How to Use Spatial Data Science in your Site Planning Process? [CARTOframes]

Many companies need to analyze large datasets that include location information. To be able to derive business insights from these datasets you need a solution that provides geospatial analysis functionalities and can scale to manage large volumes of information. The combination of CARTO and Databricks allows you to solve this kind of large scale geospatial analytics problems. CARTO provides a location intelligence platform to discover and predict key insights through location data. In this session we will see how we can integrate CARTO and Databricks and how we can take advantage of this combination to solve specific problems for industries such as logistics, telecommunications or financial services.

In this webinar in partnership with Foursquare, we outline how using POI & visits data can help QSRs strategically optimize their portfolio of site locations to generate more revenue. You can watch the recorded webinar at: https://go.carto.com/webinars/qsr-site-selection

In this webinar in partnership with Databricks, you learn how to build more accurate catchment area analysis using human mobility location data. You can watch the recorded webinar at: https://go.carto.com/webinars/databricks-spatial-data-science

In this webinar, Transparent's and CARTO's teams discuss how leaders in Real Estate and Travel are leveraging Location Intelligence to drive investment analysis and geomarketing decisions.

Discover how you can take a geographic approach to machine learning to help you "See What Others Can't". Imagery and remotely sensed data is a valuable resource for many organisations who have made substantial investment obtaining the data. The field of machine learning is both broad and deep and is constantly evolving. Using ArcGIS and machine learning allows organisations to derive valuable new content. ArcGIS is an open, interoperable platform that allows for the integration of complementary methods and techniques that empower ArcGIS users to solve complex, real-world problems in a fundamentally spatial way. These slides were used as part of episode 6 of the Esri Ireland 'Do One Thing Well' Webinar Series. You can watch the webinar recording here: https://youtu.be/zAzNqw4KZRk For any questions relating to the contents of this webinar or other GIS related inquiries, you can contact our team via mapsmakesense@esri-ireland.ie.

This document provides an overview of databases and WebGIS. It discusses different types of databases including MySQL, PostgreSQL, and spatially-enabled databases. It compares MySQL and PostgreSQL, covering when each would be used. It also covers database data conversions between formats like JSON, GeoJSON, CSV, SHP, and KML/KMZ. For WebGIS, it defines it as a distributed information system comprising a server and client, where the server is a GIS server and client a web browser. It discusses purposes, technologies, languages/frameworks like Python, JavaScript, GeoDjango, and case studies for building WebGIS systems.

This study has done to identify the applicability of Mobile GIS as a method of data collection for mobility mapping.

This document discusses geospatial digital twins. It begins by introducing the vision of digital earth and digital twins. It then discusses how digital twin technology can disrupt and improve geospatial business processes like data acquisition, storage, processing, and presentation. Examples of digital twins for healthcare and aircraft simulations are provided. The document also discusses VirtualSingapore, a 3D digital twin of Singapore used for urban planning, disaster management and tourism. It explores how technologies like crowdsourced data, augmented reality, and 3D geospatial analytics can enhance geospatial digital twins. In the end, the document envisions how digital twins could allow users to interactively explore and zoom in on high resolution geospatial data from space down to individual objects.

SuperMap Software Co., Ltd provides distributed, cross-platform, 3D, and big data GIS solutions. Their flagship product is SuperMap GIS 10i, which offers more effective, elastic, stable and real-time functionality. The solution includes cloud, edge, and terminal components that allow for distributed processing and analysis of vector, raster, imagery and other geospatial data across multiple platforms including web, mobile, and desktop.

GIS is a system for managing and analyzing geographic data. It uses two main data models: vector, representing points, lines and polygons; and raster, representing data as a grid of cells. Common file formats include shapefiles for vector data and GeoTIFF and MrSID for raster. GIS data is referenced using coordinate systems like WGS84 for global latitude/longitude or HK80Grid for Hong Kong. ESRI's ArcGIS software allows viewing, editing, and publishing this geospatial data for mapping and analysis.

This document discusses using machine learning and computer vision techniques with satellite imagery to generate addressing systems for areas that currently lack adequate street addressing. It describes a generative addressing scheme that uses hierarchical and linear descriptors, such as region names indicating orientation and distance from downtown and road names indicating distance from the center and orientation. The document outlines a pipeline that involves predicting road networks from satellite imagery, partitioning regions based on road connectivity, and assigning addressing cells along roads with distance and block offsets. Results show this approach can improve street address coverage to 80% for unmapped developing areas by discovering road networks in non-urban settings and defining regions according to natural boundaries.

Abstract-This era unlike any, is faced with explosive growth in the size of data generated/captured. Data growth has undergone a renaissance, influenced primarily by ever cheaper computing power and the ubiquity of the internet. This has led to a paradigm shift in the E-commerce sector; as data is no longer seen as the byproduct of their business activities, but as their biggest asset providing: key insights to the needs of their customers, predicting trends in customer’s behavior, democratizing of advertisement to suits consumers varied taste, as well as providing a performance metric to assess the effectiveness in meeting customers’ needs. This paper presents an overview of the unique features that differentiate big data from traditional datasets. In addition, the application of big data analytics in the E-commerce and the various technologies that make analytics of consumer data possible is discussed. Further this paper will present some case studies of how leading Ecommerce vendors like Amazon.com, Walmart Inc, and Adidas apply Big Data analytics in their business strategies/activities to improve their competitive advantage. Lastly we identify some challenges these E-commerce vendors face while implementing big data analytic

FOSS4G refers to free and open source software for geospatial applications. Using FOSS4G provides benefits like increased flexibility, rapid innovation, lower costs, and ability to customize software to specific needs. Spatial SQL allows querying and analyzing spatial data in databases by treating geometry as another data type. PostGIS is an open source spatial database extender for PostgreSQL that allows GIS functions and spatial indexing to be used in queries. PostGIS supports common spatial functions and data types and provides better performance than desktop GIS software or file-based formats for large-scale spatial analysis and management tasks.

