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Basics of geomatics
Abstract and Figures
This paper presents the volume “Basics of Geomatics” (Springer, ISBN 978-1-4020-9013-4). The volume introduces in a systematic
way the complex topics and techniques that can be assembled under Geospatial Information, namely, geodesy, cartography, photogrammetry,
remote sensing, informatics, acquisition systems, global positioning systems, digital image processing, geographic information
systems, decision support systems, and WebGIS. It describes in detail and at an accessible level the state of current knowledge.
As such, it will serve as a working tool not only to geoscientists and geographers but also to engineers, architects, computer
scientists, urban planners, specialists in geographical information system, remote sensing, forestry, agricultural science,
soil science geometry, environmental scientists, and managers. Applications can be found in security, risk management, monitoring,
infomobility, geopositioning, food traceability, etc.
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... To establish a map of LULC for each of the five-year images, a supervised classification method was used with the maximum likelihood algorithm [54] . This approach produces generally better results than the minimum distance approach [1,55] . Seven LULC categories, in accordance with the Cambodia land use map of 2002 produced by the JICA, were chosen for this study: urban/built-up area, water feature, grassland, shrubland, agricultural land, barren land, and forest cover. ...
This study analyzed land use and land cover (LULC) change from 1998 to 2018 in Battambang, Cambodia, and determined factors and constraints affecting agricultural production. Landsat satellite images in 1998, 2008, and 2018 were used to identify the changes in LULC. In combination, a social survey was conducted in August 2021 using purposive sampling, selecting a total sample of 200 from two wealth classes: the poor (65) and the better off (135) based on the Cambodia poverty assessment by the World Bank, from uplands to lowlands of Battambang Province, Cambodia. Household characteristics, farm size, and constraints were compared between the classes. T-tests, the analysis of variance (ANOVA), and Likert scale analysis were adopted using the R Program and RStudio, while Pearson's correlation test was used to determine the factors affecting agricultural land. The results show that between 1998 and 2018, the forest cover decreased by 79%. In contrast, agricultural land expansion was the highest (54%). The average household size and age of the respondents were 5.0 persons/household and 50.1 years, respectively. Of all the interviewees, about 80% attended no higher than primary school. The total farm size of the better-off (7.0 ha/household) was larger than that of the poor (5.2 ha/household). The population growth, machinery use, and improved infrastructure were found to be positive and strongly related to agricultural land use. The highest constraints of the poor and the better-off households were the same: chemical fertilizer use. Then, drought and flooding were also challenges for all. In terms of land, credit, and labor, they were not the main constraints. Thus, it is recommended that the involvement of interdisciplinary stakeholders and policy frameworks is really important from both biophysical and social perspectives.
... As the processing of such information increasingly requires an interdisciplinary and interoperable environment, we thought that geomatics technologies satisfy such requirements. As reviewed by Gomarasca [23], the term geomatics was based on the concept that the increased potential of electronic computing was revolutionizing surveys and representation sciences and that the use of computerized design was compatible with the treatment of huge amounts of data. Among the different geomatics techniques and disciplines able to assign a geospatial location to each object on the planet, we considered as a specific point of interest those of satellite-based remote sensing Earth Observation. ...
This research is part of a wider framework of index literature studies that have been conducted in the past few years. Some of these have had a focus on specific remote sensing (RS) technologies, while others have tackled specific threats to cultural heritage and landscapes. By considering both damages to heritage sites and technologies used for documentation and the monitoring of such occurrences, this paper unveils the current trends on a global scale in the study of the threats to heritage caused by both human-induced and natural hazards. Papers published by Europe-based researchers over the last 20 years using RS and Earth Observation (EO) techniques were surveyed alongside recommendations and programmatic documents issued by institutions in charge of heritage protection and management of several countries in Europe. Around 300 documents, including scientific articles (published from 2000 until 2022) and Grey literature (from 2008 and 2022), were analysed. The data collection and analysis were undertaken by a working group that was intentionally composed to bring together diverse perspectives and expertise, i.e., requirements of heritage professionals using RS and EO technologies, knowledge on technologies and their use in the field, and expertise in methodology implementation to support heritage management. The results highlight the type of hazards considered the most and the geographical distribution of the archaeological sites and monuments targeted by these studies; the countries the researchers are affiliated with; the types of RS and specifically satellite-based technologies used (and hence the type of data used); the tendencies of satellite data usage—visual interpretation, image processing, employment of machine learning, and AI; the technologies most applied by public institutions and practitioners; and many others. Recommendations and future trajectories are then outlined to efficiently reframe discrepancies between types of damage that have received the greatest attention in the literature and the most impactful ones in terms of the number of sites damaged.
