Prototype Service Research Articles

A Framework for Joint Verification and Evaluation of Seasonal Climate Services across Socioeconomic Sectors

Abstract Assessing the information provided by coproduced climate services is a timely challenge, given the continuously evolving scientific knowledge and its increasing translation to address societal needs. Here, we propose a joint evaluation and verification framework to assess prototype services that provide seasonal forecast information based on the experience from the Horizon 2020 (H2020) Climate forecasts enabled knowledge services (CLARA) project. The quality and value of the forecasts generated by CLARA services were first assessed for five climate services utilizing the Copernicus Climate Change Service seasonal forecasts and responding to knowledge needs from the water resources management, agriculture, and energy production sectors. This joint forecast verification and service evaluation highlights various skills and values across physical variables, services, and sectors, as well as a need to bridge the gap between verification and user-oriented evaluation. We provide lessons learned based on the service developers’ and users’ experience and recommendations to consortia that may want to deploy such verification and evaluation exercises. Last, we formalize a framework for joint verification and evaluation in service development, following a transdisciplinary (from data purveyors to service users) and interdisciplinary chain (climate, hydrology, economics, and decision analysis).

Exploring citizens’ stances on AI in public services: A social contract perspective

Abstract This paper explores citizens’ stances toward the use of artificial intelligence (AI) in public services in Norway. Utilizing a social contract perspective, the study analyzes the government–citizen relationship at macro, meso, and micro levels. A prototype of an AI-enabled public welfare service was designed and presented to 20 participants who were interviewed to investigate their stances on the described AI use. We found a generally positive attitude and identified three factors contributing to this: (a) the high level of trust in government (macro level); (b) the balanced value proposition between individual and collective needs (meso level); and (c) the reassurance provided by having humans in the loop and providing transparency into processes, data, and model’s logic (microlevel). The findings provide valuable insights into citizens’ stances for socially responsible AI in public services. These insights can inform policy and guide the design and implementation of AI systems in the public sector by foregrounding the government–citizen relationship.

Практическое применение сервиса с искусственным интеллектом в диагностике болезни Паркинсона

In the article we discuss the features of Parkinson’s disease (PD) diagnostics: the generally accepted clinical criteria, their sensitivity and specificity compared to modern diagnostic methods like a voice diagnostic service for PD based on artificial intelligence technologies. The purpose was to clinically test a prototype of a voice-based PD diagnostic service developed as part of the BRAINPHONE project. Material and methods. 100 patients (a balanced sample) who applied to the Republic Consultative and Diagnostic Center for Extrapyramidal Pathology (Kazan) were included in the unselected cohort clinical study. All patients were first examined by two experienced specialists in Parkinson’s disease and then by a trained neural network. The neural network conclusions options were «Parkinson’s disease cannot be excluded» or «No signs of Parkinson’s disease» (decision threshold 0.5). Results. As a result of testing the service, the following data were obtained: sensitivity — 80%, specificity — 92%. Compared with the generally accepted clinical criteria for diagnosing PD, voice diagnosis using a trained neural network developed within the BRAINPHONE project in this study showed comparable results in sensitivity and better results in specificity.

Game Theory-Inspired Motivation and Blockchain-Enhanced Agent Version Evolution Management and Case Study Design

The evolution of versions must be secure and traceable, particularly in asset-sharing systems managed by intricate agents, to bolster the adaptability and service potential of intelligent workshop collaborative frameworks. This article presents a conceptual framework that integrates a blockchain and data space-based hybrid version management model within a customized Industry 4.0 platform. It aims to enhance collaborative management of agent assets by leveraging low-code configuration and implementing incentives for confidentiality. (1) Design a BPMN-driven smart contract Swarm module for user-oriented visualization frameworks. The module is supported by an automated BPMN model and utilizes distributed blockchain technology to facilitate trusted dynamic interactions between multi-stakeholder and Agent version activities; (2) The core activity container framework integrates two-layer distributed container modules from IPFS and industrial data space. By designing interoperable containers based on private and shared versions, and deploying a trust-based dynamic access control model based on game theory, it implements an agent version activity trusted service based on reward and punishment mechanisms; (3) The paper conducted a test case demonstrating the integration of multiple open-source software to create an intelligent agent workshop service prototype built upon the AAS.

