Mapping Methodology Research Articles

Validity of resting heart rate derived from contact-based smartphone photoplethysmography compared with electrocardiography: a scoping review and checklist for optimal acquisition and reporting.

With the rise of smartphone ownership and increasing evidence to support the suitability of smartphone usage in healthcare, the light source and smartphone camera could be utilized to perform photoplethysmography (PPG) for the assessment of vital signs, such as heart rate (HR). However, until rigorous validity assessment has been conducted, PPG will have limited use in clinical settings. We aimed to conduct a scoping review assessing the validity of resting heart rate (RHR) acquisition from PPG utilizing contact-based smartphone devices. Our four specific objectives of this scoping review were to (1) conduct a systematic search of the published literature concerning contact-based smartphone device-derived PPG, (2) map study characteristics and methodologies, (3) identify if methodological and technological advancements have been made, and (4) provide recommendations for the advancement of the investigative area. ScienceDirect, PubMed and SPORTDiscus were searched for relevant studies between January 1st, 2007, and November 6th, 2022. Filters were applied to ensure only literature written in English were included. Reference lists of included studies were manually searched for additional eligible studies. In total 10 articles were included. Articles varied in terms of methodology including study characteristics, index measurement characteristics, criterion measurement characteristics, and experimental procedure. Additionally, there were variations in reporting details including primary outcome measure and measure of validity. However, all studies reached the same conclusion, with agreement ranging between good to very strong and correlations ranging from r = .98 to 1. Smartphone applications measuring RHR derived from contact-based smartphone PPG appear to agree with gold standard electrocardiography (ECG) in healthy subjects. However, agreement was established under highly controlled conditions. Future research could investigate their validity and consider effective approaches that transfer these methods from laboratory conditions into the "real-world", in both healthy and clinical populations.

Educational actions in cultural spaces and their links with concepts of aesthetic education and cultural mediation

This article aims to outline links between educational actions of cultural spaces with concepts of aesthetic education and cultural mediation. Pointing to a bibliographical investigation, of a qualitative approach, as a methodology, we opted for the use of cartography, which proved to be appropriate for the possibility of expanding and multiplying research paths. The choice of mapping methodology is based on Deleuze and Guattari (2019) and Passos, Kastrup and Scotland (2020). We research on cultural institutions in Brazil to identify the characteristics and type of educational actions they offer, as well as the availability of digital materials. Recognizing the existence of a significant number of materials, we find that interested parties need to seek the information. We emphasize the importance of research into these materials by teachers, to promote students' contact with art and culture. We emphasize the importance of this research with regard to the articulation of educational actions of cultural institutions, which through their materials make possible encounters of students from various regions of the country with art. In this sense we understand that the teacher mediator, who researches and shares this knowledge allows his students to make an experience with art. We sought theoretical input for the concept of aesthetic education in Schiller (2013), on the concept of cultural mediation in Martins (2012), Heidegger (2003) assured us the concept of doing an experiment, Rancière (2015), (2017) supported emancipation, among other important authors. As a result, we understand that cultural spaces that offer possibilities to expand dialog, poetic exercise and the perspective of aesthetic education through educational actions, promote opportunities for encounters with art. In the dialogical and poetic exercise of the subject with art the subject plays and moves reason and emotion, which makes it possible to make an experience and educate aesthetically. We emphasize the importance of the teacher researcher and mediator, who is a proponent, who provokes and challenges students to dialog with works of art, activating the playful impulse in the subject, so that he can make an experience on the way to aesthetic education.

Variability in road surface temperature in urban road network – A case study making use of mobile measurements

Abstract This work presents the results of the research on the thermal state of the road surface measured by means of a mobile road condition sensor. A 15 km route circumnavigating the city centre and used by urban traffic was taken as the research area. Sixteen test runs were performed under summer and winter conditions. An analysis of the locations at which the rate of change of surface temperature had extreme values between consecutive test runs (which lasted around 25 min) was carried out. Based on that, critical sections of the test route were identified, and thus points characterised by readings deviating significantly from the mean values. Based on the thermal mapping methodology, an analysis of the rate of surface cooling was carried out. It was shown to be characterised by temporal (as well as spatial) non-uniformity. The rate of change of surface and air temperatures was calculated as a function of time, which was equal to −2.22 and −1.97°C/h, respectively. During the analysis, it came to light that hourly intervals represent the optimal frequency for thermal monitoring of a road network. Exceptions to the above are the aforementioned sections selected on the basis of the mobile measurements, in which permanent monitoring of road conditions via ESS stationary systems are recommended.