... Geoinformation technology is widely used for data visualization and technical analysis of the environment, urban planning, recreating the past, 3D city modeling, biodiversity monitoring, access to geo-data for citizens and tourists, forest biomass mapping, public health, military, transport network planning, and management, agriculture, meteorology, and climate change, oceanography and coupled ocean and atmosphere modeling, business location planning, architecture and, telecommunications, criminology and crime simulation, aviation, and renewable energy (Amade et al. 2018;Fuhrmann et al. 2008;Kundu et al. 2020;Kuzhelev 2013;Lemmens 2011;Levina et al. 2017;Malczewski and Rinner 2017;Morkul et al. 2018;Neussner et al. 2008;Petrescu 2007;Prasannakumar et al. 2012). According to Gomarasca (2010), "Geoinformation technology or Geomatics is defined as a systemic, multidisciplinary, integrated approach to selecting the instruments and the appropriate techniques for collecting, storing, integrating, modeling, analyzing, retrieving at will, transforming, displaying, and distributing spatially georeferenced data from different sources with well-defined accuracy characteristics and continuity in a digital format". Therefore, the objective of this research was to assess the risk and physical vulnerability of building structures to floods at the household level in a riverside communities. ...
Climate change causes major effects on the environment and nature as it leads to increasing urban flood hazards. Flooding is the most frequent natural hazard that occurs in the Asia–Pacific region where an increasing number of people are choosing to live in floodplain areas. Communities living in monsoonal regions have learned to live with floods. The most important component of flood management is assessing flood vulnerability on an urban scale. This study conducted flood vulnerability assessment and analysis of physical building structures in Warin Chamrap municipality, Thailand. GIS-based method of estimating the vulnerability of buildings to floods was employed for flood vulnerability assessment. The results identified building structures in the flood-prone area that are at extreme risk. The study found that 87 households were at a moderate to extreme risk in the extreme flood vulnerability area and 130 households with structural damage. The flood vulnerability index (FVI) is a powerful tool for a better understanding of community and building structures and to identify adaptations for vulnerability reduction. However, the FVI is limited by a number of factors that reduce its capacity as an accurate and practical tool for decision-makers. For future development, geospatial data visualization and GIS-based flood vulnerability assessment techniques should be considered as a method to provide a baseline to guide further study.KeywordsGeospatial technologyFlood vulnerability indexNatural hazardPhysical vulnerability
... « La géomatique est une approche systémique, multidisciplinaire et intégrée pour sélectionner les instruments et les techniques appropriées pour collecter, stocker, intégrer, modéliser, analyser, afficher et distribuer des données spatialement géoréférencées dans un format numérique » [Gomarasca, 2009]. La résolution photogrammétrique 3D est fonction de la taille des pixels. ...
EOMATICS ON LEBANESE KARST,
APPLIED RESEARCH IN THE ARZ JAJ NATURE RESERVE
(BYBLOS). The karst of the Jurassic bastion of Jabal Jaj is highly developed. The altitude reaches 1959 m and precipitation amounts of 1700 mm per year. Mapping using the
classical methods of photokarstology and field visits has given a satisfactory idea of Arz Jaj Nature Reserve karst in conjunction with the existing lithology mainly formed of limestone and dolomites. New geomatics methods, based on high resolution drone imagery, allow the details mapping of karst expressed in closed depressions and inaccessible karst towers.
KEYWORDS: cartography of karst phenomena, drone, photogrammetry, geomatics, fields of lapies, fields of dolinas, sinkholes, snow pits, dry valleys..
Artificial intelligence (AI) has made significant advancements in the field of geomatics, revolutionizing the way geospatial data is processed, analyzed, and interpreted. While these advancements have brought numerous benefits, they also raise ethical risks that must be carefully considered. The improvement of AI in geomatics has introduced ethical considerations such as data privacy, algorithmic bias, transparency, accountability, and the responsible use of AI technology. As AI algorithms process and analyze vast amounts of geospatial data, concerns regarding data privacy and security become paramount. Geospatial data often contains sensitive information, and the use of AI requires robust measures to protect individual privacy and prevent unauthorized access or misuse of data. This paper examines the ethical implications of the use of AI in geomatics and proposes the concept of GeomEthics as a framework for analyzing these ethical considerations. It explores the technical aspects of AI in geomatics and highlights the ethical principles of fairness, privacy, bias, accountability, and transparency. By coining the term GeomEthics, the paper emphasizes the importance of addressing these ethical concerns. It proposes the development of ethical guidelines and best practices for the responsible integration of AI in geomatics and discusses future research directions in the field. This paper contributes to a comprehensive understanding of the ethical implications of AI in geomatics and provides insights for ensuring the responsible and beneficial use of AI technologies in the geospatial domain. By addressing these ethical challenges, the field of geomatics can harness the benefits of AI while mitigating its potential risks and ensuring that geospatial analysis and decision-making processes are conducted ethically and responsibly.
