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Related Concept Videos

Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
Responses to Drought and Flooding02:41

Responses to Drought and Flooding

Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Levels of Use of a GIS01:29

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
Habitat Fragmentation02:31

Habitat Fragmentation

Habitat fragmentation describes the division of a more extensive, continuous habitat into smaller, discontinuous areas. Human activities such as land conversion, as well as slower geological processes leading to changes in the physical environment, are the two leading causes of habitat fragmentation. The fragmentation process typically follows the same steps: perforation, dissection, fragmentation, shrinkage, and attrition.
Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

As the construction industry moves towards more eco-friendly practices, concrete's adaptability and its ability to incorporate sustainable features make it a key material in the drive towards greener building solutions.
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground cistern.

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Related Experiment Video

Updated: Jul 10, 2026

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
07:12

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Published on: December 12, 2025

Fusion sensing for urban resilience.

Yu Liu1,2,3, Wenjie Fan1, Qinghua Guo1

  • 1Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China.

Innovation (Cambridge (Mass.))
|July 9, 2026
PubMed
Summary

Enhancing urban resilience requires integrated sensing and artificial intelligence. This approach enables smart decision-making for sustainable development goals amidst global change challenges.

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Cities As Interfaces of Zoonotic Hazard Emergence: Development of the New York City Tick and Wildlife Urban Surveillance System
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Cities As Interfaces of Zoonotic Hazard Emergence: Development of the New York City Tick and Wildlife Urban Surveillance System

Published on: March 10, 2026

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Last Updated: Jul 10, 2026

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
07:12

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Published on: December 12, 2025

Cities As Interfaces of Zoonotic Hazard Emergence: Development of the New York City Tick and Wildlife Urban Surveillance System
10:17

Cities As Interfaces of Zoonotic Hazard Emergence: Development of the New York City Tick and Wildlife Urban Surveillance System

Published on: March 10, 2026

Area of Science:

  • Urban planning and sustainability science.
  • Environmental monitoring and sensor networks.
  • Artificial intelligence and data analytics.

Background:

  • Achieving sustainable development goals is hindered by inadequate monitoring of urban stressors and system responses.
  • Lack of fine-grained spatiotemporal data limits smart decision support for urban resilience.
  • Global change necessitates proactive strategies for urban resilience.

Purpose of the Study:

  • To propose an integrated framework for monitoring urban systems.
  • To enhance decision-making capabilities for urban resilience studies.
  • To address the limitations of current sensing and analytical frameworks.

Main Methods:

  • Integration of multi-source sensing technologies: remote sensing, social sensing, and Internet of Things (IoT)-based sensing, termed 'fusion sensing'.
  • Real-time data collection and analysis using fusion sensing.
  • Application of artificial intelligence (AI) methods for short-term emergency management and long-term planning.

Main Results:

  • Fusion sensing enhances the monitoring capability of urban systems.
  • Real-time data facilitates adaptive responses to disturbances.
  • AI optimizes resource allocation and improves urban resilience.

Conclusions:

  • The integration of fusion sensing and AI is vital for enhancing urban resilience.
  • Proactive and informed decision-making is achievable through these technologies.
  • Collaboration among stakeholders is essential to leverage these advancements for sustainable urban development.