An integrated climate and water resource climate service prototype for long term water allocation in the Upper Yellow River region of China

Water Resourcing in China has historically been a complex issue requiring the ability to deal with regular floods, droughts and diverse water needs. Climate change represents another challenge to this sector, albeit one that is not traditionally considered by water managers. In this sector in China water management is predominantly based on historic, seasonal and annual forecast data while multi-annual and (multi-)decadal data are seldom used. In this paper, we present the co-development of a climate service prototype designed to provide water managers with insights into the impacts of climate change on the Upper Yellow River region for the next century. The paper is an outcome from our project that encouraged water resource planners and water resource managers to utilise long-term climate information to understand the uncertainties and the challenges our changing climate is likely to have in the region. Using an interdisciplinary team and adopting a user-centred, co-production approach, a prototype web-based data visualisation tool was developed. The development of the prototype was based on a design specification constructed from the findings of detailed interviews that allowed it to be developed and tested under SARS-CoV-2 pandemic restrictions that prevented the typical development process to be undertaken. The developed prototype presents climate information and communicates uncertainties regarding climate change in the remainder of the century through data sets that are typically used by the water sector in China in a simple, easy to understand style. Models that estimate river levels under different extraction scenarios and results about estimated river level and flow, and flood risk are also presented. The prototype was shown to be successful, as key messages relating to the impact of climate change and the challenges for water resource management could be effectively communicated through the tool interface. Practical implicationsUnderstanding the impacts of climate change on water resourcing is complicated and multifaceted. There is a need for better data about what water there is and how it is moving around between and within catchments. Estimates of past, present and future climate variables along with historical measurements of river flow can be used to help visualise some of the uncertainties and changes that may happen in the next 50 years. In addition, there is a need to understand changing water demands and water resource management practices. Current water resource management practices are based on historical conditions and assumptions that are less likely to hold true in a more variable and warmer climate. Communicating how future changes will impact future water resourcing is critical to water resources in a changing climate (Belcher et al. 2018).This research outlines the construction of a tool to visualise the impacts of climate change on water availability in part of China that is typically water scarce, using models developed using the Soil Water Assessment Toolkit (SWAT). A model of the Upper Yellow River (UYR) was developed to demonstrate the impact of climate change on river levels in the catchment based on climate variables. The rainfall-runoff model was based on climate predictions from the CMIP5 assessment HadGEM3-GC3.05 climate model and incorporated information about water resource allocations for different administrative regions of the catchment The general climate trend for the region is that it is expected to become significantly warmer. The total amount of precipitation is likely to be about the same, and yet it is expected that overall, the catchment will become significantly drier over time as winter shortens and summer lengthens. The outputs from the model reflect the changes in climate variables. The uncertainties were communicated via a Web based tool. Water resource managers in China helped to coproduce the tool by participating in workshops and providing feedback on prototypes. The workshops helped scientists and water resource managers to communicate about climate change impacts on water resources and water resource management.

An Artificial Intelligence (AI) Framework for Detection of Distributed Reflection Denial of Service Attacks

