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Satellite imagery has become a major source for identifying and mapping terrestrial and planetary landforms. However, interpretating landforms and their significance, especially in changing environments, may still be questionable. Consequently, ground truth to check training models, especially in mountainous areas, can be problematic. This paper outlines a decimal format, [dLL], for latitude and longitude geolocation that can be used for model interpretation and validation and in data sets. As data have positions in space and time, [dLL] defined points, as for images, can be associated with metadata as nodes. Together with vertices, metadata nodes help build 'information surfaces' as part of the Digital Earth. This paper examines aspects of the Critical Zone and data integration via the FAIR data principles, data that are; findable, accessible, interoperable and re-usable. Mapping and making inventories of rock glacier landforms are examined in the context of their geomorphic and environmental significance and the need for geolocated ground truth. Terrestrial examination of rock glaciers shows them to be predominantly glacier-derived landforms and not indicators of permafrost. Remote-sensing technologies used to track developing rock glacier surface features show them to be climatically melting glaciers beneath rock debris covers. Distinguishing between glaciers, debris-covered glaciers and rock glaciers over time is a challenge for new remote sensing satellites and technologies and shows the necessity for a common geolocation format to report many Earth surface features. [ABSTRACT FROM AUTHOR]

This study examines the development trajectory and current trends of three-dimensional (3D) geological modelling. In recent years, due to the rising global energy demand and the increasing frequency of regional geological disasters, significant progress has been made in this field. The purpose of this study is to clarify the potential complexity of 3D geological modelling, identify persistent challenges, and propose potential avenues for improvement. The main objectives include simplifying the modelling process, improving model accuracy, integrating different data sources, and quantitatively evaluating model parameters. This study integrates global research in this field, focusing on the latest breakthroughs and applications in mineral exploration, engineering geology, geological disaster assessment, and military geosciences. For example, unmanned aerial vehicle (UAV) tilt photography technology, multisource data fusion, 3D geological modelling method based on machine learning, etc. By identifying areas for improvement and making recommendations, this work aims to provide valuable insights to guide the future development of geological modelling toward a more comprehensive and accurate "Transparent Earth". This review underscores the global applications of 3D geological modelling, highlighting its crucial role across various sectors such as mineral exploration, the oil and gas industry, urban planning, geological hazard assessment, and geoscientific research. The review emphasizes the sector-specific importance of this technology in enhancing modelling accuracy and efficiency, optimizing resource management, driving technological innovation, and improving disaster response capabilities. These insights provide a comprehensive understanding of how 3D geological modelling can significantly impact and benefit multiple industries worldwide. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this interview, scholar–curator Bryan Norton discusses new forms of planetary-scale image-making with artist–researcher Asia Bazydrieva (Geocinema) and media theorist Jussi Parikka. While collaborating with Bazdyrieva during the production of Geocinema's 'Making of Earths', a documentary exploring the Digital Belt and Road Initiative in China, Parikka wrote a new book, Operational Images: From the Visual to the Invisual (2023). In this study, Parikka suggests that the forms of image-making explored in 'Making of Earths' press against the very borders of the visible, possessing a long history with drastic political and social consequences. Drawing on the history of satellite imagery, drone footage and climate models, both Parikka's and Bazydrieva's work present fecund modes of artistic and scholarly engagement with the contemporary creation and dissemination of what Harun Farocki called 'operational images' in his audiovisual work from the early 2000s. In this conversation, Bazdyrieva, Norton and Parikka discuss the ever-increasing ubiquity of these types of images in order to highlight their role in planetary-scale computation systems, the production of scientific knowledge and the ongoing war in Ukraine. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We present GeoGlue, a novel method using high-resolution UAV imagery for accurate feature matching, which is normally challenging due to the complicated scenes. Current feature detection methods are performed without guidance of geometric priors (e.g., geometric lines), lacking enough attention given to salient geometric features which are indispensable for accurate matching due to their stable existence across views. In this work, geometric lines are firstly detected by a CNN-based geometry detector (GD) which is pre-trained in a self-supervised manner through automatically generated images. Then, geometric lines are naturally vectorized based on GD and thus non-significant features can be disregarded as judged by their disordered geometric morphology. A graph attention network (GAT) is utilized for final feature matching, spanning across the image pair with geometric priors informed by GD. Comprehensive experiments show that GeoGlue outperforms other state-of-the-art methods in feature-matching accuracy and performance stability, achieving pose estimation with maximum rotation and translation errors under 1% in challenging scenes from benchmark datasets, Tanks & Temples and ETH3D. This study also proposes the first self-supervised deep-learning model for curved line detection, generating geometric priors for matching so that more attention is put on prominent features and improving the visual effect of 3D reconstruction. [ABSTRACT FROM AUTHOR]

