Advanced GIS

GIS and Spatial analysis offer a unique and insightful perspective on our world, serving as a distinctive lens through which we explore events, patterns, and processes that unfold on or near the Earth's surface. At its core, spatial analysis resides at the crossroads of human insight and computational power, combining the art of interpretation with the precision of spatial data analysis, modeling, machine learning, deep learning, and AI. This fusion of human expertise with advanced technologies is pivotal in shaping decision-making processes, enabling us to unravel complex spatial phenomena and make informed choices that drive progress and innovation.

This course is designed to immerse professionals in training in a rich learning experience, blending lab sessions with hands-on activities and engaging lectures and discussions through a holistic approach. The course not only covers spatial data science but also delves into the intricate realms of machine learning, deep learning, and AI. Participants will gain the knowledge and skills needed to apply these cutting-edge technologies to spatial analyses and decision-making processes. Throughout the course, the emphasis is on practical, real-world applications, including topics such as modeling, suitability analysis, pattern detection, deep learning, neural networks, dynamic visualization, and the nuanced examination of complex spatial datasets. This ensures that students are well-equipped with various quantitative methods, from descriptive to geostatistical methodologies. Finally, decision-making methods and visualization techniques are embedded to ensure we equip students with the practical skills to effectively interpret and communicate complex spatial data. These skills help bridge the gap between data analysis and real-world applications, fostering a deeper understanding of spatial relationships and their impact on decision outcomes.

This course is designed to fulfill the quantitative reasoning requirements for both the Master of Arts in Law and Diplomacy (MALD) and the Master of Global Affairs (MGA) programs.

Geospatial technology and GIS have become indispensable tools in today's data-driven world. GIS allows us to analyze, visualize, and interpret spatial data, offering profound insights into our environment, society, operations, management and systems. By diving into spatial analysis, you gain the ability to harness the power of location intelligence, which has applications in various fields including including urban planning, environmental management, public health, humanitarian aid, cybersecurity and policy development. GIS not only helps in understanding the 'where' of things but also enables informed decisions based on spatial patterns, relationships and location intelligence.

Geospatial technology and AI have become indispensable tools in our modern world, revolutionizing our capacity to leverage the wealth of available data, thereby improving our comprehension and problem-solving abilities in the face of intricate challenges. Geospatial technology excels in mapping and analyzing spatial information, and when seamlessly integrated with cutting-edge AI and deep learning techniques, it offers a powerful combination for the development of effective and pragmatic solutions in fields as diverse as climate change, healthcare, transportation, and resource management. This dynamic fusion of geospatial technology and AI not only redefines our approach to perceiving and interacting with our surroundings but also propels innovation and facilitates comprehensive problem-solving across a wide array of industries.

Effective decision-making is the keystone of success in any endeavor. Whether you're a manager, a researcher, or a policymaker, the ability to make informed decisions is paramount. GIS, multi-criteria evaluations (MCE) and data visualization tools serve as essential aids in this process. GIS provides the spatial context necessary for understanding the 'where' of a problem, MCE provides with techniques and methods to compare alternatives and drive objective decision-making, while data visualization simplifies the 'what' and 'how' aspects. This equips anyone with a comprehensive perspective on the challenges and opportunities associated with complex problems. Moreover, these skills empower professionals to make data-driven decisions, reducing uncertainty and increasing the likelihood of achieving desired outcomes.

Data visualization is the art of presenting data in a visually compelling manner. In an era where information overload is prevalent, the skill of data visualization is essential for conveying complex ideas and trends in a simple, understandable way. With data visualization, you can transform raw data into meaningful insights that resonate with your audience. In this course I combine different software (e.g., Tableau, ArcGIS Online and ArcGIS Pro), bringing different skills that help practitioners perform exploratory analysis, define hypothesis and convey their findings and recommendations.

Explore how spatial data, tools, and analysis techniques augment traditional data science. Understand that “spatial” means more than x,y coordinates and that place-based context reveals patterns in data that otherwise may be hidden. Start applying data engineering and visualization techniques in ArcGIS Pro and ArcGIS Notebooks.

Prediction is fundamental to data science. See how incorporating spatial properties into modeling workflows deepens understanding of data and adds predictive power. Learn how to apply random forest, a widely used machine learning approach, to solve problems. Train and evaluate a model, then use it to generate robust predictions.

Apply widely used spatial analysis techniques to answer this universal question asked by all kinds of organizations: Where is the best location for ? Perform a weighted overlay analysis that considers and ranks multiple suitability criteria. Learn how to transform data using functions to more completely represent suitability impact.

Does a pattern have meaning or is it a product of random chance? ArcGIS includes a suite of tools to help analysts identify patterns and clusters in data and determine if they are meaningful. Learn how to apply statistical clustering methods to analyze patterns in space as well as time. Create a spacetime cube, then use space-time pattern mining tools to explore spatiotemporal trends and determine where and when high and low clusters occur.

Take a deep dive into extracting information from massive data using deep learning. Learn how to automate the process of detecting objects and identifying features from imagery. Practice preparing training sample data, then use a neural network to train an object detection model.

Successful analysts and data scientists must be effective storytellers. Learn how to present a complex analysis using information products that resonate with your audience. Design and build interactive, visual stories that share the key information you want decision-makers to understand and act on.

In this section I invite you to explore what's achievable and get inspired by these achievements:

As an instructor, my foremost commitment is to establish an accessible classroom environment characterized by unwavering respect for every individual. Our class thrives on its rich diversity, a cornerstone in cultivating an equitable and culturally inclusive community. Diversity encompasses a spectrum of identities, spanning race, color, national origin, language, sex, disability, age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status, or genetic information. This is a moment where the unique skills and tools of GIS professionals and practitioners can contribute significantly to enhancing humanity's understanding, communication, and engagement in meaningful actions. In light of this, my goal is to raise consciousness about diversity, embracing inclusiveness as a means to foster acceptance and respect. I endeavor to integrate this ethos into my classes, professional endeavors, and research.

The Fletcher School offers numerous opportunities for meaningful engagement. By joining a community that values diversity and inclusivity, you can participate in enriching conversations and be part of a collective that celebrates differences. Visit the   Diversity, Equity, and Inclusion at Fletcher   website.

All classes are supported by the Data Lab, which provides an interdisciplinary methodological and technological support for a wide range of geospatial and data science applications, including GIS, data analysis and visualization, statistics, machine learning, digital humanities, text processing, and more. Please visit the   Data Lab   at Tish Library and find other GIS courses and workshops available to Tufts University students and faculty.

Explore some of the   Tufts GIS Award Winners   in the ESRI Conference.