Mapping health services for adults with cerebral palsy in Ireland: a pilot study

Background Cerebral palsy (CP) is a common cause of physical disability in childhood. The majority of children with CP survive to adulthood. Once discharged from children’s services, adults with CP find it challenging to navigate health services. The aim of this study was to pilot and refine a methodology to map services for adults with CP in Ireland. Methods We used a multi-informant mapping methodology consisting of: 1. Defining health services; 2. Identifying informants; 3. Designing a survey; 4. Collecting data; 5. Data checking and analysis. We collected data on services from service users and service providers using an online survey. We verified data against information available online and by asking organisations to provide details about the service. Results Fifteen service users and nine service providers completed the online survey. Data on 265 unique services at 32 organisations were provided. The most commonly provided services were physiotherapy (12%) and occupational therapy (11%). We confirmed the name of 89 services (34%) against online information. We received further details from eight organisations about 27 services. Specifically, we received details about the organisation name for 27 of the 265 services (10%), service name for 25 services (9%), service type for 25 services (9%), a website for 19 services (7%), and data on eligibility criteria and types of supports provided for between 25 or 26 services (9% or 10%). Conclusion This pilot study highlighted the complexity of mapping services for adults with CP in Ireland. We recommend that an alternative methodology should be used to map services for adults with CP in Ireland.

Spectrum map construction optimisation schemes: Sampling and prediction

The proliferation of electromagnetic devices presents a significant challenge in developing effective techniques for spectrum monitoring, management, and security. The utilization of spectrum cartography has been acknowledged as a viable approach to address the aforementioned difficulties. This latter presents a variety of techniques aimed at enhancing the efficiency of the current spectrum mapping methodology. The subject matter can be categorized into two primary components, namely sampling and spectrum prediction. Sampling part includes methods to find the most valuable sampling points and methods of sampling hardware optimization. Spectrum prediction includes algorithms utilizing frequency-spatial reasoning techniques to estimate the target spectrum map by data from the nearby area, and algorithms utilizing ROSMP framework to estimate the spectrum map from past data. The introduction of techniques is divided into the 2 types, together with key algorithms and devices used in each method. Additionally, the letter lists some drawbacks of certain methods and discuss their development prospects.

Contentment and Self-acceptance: Wellbeing Beyond Happiness

Contentment is an emotion felt when the present situation is perceived to be complete as it is. Six studies are presented showing the difference between contentment and other positive emotions, documenting contentment’s unique relationship with self-acceptance, and exploring the positive associations between contentment and wellbeing. First, we demonstrated that contentment is perceived as different from happiness and other positive emotions using an emotion concept mapping methodology (Study 1), a dimensional analysis (Study 2), and a free-response narrative analysis (Study 3). We then demonstrated that both trait (Study 4 and 5) and state levels (Study 6) of contentment are associated with a sense of self-acceptance, and further related to increased wellbeing. We conclude that contentment is a unique positive emotion that is central to wellbeing and life satisfaction, and we discuss important implications for future research.

Automated Mapping Methodology and Case Study of Healthcare User Activities and Spaces from a Sustainable Perspective

Operational inefficiencies in healthcare buildings and sustainability issues have become increasingly prominent. The root cause of this phenomenon is the irregular and incomplete structured data related to hospital user activities and spaces that are difficult to resolve using traditional manual methods. In order to solve this problem, an automated mapping approach is presented for hospital user activity and space. Using the Revit API technology and the C# language on the Visual Studio platform, a program for automated mapping is developed. It achieves the automatic mapping of hospital user activities and spaces, along with automatic calculation of utilization rates. An illustrative case study is conducted, focusing on the activity data and building space utilization of healthcare users at Shanghai Renji Hospital. The results indicate that (1) This method can realize the automatic combination of hospital user activities and hospital spaces, and hospital administrators can optimize the utilization rate of hospital spaces quickly and accurately. (2) This approach is highly adaptable, especially to changes in hospital user activities and hospital spatial data. (3) This method promotes the sustainable development of healthcare buildings and has great practical application value.

