INTELLECTUAL PROCESSING OF GEOSPATIAL AND GEODETIC DATA IN MUNICIPAL MANAGEMENT SYSTEMS

Recommended citation:

Nesterenko S., Baistruk O., Musiienko K., Frolov O. Intellectual processing of geospatial and geodetic data in municipal management systems. Monograph. – Primedia eLaunch, Boston, USA, 2026. – 230 p.

URL: https://isg-konf.com/979-8-90214-541-7/.

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TABLE OF CONTENTS

  INTRODUCTION 9
1 GEOSPATIAL AND GEODETIC DATA IN DIGITAL MUNICIPAL MANAGEMENT SYSTEMS  

13

1.1 The role of geospatial and geodetic data in modern territorial management  

13

1.2 Classification of sources of geodetic and spatial data in municipal systems  

15

1.3 Structure and properties of geodata: accuracy, completeness, relevance, consistency  

18

1.4 Problems of geodetic data quality in digital GIS 20
1.5 Geodata as the basis for management decisions in local communities 23
1.6 The conceptual role of geodetic and geospatial data in the transformation of municipal GIS  

26

1.7 Regulatory, legal and standard support for geodetic and geospatial data in Ukraine and the European Union  

28

1.8 Geospatial data in the context of the Smart City concept 35
2 METHODS OF PRELIMINARY PROCESSING OF GEODETIC AND GEOSPATIAL DATA  

41

2.1 Theoretical foundations of preliminary processing of geodetic data 41
2.2 Filtering, smoothing and normalisation of geodetic measurements 44
2.3 Transformation of coordinate systems and conversion of data to a single spatial environment  

46

2.4 Office processing of geodetic data in GIS and CAD 48
2.5 Preparation of geodetic data for intelligent analysis and machine learning  

51

2.6 Methodological readiness of geodetic data for intelligent modelling in municipal GIS  

54

2.7 Methods of quality control, validation and accuracy management of geospatial data  

57

2.8 Integration of geospatial data from different sources 61
2.9 Spatial-topological operations as a key element of geospatial data preprocessing  

65

2.10 Automation of geospatial data preprocessing 68
2.11 High-performance processing of large geospatial data in municipal geographic information system  

74

3 ARTIFICIAL INTELLIGENCE METHODS IN GEODETIC DATA PROCESSING  

80

3.1 Relevance of artificial intelligence technologies 80
3.2 Overview of existing methods for processing geodetic data 82
3.3 Analysis of approaches to developing methods for processing geodetic data using artificial intelligence  

85

3.4 Types of artificial intelligence algorithms 87
3.5 The capabilities of artificial intelligence combined with AutoCAD software  

89

3.6 Artificial intelligence in satellite image processing 91
3.7 Integration of artificial intelligence methods into surveying production processes and municipal GIS  

99

3.8 Automation of production processes based on artificial intelligence 106
3.9 Intelligent methods for constructing digital twins of territories based on geodetic and geospatial data  

114

3.10 Intelligent methods for analyzing and modeling Earth surface deformations based on GNSS, InSAR, and LiDAR data  

121

3.11 Intelligent models for anomaly detection and diagnosis of geodynamic processes in geodetic data  

130

3.12 Intelligent systems for automated classification and vectorization of geodetic and cartographic data  

135

4 INTEGRATION OF INTELLIGENT DATA PROCESSING INTO MUNICIPAL GEOINFORMATION SYSTEMS  

145

4.1 Architecture of municipal GIS with intelligent modules 145
4.2 Geoanalytical geodata processing pipeline 147
4.3 Integration of artificial intelligence models with spatial databases 150
4.4 ETL processes and automated processing of geospatial data streams 152
4.5 Intelligent decision support services in local communities 155
5 APPLICABLE SCENARIOS AND PROSPECTS FOR THE DEVELOPMENT OF INTELLIGENT GEODATA PROCESSING  

 

159

5.1 Use of intelligent geodata processing in municipal management 159
5.2 Geodetic and GIS solutions for monitoring infrastructure and territories  

168

5.3 Intellectual support for the processes of restoration and development of territorial communities  

178

5.4 Standardisation, interoperability and open geodata 187
5.5 Prospects for scientific research and educational application of results  

194

  CONCLUSIONS 204
  REFERENCES 207
  APPENDICES 224