The concept of Digital Earth (DE) was formalized by Al Gore in 1998. At that time the technologies needed for its implementation were in an embryonic stage and the concept was quite visionary. Since then digital technologies have progressed significantly and their speed and pervasiveness have generated and are still causing the digital transformation of our society. This creates new opportunities and challenges for the realization of DE. 'What is DE today?', 'What could DE be in the future?', and 'What is needed to make DE a reality?'. To answer these questions it is necessary to examine DE considering all the technological, scientific, social, and economic aspects, but also bearing in mind the principles that inspired its formulation. By understanding the lessons learned from the past, it becomes possible to identify the remaining scientific and technological challenges, and the actions needed to achieve the ultimate goal of a 'Digital Earth for all'. This article reviews the evolution of the DE vision and its multiple definitions, illustrates what has been achieved so far, explains the impact of digital transformation, illustrates the new vision, and concludes with possible future scenarios and recommended actions to facilitate full DE implementation. [ABSTRACT FROM AUTHOR]

Geospatial data visualisation and interaction have been cartographic challenges from many perspectives. User experience in this field is tailored to various variables such as the level of detail, the sophistication of the required demonstration, the traditional visualisation paradigm, the volume of the data and the user's domain knowledge. Additionally, in an era of ubiquitous map consumption on various devices, including those in immersive experiences, the context of use stands out as an essential factor for map design. Understanding context involves grasping the interaction between the map user, the map use environment, the map use activity, and the map itself (Griffin et al., 2017). However, efforts have been made to design a user-friendly interface to improve navigation and interaction, but the geospatial data platforms available on demand are still not fully multimodal interfaces. The available platform's design, usability and accessibility are bound to the mouse, keyboard or touchscreen. Multimodal interfaces have been shown to significantly reduce the complexity of GIS interfaces (Fuhrmann et al., 2005), (Oviatt, 1996). Voice input can be considered one of the features that overcome the mentioned obstacles. Furthermore, it can allow users to control their interaction and selection while processing the data. Therefore, the integration of speech recognition technology with map applications can enable users to interact with map data and access information in a more natural and intuitive way without the need for complex user interfaces or manual input. (J. Austerjost, 2018). [ABSTRACT FROM AUTHOR]

The rapid decline of Arctic sea ice has been reminding us the significant impacts caused by global warming. However, the other side of the coin is that this opens a window to utilize the Arctic sea routes in the summer seasons, bringing remarkable economic benefits for ocean transportation between Asia and Europe. However, commercial vessels with low ice classes must tackle substantial environmental challenges in the Arctic sea routes, particularly those caused by variable sea ice, even in the melting seasons. Therefore, the science-based support for shipping safety in the Arctic sea routes is being given more prominence. Emerging satellite remote sensing technology plays a critical role in environmental monitoring in the Arctic. This paper reviews state-of-the-art satellite observations on monitoring sea ice and potential applications on supporting shipping activities in the Arctic Ocean. Moreover, we introduced a recently developed system based on satellite observations to support the safe transportation of Chinese cargo vessels in the Arctic northern sea route, demonstrating the efforts by both the science and business communities to promote the development of the polar silk road. [ABSTRACT FROM AUTHOR]

The aim of this study was the spatial and temporal monitoring of soil erosion patterns in Iran. The G2 model was used, as an appropriate tool to provide the required month-time step country-wide soil loss maps and statistical outputs. The input parameters were derived with field surveys and remote sensing imagery (MODIS, SRTM, SPOT, and Sentinel-2 scenes). An innovation for G2 was the consideration of the snow cover effect on the rainfall erosivity. It was also the first time G2 was used to map such a big country like Iran on a country scale. The mean annual soil erosion in Iran was found to be 16.5 t ha−1, which is equal to about 2.7 billion tons of soil loss. In spatial terms, the highest soil loss values were found in the north, west and southwest part of Iran, in the steep slopes in Alborz and Zagros mountains. In temporal terms, the highest and lowest monthly erosion values of 3.2 and 0.09 t ha−1 correspond to January and July, respectively. [ABSTRACT FROM AUTHOR]

Reminding us of the importance of the narratives and stories we tell each other and their numerous effects on us, Kate Davies, co‐founder of the Unknown Fields travelling design studio, and art and architecture collective Liquid Factory, introduces us to architecture that is a synthesis of the real and virtual worlds that are starting to seamlessly permeate our environment. [ABSTRACT FROM AUTHOR]