Researchers have explored the benefits and applications of modern artificial intelligence (AI) algorithms in different scenarios. For the processing of geomatics data, AI offers overwhelming opportunities. Fundamental questions include how AI can be specifically applied to or must be specifically created for geomatics data. This change is also having a significant impact on geospatial data. The integration of AI approaches in geomatics has developed into the concept of geospatial artificial intelligence (GeoAI), which is a new paradigm for geographic knowledge discovery and beyond. However, little systematic work currently exists on how researchers have applied AI for geospatial domains. Hence, this contribution outlines AI-based techniques for analysing and interpreting complex geomatics data. Our analysis has covered several gaps, for instance defining relationships between AI-based approaches and geomatics data. First, technologies and tools used for data acquisition are outlined, with a particular focus on red–green–blue (RGB) images, thermal images, 3D point clouds, trajectories, and hyperspectral–multispectral images. Then, how AI approaches have been exploited for the interpretation of geomatic data is explained. Finally, a broad set of examples of applications is given, together with the specific method applied. Limitations point towards unexplored areas for future investigations, serving as useful guidelines for future research directions.
O planejamento de recursos hídricos é tarefa complexa, pois envolve uma gama de atores com interesses muitas
vezes conflitantes. Aliado a isso, o crescimento desorganizado das grandes cidades e a escassez hídrica
levam os gestores a tomarem decisões balizadas por Sistemas de Apoio a Decisão - SADs. Nessa problemática
inserem-se as Companhias de Saneamento que compõem o sistema de recursos hídricos no Ceará como uma
indústria que solicita outorga de uso para tratamento e distribuição de água tratada dentro dos parâmetros
exigidos por lei. Nesse contexto, o gerenciamento do sistema de abastecimento de água é um desafio para as
companhias estaduais, tendo em vista que a grande malha de sua infraestrutura está enterrada. Conhecer o
sistema para decidir ampliar ou dar manutenção é estratégico para a sobrevivência das companhias. Surge,
assim, o Sistema de Informação Geográfica, que busca prover ao gestor público uma ferramenta de apoio à
decisão. No presente trabalho, buscou-se demonstrar a aplicabilidade de tal ferramenta sob a visão de um
estudo de caso de viabilização da interligação de empreendimentos particulares na Região Metropolitana de
Fortaleza, por meio de acoplamento entre SIG e software hidráulico, dispondo, no final, de solução técnica
para a viabilização da entrada de demanda no Sistema de Abastecimento de Água.
Purpose
This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings.
Design/methodology/approach
To do so, this study discusses the European Union (EU) and China’s approaches to data-driven technologies highlighting their similarities and differences when it comes to the vision underpinning how tech innovation is shaped.
Findings
Regardless of the different attention to the subject (the EU) and the collective (China), the normative understandings of technology by both actors remain trapped into a positivist approach that overlooks all that is not and cannot be turned into data, thus hindering the elaboration of a more holistic ecological thinking merging humans and technologies.
Originality/value
Revising the philosophical and political debate on data and data-driven technologies, a third way is elaborated, i.e. federated data as commons. This third way puts the subject as part by default of a collective at the centre of discussion. This framing can serve as the basis for elaborating sociotechnical alternatives when it comes to define and regulate the mash-up of humans and technology.
Owing to the fact that nearly all economic sector of a country has embraced technology in their mode of operation. The banking industry as a financial institution in its recent implementation of electronic banking and the use of Automated Teller Machine has not been left out. The location of this ATM's with respect to their users is a geospatial problem, the industry aim is to ensure that such facilities are optimally located. The location-allocation tools in Geographic Information System thus become useful. This study investigates and assess the existing ATMs in the study area using location and service ability as a factor. Questionnaires were administered to assess the service ability of existing ATMs. For location evaluation the geographic coordinates of ATMs and Police stations were acquired using Garmin 78 Handheld Global Positioning System, the remotely sensed image of the study area was gotten from the Surveyor General of the Federation Office, it was digitized and used along with the acquired coordinates to create a database using ArcGIS 10.3. The resulting map was used to create a network analysis. Various Location-Allocation model were then used to assess and fix new optimal locations for ATMs. The results show that with a travel distance of 1.5km used in the models, the maximum coverage mode is the most suitable location-allocation models, for a banking system that seeks for equity among various banks, ATM centers can be sited using this model. The marginalization that occurs from other models makes them unfit for the banking industry. One of the final results from this study is that the optimal area for locating new ATMs amongst potential sites in terms of compatibility with the chosen criteria. This study suggests that; decision making future siting of ATMs to serve customers within this distance zone could use this model.
