Specialists of KB "Panorama" have prepared an educational video material demonstrating a practical approach to creating custom scripts for spatial data processing using artificial intelligence. The video tutorial is dedicated to how to use modern AI tools to accelerate Python development and solve applied problems in the GIS "Panorama" environment, without spending much time on manual code preparation from scratch.

The educational material is based on a real production task: automatic placement of pickets along a pipeline in the object's linear coordinate system. The "Linear Coordinate System" (LCS) is a system for measuring linear coordinates along an object's contour from the first point of the object to a given point. This measurement is performed in meters along the axis, sequentially passing through all contours of the linear object from the first point of the first contour's metric. The LCS is formed relative to calibration points located along the object's contour, with the axis contours possibly adjoining each other or located with gaps. The calibration points provide the transition from plane rectangular coordinates X, Y to the linear coordinate M along the object and back.

The video tutorial analyzes a scenario in which, based on a selected point object and one or more linear objects, new points are formed every kilometer along the LCS, rather than along the geographic length of the line on the map. This example clearly shows how automating script writing helps perform spatial analysis more accurately, faster, and in compliance with specified rules for metric and semantic formation.

Artificial intelligence is becoming a working tool for preparing scripts based on user requests, relying on materials from the open panorama-sdk repository. For GIS specialists, this means a faster transition from problem statement to a ready-made data processing scenario, lowering the entry barrier to programming, and the ability to focus not on technical routine, but on checking analysis logic and interpreting results. This approach can serve as a convenient starting point for mastering Python and the MAPAPI interface when solving spatial data processing problems.

You can view the video material in the "Video Tutorials" section.

Specialists of KB "Panorama" have deployed a centralized Docker Registry container repository. The new infrastructure allows development, testing, and operations teams to work with a single internal repository of Docker images. This makes it possible to accelerate application build, delivery, and deployment processes. The repository contains images of the products: GIS WebServer SE, GIS WebService SE, Imagery Service SE и GIS Server.

Using a private Docker Registry helps solve several problems at once. First of all, it is centralized storage of container images: all current versions of services are now in one secure location and accessible to internal teams. This reduces dependence on external public repositories and increases the stability of development and release processes. In addition, the internal Docker Registry provides version control and transparency of software delivery. Developers can store verified and approved images, use common tags, revert to previous versions, and maintain reproducibility of environments. Another important advantage is security. Placing the Registry inside the corporate perimeter simplifies access control, auditing of image usage, and compliance with internal requirements for storing and distributing software components.

Having a dedicated repository increases the performance and convenience of CI/CD processes. Build and delivery systems get fast access to local images, which reduces publication and deployment time for services. Using a private Docker Registry is a step towards a more manageable, secure, and sustainable container infrastructure for the company, which will accelerate the release of new product versions and increase the reliability of internal services.

Access to the Docker Registry container repository can be obtained via the link.

Geoportal "Bank of spatial data" has been supplemented with a map of Prince Edward Island, formed according to OpenStreetMap data. To work with the map, you can use the GIS Panorama Mini program or other software products of KB "Panorama".

The map was led to the modernised classifier of large-scale plans of scale 1: 5 000 (map5000m). Publishing of updates in bank of spatial data is made by using the program of Databank of digital maps and remote sensing data. Publishing contents of bank of spatial data on the geoportal and data access for downloading are implemented by means of GIS WebServer SE.

Free maps on the basis of OpenStreetMap data are available for download on the page "Digital maps".

Specialists of KB "Panorama" have prepared a video tutorial demonstrating the capabilities of vehicle recognition using the "Automatic image recognition" task within GIS "Panorama". Using remote sensing data as an example, the full cycle of material processing is shown: from selecting the source image to obtaining ready-made vector objects. The service allows for automatically detecting vehicles on satellite images, aerial photographs, and data obtained from unmanned aerial vehicles. Processing is performed using "Panorama Vision", where neural network models carry out analysis, segmentation, and classification of objects.

A key element of the video is the demonstration of the specialized "Vehicles" model. It enables the recognition of various types of objects: cars and trucks, special equipment, aircraft, and marine vessels. The model's algorithms allow for accurately determining the position of objects and correctly separating them even in dense placement conditions - in parking lots, industrial zones, airfields, and port terminals.

The processing results are automatically formed as vector objects linked to a digital classifier, allowing them to be immediately used in geographic information systems for analysis and further work. The user receives not just an image with markings, but structured spatial data suitable for accounting, monitoring, and decision-making.

The technology can be applied in a wide range of tasks: monitoring transport infrastructure and road congestion, analyzing logistics flows, controlling the activities of ports and airfields, assessing equipment usage at industrial and construction sites, as well as solving tasks in the field of security and operational situation control.

The use of "Panorama Vision" within GIS "Panorama" significantly speeds up image processing, reduces the labor intensity of manual vectorization, and improves the accuracy of object detection. As a result, the user receives up-to-date and detailed information about transport activity in the area in the shortest possible time.

You can familiarize yourself with the video material in the "Video tutorials" section.

KB "Panorama" has developed GIS WebService SE version 15.15.3. The new version of the service adds support for publishing large-volume height matrices occupying several terabytes of disk space. The data is provided to end users according to the OGC WCS standard in the form of tiles or upon requests for a given territory.

A height matrix for the entire globe, GEBCO with a resolution of 15 seconds (about 463 m/pixel), has been published on the demonstration GIS WebService SE service. GEBCO contains ocean bathymetry data, including depths, seabed topography and names of underwater objects, as well as information on land and ice surface heights. The data is published as MPT projects consisting of multiple matrices. This approach allows for efficiently working with large sets of spatial data and providing them to users via a web service without needing to store the entire volume of information locally.

The task of connecting geoportals via the OGC WCS protocol in GIS "Panorama" has been improved. In the new version, the display of height matrices has been significantly accelerated. Visualization is performed taking into account the current map scale: tiles corresponding to the current zoom level are requested from the server to speed up rendering.

At the same time, for analytical operations — constructing terrain profiles, querying information at a point, and other calculations — data of the base resolution is always used. For example, for the GEBCO matrix, the original resolution of 463 m/pixel is used, ensuring calculation accuracy when working with digital surface models.

GIS WebService SE supports all international standards (OGC WFS, WFS-T, WMS, WMTS, WCS, WPS), through which spatial data is transmitted and displayed. The program implements the ability to issue tiles in any user or local coordinate system. The service supports OpenAPI 3.0 specification and RESTAPI methods. The application is implemented on Windows and Linux platforms and is compatible with Apache, IIS, and nginx web servers.

The new version of the program and documentation are available on the website in the Download section.