Planter: Rapid Prototyping of In-Network Machine Learning Inference

In-network machine learning inference provides high throughput and low latency. It is ideally located within the network, power efficient, and improves applications' performance. Despite its advantages, the bar to in-network machine learning research is high, requiring significant expertise in programmable data planes, in addition to knowledge of machine learning and the application area. Existing solutions are mostly one-time efforts, hard to reproduce, change, or port across platforms. In this paper, we present Planter: a modular and efficient open-source framework for rapid prototyping of in-network machine learning models across a range of platforms and pipeline architectures. By identifying general mapping methodologies for machine learning algorithms, Planter introduces new machine learning mappings and improves existing ones. It provides users with several example use cases and supports different datasets, and was already extended by users to new fields and applications. Our evaluation shows that Planter improves machine learning performance compared with previous model-tailored works, while significantly reducing resource consumption and co-existing with network functionality. Planter-supported algorithms run at line rate on unmodified commodity hardware, providing billions of inference decisions per second.

Method of Construction of a Fuzzy Cognitive Map of the Competitiveness of a Machine-Building Enterprise

The purpose of research is to evaluate the factors influencing the competitiveness of machine-building enterprises and to develop a methodology for fuzzy cognitive mapping (FCM) to analyze these factors.Methods. Data analysis and modeling methods, including FCM, were used in this study to formalize the relationships between factors and their influence on the competitiveness of machine-building enterprises. Data related to factors affecting competitiveness, such as technological level, product quality, price level, innovation potential, and managerial experience, were analyzed.Results. The study resulted in the development of an FCM methodology to analyze the relationships between factors and their influence on the competitiveness of machine-building enterprises. The factors influencing competitiveness, including technological level, product quality, price level, innovation potential, and managerial experience, were evaluated. Key factors with the greatest impact on competitiveness were identified, and the degrees of influence of each factor on competitiveness were established using a scale to formalize the strength of influence.Conclusion. The results of the study demonstrate that the FCM method is an effective tool for analyzing the competitiveness of machine-building enterprises. It allows for uncertainty and vagueness in the input data and provides a better understanding of the relationships between conceptual variables. The developed FCM methodology can be used to make informed decisions to improve enterprise competitiveness. Overall, the study confirms the importance of analyzing factors influencing competitiveness and demonstrates that FCM can help to represent a complex system and its relationships in a more visual and understandable form. This can be useful for enterprise management in making informed decisions to improve company competitiveness and increase market share.

Concept Mapping to Define Components for an Occupation-Based Intervention for Parkinson's Disease and Anxiety.

Anxiety, a common symptom of Parkinson's disease (PD), results in reduced life quality, reduced participation in meaningful roles and daily activities, and increased health burden. There are no evidence-based interventions to reduce the impact of anxiety in PD on participation. This study aimed to identify the key components required for the co-production of an occupation- and community-based intervention for people with PD-related anxiety. A participatory mixed-methods research study was conducted using online Group Concept Mapping methodology that included five stages: brainstorming, idea synthesis, sorting activity, rating activity, and analysis. A cluster map, pattern match, and 'go-zone' charts were created through multivariate statistical analysis based on participants' responses. The stages were guided by questions generated by the research team working with stakeholders. Eighty-three people participated, with 64 taking part in more than one activity. Participants included people with PD (n = 72), care partners (n = 6), and occupational therapists (n = 5). The final map contained 119 statements with eight clusters (stress value 0.252): exercise, lifestyle changes, self-help, coping, access to information, professional help, peers and groups, support from others. Significant agreement existed between the importance and feasibility rating activities (r = -0.07). 'Go-zone' charts highlighted the priority statements for intervention development. This novel participatory study highlighted priority components that provide starting points for future development of an occupation- and community-based intervention for people with PD-related anxiety.