In the contemporary digital world, cyber space is growing continuously witnessing amalgamation of different technologies associated with telecommunications, networking and sensing to mention few. This has enabled Service Oriented Architecture (SOA) to realize distributed applications that cater to the needs of enterprises in the real world. With the advantages of such environments, there has been increased number of instances of cyber-attacks. Distributed Denial of Service (DDoS) is the large-scale attack targeting critical digital infrastructure to make it useless for certain amount of time. Such attacks have several implications and lead to collapse of businesses unless there are countermeasures to detect it and handle it properly. Distributed Reflection Denial of Service (DRDoS) is a variant of such attacks which is more destructive in nature. It is more so in the presence of Internet of Things (IoT) devices deployed in cyber space in large scale. The existing DDoS countermeasures do not work to solve the problem of DRDoS directly. We propose an Artificial Intelligence (AI) framework for detection of DRDoS attacks. We propose an algorithm known as Machine Learning based DRDoS Attack Detection (ML-DAD) for effective detection of attacks. The prototype service built in Python monitors such attacks and take necessary steps to defeat it. The empirical results revealed that the proposed framework has superior performance improvement over the stat of the art. The research in this paper leads to new ideas in the area of detection and prevention of DRDoS attacks.

A Prototype of a Background Solar Wind Forecasting Service Based on MHD Modeling and WSA Boundary Conditions

A prototype service for MHD modeling of the calm solar wind and forecasting the speed and density of solar wind particles in interplanetary space, similar to the NOAA and ESA services, has been created. The service consists of an MHD simulator, a module for processing simulation results, and a web interface. The simulator is based on the implementation of the TVDLF method in the PLUTO package. The boundary conditions of the model (density, radial velocity, magnetic field, temperature) at a distance of 0.1 AU from the origin are obtained regularly from the corresponding NOAA service, in which they are calculated according to the WSA model based on the magnetograms of the GONG network. Two modes of boundary conditions are available: constant and daily. The simulations were carried out on a uniform grid in the range of 0.1–1.7 AU by distance (512 elements), –60°...+60° by latitude (60 elements), 0°–360° by longitude (180 elements). The calculated particle velocity and density maps are compared with the NOAA SWPC and NASA CCMC calculations under the same boundary conditions. A retrospective comparison of the resulting forecasts with data from direct measurements (OMNI) was carried out.

APPLICATION OF DESIGN THINKING METHOD IN REDESIGNING THE UI/UX OF SIMAK (ACADEMIC INFORMATION SYSTEM) OF SRIWIJAYA UNIVERSITY BASED ON A MOBILE PLATFORM

Students at Sriwijaya University are having difficulty accessing academic information through SIMAK using their mobile devices due to a user interface that is not optimized for smartphones. In this study, the author used the Design Thinking method because it has stages that are very helpful in creating prototypes, such as the Empathize stage where the author can directly interact with users' personal opinions, up to the testing stage, which helps the author analyze the results of prototype creation so that further development can be more responsive and better. The prototype was tested through Maze, a platform that helps users test product or service prototypes quickly and efficiently. This platform is integrated with various prototype-making applications and allows users to collect qualitative and quantitative data in one place and the User Experience Questionnaire (UEQ) to analyze data from prototype testing. Based on the results of usability testing, the UEQ scores from 26 SIMAK users were above 1.6, with almost all assessment categories such as "Appeal", "Efficiency", "Accuracy", "Stimulation", "Novelty", and 1.3 in " Perspicuity". Therefore, it can be concluded that the SIMAK prototype design has a good user experience, and the design can be used as a reference for SIMAK mobile-based displays in the future.

Dynamic ventilation certificate for smart universities using artificial intelligence techniques

The issue of room ventilation has recently gained momentum due to the COVID-19 pandemic. Ventilation is in fact of particular relevance in educational environments. Smart University platforms, today widespread, are a good starting point to offer control services of different relevant indicators in universities. This study advances a Ventilation Quality Certificate (VQC) for Smart Universities. The certificate informs the university community of the ventilation status of its buildings and premises. It also supports senior management's decision-making, because it allows assessing preventive measures and actions taken. The VQC algorithm models the adequacy of classroom ventilation according to the number of persons present. The input used is the organisation's existing data relating to CO2 concentration and number of room occupants. AI techniques, specifically Artificial Neural Networks (ANN), were employed to determine the relationship between the different data sources included. A prototype of value-added services was developed for the Smart University platform of the University of Alicante, which allowed to implement the resulting models, together with the VQC. The prototype is currently being replicated in other universities. The case study allowed us to validate the VQC, demonstrating both its usefulness and the advantage of using pre-existing university services and resources.

