Lecture

GIS and Participative Planning: Case Study

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture introduces Geographic Information Systems (GIS) through a case study on GIS and participative planning. It covers topics such as territorial dynamics in cities like Thies and Seychelles, challenges related to rapid growth, water management issues, and urban planning constraints. The lecture also delves into participative planning processes, including systemic analysis and workshops for capacity building and data validation. It emphasizes the role of GIS as a communication tool to facilitate information sharing among stakeholders with limited technical skills. Specific constraints, predefined indicators, and data updating processes are discussed, along with the importance of simplicity and tailored approaches in participative dynamics.

In MOOC

Geographical Information Systems 1

In this first part of the course, we will focus on the digitization and the storage of geodata. In particular, you will learn:

To characterize spatial objects and/or phenomena (territory modeling) with respect to their position in space (through coordinate systems, projections, and spatial relationships) and according to their intrinsic nature (object/vector mode vs. Image/raster mode);
About the different means used to acquire spatial data; including direct measurement, georeferencing images, digitiza

Official source

Related concepts (19)

Theories of urban planning

Planning theory is the body of scientific concepts, definitions, behavioral relationships, and assumptions that define the body of knowledge of urban planning. There are nine procedural theories of planning that remain the principal theories of planning procedure today: the Rational-Comprehensive approach, the Incremental approach, the Transformative Incremental (TI) approach, the Transactive approach, the Communicative approach, the Advocacy approach, the Equity approach, the Radical approach, and the Humanist or Phenomenological approach.

Urban planning

Urban planning, also known as town planning, city planning, regional planning, or rural planning, is a technical and political process that is focused on the development and design of land use and the built environment, including air, water, and the infrastructure passing into and out of urban areas, such as transportation, communications, and distribution networks and their accessibility.

Technical communication

Technical communication (or Tech Comm) is communication of technical subject matter such as engineering, science, or technology content. The largest part of it tends to be technical writing, though importantly it often requires aspects of visual communication (which in turn sometimes entails technical drawing, requiring more specialized training). Technical communication also encompasses oral delivery modes such as presentations involving technical material.

Communication

Communication is usually defined as the transmission of information. The term can also refer to the message itself, or the field of inquiry studying these transmissions, also known as communication studies. The precise definition of communication is disputed. Controversial issues are whether unintentional or failed transmissions are included and whether communication does not just transmit meaning but also create it. Models of communication aim to provide a simplified overview of its main components and their interaction.

Training, validation, and test data sets

In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets.

Related lectures (39)

Linear and Ridge Regression

Covers linear and ridge regression, overfitting, hyperparameters, and test sets.

Model Assessment and Hyperparameter Tuning

Explores model assessment, hyperparameter tuning, and resampling strategies in machine learning.

Using cross-validation: Building a final predictor

Covers the interpretation of cross-validation risk estimates and building a final predictor from cross-validation results.

Urban Planning: African Cities MOOC: African cities I, An introduction to urban planning

Covers the fundamentals of urban planning in African cities, emphasizing community involvement.

Playing Connect Four