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What is Urban Network Analysis Toolbox for ArcGIS?

The City Form Lab has introduced a groundbreaking toolbox tailored for the examination of urban networks. This pioneering ArcGIS toolbox stands out as the first of its kind, incorporating centrality tools that enable the calculation of five unique graph analysis metrics on spatial networks: reach, gravity, betweenness, closeness, and straightness. Furthermore, it contains redundancy tools that compute the redundancy index, pinpoint redundant pathways, and evaluate the wayfinding index. Remarkably, these tools feature three significant capabilities that enhance their utility in spatial analysis of urban street networks. To begin with, they can take into account both geometry and topology in the input networks, allowing the incorporation of metric distance (like meters) and topological distance (such as turns) as impedance factors during analysis. Additionally, unlike previous software that only addressed two network components—nodes and edges—the UNA tools introduce a third component: buildings, which act as the spatial units for all analytical evaluations. This holistic methodology not only bolsters the precision of urban analysis but also yields richer insights into the interactions within urban settings. As urban environments continue to evolve, such tools will be essential for planners and researchers aiming to understand complex urban dynamics.

What is Aspect Analytics?

Aspect Analytics introduces an advanced spatial multi-omics platform that revolutionizes collaborative data analysis and management across diverse scientific fields. This innovative tool is specifically designed for research teams engaged in drug development, biomarker discovery, pathology evaluation, and various other applications, enabling them to achieve remarkable research breakthroughs. By integrating multi-omics data into a cohesive and collaborative interface, Aspect Analytics significantly boosts teamwork across different disciplines and promotes innovative thinking. Users can effortlessly merge multiple spatial omics measurements into a singular visual format, facilitating simultaneous examination of the data. The platform adeptly amalgamates information from all spatial multi-omics assays, ensuring that critical insights are easily accessible. It also boasts the ability to securely store and manage extensive datasets, scaling up to petabytes, allowing users to retrieve their information from anywhere at any time. Additionally, the platform is designed with a scalable and customizable data infrastructure that is tailored to meet specific requirements, accommodating spatial biology data from numerous technologies and vendors, irrespective of the data format. An added advantage for users is the capability to set up automated workflows, which streamline the analysis of large datasets concurrently, ultimately enhancing the efficiency of research efforts. This groundbreaking approach not only simplifies data management but also significantly increases the opportunities for scientific discovery, thereby shaping the future of research in the life sciences. As the platform continues to evolve, it promises to keep pushing the boundaries of what is possible in the realm of multi-omics research.

Media

Media

Integrations Supported

ArcGIS

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

City Form Lab

Company Location

United States

Company Website

cityform.mit.edu/projects/urban-network-analysis.html

Company Facts

Organization Name

Aspect Analytics

Date Founded

2018

Company Location

Belgium

Company Website

www.aspect-analytics.com

Categories and Features

Urban Planning

Not specified

Categories and Features

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