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Low-Impact Tourism Modelling | Cities | Envisioning
  1. Home
  2. Research
  3. Cities
  4. Low-Impact Tourism Modelling

Low-Impact Tourism Modelling

This solution addresses significant environmental and societal challenges posed by traditional tourism practices, such as pollution, resource depletion, and cultural disruption. This innovative approach utilises advanced data analytics, Geographic Information Systems (GIS), Internet of Things (IoT) sensors, and artificial intelligence (AI) to collect and analyse data on tourist activities, environmental conditions, and community feedback. By doing so, LITM helps city planners manage and mitigate the adverse effects of tourism, optimising visitor distribution, reducing overcrowding, and protecting sensitive areas.

Related Organizations

City of Venice

IT · Government Agency

95%

The municipal government of Venice, Italy.

Deployer
Mabrian Technologies logo
Mabrian Technologies

ES · Company

95%

A travel intelligence platform that analyzes big data to help destinations manage tourism sustainability and demand.

Developer
Murmuration logo
Murmuration

FR · Company

95%

Uses satellite data to monitor the environmental impact of tourism.

Developer

Supporting Evidence

Article

Leveraging spatiotemporal big data for sustainable destination development: an interdisciplinary approach

Information Technology & Tourism · Aug 22, 2025

This research presents a prototype system for the Island of Corfu that integrates IoT sensing networks, Earth Observation imagery, and user-generated content to model tourism flows and environmental dynamics for sustainable governance.

Support 98%Confidence 100%

Paper

Leveraging spatiotemporal big data for sustainable destination development: an interdisciplinary approach

Information Technology & Tourism · Aug 22, 2025

This study presents a prototype system for the Island of Corfu that integrates IoT sensing networks, Earth Observation imagery, and user-generated content to model tourism flows and environmental dynamics, enabling real-time governance and sustainable planning.

Support 95%Confidence 92%

Paper

(Big) Data Driven Strategic Decision-Making in Overtourism Management

Springer · Aug 28, 2025

This paper explores the transformative role of Big Data Analytics in addressing overtourism, using descriptive, diagnostic, predictive, and prescriptive analytics to quantify and manage visitor pressures.

Connections

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Autonomous Sustainability Monitoring

This solution addresses urban challenges such as pollution, resource inefficiency, and disaster management. It integrates a network of sensors, artificial intelligence (AI), and data analytics to continuously track and manage environmental parameters like air and water quality, energy consumption, and waste management in real-time. By providing accurate, actionable data, these systems help city planners and policymakers design better sustainability strategies, enhancing urban living conditions and reducing environmental impacts.

Technology Readiness Level
6/9
Diffusion of Innovation
2/5

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The Data Appeal Company

IT · Company

95%

Provides data analysis on human experience and tourism flows for destination management organizations.

Developer
UN Tourism (UNWTO)

ES · Nonprofit

95%

The United Nations agency responsible for the promotion of responsible, sustainable and universally accessible tourism.

Standards Body
ForwardKeys logo
ForwardKeys

ES · Company

90%

Analyzes global flight booking data to predict traveler trends and flows.

Developer
Segittur

ES · Government Agency

90%

State-owned company responsible for promoting innovation and technology in the Spanish tourism sector.

Standards Body
TCI Research logo
TCI Research

BE · Company

90%

A travel data intelligence agency focusing on destination reputation and resident sentiment.

Developer
Bloom Consulting logo
Bloom Consulting

ES · Company

85%

Specializes in Nation Branding and City Branding, using data to analyze digital demand.

Developer
Esri logo
Esri

US · Company

85%

Global leader in GIS software (ArcGIS), providing the spatial analytics layer used by thousands of local governments for urban planning and policy.

Developer
Orange Business logo
Orange Business

FR · Company

85%

The B2B division of Orange Group, offering the 'Flux Vision' solution.

Developer
Mastercard logo
Mastercard

US · Company

80%

Global payments technology company offering the 'Tourism Insights' platform.

Developer
Support 92%
Confidence 95%

Paper

IoT and AI-driven approaches to sustainable eco-tourism and cultural heritage management in Uzbekistan: Multidisciplinary frameworks and local implementation

E3S Web of Conferences · Jan 15, 2026

The paper explores multidisciplinary frameworks utilizing IoT and AI to manage eco-tourism and cultural heritage sustainably, focusing on local implementation in Uzbekistan.

Support 90%Confidence 95%

Paper

Digital Twins in Smart Tourist Destinations: Addressing Overtourism, Sustainability, and Governance Challenges

World · Nov 6, 2025

Investigates the application of Digital Twin technology in smart destinations to simulate and manage overtourism, enhancing sustainability and governance through data-driven modeling.

Support 90%Confidence 95%
Technology Life Cycle
1/4

Low-Impact Tourism Modelling (LITM) addresses the significant environmental and societal challenges posed by traditional tourism practices. As cities and popular destinations deal with the adverse effects of mass tourism—such as pollution, resource depletion, and social and cultural disruption—LITM emerges as a vital solution to promote sustainable travel. This innovative model leverages advanced data analytics and predictive technologies to minimise tourism's ecological footprint while enhancing the cultural and social experiences for both visitors and local communities.

At its core, LITM integrates a suite of technologies, including Geographic Information Systems (GIS), Internet of Things (IoT) sensors, and artificial intelligence (AI). These tools work in tandem to collect and analyse vast amounts of data related to tourist activities, environmental conditions, and community feedback. By utilising GIS, urban planners can map tourist flows and identify areas of high impact. IoT sensors monitor environmental parameters like air and water quality, providing real-time data to assess the ecological impact of tourism. AI algorithms then process this information to predict potential hotspots and recommend actionable strategies for mitigating negative effects.

One of the primary benefits of Low-Impact Tourism Modelling is its ability to offer precise and proactive management of tourism activities. By forecasting visitor numbers and their potential impact on specific locations, city planners can implement measures such as visitor caps, dynamic pricing, and alternative route suggestions. These strategies help disperse tourist traffic, reduce overcrowding, and protect sensitive areas. Furthermore, LITM supports the creation of tailored experiences that align with sustainable practices, thereby fostering a more conscious and responsible tourism culture.

As urban areas continue to grow and attract more visitors, the pressure on local infrastructure and natural resources intensifies. LITM provides a scalable and adaptable framework that not only mitigates the environmental impact but also enhances the quality of life for residents. By promoting sustainable tourism, cities can preserve their unique heritage and ecosystems while still benefiting economically from tourist activities.

Technology Readiness Level
7/9Prototype Demonstration
Diffusion of Innovation
2/5Early Adopters
Technology Life Cycle
2/4Growth
Category
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