In this study, we sketch the history of the term remote sensing, comment on its usage, note the continuing search for substitute terms, examine maximal and minimal definitions, compare synonyms and antonyms, and classify definitions into three groups. Finally, we offer extended meaning to the term remote.-from Authors
Object-oriented modelling has gained prominence in the GIS environment in the last 10 yr, and the approach has been recommended for the modelling and management of spatial data. However, a gap between research and implementation is still noticeable because of a lack of mature operational systems for object-oriented implementations and the fact that the modelling concepts are still confusing to most users. Its application in spatial data modelling is thus minimal at the moment. This latter problem is addressed in this paper by reviewing the important object-oriented concepts. General issues concerning the implementation of an object-oriented data structure are also presented. -Author
Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for improved classification with the remote sensing data, Wiener filter-based method, and other modern approaches and methods of image processing for remotely sensed data. Each chapter explores a technique for dealing with a specific remote sensing problem. The book offers physical insights on the steps for constructing various digital seismic images. The volume examines image modeling, statistical image classifiers, change detection, independent component analysis, vertex component analysis, image fusion for better classification. It explores unique topics such as accuracy assessment and information-theoretic measure of multiband images and many chapters emphasize issues with synthetic aperture radar (SAR) images. Continued development on imaging sensors creates new opportunities and challenges in image processing for remote sensing. Image Processing for Remote Sensing not only presents the most up to date developments of image processing for remote sensing but also suggests to readers the many challenging problems ahead for further study.
The European Remote Sensing Satellite ERS-1, lauched by ESA in 1991, carries an Active Microwave Instrument (AMI). During several phases of its operations, ERS-1 has been operated in almost exact repeat orbits with periods of 3 and 35 days. The data acquired during these repeat orbits can be used to perform repeat-pass SAR interferometry. The excellence of ERS-1's orbit and attitude control system and the high reliability of its SAR system result in excellent interferograms. -Authors
The growth of automation in cartography and the development of the fields of remote sensing and geographic information systems (GIS) have led to a situation where the subject matter of each is poorly defined with respect to the others. From a review of the literature, a number of models of interaction are identified among these fields, and the alternatives are explored. In the favored model, the three fields each have a unique domain, as well as two-way and three-way interactions. -Authors
During the last decade, vegetation indices have been widely used by the remote sensing community to monitor land surfaces and vegetation canopies. Most vegetation indices related well to the amount of vegetation; however, they are also affected, to a greater or lesser extent, by external factors such as measurement geometry, atmospheric influences and soil spectral properties. Meanwhile, as new sensors such as the high spectral resolution sensors and the two look-angle ATSR-2 radiometer are developed, a need has arisen to extend the concept of vegetation indices to include more than two spectral channels and one viewing angle. A review of the commonly used indices is presented here, focusing particularly on the literature of last five years. A summary of the biophysical processes relating vegetation bidirectional response to plant characteristics is also included. -from Author
Since the early emergence of Earth observation satellites, researchers have investigated different methods of extracting three-dimensional information using satellite data. Apart from a few early stereo images by hand-held photographs acquired during the Gemini and Apollo missions, the first experiments to extract three-dimensional data using stereo viewing from space began with the Earth Terrain Camera flown onboard SkyLab in 1973/74. Since this time, various analogue or digital sensors in the visible spectrum have flown to provide researchers and geoscientists with spatial data to extract and interpret three-dimensional information of the Earth's surface. Although clinometry techniques can be applied with the optical sensor images, stereo viewing of images was and still is the most common method used by the mapping, photogrammetry and remote sensing communities for elevation modelling. The paper will review clinometry and stereoscopy and their applicability to the different satellite sensors (space photographs and scanners). Their performances to extract absolute or relative elevation from various research and commercial organizations are addressed. The respective advantages, difficulties and constraints of the sensors are discussed, as well as the methods and the technologies used for extracting elevation data in an operational context.