Globe-based Digital Earth (DE) is a promising system that uses 3D models of the Earth for integration, organization, processing, and visualization of vast multiscale geospatial datasets. The growing size and scale of geospatial datasets present significant obstacles to interactive viewing and meaningful visualizations of these DE systems. To address these challenges, we present a novel web-based multiresolution DE system using a hierarchical discretization of the globe on both server and client sides. The presented web-based system makes use of a novel data encoding technique for rendering large multiscale geospatial datasets, with the additional capability of displaying multiple simultaneous viewpoints. Only the data needed for the current views and scales are encoded and processed. We leverage the power of GPU acceleration on the client-side to perform real-time data rendering and dynamic styling. Efficient rendering of multiple views allows us to support multilevel focus+context visualization, an effective approach to navigate through large multiscale global datasets. The client–server interaction as well as the data encoding, rendering, styling, and visualization techniques utilized by our presented system contribute toward making DE more accessible and informative. [ABSTRACT FROM AUTHOR]

The monitoring, analysis and prediction of epidemic spread in the region require the construction of mathematical model, big data processing and visualization because the amount of population and the size of the region could be huge. One of the important steps is refinement of mathematical model, i.e. determination of initial data and coefficients of system of differential equations of epidemiologic processes using additional information. We analyze numerical method for solving inverse problem of epidemiology based on genetic algorithm and traditional optimization approach. Our algorithms are applied to analysis and prediction of epidemic situation in regions of Russian Federation, Republic of Kazakhstan and People's Republic of China. Due to a great amount of data we use a special software "Digital Earth" for visualization of epidemic. [ABSTRACT FROM AUTHOR]

The transforming world evokes changes in social, environmental, and economic dimensions, pushed by the digitalisation of many, if not all, aspects of our lives. Satellite Earth observation, while being "digital" from early on, has experienced a boost by digitalisation in recent years, with new trend s of cloud processing, data cube infrastructure, computer vision, machine learning, at unprecedented speeds. This Special Issue on "Digital | Earth | Observation" is dedicated to the fruitful interplay between the Digital Earth concept and Earth observation, embedded in the great technological trends in this field, and demonstrates how this potential can be used in various application contexts. [ABSTRACT FROM AUTHOR]

A novel method to create a physicalization of Digital Earth resulted a new type of analogue and tactile geographic information system (GIS). The model was tested by students in Australia, who shared insights into how the model supported their learning about the concept of "overlay" while providing an interesting and engaging learning platform. Observations suggest the model promoted collaborative learning, and provided a bridge between paper maps and digital GIS. This study offers insight into preferences of school children for physicalization models in geography education and contributes to an understanding of children's spatial thinking and understanding of the overlay concept. [ABSTRACT FROM AUTHOR]

Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location characteristics. Location choice is driven by diverse characteristics; including but not limited to environmental factors, access, services, and the socioeconomic status of a neighbourhood. This article aims to identify the gap between theory and practice in presenting information on location choice by using a gap analysis methodology through the development of a seven-factor classification tool and an assessment of international property websites. Despite the availability of digital earth data, the results suggest that real-estate websites are poor at providing sufficient location information to support efficient spatial decision making. Based on a case study in Dublin, Ireland, we find that although neighbourhood digital earth data may be readily available to support decision making, the gap persists. We hypothesise that the reason is two-fold. Firstly, there is a technical challenge to transform location data into usable information. Secondly, the market may not wish to provide location information which can be perceived as negative. We conclude this article with a discussion of critical issues necessary for designing a spatial decision support system for real-estate decision making. [ABSTRACT FROM AUTHOR]

The advancements of sensing technologies, including remote sensing, in situ sensing, social sensing, and health sensing, have tremendously improved our capability to observe and record natural and social phenomena, such as natural disasters, presidential elections, and infectious diseases. The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal dynamics of the environment, urban settings, health and disease propagation, business decisions, and crisis and crime. Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena. This paper reviews the literature for different sensing capabilities, spatiotemporal event extraction methods, and categories of applications for the detected events. The novelty of this review is to revisit the definition and requirements of event detection and to layout the overall workflow (from sensing and event extraction methods to the operations and decision-supporting processes based on the extracted events) as an agenda for future event detection research. Guidance is presented on the current challenges to this research agenda, and future directions are discussed for conducting spatiotemporal event detection in the era of big data, advanced sensing, and artificial intelligence. [ABSTRACT FROM AUTHOR]