Changes in Sustainable Development in Manufacturing in Cases of Unexpected Occurrences—A Systematic Review

Nowadays, managers are facing the challenge of operating in situations of high uncertainty: delayed deliveries, lack of energy or rising energy and gas costs, the need to replace energy sources, and changing supply and sales markets. In the literature, two dominant trends in the activities of enterprises in the face of crises can be distinguished: (I) changes in supply chain management (increased flexibility by searching for local suppliers); and (II) transition to digital production and investment in technologies in the concept of Industry 4.0 or even Industry 5.0, such as artificial intelligence, 3D printing, robots, cyber-physical systems, digital manufacturing, and blockchain. A gap in the research has been observed in examining the impacts of these actions on the implementation of sustainable solutions and designating organizational changes in manufacturing. The main goal of this study is to review the literature using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for data collection and, secondly, the methodology of Systematic Literature Review (SLR) and Mapping in Literature Reviews (MLR). Our literature review of the selected databases is based on 566 published articles in 2020–2022. The achieved results indicate the main organizational changes in the context of sustainable development in manufacturing, namely in the business management area (adopting Sustainable Project Management (SPM), Sustainable Supply Chain Management practices, Sustainable Supplier Selection (SSS), and Resilient Manufacturing Strategy (RMS)) and in the production area (adopting Internet of Things (IoT)-enabled Additive Manufacturing assists, simulation software, and Life Cycle Assessment. The findings of our study revealed key relationships between the adoption of fifth-generation industrial technologies and the sustainable development of manufacturing.

Measuring Backsliding with Observables: Observable-to-Subjective Score Mapping

ABSTRACTMultiple well-known democracy-rating projects—including Freedom House, Polity, and Varieties of Democracy (V-Dem)—have identified apparent global regression in recent years. These measures rely on partly subjective indicators, which—in principle—could suffer from rater bias. For instance, Little and Meng (2023) argue that shared beliefs driven by the current zeitgeist could lead to shared biases that produce the appearance of democratic backsliding in subjectively coded measures. To assess this argument and the strength of the evidence for global democratic backsliding, we propose an observable-to-subjective score mapping (OSM) methodology that uses only easily observable features of democracy to predict existing indices of democracy. Applying this methodology to three prominent democracy indices, we find evidence of backsliding—but beginning later and not as pronounced as suggested by some of the original indices. Our approach suggests that the Freedom House measure particularly does not track with the recent patterns in observable indicators and that there has been a stasis or—at most—a modest decline in the average level of democracy.

Dysphagia Management in the Emergency Department: Using Concept Mapping to Identify Actionable Change to Improve Services

BackgroundIntegrated speech-language pathology (SLP) services within the emergency department (ED) may facilitate timely dysphagia management. However, there are multiple patient and logistical factors specific to the ED that challenge the delivery of optimal dysphagia referral and management practices within this setting. The aim of the current study was to engage a stakeholder group to identify prioritised, actionable goals that could help enhance dysphagia management within the ED.Methods and ProceduresApplying concept mapping methodology, 16 ED stakeholders from SLP, medical, nursing, and leadership participated in semi-structured interviews to develop action statements which were sorted and ranked for importance and changeability. Multidimensional scaling and hierarchical cluster analysis were used to organise data in clusters with unifying themes before statements were ranked by importance and changeability.Outcomes and ResultsStakeholders identified 53 unique statements, grouped into 8 clusters. Review of the 8 clusters identified 3 overarching aspects for change: (a) Improving processes related to identification and referral of patients as well as communication; (b) Teamwork and collaboration amongst the ED multidisciplinary team and SLP; and (c) Improving staffing and access to training resources for SLP and nursing teams.Seventeen statements were within the Go-zone rated highest for importance and changeability) with the highest rated statement being: Clear documentation by SLP re: recommendations.ConclusionThe current data identified multiple aspects of service provision that require change to facilitate improved dysphagia referral and management services in the ED. Collaborative actions are required by both SLP and the ED multidisciplinary team to help optimise dysphagia services.

Pediatric Resident Well-being: A Group Concept Mapping Study

ObjectivePediatric residency programs invest substantial resources in supporting resident well-being. However, no pediatric resident well-being conceptual model exists to guide interventions. This study aimed to understand how a diverse stakeholder sample conceptualized well-being. MethodsWe used group concept mapping methodology. We sent a brainstorming survey to pediatric residents and program leaders at 24 US residencies with the prompt, “The experience of well-being for resident physicians includes…” Participants at 4 residencies sorted well-being ideas conceptually and rated idea importance. We performed multidimensional scaling and hierarchical cluster analysis to develop cluster maps. Using participant feedback and a consensus-driven process, we determined best cluster representation. We used pattern matching to compare domain ratings between subgroups. ResultsIn brainstorming, 136 residents and 22 program leaders from 22 residency programs generated 97 unique ideas. Ideas were sorted and rated by 33 residents, 14 program leaders. Eight domains aligning with 4 resident roles were identified. Domains were: 1) positive, safe, and diverse culture; 2) unity and connection; 3) professional fulfillment and mindset; 4) personal health and life satisfaction; 5) professional development and recognition; 6) schedule protections and downtime; 7) work systems and benefits; 8) proactive and compassionate leadership. Domains aligned with the following roles: 1) individual, 2) colleague, 3) employee, 4) emerging pediatrician. Residents placed higher value on schedule protections and downtime than program leaders, P < .05. ConclusionsPediatric resident well-being may be conceptualized as inter-related domains corresponding with various resident roles. Participants aligned on many well-being priorities but differed regarding work schedules.

