GEODATA INTELLIGENCE FOR INTEROPERABLE DATA MANAGEMENT WITH THE ENVVISIO METHOD – ENVVISIO-GI

The objective of the envVisio method is to create generic tools and a flexible data backbone for the preparation, storage, linking and provision of complex and multi-thematic municipal geodata. Although geographic base data of the federal states in Germany are represented and processed in standardized and established data models and systems, there is also a large number of additional geodata such as environmental data and mobility data that are not managed in a uniform manner. Specifically, the envVisio method is about the further development of the model approaches for geospatial and environmental data provision. It is a new type of modeling method that has already been tested in individual state environmental authorities for interdisciplinary cooperation between the specialist departments. The development of technical solutions is intended to reduce the effort required to provide municipal geospatial data and to promote higher usability of public data. The aim of this article is to present the methods and the use cases to be implemented.

Online Communication of Local Governments During COVID-19 Pandemic in Hungary

Local governments had key and prominent roles in tackling the COVID-19 pandemic. Their task was to take short-term measures quickly and to organize protection and care for those in need. The main objective of our paper is to present how local governments communicated with their inhabitants on various online interfaces in this crisis situation. Our analysis covers 54 settlements representing all the different levels of the settlement network from large cities to small villages. We examined the webpages and Facebook pages of local governments and mayors, first during the first wave and then during the second and third waves of the pandemic. Recognizing their responsibility, local governments clearly tried to provide information to the inhabitants as quickly as possible. They considered the online interfaces the most effective, but the online communication had typically been complemented by information published on more traditional channels as well. There were no significant differences in terms of the way and characteristics of communication among the different types of settlements, although local governments of different sizes obviously had to face different challenges in terms of the amount of tasks they had to tackle. The communication process was a very difficult task because of the lack of information and the not-transparent data provision. Even on the Facebook pages especially suitable for this purpose, interactivity rumbled, and in many cases the questions and suggestions of the inhabitants remained unanswered. It is instructive that, with few exceptions, settlements do not place emphasis on surveying local needs and opinions.

Space Weather Services for Civil Aviation—Challenges and Solutions

This paper presents a review on the PECASUS service, which provides advisories on enhanced space weather activity for civil aviation. The advisories are tailored according to the Standards and Recommended Practices of the International Civil Aviation Organization (ICAO). Advisories are disseminated in three impact areas: radiation levels at flight altitudes, GNSS-based navigation and positioning, and HF communication. The review, which is based on the experiences of the authors from two years of running pilot ICAO services, describes empirical models behind PECASUS products and lists ground- and space-based sensors, providing inputs for the models and 24/7 manual monitoring activities. As a concrete example of PECASUS performance, its products for a post-storm ionospheric F2-layer depression event are analyzed in more detail. As PECASUS models are particularly tailored to describe F2-layer thinning, they reproduce observations more accurately than the International Reference Ionosphere model (IRI(STORM)), but, on the other hand, it is recognized that the service performance is much affected by the coverage of its input data. Therefore, more efforts will be directed toward systematic measuring of the availability, timeliness and quality of the data provision in the next steps of the service development.

Knowledge Accumulation, Privacy, and Growth in a Data Economy

We build an endogenous growth model with consumer-generated data as a new key factor for knowledge accumulation. Consumers balance between providing data for profit and potential privacy infringement. Intermediate good producers use data to innovate and contribute to the final good production, which fuels economic growth. Data are dynamically nonrival with flexible ownership while their production is endogenous and policy-dependent. Although a decentralized economy can grow at the same rate (but are at different levels) as the social optimum on the Balanced Growth Path, the R&D sector underemploys labor and overuses data—an inefficiency mitigated by subsidizing innovators instead of direct data regulation. As a data economy emerges and matures, consumers’ data provision endogenously declines after a transitional acceleration, allaying long-run privacy concerns but portending initial growth traps that call for interventions. This paper was accepted by Kay Giesecke, finance.

Automated vehicles and the morality of post-collision behavior

We address the considerations of the European Commission Expert Group on the ethics of connected and automated vehicles regarding data provision in the event of collisions. While human drivers’ appropriate post-collision behavior is clearly defined, regulations for automated driving do not provide for collision detection. We agree it is important to systematically incorporate citizens’ intuitions into the discourse on the ethics of automated vehicles. Therefore, we investigate whether people expect automated vehicles to behave like humans after an accident, even if this behavior does not directly affect the consequences of the accident. We find that appropriate post-collision behavior substantially influences people’s evaluation of the underlying crash scenario. Moreover, people clearly think that automated vehicles can and should record the accident, stop at the site, and call the police. They are even willing to pay for technological features that enable post-collision behavior. Our study might begin a research program on post-collision behavior, enriching the empirically informed study of automated driving ethics that so far exclusively focuses on pre-collision behavior.