Subseasonal predictions for climate services, a recipe for operational implementation

The implementation of operational climate service prototypes, which encompasses the co-design and delivery of real-time actionable products with/to stakeholders, contributes to efficiently leveraging operational climate predictions into actionable climate information by providing practical insight on the actual use of climate predictions. This work showcases a general guideline for implementing an operational climate service based on subseasonal predictions. At this timescale, many strategic decisions can benefit from timely predictions of climate variables. Still, the use of subseasonal predictions is not fully exploited. Here, we describe the key aspects considered to set up an operational climate service from the conception to the production phase. These include the choice of the subseasonal systems, the data sources and the methodology employed for post-processing the predictions. To illustrate the process with a real case, we present the detailed workflow design of the implementation of a climate service based on subseasonal predictions and describe the bias adjustment and verification methodologies implemented. This work was developed in the H2020 S2S4E project, where industrial and research partners co-developed a fully-operational Decision Support Tool (DST) providing 18 months of real-time subseasonal and seasonal forecasts tailored to the specific needs of the renewable energy sector. The operational workflow can be adapted to serve forecast products to other sectors, as has been proved in the H2020 vitiGEOSS project, where the workflow was modified to provide downscaled subseasonal predictions to specific locations. We consider this a valuable contribution to future developments of similar service implementations and the producers of the climate data.

Low-cost mobile augmented reality service for building information modeling

Informed decision-making is crucial for construction site operators. Cyber-physical systems, including various technologies such as augmented reality and building automation tools, are gathering popularity within the infrastructure management sector. However, they are expensive and inaccessible to adopt for most small organizations. This paper describes a prototype of low-cost mobile augmented reality service for BIM and demonstrated its usability for pipe maintenance by supporting inspection, workflow management, data reduction, and augmented reality. User views about the decision support, integration and ease of use of the prototype were also collected from the organisations in the UK and South Korea. The results showed that integrating the augmented reality service with the building automation tool connected to the BIM server enhances decision-making for on-site operations by generating a closed loop. This paper also highlights the need for developing low-cost digital solutions to foster the digitalization of construction organisations with limited budgets.

Технології реалізації штучного інтелекту як сервісу на основі апаратних прискорювачів

The subject of study in this article is modern technologies, tools and methods of building AI systems as a service using FPGA as a platform. The goal is to analyze modern technologies and tools used to develop FPGA-based projects for systems that implement artificial intelligence as a service and to prepare a practical AI service prototype. Task: to analyze the evolution of changes in the products of leading manufacturers of programmable logic devices and experimental and practical examples of the implementation of the paradigm of continuous reprogramming of programmable logic; analyze the dynamics of changes in the development environment of programmable logic systems for AI; analyze the essential elements of building projects for AI systems using programmable logic. According to the tasks, the following results were obtained. The area of application of hardware implementation of artificial intelligence for on-board and embedded systems including airspace industry, smart cars and medical systems is analyzed. The process of programming FPGA accelerators for AI projects is analyzed. The analysis of the capabilities of FPGA with HBM for building projects that require enough of high speed memory is performed. Description languages, frameworks, the hierarchy of tools for building of hardware accelerators for AI projects are analyzed in detail. The stages of prototyping of AI projects using new FPGA development tools and basic DPU blocks are analyzed. The parameters of the DPU blocks were analyzed. Practical steps for building such systems are offered. The practical recommendations for optimizing the neural network for FPGA implementation are given. The stages of neural network optimization are provided. The proposed steps include pruning of branches with low priority and the use of fixed point computations with custom range based on the requirements of an exact neural network. Based on these solutions, a practical case of AI service was prepared, trained and tested. Conclusions. The main contribution of this study is that, based on the proposed ideas and solutions, the next steps to create heterogeneous systems based on the combination of three elements are clear: AI as a service, FPGA accelerators as a technology for improving performance, reliability and security, and cloud or Edge resources to create FPGA infrastructure and AI as service. The development of this methodological and technological basis is the direction of further R&D.

