The developed geoid model "HELLAS GEOID 2022" (HG2022) is the most comprehensive geoid model ever computed by the Hellenic Military Geographical Service (GYS) for the entire Greek territory. Its computation was based on long-term gravity data, orthometric and geometric height measurements, as well as high-resolution digital terrain and bathymetric models. All datasets were thoroughly evaluated for both compatibility and accuracy. In addition, data from other studies were incorporated to supplement measurements in areas with limited coverage, including marine regions and neighboring countries.

     For the computations, the "remove–compute–restore" technique was adopted in order to separate the gravity signal within the heterogeneous datasets. The global geopotential model found to best fit the Greek territory was EIGEN-6C4, developed to degree and order 2190. The contribution of the mean residual gravity to the geoid was computed using Stokes' theorem in the frequency domain through the Fourier transform.

     The final gravimetric geoid surface was subsequently fitted to the existing national height reference system with an accuracy of approximately 5 cm. This adjustment was performed using the point collocation method and a network of points with known orthometric and geometric heights distributed throughout the Greek territory.

     Tags: Geoid, HELLAS GEOID 2022, HG2022, Gravity Data, Gravimetric Geoid, Geodesy, Height Reference System, Orthometric Heights, Geometric Heights, Geopotential Model, EIGEN-6C4, Stokes Theorem, Fourier Transform, Point Collocation, Digital Terrain Model (DTM), Bathymetry, Greece, Hellenic Military Geographical Service (GYS).

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     Greece has approximately 16,000 km of coastline. Nearly 70% of the country's population resides within the coastal zone, where a wide range of economic activities and land uses are concentrated. Consequently, there is a clear need for methods and tools that can support the monitoring and management of coastal areas, with the ultimate goal of ensuring their sustainable and optimal utilization. This study examines the process of automatic recognition of coastal features, specifically coastal wetlands, through object-oriented image analysis using digital multispectral remote sensing imagery. Initially, the study briefly investigates the characteristics of coastal wetlands and the properties of multispectral imagery. These characteristics are then incorporated into an object-oriented analysis methodology to develop appropriate fuzzy logic functions, which are subsequently used to identify and extract the features under investigation. The study further analyzes the development of an automated workflow for recognizing these coastal features and proposes innovative and practical approaches through which this methodology can be applied in real-world environmental monitoring and management scenarios. Tags: Coastal Features, Coastal Wetlands, Remote Sensing, Digital Remote Sensing Data, Multispectral Imagery, Object-Oriented Image Analysis (OBIA), Fuzzy Logic, Feature Extraction, Coastal Monitoring, Coastal Zone Management, Geographic Information Systems (GIS), Environmental Monitoring, Land Cover Classification, Earth Observation, Image Processing, Spatial Analysis, Greece.

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      Satellite images are undoubtedly one of the most important tools for monitoring the Earth's surface. The acquired satellite images vary due to orbital parameters, sensor specifications, acquisition periods, and spatial resolutions. Therefore, continuous search for the most recent and highest-resolution satellite imagery is essential, information that can be obtained by monitoring their metadata.

      This technical report presents a metadata retrieval procedure for the ESRI satellite basemap. Regular metadata monitoring is essential to ensure access to the most recent satellite imagery and also provides an overall picture of acquisition years, update frequency, and spatial resolution. For this purpose, HMGS developed Python code used to retrieve satellite image metadata for user-defined areas.

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      The Hellenic Armed Forces (HAF), through the Hellenic Military Geographical Service (HMGS), are called upon to support the spatial organization and planning of the state in cases of natural disasters. The purpose of this technical bulletin is to highlight the social contribution of HMGS and the usefulness of orthophotos as a civil protection tool since the 1990s. For this purpose, HMGS conducts aerial photography missions and produces geospatial products after disasters and other required needs, with speed, consistency, and geometric accuracy.

      Wildfires are one of the large-scale natural phenomena that humans are still unable to control. They represent one of the most serious threats to forests, destroying valuable ecosystems and socially important areas every year. In many cases, they also result in tragic losses of human lives, animals, and property. Their destructiveness lies both in their increasing frequency and intensity and in the insufficient protection of natural regeneration processes and land use. The problem in Greece is severe, with extreme events occurring periodically. Some of the most significant wildfires include: 1997 Seikh Sou Forest - Thessaloniki, 2007 Peloponnese, 2008 Western Peloponnese, 2009 NE Attica, 2018 Mati Attica, 2021 Northern Evia, Peloponnese and Attica. In particular, only in the summer of 2021 in Northern Evia and Attica, property and forest areas totaling 650,000 hectares were destroyed. All these highlight the need for prevention, planning, and immediate response from the state.