Geoportals are a consolidated web-based solution to provide open spatial data sharing and online geo-information management. Their roles and possible advancements according to the Digital Earth vision and implementation require investigations. This paper presents a review of the literature concerning geoportals and serves the following primary purposes. First, various geoportal approaches for discovering and accessing Earth observation data and geo-information, mainly with scientific purposes, are summarized according to their characteristics and functionalities. Second, current major challenges in geoportals are identified in terms of functionalities, technologies, and especially big data support, from geoportal cases of China. Finally, based on lessons learned from the international and Chinese geoportals, solutions and recommendations for the challenges in geoportals are proposed in terms of their architectures, services, and technologies. The results show that geoportals usually provide access to distributed data systems, offering maps, data discovery, and data downloads. Some of them are also capable of offering online analysis and processing service, enhanced semantic search engines, and dynamic visualization tools. The strength of geoportals could lead to a full-fledged online Digital Earth system that could provide better data sharing and dissemination solutions to the challenges posed by big data. [ABSTRACT FROM AUTHOR]

The foundation of modern Digital Earth frameworks is the Discrete Global Grid System (DGGS). To standardize the DGGS model, the Open Geospatial Consortium (OGC) recently created the DGGS Abstract Specification, which also aims to increase usability and interoperability between DGGSs. To support these demands and aid future research, open implementations are necessary. However, several OGC conformant DGGSs are not available for researchers to use. This has motivated us to develop an open-source web service that allows users to create quadrilateral grids based on the rHEALPix DGGS. In this paper, we describe the implementation of the web service, including issues and limitations, and demonstrate how discrete global grids and regional grids can be created. Lastly, we present examples that show how vector data sets can be modeled and integrated at different levels of resolution – a key benefit of the DGGS model. [ABSTRACT FROM AUTHOR]

Turning Earth observation (EO) data consistently and systematically into valuable global information layers is an ongoing challenge for the EO community. Recently, the term 'big Earth data' emerged to describe massive EO datasets that confronts analysts and their traditional workflows with a range of challenges. We argue that the altered circumstances must be actively intercepted by an evolution of EO to revolutionise their application in various domains. The disruptive element is that analysts and end-users increasingly rely on Web-based workflows. In this contribution we study selected systems and portals, put them in the context of challenges and opportunities and highlight selected shortcomings and possible future developments that we consider relevant for the imminent uptake of big Earth data. [ABSTRACT FROM AUTHOR]

The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before. These changes will unlikely stop or even decelerate in the near future. There is an urgent need for a new scientific approach and an advanced form of evidence-based decision-making towards the benefit of society, the economy, and the environment. To understand the impacts and interrelationships between humans as a society and natural Earth system processes, we propose a new engineering discipline, Big Earth Data science. This science is called to provide the methodologies and tools to generate knowledge from diverse, numerous, and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth. Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves. The manuscript introduces the universe of discourse characterizing this new science, its foundational paradigms and methodologies, and a possible technological framework to be implemented by applying an ecosystem approach. CASEarth and GEOSS are presented as examples of international implementation attempts. Conclusions discuss important challenges and collaboration opportunities. [ABSTRACT FROM AUTHOR]

Sentinel-2 scenes are increasingly being used in operational Earth observation (EO) applications at regional, continental and global scales, in near-real time applications, and with multi-temporal approaches. On a broader scale, they are therefore one of the most important facilitators of the Digital Earth. However, the data quality and availability are not spatially and temporally homogeneous due to effects related to cloudiness, the position on the Earth or the acquisition plan. The spatio-temporal inhomogeneity of the underlying data may therefore affect any big remote sensing analysis and is important to consider. This study presents an assessment of the metadata for all accessible Sentinel-2 Level-1C scenes acquired in 2017, enabling the spatio-temporal coverage and availability to be quantified, including scene availability and cloudiness. Spatial exploratory analysis of the global, multi-temporal metadata also reveals that higher acquisition frequencies do not necessarily yield more cloud-free scenes and exposes metadata quality issues, e.g. systematically incorrect cloud cover estimation in high, non-vegetated altitudes. The continuously updated datasets and analysis results are accessible as a Web application called EO-Compass. It contributes to a better understanding and selection of Sentinel-2 scenes, and improves the planning and interpretation of remote sensing analyses. [ABSTRACT FROM AUTHOR]

Almost all causative factors of diseases depend on location. The Digital Earth approach is suitable for studying diseases globally. Geospatial information systems integrated with statistical models can be used to model the relationship between a disease and its causative factors. Through modelling, the most important causative factors can be extracted and the epidemiology of the disease can be observed. In this paper, skin cancer (the most common type of cancer) has been modelled based on its causative factors, including climate factors, people's occupations, nutrition habits, socio-economic factors, and usage of chemical fertiliser. To fit the model, a data framework was first designed, and then data were gathered and processed. Finally, the disease was modelled using Generalised Linear Models (GLM), a statistical model based on the location of the factors. The results of this study identify the most important causative factors together with their relative priority. Furthermore, a model was used to predict the change in skin cancer occurrences caused by a change in one of its causative factors. This work illustrates the ability of the model to predict disease occurrence. Thus, by using this Digital Earth approach, skincancer can be studied in all the key countries around the world. [ABSTRACT FROM AUTHOR]

Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today's focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) is a frequently emphasized issue on the Digital Earth (DE) agenda. While current DE research is more engaged in the technical aspects of VR applications, this paper focuses on what is possible with immersive virtual environments (IVE) from the user's perspective. After a brief discussion of spatial presence and embodiment in the context of IVE, both concepts will be merged into a geovisualization immersion pipeline (GIP) as a framework with which to systematically link technical and cognitive aspects of IVE. We will then analyze the general criteria that must be met by IVE in order to facilitate the experience of spatial presence. Adapting these criteria to the special requirements of geospatial data, a definition of geovisualization immersive virtual environments (GeoIVE) is formulated. Finally, the theoretical considerations of this paper are set into practice, using a GeoIVE of a coral reef ecosystem as an example. As we shall see, while GIS do not provide data models or data compatibility for direct visualization of GeoIVE on VR output devices, game engines can serve as middleware to fill this gap. [ABSTRACT FROM AUTHOR]

Broadly, this paper is about designing memorable 3D geovisualizations for spatial knowledge acquisition during (virtual) navigation. Navigation is a fundamentally important task, and even though most people navigate every day, many find it difficult in unfamiliar environments. When people get lost in an unfamiliar environment, or are unable to remember a route that they took, they might feel anxiety, disappointment and frustration; and in real world, such incidents can be costly, and at times, life-threatening. Therefore, in this paper, we study the design decisions in terms of visual realism in a city model, propose a visualization design optimized for route learning, implement and empirically evaluate this design. The evaluation features a navigational route learning task, where we measure short- and long-term recall accuracy of 42 participants with varying spatial abilities and memory capacity. Our findings provide unique empirical evidence on how design choices affect memory in route learning with geovirtual environments, contributing toward empirically verified design guidelines for digital cities. [ABSTRACT FROM AUTHOR]

The problem of human adaptation to living conditions in the society of the digital revolution is the main content of this study. The change of the communicative paradigm, the essence of social relations and interactions, the problem of critical thinking and the humanitarian basis of classical education is analyzed through the prism of the problem of socio-cultural transformations, social justice, and identification procedures of the modern individual. The article develops the key problem of The XXIV World Congress of Philosophy through the analysis of educational mechanisms of prevention of human nature and spiritual orientations in the face of digital era challenges. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques that are typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by health informaticians to tackle problems of domain specific use-case knowledge modelling can be re-used within ESS informatics. A translational approach to enable a two-level modelling process within geo-observational sensor systems design is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A rudimentary use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems. [ABSTRACT FROM AUTHOR]

The aim of this study is to design and implement a digital interactive globe system (DIGS), by integrating low-cost equipment to make DIGS cost-effective. DIGS includes a data processing unit, a wireless control unit, an image-capturing unit, a laser emission unit, and a three-dimensional hemispheric body-imaging screen. A quasi-experimental study was conducted to evaluate the learning effectiveness of our system. A total of 105 junior high-school students from Taiwan participated in this 8-week experiment. The students were divided into three individual groups of 35 students each, with one control group and two experimental groups (EG1 and EG2). The results of one-way mixed design ANOVA indicated that participants in the experimental group, who used the DIGS, outperformed the other two groups, in the post-test as well as in the delayed test. These findings demonstrate that the proposed DIGS can effectively enhance the performance of the learners in an Earth Science course. [ABSTRACT FROM AUTHOR]

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Web mapping and the use of geospatial information online have evolved rapidly over the past few decades. Almost everyone in the world uses mapping information, whether or not one realizes it. Almost every mobile phone now has location services and every event and object on the earth has a location. The use of this geospatial location data has expanded rapidly, thanks to the development of the Internet. Huge volumes of geospatial data are available and daily being captured online, and are used in web applications and maps for viewing, analysis, modeling and simulation. This paper reviews the developments of web mapping from the first static online map images to the current highly interactive, multi-sourced web mapping services that have been increasingly moved to cloud computing platforms. The whole environment of web mapping captures the integration and interaction between three components found online, namely, geospatial information, people and functionality. In this paper, the trends and interactions among these components are identified and reviewed in relation to the technology developments. The review then concludes by exploring some of the opportunities and directions. [ABSTRACT FROM AUTHOR]