Are you a Data Scientist working in the Real Estate industry? Are you trying to build a Data Science team with expertise in spatial? We bring the London Real Estate Data Science community together to discuss use cases such as whitespace analysis, twin area analysis & indoor analytics - sharing best practices and experiences from both residential and commercial. Jaime Sanchez walked through a specific case of Spatial Data Science applied to Shared Workspace investment analysis, with an interactive component, before we break out into a discussion about the challenges and opportunities of building Data Science teams in the Real Estate sector. Geolytix joined the conversation to speak about location planning. As trusted advisors, they help their customers decide how many stores, who to acquire, where to open, which format and how to optimize home delivery and click & collect operations. Visit our website for more information: https://carto.com/

Conceptual models of geographical phenomena abstract and simplify aspects of reality for representation in geographic information systems (GIS). Data can be represented as discrete entities with boundaries or precise attributes, or as continuous fields that vary smoothly over space. GIS uses both vector and raster data structures, with vectors best for objects and topology but rasters more suitable for analysis of continuous surface variables like elevation.

RINEX files contain GPS data collected at receiver stations in an open format to allow for processing using different software. There are three main types of RINEX files - observation data files containing GPS measurements, navigation message files containing ephemeris data, and meteorological files. GAMIT and GLOBK are widely used open source software for processing and combining GNSS data. GAMIT analyzes GPS data to estimate parameters like station positions and satellite orbits through least squares estimation. GLOBK combines solutions from different techniques like GPS, SLR, VLBI using their parameter estimates and covariance matrices.

Building Information Modelling is changing the way the engineering, architecture and construction industry is operating. The availability of BIM models provide a very rich source of data but due to the use of specific data models and standards integrating this data with GIS introduces challenges. In this presentation we introduce BIM and the major differences with GIS, we give an overview of the standards in the BIM end Geo domain, introduce the major open source BIM tools and demonstrate the integration of BIM models in a GIS environment.

Dans ce webinar on évoquera comment utiliser les données géospatiales pour stimuler les entreprises après la COVID19 avec CARTO et Arkeup.

En este webinar repasamos - mediante una demostración con el mercado de Real Estate de Los Angeles como ejemplo - cada uno de los cinco pasos que la plataforma de CARTO sigue para una toma de decisiones eficaz basada en los datos. Watch it now at: https://go.carto.com/carto-pasos-dato-toma-decisiones-recorded

In this webinar, learn how to integrate spatial data and analysis to your data science models using CARTOframes—a Python package that allows data scientists to seamlessly integrate CARTO maps, data, and analysis into their current environment. Watch the recorded at: https://go.carto.com/webinars/spatial-analysis-carto-python-recorded

In this webinar in partnership with Safegraph, you learn how to use spatial analysis and leading POI data to drive superior market analysis workflows. Watch the recorded webinar at: https://go.carto.com/webinars/safegraph-market-analysis-recorded

Discusses Location Intelligence as the Next Evolution of Business Applications. Shows Cognos v10 Map Integration

I designed the entire end-to-end trading architecture of a hedge fund. The execution system for integrating a fund with Credit default swap capabilities and also solved Hedge fund's liquidity constraint in moving funds across the countries.

The traditional approach to insurance pricing involves fitting a generalized linear model (GLM) to data collected on historical claims payments and premiums received. The explosive growth in data availability and increasing competitiveness in the marketplace are challenging actuaries to find new insights in their data and make predictions with more granularity, improved speed and efficiency, and with tighter integration among business units to support strategic decisions. In this session we will share our experience implementing deep hierarchical neural networks using TensorFlow and PySpark on Databricks. We will discuss the benefits of the ML Runtime, our experience using the goofys mount, our process for hyperparameter tuning, specific considerations for the large dataset size and extreme volatility present in insurance data, among other topics. Authors: Bryn Clark, Krish Rajaram

This webinar focuses on working with our Data Observatory using the CARTOframes library for Python. Our speakers, Holly Orr, and Alex Roth, present tips and solutions to common problems encountered when working with demographic data. Watch it now at https://go.carto.com/tips-working-demographic-data-webinar-recorded

- Location data from sources like social media, sensors, and smart devices is increasingly important for improving city services, security, and operations in smart cities (paragraph 1, 2) - Oracle provides tools for managing and analyzing large volumes of spatial and location data using big data technologies like Hadoop and streaming data platforms to enable use cases like predictive analytics (paragraph 3, 4, 5, 19) - Oracle's spatial capabilities allow for indexing, visualization, and analysis of geospatial vector and raster data at scale, including tools for data preparation, spatial queries, and analyzing streaming location data (paragraph 10, 13, 14, 20)

Lepton provides a location Intelligence platform , MarketPulse, that organize enterprise business information geographically and make it universally accessible and useful in a unified manner to entire Sales & Marketing ecosystem. It facilitate Connect with right people at the right time at the right place, Optimise people and assets, Make better decisions.