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Tag: Yetunde Adesiyan

  • ‘How GIS can solve the urban challenge’

    ‘How GIS can solve the urban challenge’

    An expert, Yetunde Adesiyan, has called for deployment of Geographic Information Science (GIS) in resolving challenges of urbanisation.

    She said: “Urban Change Detection and Machine Learning Techniques’ can determine suitable sites for building roads for effective transportation network in Lagos metropolis.

    “Lagos is the largest urban agglomeration in Nigeria and one of the biggest and fastest-growing megacities in the world, with population from 12 to over 20 million people

    “As one of the fastest-growing cities in Africa and the world, it becomes imperative to visualise and analyse changes and patterns of urbanisation over time in this megacity.

    “By understanding urban growth patterns, urban planners can make informed decisions about infrastructure development, such as an effective road network, resource allocation, and environmental impact mitigation in the state.”

    Adesiyan said in a statement that “one of the spatial analysis techniques that can be used in urbanisation trend analysis is urban change detection.”

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    She said urban change detection is a process of monitoring and identifying changes in an urban system, using technology that compares satellite images of an urban system at different times and analyses how the landscape has evolved.

    Justifying the need to determine urban trend analysis, she said: “A sample case of using Urban Change Detection and Machine Learning Techniques to determine sites for building roads for an effective transportation network in the city.

    “With rising urban growth comes increased building footprints, and rising demand for transport. The need for good road network, in line with urban growth trend analysis, becomes key to mitigate environmental impact and ensure improvements in transport accessibility and connectivity.”

    Adesiyan added: “As traffic volume increases due to urban growth, effective road planning helps distribute traffic, reduce congestion, and improve the overall flow of vehicles.

    “In planning an effective road network, it is imperative to find suitable sites to construct these roads. This will involve analyzing road location selection parameters like proximity to settlements and land use zoning

  • How to tackle management problems with GIS, machine learning, by Adesiyan

    How to tackle management problems with GIS, machine learning, by Adesiyan

    An expert, Yetunde Adesiyan, has called for the development of skills in Geographic Information Science (GIS) and machine learning to tackle real-world challenges.

    She said in a statement that operational challenges can be addressed through innovation.

    She said GIS are very critical to the integration, analysis, and visualization of geographic data, which opens the pathway to better decision-making.

    Adesiyan also said it can improve planning, better resource management, and effective communication in urban planning, environmental management, and infrastructure development.

    According to her, through the understanding of spatial patterns and relationships, organizations, institutions and individusls can manage assets, assess risks, plan for future growth, and create more informed and sustainable solutions to complex problems.

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    From mapping storm surge hazard zones along Baltimore’s coastal perimeter to predicting the distribution of endangered species in California, Adesiyan has built a reputation as a geospatial expert using technology to solve pressing global problems.

    With more than 15 years of experience spanning business strategy, oil services, and banking, she has seamlessly transitioned into the fast-evolving world of Geographic Information Systems (GIS) and geospatial analytics.

    Armed with a master’s degree in GIS and Cartography from Sam Houston State University, Huntsville, Texas, Adesiyan has consistently demonstrated how advanced geospatial tools can drive innovation across industries. Her work integrates spatial analysis with machine learning, uncovering patterns and insights that improve decision-making and long-term planning.

    One of her groundbreaking studies applied species distribution modeling to forecast the probable habitats of an endangered fox species in California, contributing fresh insights for conservation and resource management.

    Her expertise extends to high-impact infrastructure and energy projects. She has carried out site suitability analyses for offshore wind energy farms in BOEM-designated lease areas of the United States, identified High Consequence Areas (HCAs) around pipeline infrastructures in Texas, and employed urban change detection techniques using ERDAS Imagine and ArcGIS Pro.

    These efforts not only highlight her technical skills but also her commitment to applying geospatial intelligence in ways that enhance safety, sustainability, and efficiency.

    Beyond her professional projects, Adesiyan has contributed to academic research, co-authoring two peer-reviewed journal articles on renewable energy, including an in-depth review of switchgrass as a viable bioenergy feedstock. Her work bridges academia and industry, positioning her as both a practitioner and thought leader in geospatial science.

    Drawing from her earlier career as a business strategist and development manager, where she led cross-functional teams in banking and oil services, Adesiyan brings a unique leadership perspective to her current role. She continues to advocate for the integration of geospatial technologies in strategic planning, ensuring that organizations are not only data-driven but also future-focused.

    Adesiyan stands out as a professional deeply invested in harnessing GIS, analytics, and machine learning to shape smarter solutions for environmental, industrial, and urban challenges. Her work highlighted the growing importance of geospatial intelligence in addressing the complex realities of a rapidly changing world.