In this opinion paper, we, a group of scientists from environmental-, geo-, ocean- and information science, argue visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal data. We discuss the challenges that appear such as synthesis of heterogeneous data from various sources, reducing the amount of information and facilitating multidisciplinary, collaborative research. We argue that to fully exploit the potential of visual data exploration, several bottlenecks and challenges have to be addressed: providing an efficient data management and an integrated modular workflow, developing and applying suitable visual exploration concepts and methods with the help of effective and tailored tools as well as generating and raising the awareness of visual data exploration and education. We are convinced visual data exploration is worth the effort since it significantly facilitates insight into environmental data and derivation of knowledge from it. [ABSTRACT FROM PUBLISHER]

Since Al Gore created the vision for Digital Earth in 1998, a wide range of research in this field has been published in journals. However, little attention has been paid to bibliometric analysis of the literature on Digital Earth. This study uses a bibliometric analysis methodology to study the publications related to Digital Earth in the Science Citation Index database and Social Science Citation Index database (via the Web of Science online services) during the period from 1998 to 2015. In this paper, we developed a novel keyword set for ‘Digital Earth’. Using this keyword set, 11,061 scientific articles from 23 subject categories were retrieved. Based on the searched articles, we analyzed the spatiotemporal characteristics of publication outputs, the subject categories and the major journals. Then, authors’ performance, affiliations, cooperation, and funding institutes were evaluated. Finally, keywords were examined. Through keyword clustering, research hotspots in the field of Digital Earth were detected. We assume that the results coincide well with the position of Digital Earth research in the context of big data. [ABSTRACT FROM AUTHOR]

Geospatial datasets are too complex to easily visualize and understand on a computer screen. Combining digital fabrication with a discrete global grid system (DGGS) can produce physical models of the Earth for visualizing multiresolution geospatial datasets. This proposed approach includes a mechanism for attaching a set of 3D printed segments to produce a scalable model of the Earth. The authors have produced two models that support the attachment of different datasets both in 2D and 3D format. [ABSTRACT FROM PUBLISHER]

Discrete global grid systems have become an important component of Digital Earth systems. However, previously there has not existed an easy way to map between named places (toponyms) and the cells of a discrete global grid system. The lack of such a tool has limited the opportunities to synthesize social place-based data with the more standard Earth and environmental science data currently being analyzed in Digital Earth applications. This paper introduces Wāhi, the first gazetteer to map entities from the GeoNames database to multiple discrete global grid systems. A gazetteer service is presented that exposes the grid system and the associated gazetteer data as Linked Data. A set of use cases for the discrete global grid gazetteer is discussed. [ABSTRACT FROM AUTHOR]

The development, integration, and distribution of the information and spatial data infrastructure (i.e. Digital Earth; DE) necessary to support the vision and goals of Future Earth (FE) will occur in a distributed fashion, in very diverse technological, institutional, socio-cultural, and economic contexts around the world. This complex context and ambitious goals require bringing to bear not only the best minds, but also the best science and technologies available. Free and Open Source Software for Geospatial Applications (FOSS4G) offers mature, capable and reliable software to contribute to the creation of this infrastructure. In this paper we point to a selected set of some of the most mature and reliable FOSS4G solutions that can be used to develop the functionality required as part of DE and FE. We provide examples of large-scale, sophisticated, mission-critical applications of each software to illustrate their power and capabilities in systems where they perform roles or functionality similar to the ones they could perform as part of DE and FE. We provide information and resources to assist the readers in carrying out their own assessments to select the best FOSS4G solutions for their particular contexts and system development needs. [ABSTRACT FROM PUBLISHER]

Digital Earth has seen great progress during the last 19 years. When it entered into the era of big data, Digital Earth developed into a new stage, namely one characterized by ‘Big Earth Data’, confronting new challenges and opportunities. In this paper we give an overview of the development of Digital Earth by summarizing research achievements and marking the milestones of Digital Earth’s development. Then, the opportunities and challenges that Big Earth Data faces are discussed. As a data-intensive scientific research approach, Big Earth Data provides a new vision and methodology to Earth sciences, and the paper identifies the advantages of Big Earth Data to scientific research, especially in knowledge discovery and global change research. We believe that Big Earth Data will advance and promote the development of Digital Earth. [ABSTRACT FROM PUBLISHER]

Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications. [ABSTRACT FROM PUBLISHER]

The article discusses the development in computational technology impacting the data regarding Earth science and evolution of Deep-time.