      Greece is the most seismically active country in Europe and ranks sixth worldwide. Although it represents only 0.02% of the Earth's surface, it releases about 2% of global seismic energy annually and more than 50% of Europe's. The use of orthophotos after major earthquakes began in 1999 with the Athens earthquake and the creation of refugee settlements as a contribution of the armed forces to society and the state.

      The contribution of HMGS in the above areas is twofold, as will be presented below. It concerns the rapid mapping of affected areas within hours or days after an event, the precise delineation of boundaries, and their use by civil protection authorities or legislative frameworks. At the same time, it involves the processing and creation of orthophoto maps of affected areas, which serve as high-precision geospatial tools.

      As highlighted by the International Commission on Large Dams (ICOLD) in its 2007 report, dams play a critical role in modern human history. In every structure, a potential source of risk is failure or collapse. The failure of a water storage dam could cause severe losses and extensive damage to infrastructure, the environment, and social networks, as well as hinder regional development. In Greece, there are more than 130 large and medium-sized dams, many of which are located near populated areas. The country is also highly seismic and, in recent years, has experienced several strong earthquakes. At the same time, due to socio-economic conditions in recent years, the maintenance of many dams can be considered insufficient. For safety planning, it is essential to study the impacts of a potential dam breach or failure in order to determine evacuation times and response actions for all state authorities.

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      Temporal variations of gravity are characterized as abrupt, periodic, quasi-periodic, or secular. The effects of gravity changes on the Earth's surface can be local, regional, or global. As the depth of the source increases, the affected area becomes larger. Local gravity variations are observed in seismic and volcanic regions during active phases. To identify these changes, gravity networks covering wider areas are required and must be re-measured at regular intervals. These local variations are closely related to seismotectonic processes, as well as pre- and post-seismic phenomena, volcanic activity, and fault movements. Seismic activity leads to abrupt and short-term gravity changes.

      Within its annual field operations, HMGS conducted gravity measurements at gravimetric stations across Greece for the year 2020. Among the measured points were five stations in Samos during 05–07 August and 09–10 August, i.e., 82 days before the 6.7 magnitude earthquake that occurred north of the island. Additionally, repeated measurements were carried out in Larissa at different times during 2020, on 26 and 30 January 2021, and one week after the 6.0 magnitude earthquake in Elassona (03 March 2021). Analysis of these data allows useful conclusions regarding the correlation between gravity variations and seismic activity. Finally, the establishment and monitoring of a gravimetric station network in historically seismically active regions is proposed.

      The contribution of the Third Community Support Framework (CSF) to the upgrading and modernization of economic and social processes and ultimately to the development of Greece was particularly significant. This helped reduce disparities between Greece and other EU member states both in living standards and economic level. One of the operational programs of the Third CSF is the Information Society (IS), which through a series of actions aimed to create the conditions under which Greece would respond to the new "digital" era across various sectors of the economy and society. One of these sectors is Public Administration and consequently the Hellenic Military Geographical Service (HMGS). HMGS has been, for over 130 years, a military and scientific service providing consistent support to the Armed Forces and to society. Within the framework of the Third CSF and the Information Society program, an important project was implemented concerning the conversion of available analog spatial data of HMGS into digital form. This resulted in a qualitative upgrade of HMGS services. The completion and validation of this project for data completeness in digital form and for faster and more efficient public service was a long-standing necessity.

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      Across the Greek territory there are concrete bridges used by infantry and mechanized units of the Hellenic Army for transportation and movement operations. Using digital clinometers and machine learning models, conclusions were derived and predictions were made regarding the structural behavior of some concrete bridges in order to support decisions about the structural integrity of their pylons. Specifically, span 8 of the bridge located at the Metamorfosi interchange of the Attiki Odos motorway was analyzed in detail. The purpose of this study is the collection and analysis of field data from the aforementioned sensors using machine learning techniques in order to compute semi-static inclinations at pylon M8 of the bridge.

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      This technical bulletin describes the process of exploiting the digital repository of 1:5.000 Topographic Diagrams (TD) of the Hellenic Military Geographical Service (HMGS). Using Geographic Information Systems technology, the entire set of raster files was recorded, radiometrically and planimetrically checked, and their vector polygon distribution was corrected. Additionally, through Python-based automation, new derivative files were created in a simplified directory structure, and the technical characteristics of the raster files were homogenized and optimized in terms of resolution and size. Using these derived files, a mosaic-type data structure was created. Furthermore, a standardized cartographic composition template at 1:5.000 scale was developed for rapid production of topographic diagram series. As a result, HMGS now maintains a unified and validated distribution of 1:5.000 TDs and a new set of correct derivative datasets. The mosaic structure enables rapid overview of all files in a unified dynamic representation as well as easy search and extraction of specific TDs for operational use. With the final derivative TD 1:5.000 dataset, fast and automated production of digital TDs and the provision of a web-based cartographic background service became possible.

