May 2022 Summaries

Ghost kitchens, also known as dark or virtual restaurants, are kitchens that deliver restaurant-quality food without a physical restaurant attached to it. The market for ghost kitchens is expected to grow significantly, with estimates suggesting it will be worth $1 trillion by 2030 in the US alone. These businesses are attractive due to lower costs, including rent and labor expenses, as well as an opportunity to exploit an unsaturated market in residential areas with low competition from brick-and-mortar restaurants. To succeed, ghost kitchens need to identify locations with a strong local market, high population density within a 5-mile radius, and a suitable customer base. Analyzing spatial patterns using data visualization tools and geospatial analysis can help pinpoint successful locations for ghost kitchens, such as areas outside the urban core in places like Vernon Beverly Hills and Ladera Heights. Additionally, considering factors like rent, zoning, and travel time is crucial for a city like Los Angeles known for its slow traffic.

Procedural Ltd, the company behind Procedural GL, a popular open source 3D mapping library, is joining forces with CARTO to enhance the visualization capabilities of its platform. CARTO's professional services team will work closely with the Procedural GL team to deliver cutting-edge solutions that were previously unimaginable. The integration of Procedural GL's GPU-first architecture and deck.gl's data-visualization capabilities will enable customers to create rich, interactive visualizations that better understand geospatial data. This collaboration aims to push the boundaries of map rendering, leveraging the latest browser APIs such as WebGPU, and providing a seamless user experience on mobile devices. With Procedural GL's expertise in 3D mapping and deck.gl's focus on data visualization, CARTO will become an even more powerful platform for Location Intelligence, empowering customers to optimize business processes and predict future outcomes through Spatial Data Science.

CARTO for Retail is a cloud-native analytics platform designed specifically for retailers, addressing key data challenges and offering location-based insights to inform strategic decisions on store locations, supply operations, and marketing efforts. The platform is built on top of leading cloud data platforms such as Google BigQuery, Amazon Redshift, Snowflake, and Databricks, providing seamless connectivity and scalability. It offers advanced analytical functions, including spatial analysis tools like Clustering Commercial Hotspots Twin Areas White Space and Store Revenue Prediction analysis, as well as a suite of retail-specific modules and pre-built applications for Retail Location Intelligence. CARTO also provides developer resources, including APIs and front-end frameworks, to enable retailers to build their own visualizations and spatial applications.

OOH (out-of-home) advertising is growing in tandem with travel and commuting speed, with major brands investing heavily in creative campaigns in high-traffic areas. To stay ahead of the competition, outdoor media owners and planners are turning to Location Intelligence and GIS to improve their strategies. This includes improved targeting through geospatial data analysis, enhanced campaign planning and analysis, heightened audience analysis, refined inventory visualization and exploration, and increased ROI through geomarketing strategies. By leveraging these tools, OOH professionals can better align with target audiences, visualize and analyze data from a holistic perspective, and make informed data-driven decisions to develop efficient advertising solutions that promote a greater return on investment.

The text discusses the development of a Wildfire Risk Index (WRI) using spatial data and weather forecasts to estimate the potential risk of wildfire ignition in different regions. The WRI is based on a combination of geographical, meteorological, and land cover variables, including standardized precipitation evapotranspiration index (SPEI), soil moisture, and land cover type. The analysis shows that wildfires tend to occur during summer and fall months when drought conditions and extreme winds become more frequent and vegetation becomes dry. The WRI can be used by government agencies, insurance companies, real estate/investment companies, and power utilities to develop wildfire suppression plans, provide affordable coverage, prioritize investments in treating wildland fuels, and design contingency plans for energy supply during disaster recovery. The analysis also highlights the importance of considering human activities such as campfires or smoking as potential causes of wildfires. The WRI can be used to improve home insurance by adjusting coverage costs based on risk level and providing targeted marketing campaigns to high-risk areas. Future work includes exploring other meteorological variables, using wildfire data with better temporal resolution, and combining the temporal information to construct the index.