Small Area Poverty Estimation Under Heteroskedasticity

Abstract Multilevel models with nested errors are widely used in poverty estimation. An important application in this context is estimating the distribution of poverty as defined by the distribution of income within a set of domains that cover the population of interest. Since unit-level values of income are usually heteroskedastic, the standard homoskedasticity assumptions implicit in popular multilevel models may not be appropriate and can lead to bias, particularly when used to estimate domain-specific income distributions. This article addresses this problem when the income values in the population of interest can be characterized by a two-level mixed linear model with independent and identically distributed domain effects and with independent but not identically distributed individual effects. Estimation of poverty indicators that are functionals of domain-level income distributions is also addressed, and a nonparametric bootstrap procedure is used to estimate mean squared errors and confidence intervals. The proposed methodology is compared with the well-known World Bank poverty mapping methodology for this situation, using model-based simulation experiments as well as an empirical study based on Bangladesh poverty data.

Cost-effective disaster-induced land cover analysis: a semi-automatic methodology Using machine learning and satellite imagery

ABSTRACT This study introduces a cost-effective and automated methodology to swiftly and accurately gauge disaster-induced land cover changes, harnessing satellite imagery and machine learning. Using open-source platforms like Google Earth Engine, the approach streamlines training sample generation and assesses diverse machine learning algorithms on pre- and post-disaster Landsat images. The innovation lies in its semi-automatic training sample generation methodology, reducing time and manual effort for accurate land cover mapping and addressing the challenge of crafting training samples in disaster settings. The methodology was tested on the 2010 Chilean earthquake and tsunami, revealing a 45% increase in sediment cover and a 15% reduction in water cover, underlining vast landscape alterations. SVM stood out for its consistent accuracy. To validate the methodological robustness and broaden its applicability, we replicated the procedures using diverse land cover collection, including ESA WorldCover 10 m and Dynamic World. This comprehensive validation encompassed varied catastrophic events, extending the methodology’s relevance beyond its original scope. The consistent findings across different scenarios underscored the method’s robustness and underscored its potential for broader utilization. This streamlined, cost-effective approach suits multiple land cover products, setting the stage for constant Earth feature monitoring. In light of escalating natural disasters, the synergy of machine learning and geospatial technology spotlighted here offers promising avenues for improved disaster preparedness and response.

Strategies for enhancing the representation of women in clinical trials: an evidence map

BackgroundEquitable sex- and gender-based representation in clinical trials is an essential step to ensuring evidence-based care for women. While multi-institutional actions have led to significant improvements in the inclusion of women in trials, inequity persists in areas like sex-neutral cancers and cardiovascular disease. We sought to identify strategies described or evaluated to boost the inclusion of women in clinical trials.MethodsWe used evidence mapping methodology to examine the breadth of relevant literature. We developed an a priori protocol and followed reporting guidance from the Preferred Reporting Items for Systematic Reviews and Meta-Analysis where applicable. We searched MEDLINE® (via PubMed) and EMBASE (via Elsevier) databases from inception through April 4, 2023, and used standardized procedures incorporating duplication and data verification. We included articles that described strategies to improve the recruitment and retention of women in clinical trials.ResultsWe identified 122 articles describing recruitment and retention strategies for 136 trials (377,595 women). Only one article distinguished between the sex and gender identity of participants, and none defined their use of the terms such as “women” or “female”. The majority of articles (95%) described recruitment for only women, and 64% were conducted in the USA. Ninety-two articles (75%) described strategies in the context of sex-specific conditions (e.g., gynecologic diagnosis). The majority of included articles evaluated a behavioral intervention (52%), with 23% evaluating pharmacologic interventions and 4% invasive interventions. The most common trial phase for reported strategies was during outreach to potential participants (116 articles), followed by intervention delivery (76), enrollment (40), outcomes assessment (21), analysis and interpretation (3), and dissemination (4). We describe specific types of strategies within each of these phases.ConclusionsMost of the existing literature describing strategies to improve the inclusion of women draws from trials for sex-specific conditions and is largely related to outreach to potential participants. There is little information about how and if studies have attempted to proportionally increase the inclusion of women in trials with both men and women or those focused on invasive and pharmacologic interventions. Future work in this area should focus on how to increase the participation of women in mixed-sex studies and on those areas with remaining inequities in trial participation.