RiderAuth: A cancelable touch-signature based rider authentication scheme for driverless taxis

Driverless taxis are now closer to their worldwide launch, however, unsupervised physical access to the riders can pose unexpected safety and security risks to the connected and autonomous vehicle’s ecosystems. Thus, the need for human-to-machine authentication in driverless settings cannot be disregarded to maintain their smooth operations. In this paper, we propose a first rider authentication scheme, RiderAuth, using touch-signature behavioral biometrics to authenticate customers before they commence their ride in driverless settings. We also propose a template protection scheme for finite length touch-signature features using a random orthogonal projection method to address biometric template leakage. We design Android-based client and Cloud-based server prototypes to evaluate both the security and usability of our proposed scheme. We collect a new database of 1800 touch-signatures samples from 30 users in an unsupervised field experiment for two weeks. RiderAuth achieves a True Acceptance Rate (TAR) of 96.66% at False Acceptance Rate (FAR) of 0.01% without template protection and a TAR of 94.88% at FAR=0.01% with proposed template protection scheme. Subsequently, we implement a d-prime weighted score-level fusion to further enhance RiderAuth’s accuracy. We evaluate the unlinkability and revocability of the proposed template protection scheme to verify its suitability for authenticating riders in a privacy preserved setting. In addition, we conduct a survey to evaluate user acceptance of our proposed scheme using the System Usability Scale (SUS) where we get a score of ≈70% suggesting a positive experience and acceptance of RiderAuth.

A Blockchain and Fingerprinting Traceability Method for Digital Product Lifecycle Management.

The rise of digitalization, sensory devices, cloud computing and internet of things (IoT) technologies enables the design of novel digital product lifecycle management (DPLM) applications for use cases such as manufacturing and delivery of digital products. The verification of the accomplishment/violations of agreements defined in digital contracts is a key task in digital business transactions. However, this verification represents a challenge when validating both the integrity of digital product content and the transactions performed during multiple stages of the DPLM. This paper presents a traceability method for DPLM based on the integration of online and offline verification mechanisms based on blockchain and fingerprinting, respectively. A blockchain lifecycle registration model is used for organizations to register the exchange of digital products in the cloud with partners and/or consumers throughout the DPLM stages as well as to verify the accomplishment of agreements at each DPLM stage. The fingerprinting scheme is used for offline verification of digital product integrity and to register the DPLM logs within digital products, which is useful in either dispute or violation of agreements scenarios. We built a DPLM service prototype based on this method, which was implemented as a cloud computing service. A case study based on the DPLM of audios was conducted to evaluate this prototype. The experimental evaluation revealed the ability of this method to be applied to DPLM in real scenarios in an efficient manner.

Applying a design mindset to develop a prototype of an electronic service for assessing the impact on the environment

The object of research considered in this paper is the design mindset process in the development of a prototype of electronic service for assessing the environmental impact of the planned activities of business entities. The problems of applying the design mindset approach to the process of automating environmental impact assessment have been investigated. As a result of the application of the design mindset in combination with the stakeholder approach, a logical-structural scheme and architecture of the electronic service interface for different categories of users have been developed. The peculiarities of the prototype of the electronic service of environmental impact assessment (EIA ES) are to provide a common understanding of the requirements and results obtained, and convenient access to the execution of calculations. Distinctive features for the implementation of calculations in EIA ES are the quantitative obtaining of the values of indicators, which are represented by a report in the form of qualitative parameters through the use of a new algorithm. This allows business entities to perform calculations of indicators using online access at the stage of preparing the report. The developed interface design and functionality of the EIA prototype were evaluated by the expert method on a 10-point scale when making calculations for a real project. The effectiveness of the electronic service has been confirmed by the consistency of expert opinions in line with the concordation method. The estimated concordation coefficient was 0.83 and was checked for adequacy according to the Pearson criterion (20.75), which confirmed the reliability of the calculations at a significance level of 0.05. The scope of application may be environmental impact assessment of transport construction objects and gas stations. The conditions for practical use are the availability of access to the Internet and the availability of sufficient user qualifications for performing calculations.