Digital Earth is a global reference model for integrating, processing and visualizing geospatial datasets. In this reference model, various data-types, including Digital Elevation Models (DEM) and imagery (orthophotos), are universally and openly available for the entire globe. However, 3D content such as detailed terrains with features, man-made structures, 3D water bodies and 3D vegetation are not commonly available in Digital Earth. In this paper, we present an interactive system for the rapid creation and integration of these types of 3D content to augment Digital Earth. The inputs to our system include available data sources, such as DEM and imagery information depicting landscapes and urban environments. The proposed system employs sketch-based and image-assisted tools to support interactive creation of textured 3D content. For adding terrain features visible in orthophotos, and also the basin of water bodies, we use a multiscale least square surface fitting to generate an adaptive triangular subdivision. For modeling forests and vegetation, we use image-based techniques and take advantage of visible regions and colors of forests in orthophotos. For 3D man-made structures, starting from a single photograph, we provide a simple image-assisted sketching tool to extract these objects, correct for perspective distortion and place them into desired locations. [ABSTRACT FROM AUTHOR]

Soil erosion by water is a serious threat for the Mediterranean region. Raindrop impacts and consequent runoff generation are the main driving forces of this geomorphic process of soil degradation. The potential ability for rainfall to cause soil loss is expressed as rainfall erosivity, a key parameter required by most soil loss prediction models. In Italy, rainfall erosivity measurements are limited to few locations, preventing researchers from effectively assessing the geography and magnitude of soil loss across the country. The objectives of this study were to investigate the spatio-temporal distribution of rainfall erosivity in Italy and to develop a national-scale grid-based map of rainfall erosivity. Thus, annual rainfall erosivity values were measured and subsequently interpolated using a geostatistical approach. Time series of pluviographic records (10-years) with high temporal resolution (mostly 30-min) for 386 meteorological stations were analysed. Regression-kriging was used to interpolate rainfall erosivity values of the meteorological stations to an Italian rainfall erosivity map (500-m). A set of 23 environmental covariates was tested, of which seven covariates were selected based on a stepwise approach (mostly significant at the 0.01 level). The interpolation method showed a good performance for both the cross-validation data set ( = 0.777) and the fitting data set (R2 = 0.779). [ABSTRACT FROM AUTHOR]

The aim of this study was to map soil erosion on the Mediterranean island of Cyprus. The G2 model, an empirical model for month-time step erosion assessments, was used. Soil losses in Cyprus were mapped at a 100 m cell size, while sediment yields at a sub-basin scale of 0.62 km2mean size. The results indicated a mean annual erosion rate of 11.75 t ha−1 y−1, with October and November being the most erosive months. The 34% of the island's surface was found to exceed non-sustainable erosion rates (>10 t ha−1 y−1), with sclerophyllous vegetation, coniferous forests, and non-irrigated arable land being the most extensive non-sustainable erosive land covers. The mean sediment delivery ratio (SDR) was found to be 0.26, while the mean annual specific sediment yield (SSY) value for Cyprus was found to be 3.32 t ha−1 y−1. The annual sediment yield of the entire island was found to be 2.746 Mt y−1. This study was the first to provide complete and detailed erosion figures for Cyprus at a country scale. The geodatabase and all information records of the study are available at the European Soil Data Centre (ESDAC) of the Joint Research Centre (JRC). [ABSTRACT FROM PUBLISHER]

Quantitative remote sensing retrieval algorithms help understanding the dynamic aspects of Digital Earth. However, the Big Data and complex models in Digital Earth pose grand challenges for computation infrastructures. In this article, taking the aerosol optical depth (AOD) retrieval as a study case, we exploit parallel computing methods for high efficient geophysical parameter retrieval. We present an efficient geocomputation workflow for the AOD calculation from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. According to their individual potential for parallelization, several procedures were adapted and implemented for a successful parallel execution on multi-core processors and Graphics Processing Units (GPUs). The benchmarks in this paper validate the high parallel performance of the retrieval workflow with speedups of up to 5.x on a multi-core processor with 8 threads and 43.x on a GPU. To specifically address the time-consuming model retrieval part, hybrid parallel patterns which combine the multi-core processor’s and the GPU’s compute power were implemented with static and dynamic workload distributions and evaluated on two systems with different CPU–GPU configurations. It is shown that only the dynamic hybrid implementation leads to a greatly enhanced overall exploitation of the heterogeneous hardware environment in varying circumstances. [ABSTRACT FROM PUBLISHER]

Due to advances in rendering techniques and hardware capability, stereoscopic 3D (s3D) visualization is becoming increasingly common in daily life. However, this does not change the fact that stereo effects and visual comfort depend greatly on how the related parameters are controlled during the production of the s3D images. In geo-virtual reality systems, which are important browsers for Digital Earth, the maintenance of these parameters is deeply related to the navigation process. Therefore, the navigation method in such systems requires special care. This paper presents a new flying method based on aCubemapstructure. The method defines aVehiclemodel and modifies the originalCubemapstructure by adding a front view camera during the navigation; it allows the users to fly through a virtual geographic environment with automatic speed control, smooth collision resolution, and dynamic adjustment of the s3D-related parameters. A user test was conducted to compare this new method with the original method based on theCubemapstructure. The results show that the new method performs better than the former one for it provides a convenient interaction experience with improved stereoscopic effect, and diminishes visual discomfort. [ABSTRACT FROM PUBLISHER]