Spatial Leaders Gather in London for #SDSC22` Having brought together more than 12,000 experts online in 2020 and 2021, the Spatial Data Science Conference is excited to host its long-awaited in-person conference in London this week. The UK edition of #SDSC22 will take place on May 19, bringing together hundreds of data scientists, developers, academics, and business leaders for a full day of discussions and discoveries about the future of Spatial Data Science. One day prior to the conference, interactive spatial modeling workshops will be held by experts in the field. The conference will feature an opening keynote from Javier de la Torre, followed by sessions on how leading enterprise organizations use Spatial Data Science in their daily operations. The event will take place at the Royal Geographical Society and attendees are encouraged to connect with others using #SDSC22 on social media. Those who cannot attend the London conference can look forward to attending the Spatial Data Science Conference in New York City on October 20th, 2022.

We are excited to announce that CARTO will be attending and presenting at Snowflake Summit 2022, taking place June 13-16 in Las Vegas, Nevada, where we will showcase our collaboration with Snowflake and discuss the latest advancements in spatial analytics. Our session will be presented by Sergei Sokolenko from Snowflake and Javier de la Torre from CARTO, who will explore how to use Snowflake and CARTO together to make real-time decisions for a Quick Commerce company. We also have a designated stand throughout the conference where attendees can interact with live demos of the CARTO platform and schedule meetings with our team.

CARTO has been selected as a strategic partner by SEAT and Volkswagen, two major automotive companies, to support the Future: Fast Forward project aimed at turning Spain into a hub for electric vehicles in Europe. The goal of this project is to create a comprehensive ecosystem for electric vehicle production, including battery manufacturing, localization of essential components, and training on digitalization and circular economy. CARTO's expertise in spatial analytics will be applied to key EV charging infrastructure questions, such as EV station analysis. This partnership highlights the growing importance of data-driven decision-making in the electric vehicle industry.

Hexagons are a type of spatial grid used in location intelligence that offer several advantages over irregular zoning, including tessellation and well-structured geometry. They can be particularly useful for representing curves of geographic features and gradual spatial changes. However, they also have some limitations, such as potential loss of raw data and precision issues when aggregating data. CARTO offers a global hierarchical grid system called H3 that provides a workaround to these problems and enables efficient spatial operations. H3 grids are well-suited for machine learning and modeling flows and movement, making them ideal for users with specific use cases. By using hexagons and H3 grids, users can create more accurate and informative maps that tell compelling stories about their data.

The concept of equity has gained significant attention recently, particularly within President Biden's Build Back Better framework, which aims to empower individuals and ensure access to essential resources regardless of location, race, or wealth. A wide gap in accessibility exists between high- and low-income neighborhoods, urban and rural areas, and communities of differing ethnicities. Spatial analysis and opportunity index scores can help determine equitable access to resources. The use of location data can aid in discovering equity gaps, such as in tree coverage, transportation safety, and opportunity. Cities like Chicago and Seattle are utilizing location intelligence platforms like CARTO to analyze and visualize data, leading to informed decision-making and improved outcomes for vulnerable communities.

At CARTO, they will be sponsoring and attending multiple Amazon Web Services (AWS) Summits across the world in May and June, bringing together the cloud computing community to collaborate, connect, and learn about how to modernize data warehouses, use advanced analytics, and empower digital transformation using AI. CARTO will showcase their Spatial Extension for Amazon Redshift at various demos, highlighting its capabilities for site selection, geomarketing, market analysis, and more. The company is also participating in two speaking sessions at the AWS Summit Madrid on May 5, discussing how to build global leaders through technology and unlock the power of data with Amazon Redshift. Additionally, CARTO will be attending AWS Summits in Stockholm, Berlin, and Milan, offering a range of demos and insights into Location Intelligence and its applications for businesses.