DESIGN AND BUILD A WEBSITE-BASED FOREIGNER SERVICE APPLICATION APPLICATION AT THE CLASS 1 IMMIGRATION OFFICE SPECIFICALLY FOR NON-TPI WEST JAKARTA

The use of information technology has now been widely applied in the process of immigration services and supervision carried out by the Directorate General of Immigration. One of them is return of immigration documents and transferring foreigner data using a Google form. However, in its implementation there are still some problems. This study aims to determine the current business process for document return services and foreigner data mutations at West Jakarta Immigration Office and to provide an overview of designing a web-based application for immigration services for foreigner. The design of this application uses the Waterfall Model System Development Life Cycle (SDLC) method. The results of this study are a website-based application prototype for foreign citizen services with various features provided such as checking application status, information on requirements for submitting requests for return of immigration documents and mutation of foreigner data, submission of ERP applications, submission of EPO applications, submission of transfer requests address, and submission of a passport mutation application which can later be used as a reference to be applied to immigration document return services and foreigner data mutations at the Special Class 1 Immigration Office for non-TPI West Jakarta.

Patient Experience in Pancreas-Kidney Transplantation-A Methodological Approach Towards Innovation in an Established Program.

Simultaneous pancreas-kidney transplantation (SPKT) leads to increased survival and quality of life, and is an alternative treatment for insulin-dependent diabetes mellitus and end-stage kidney disease. Due to the particularities of this population (often with multiple comorbidities) and of the surgery (only performed in a few centers), a comprehensive analysis of patients’ experience along the SPKT process is crucial to improve patient care and add value to this procedure. Therefore, we applied a systematic and iterative methodology with the participation of both patients and professional teams working together to explore and identify unmet needs and value-adding steps along the transplant patient journey at an established pancreas transplant program. Four main steps (to comprehend, to explore, to experiment and to assess) led to several interventions around three major areas: Administration and logistics, information and communication, and perceived quality of assistance. As a result, both displacements to the hospital for diagnostic purposes and the time delay involved in joining the patient waiting list for transplantation were reduced in parallel to the administrative procedures. In conclusion, the methodological implementation of key organizational changes has great impact on overall patient experience. Further quantitative analysis from the patient’s perspective will consolidate our program and may add new prototype service design components.

Improving mental health care outcomes: the agile psychological medicine clinic

ABSTRACT Objective We hypothesised that providing evidence-based care to people presenting in crisis to three Emergency Departments and the 24/7 phone Psychiatric Triage Service in Victoria, Australia, would improve their clinical outcomes over time and experience of the adult mental health system. We tested this through a service prototype, the agile Psychological Medicine clinic. Method Descriptive statistics were used to understand the characteristics of people who presented in crisis. Patient journey maps were used to understand the impact of the system on the patient and assess whether they received the best clinical care over time. Insights from these analyses, and the evidence base, led to the development of the prototype. Using an open trial design, 194 patients received specialist treatment and effectiveness was measured through patient-reported outcome measures administered at initial and final appointments. Service utilisation was measured 12-months pre and post treatment. Results The agile Psychological Medicine clinic delivered value; outcomes significantly improved across psychological symptomology and behaviours. Reductions in emergency department presentations, phone triage calls and service costs resulted. Conclusions This innovative clinic demonstrated that access to front-end mental health treatment improves clinical outcomes, mitigates later complications and increases the prospects of keeping patients well over the longer term. KEY POINTS What is already known about this topic (1) Hospital emergency departments (EDs) can often be the initial point of care for people seeking immediate help for mental health crises. (2) Demand has increased, patient satisfaction has decreased and patients increasingly re-present in crisis. (3) Therapeutic alliance has been shown to be a robust predictor of treatment outcome. What this paper adds (1) Mental health care could be improved for those presenting in situational crises by bringing evidence-based treatment with a consistent clinician with whom they could form a therapeutic alliance (2) The agile Psychological Medicine clinic demonstrated that bringing specialist treatment to the front end of the system of care, improves clinical outcomes, mitigates later complications and increases the prospects of keeping patients well over the longer term. (3) Patients who engaged in treatment had a 37% reduction in ED presentations 12 months after therapeutic intervention resulting in significant cost savings. Abbreviations: aPM: agile Psychological Medicine; CATT: Crisis Assessment and Treatment Team; CBT: Cognitive behaviour therapy; CCT: Continuing Care Team; ECATT: Emergency Crisis Assessment and Treatment Team; ED: Emergency Department; PTS: Psychiatric Triage Service; SECASA: South Eastern Centre Against Sexual Assault

