics for Planners -II

• Quantitative Methods, Analysis & Techniques