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      Tectonic behavior and intense geodynamic processes occurring in the Greek region require continuous and long-term monitoring of the phenomena that generate them and their resulting effects. In particular, within the science of Geodesy, the precise determination of positions on the continuously deforming Earth’s surface represents a major challenge. A key tool in this direction is the determination of a geodetic velocity field that accurately describes crustal movements and is continuously monitored and updated. Modern GNSS observations provide an unparalleled advantage in terms of density and accuracy, enabling continuous direct monitoring of crustal displacements at relatively low cost. Thus, in this study, a geodetic velocity model for the entire Greek territory is derived using data from permanent GNSS stations operating in Greece as well as stations of the international IGS network, for the period 2015–2019. The processing of raw observations at code and phase level, the final network adjustment, and the transformation to the latest reference frame ITRF2014 were performed entirely using the scientific software GAMIT/GLOBK version 10.71. The results confirm the heterogeneity of velocity magnitudes and directions across the Greek region and are consistent with both officially published velocities from European agencies and global tectonic motion models. This highlights the necessity of adopting a velocity field for the Greek territory within the framework of a modern kinematic or semi-kinematic reference system that incorporates observed displacements and enables connection with international reference frames or observations from different epochs.

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      The Hellenic Military Geographical Service (HMGS) uses aerial photographs, digital orthorectified images, and even satellite imagery for the production of various geographic products and for national mapping activities.

In order to produce and support modern, innovative, flexible, high-quality, and reliable geospatial products and services for both the Armed Forces and the wider public and private sector, it is essential to ensure quality control of the primary image data from which geographic products are derived.

The purpose of this study is the investigation and understanding of digital image quality assessment methods that assist in selecting appropriate optical systems for aerial photography and choosing the most suitable images that lead to optimal results in final geospatial products.

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      Prior to military operations, an analysis of the operational area characteristics is conducted. Terrain analysis is a key part of this process, and soil trafficability is directly influenced by soil moisture content. Therefore, soil moisture values are critical information for command levels during operational planning.

In-situ soil moisture measurements, although accurate, are time-consuming and costly and provide only point-based data. Consequently, the scientific community has turned to remote sensing methods using satellite data for soil moisture estimation.

For this study, the MULESME (MUltitemporal Least Square Moisture Estimator) software was used, designed for systematic mapping of surface soil moisture using SAR (Synthetic Aperture Radar) data from Sentinel-1 satellites. Although originally developed for Italy, it can be applied to other regions as well. It implements a multi-temporal algorithm using Sentinel-1 time series data and auxiliary datasets such as land cover maps and vegetation water content indices.

The software was applied, with modifications, to the broader Komotini area, using in-situ soil moisture data provided by NEUROPUBLIC. The dataset included 8 ground stations located in cotton fields. A total of 13 Sentinel-1A and Sentinel-1B images were used to estimate soil moisture from July to September 2018.

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      The spatial dimension of information refers to the ability to associate it with real-world locations and overlay it on a map. The science of Geospatial Intelligence leverages this capability to integrate information from multiple sources, visualize it on mapping or imagery backgrounds, and produce comprehensive products that clearly represent the current state of an ongoing phenomenon or activity.

This practice provides significant advantages by enhancing situational awareness and supporting well-informed decision-making by relevant authorities and organizations.

Geospatial Intelligence did not emerge as a standalone discipline but evolved from military operational practices. It was formalized following the September 11, 2001 attacks in the United States, with the National Geospatial Intelligence Agency (NGA) as a key institution.

This technical report analyzes the historical development of the Geospatial Intelligence doctrine, its main components, and current trends in the field.

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      In collaboration with the Medical Association of Athens (ISA) and the Region of Attica, HMGS developed a geospatial system for recording and monitoring COVID-19 cases. The main objective is the rapid collection and real-time dissemination of data to support decision-making.

The system reduced the exposure time of medical personnel and improved safety. It also accelerated questionnaire processing and enabled immediate statistical analysis at operational centers.

The system consists of three applications and provides data analysis tools for scientific staff.

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      In the modern era, where information is produced and disseminated at extremely high rates, the demand for geospatial information is continuously increasing. For geospatial data to be usable, it must be updated; otherwise, it loses its purpose.

For the Hellenic Military Geographical Service, as well as other public bodies such as the Hellenic Cadastre and OPEKEPE, updating geospatial information is essential for fulfilling their responsibilities.

For this reason, the revision of base layers (aerial photographs, orthophotos, satellite imagery) is considered critical and is the subject of ongoing efforts.

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