With the increased use of locational information, spatial location referencing and coding methods have become much more important to the mining of both geographical and nongeographical data in digital earth system. Unfortunately, current methods of geocoding, based on reverse lookup of coordinates for a given address, have proven too lossy with respect to administrative and socioeconomic data. This paper proposes a spatial subdivision and geocoding model based on spatial address regional tessellation (SART). Given a hierarchical address object definition, and based on the ‘region of influence’ characteristics of an address, SART creates multiresolution spatial subdivisions by irregular and continuous address regions. This model reflects most of the geographical features and many of the social and economic implications for a given address. It also better reflects the way people understand addresses and spatial locations. We also propose an appropriate method of geocoding for standard addresses (SART-GC). The codes generated by this method can record address footprints, hierarchical relationships, and spatial scales in a single data structure. Finally, by applying our methods to the Shibei District of Qingdao, we demonstrate the suitability of SART-GC for multi-scale spatial information representation in digital earth systems. [ABSTRACT FROM AUTHOR]

Maps have always been tools that have fascinated men, for their ability to make us see the world that surrounds us. They were and are the outcome of models and methods applied to the observation of the world, starting from geodesy, surveying photogrammetry and remote sensing. All these disciplines, which we now group under the new name of geomatics, have had a tremendous boost in recent years. However, the synergy with information computer technology is probably the aspect that is revolutionizing more cartography. Earlier computers and after the Internet have brought us to new concepts and tools that will have profound effects not only in the world of niche of cartographers, but also more generally in the life of all human beings. The Digital Earth, proposed in 1998 by Al Gore, has been enriched in just twenty years of a set of new demands, which make even more interesting and challenging being cartographers today. The paper, without claiming to be comprehensive, aims at providing a concise overview of the state of art and of the advancement in this area. Moreover, it urges the community of geomatics to be protagonist and promoter of a new cartography, largely to be reinvented, and that would put us at the center of processes of knowledge and management of the Earth. The map makers in the past helped discovering new worlds, now the challenge is to rediscover our common world with new eyes of environmental, social, economic equity, sustainability and participation. [ABSTRACT FROM AUTHOR]

Most data sets and streams have a geospatial component. Some people even claim that about 80% of all data is related to location. In the era of Big Data this number might even be underestimated, as data sets interrelate and initially non-spatial data becomes indirectly geo-referenced. The optimal treatment of Big Data thus requires advanced methods and technologies for handling the geospatial aspects in data storage, processing, pattern recognition, prediction, visualisation and exploration. On the one hand, our work exploits earth and environmental sciences for existing interoperability standards, and the foundational data structures, algorithms and software that are required to meet these geospatial information handling tasks. On the other hand, we are concerned with the arising needs to combine human analysis capacities (intelligence augmentation) with machine power (artificial intelligence). This paper provides an overview of the emerging landscape and outlines our (Digital Earth) vision for addressing the upcoming issues. We particularly request the projection and re-use of the existing environmental, earth observation and remote sensing expertise in other sectors, i.e. to break the barriers of all of these silos by investigating integrated applications. [ABSTRACT FROM AUTHOR]

Digital Earth frameworks provide a tool to receive, send and interact with large location-based datasets, organized usually according to Discrete Global Grid Systems (DGGS). In DGGS, an indexing method is used to assign a unique index to each cell of a global grid, and the datasets corresponding to these cells are retrieved or allocated using this unique index. There exist many methods to index cells of DGGS. Toward facility, interoperability and also defining a "standard" for DGGS, a conversion is needed to translate a dataset from one DGGS to another. In this paper, we first propose a categorization of indexing methods of DGGS and then define a general conversion method from one indexing to another. Several examples are presented to describe the method. [ABSTRACT FROM AUTHOR]

This paper presents a collaborative 3D GIS to support public participation. Realizing that public-involved decision-making is often a multistage process, the proposed system is designed to provide coherent support for collaborations in the different stages. We differentiateubiquitous participationandintensive participationand identify their suitable application stages. The proposed system, then, supports both of the two types of participation by providing synchronous and asynchronous collaboration functionalities. Applying the concept of Digital Earth, the proposed system also features a virtual globe-based user interface. Such an interface integrates a variety of data, functions, and services into a unified virtual environment which is delivered to both experts and public participants through the Internet. The system has been designed as a general software framework and can be tailored for specific projects. In this study, we demonstrate it using a scene modeling case and provide a preliminary evaluation toward its usability. [ABSTRACT FROM AUTHOR]