Mapping Ecological Focus Areas within the EU CAP Controls Framework by Copernicus Sentinel-2 Data

Greening is a Common Agricultural Policy (CAP) subsidy that ensures that all EU farmers receiving income support produce climate and environmental benefits as part of their farming activities. To receive greening support, it is mandatory for the farmer to carry out three agricultural practices that are considered environmentally and climate friendly: (a) crop diversification; (b) maintenance of permanent meadows and pastures; and (c) presence of an Ecological Focus Area (EFA). Contributions are delivered and monitored by paying agencies (PP) that ordinarily perform administrative checks and spot checks. The latter are provided through photo-interpretation of high-resolution satellite or aerial images and, in specific cases, through local ground checks (GC) as well. In this work, stimulated by the Piemonte Regional Agency for Payments in Agriculture (ARPEA), a prototype service to support PPs’ controls within the greening CAP framework was proposed with special concern for EFA detection. The proposed approach is expected to represent a valid alternative or supporting tool for GC. It relies on the analysis of NDVI time series derived from Copernicus Sentinel-2 data. The study was conducted in the provinces of Turin, Asti and Vercelli within the Piedmont Region (NW Italy), and over 12,500 EFA fields were assessed. Since the recent National Report No. 5465 stipulates that mowing and any other soil management operation is prohibited on set-aside land designated as an EFA during the reference period (RP) between 1st March and 30th June, a time series (TS) of NDVI in the same period was generated. Once averaged at plot level, NDVI trends were modelled by a first-order polynomial, and the correspondent statistics (namely, R2, MAE and maximum residual) was computed. These were assumed to play the role of discriminants in EFA detection based on a thresholding approach (Otsu’s method), calibrated with reference to the training dataset. The threshold satisfaction was therefore tested, and, depending on the number of satisfied thresholds out of the possible three, EFA and non-EFA plots were detected with a different degree of reliability. The correspondent EFA map was generated for the area of interest and validated according to GCs as provided by the ARPEA. The results showed an overall accuracy of 84%, indicating that the approach is promising. The authors retain that this procedure represents a valid alternative (or integrating) tool for ground controls by PPs.

Разработка методических аспектов картографирования геопространственных знаний об объектах культурного наследия для пространственного развития территорий

Currently, mapping geospatial knowledge on maps is a poorly developed and very promising area of cartographic science. To date, there are no methods of mapping objects of cultural heritage that allow displaying not only information, but also geospatial knowledge about them. The article deals with the problem of mapping geospatial knowledge about cultural heritage objects for the spatial development of territories. The purpose of the study is formulated, the analysis of existing methods for assessing the historical and cultural value of cultural heritage objects is given. The process of obtaining geospa-tial knowledge about cultural heritage objects has been developed and formalized. The structure and content of the base of geospatial knowledge of cultural heritage objects for the spatial development of territories are developed, the principles of displaying geospatial knowledge about cultural heritage ob-jects on cartographic works are formulated. The proposed methodological foundations were tested by developing a prototype of the cartographic web service "Cultural Heritage of the Novosibirsk region".