A method for reducing energy costs in the production of construction components

This study addresses the issue of excessive energy consumption in the production of construction components. The focus of the research is the manufacturing process of window and door units. The objective is to identify excessive costs within the production processes of a construction company using lean manufacturing tools. The research methodology is based on lean manufacturing principles, specifically utilizing value stream mapping (VSM) to fully visualize the production process. The study has identified operations where losses occur due to excessive inventory, overprocessing, downtime, transportation losses, and defects. A methodology for value stream mapping of both the current and future states of the construction component manufacturing process has been developed. Practically, the value stream mapping of the construction component production process has been carried out, and maps of the current and future states of the value stream have been created. The analysis of the mapping results revealed a significant cycle time overrun at two stages of production – hole milling and glazing unit assembly. These two stages are the most time-consuming and energy-intensive within the process and require optimization. Based on the value stream mapping results, rational measures have been proposed to reduce losses at these production stages, decreasing the overall construction time from 9.845 seconds to 5.765 seconds (a 35-40% reduction) and reducing the number of operations from 19 to 17.

The importance for Ukrainian R&D system RI's mapping and the Slovak case study

The research explores the significance of mapping Research Infrastructures (RI) using the Slovak case study and try to identify the best solution for Ukrainian science. Drawing from European experiences, particularly the European Strategy Forum on Research Infrastructures (ESFRI) and its roadmap, the study proposes leveraging similar methodologies for RI mapping in Ukraine. While European projects like MERIL, CATRIS, and ONLINE S3 have advanced RI inventory efforts, Ukraine lacks a comprehensive approach in this regard. The research aims to address this gap by advocating for the development and implementation of a mapping system tailored to Ukraine's research landscape. By examining existing literature and European initiatives, it provides a framework for creating a unified catalogue of research infrastructures, essential for informed decision-making and effective resource allocation in Ukraine's scientific sector.This "Science Map of Ukraine" will enables users to filter data and access detailed information about each scientific infrastructure object, facilitating efficient resource allocation and strategic planning. In the context of wartime and post-war recovery, this project takes on added significance as a key factor in supporting digital transformation in science and research. The "Map" allows for the identification of critical research infrastructure objects, promotes collaboration among institutions, facilitates resource reallocation, monitors scientific activities, and enhances digital coordination. Through comprehensive data visualization, it contributes to broader understanding and public participation in scientific processes. The project ensures accurate representation of infrastructure locations, systematic classification of objects, and transparent monitoring of resource utilization, thereby aiding in the prioritization of research and development activities for recovery. Additionally, it promotes transparency and open science principles, enabling both the public and international community to track and evaluate the development of research infrastructure in Ukraine.In Slovakia, a national policy document, the SK VI Roadmap 2020-2030, plays a significant role in monitoring and developing research infrastructure. Prepared by the Ministry of Education, Science, Research, and Sports in collaboration with World Bank experts and research agency representatives, this document outlines a system for assessing, monitoring, managing, and financing research infrastructure. It establishes a vision and specific measures for the development of research infrastructure in Slovakia, emphasizing its interconnection with the economy, smart specialization domains, and international cooperation within ESFRI and the Horizon Europe framework. This experience in Slovakia provides valuable insights for the implementation of similar initiatives in Ukraine.

Research on the methodology of digital mapping of national natural parks

This scientific article envisages updating of basic electronic digital maps and their inclusion in the National Geoinformation Base, as well as their effective use for the preservation of national natural parks and maintenance of their cadaster. On the map base created, initial site geodetic work was carried out at the geographical location of the national nature parks. And also, an in-depth analysis of remote sensing materials was carried out. These remote sensing materials were processed in special programs, decoded, and new objects were mapped on the digital map base in ArcGIS program.