Kuzbass Economy: Regional Digital Platforms as a Modernization Strategy

A digital transformation strategy enables companies to build competitive advantages by improving interaction with their consumers and suppliers, and entering new markets. However, the creation of own trading platform by regional companies is not always economically effective. In this regard, it is important to establish digital platforms at the regional level with support from the region, in which several companies would participate. Such platforms will be able to compete more successfully not only with corporate platforms of large companies, but also with such platforms as Amazon and AliExpress. The strategic initiative for the development of regional digital platforms is primarily aimed at innovative companies, which promote their products to end users (BtC). However, regional platforms can serve different markets and different industries, including promotion of industrial products (BtB) produced in the regional industrial clusters of Kuzbass, as well as in other areas, for example, for monitoring indicators of environment pollution. The article discusses in detail the regional investment and financial platform, which is could be developed on the basis of the Kuzbass Investment Portal. Another promising digital platform is a digital system that allows to coordinate strategies at various levels – from federal, regional and industry, to local and private companies. A serious challenge in implementing strategic initiatives to establish regional platforms is the growing competition from foreign platforms. The author proposes to reduce the risks by introducing target restrictions on the operations of foreign platforms, as well as introducing a balanced level of data provision by platform participants.

Pilot provision of EARLINET/ACTRIS lidar profiles to CAMS

<p>In December 2019, a contract between CNR and ECMWF was signed for a pilot ACTRIS/EARLINET data provision to the Copernicus Atmosphere Monitoring Service (CAMS). Such pilot contract (CAMS21b) aims to put in place a first data provision for a set of selected stations and it will demonstrate the feasibility of fully traceable and quality-controlled data provision for the whole network.</p><p>In CAMS21b, the main effort is devoted to design, test and set up the provision of quality-controlled ACTRIS/EARLINET products in Real Real Time (RRT) and/or Near Real Time (NRT) to CAMS. The activities are focused on the automatic centralized data processing and data provision, ensuring the full traceability of the products from the data acquisition level up to the final quality-controlled data level. Most of the activities are done at ARES, the EARLINET/ACTRIS data center node at CNR, for assuring the centralized, harmonized and quality-controlled processing in compliance with FAIR principles.</p><p>New modules and submodules of the ACTRIS/EARLINET Single Calculus Chain (SCC) as well as optimized algorithms for cloud screening have been designed. Additional procedures were implemented for improving the quality of the data provided in NRT, but also for the quality control of the Level 2 products which are delivered with a time delay.</p><p>The release of a new version of SCC and of QC procedure is planned for mid-February.</p><p>The data provision started in October 2020 at the test site of Potenza. A system has been set up for measurement reporting and monitoring of KPIs (Key Performance Indicators). After 3 months of measurements, the overall data provision system showed no critical points.</p><p>In January 2021, the provision started for a group of 9 stations which are seen as representative for the whole network in terms of instrumental capability, but also ensuring a good geographical coverage of the European continent.</p><p>In order to accommodate also measurements from non-continuous operation systems, a measurement schedule has been set up, compromising between the need of a large number of measurements and costs/efforts at each station. The measurement schedule has been designed through a representativeness study and foresees 6 slots of measurements per week, 3 in daytime and 3 in nighttime conditions.</p><p>The successful implementation of the pilot allows the provision of aerosol optical property profiles to the CAMS services. from a set of observational sites distributed over the different European regions. These profiles is expected to be of interest for the assimilation, near real time evaluation and re-analysis evaluation of several CAMS products, including the aerosol load over Europe for air quality issues, atmospheric composition, climate forcing and solar and UV products. This allows for having a systematic solution for looking into specific events as they develop (e.g. the dust plume that you investigated earlier this month or the Californian fires in September), supporting or contradicting model forecasts. This pilot is the first provision of aerosol profiles from a high-quality ground-based network in NRT for this kind of applications. It is expected that these efforts will be continued in the next phase of CAMS/Copernicus (2021-2027).</p>

Evaluation of PNT Error Limits Using Real World Close Encounters from AIS Data

Collision avoidance is one of the main tasks on board ships to ensure safety at sea. To comply with this requirement, the direct ship environment, which is often modelled as the ship’s domain, has to be kept free of other vessels and objects. This paper addresses the question to which extent inaccuracies in position (P), navigation (N), and timing (T) data impact the reliability of collision avoidance. Employing a simplified model of the ship domain, the determined error bounds are used to derive requirements for ship-side PNT data provision. For this purpose, vessel traffic data obtained in the western Baltic Sea based on the automatic identification system (AIS) is analysed to extract all close encounters between ships considered as real-world traffic situations with a potential risk of collision. This study assumes that in these situations, erroneous data can lead to an incorrect assessment of the situation with regard to existing collision risks. The size of the error determines whether collisions are detected, spatially incorrectly assigned, or not detected. Therefore, the non-recognition of collision risks ultimately determines the limits of tolerable errors in the PNT data. The results indicate that under certain conditions, the probability of non-recognition of existing collision risks can reach non-negligible values, e.g., more than 1%, even though position accuracies are better than 10 m.

Forest Variable Estimation and Change Monitoring Solutions Based on Remote Sensing Big Data

In this pilot, we demonstrate the usability of online platforms to provide forest inventory systems for exploiting the benefits of big data. The pilot highlights the technical transferability of online platform based forest inventory services. All of the services tested in the piloting sites were technically implemented successfully. However, in new geographical areas, strong user involvement in service definition and field data provision will be needed to provide reliable and meaningful results for the users. Overall, the pilot demonstrated well the benefits of technology use in forest monitoring through a range of forest inventory applications utilizing online big data processing approaches and inter-platform connections.