Google Earth as a virtual globe tool for Earth science applications at the global scale: progress and perspectives

Yu, Le; Gong, Peng

doi:10.1080/01431161.2011.636081

Cited by 295 publications

(188 citation statements)

References 67 publications

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“…The high spatial resolution images released from GE, as a free and open data source, have provided great supports for the traditional land use/cover mapping [17,18]. They have been either treated as ancillary data to collect the training or testing samples for land use/cover classification and validation or used as a visualization tool for land use/cover maps [19,20]. However, very few studies have been undertaken to use GE images as the direct data source for land use/cover mapping.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

et al. 2013

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Google Earth (GE) releases free images in high spatial resolution that may provide some potential for regional land use/cover mapping, especially for those regions with high heterogeneous landscapes. In order to test such practicability, the GE imagery was selected for a case study in Wuhan City to perform an object-based land use/cover classification. The classification accuracy was assessed by using 570 validation points generated by a random sampling scheme and compared with a parallel classification of QuickBird (QB) imagery based on an object-based classification method. The results showed that GE has an overall classification accuracy of 78.07%, which is slightly lower than that of QB. No significant difference was found between these two classification results by the adoption of Z-test, which strongly proved the potentials of GE in land use/cover mapping. Moreover, GE has different discriminating capacity for specific land use/cover types. It possesses some advantages for mapping those types with good spatial characteristics in terms of geometric, shape and context. The object-based method is recommended for imagery classification when using GE imagery for mapping land use/cover. However, GE has some limitations for those types classified by using only spectral characteristics largely due to its poor spectral characteristics. OPEN ACCESSRemote Sens. 2013, 5 6027

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Section: Introductionmentioning

confidence: 99%

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

et al. 2013

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“…After processing, the data set was digitised and imported in to a digital database using a geographic information system (GIS) that defined the different soil types. This process generated a layer of soil attributes in the GIS database in the exportable 'kmz' format allowing display on free platforms, such as Google Earth (Figure 2) (Yamagishi et al, 2010;MartinezGraña, Goy, & Cimarra, 2013;Yu & Gong 2012).…”

Section: Methods and Resultsmentioning

confidence: 99%

Dominant soil map in ‘Las Batuecas-Sierra De Francia’ and ‘Quilamas’ nature parks (Central System, Salamanca, Spain)

2014

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To correctly and rationally plan human activities in fragile conservation areas, an exhaustive study of the soil-forming factors (climate, lithology, geomorphology, topography, hydrology and vegetation) including the soil relationships, should be conducted. We analysed the geospatial distributions of different soil types in the 'Las Batuecas -Sierra de Francia' and 'Quilamas' natural areas using soil sampling and laboratory analyses to determine the soil associations and dominant soil types and so create toposequence maps. These maps were used to assess potential soil uses and resources and to identify environmental problems from natural and/or anthropogenic causes. The GIS techniques used in this study provide georeferenced maps of forming factors and soil distribution that can be used to create databases that include fact sheets and photographs of the soil profiles. This soil information was exported in 'kmz' format to geospatially visualise the different soil units in 3D virtual tours using the Google Earth platform. This method of soil mapping allows a multidisciplinary approach that utilises other thematic layers and facilitates decision-making processes by the managers and directors of the natural areas studied in this work.

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“…At the time of writing (early 2016), examples include geology (Blenkinsop 2012;Martínez-Graña et al 2013;Zhu et al 2014), ecology (Guralnick et al 2007), history and cultural heritage (Brovelli et al 2013;Valentini et al 2014), cartographic heritage Gede et al 2013), natural disasters and disaster management (Webley 2011;Tomaszewski 2011), environmental analyses and modelling (Chien and Tan 2011;, weather forecast (Smith and Lakshmanan 2011), instruction and education (Lindner-Fally and Zwartjes 2012; Bodzin et al 2014), health (Stensgaard et al 2009), landscape planning (Schroth et al 2011) and urban studies (Nebiker et al 2010). User functions typically include data visualization, collection, exploration, integration, validation, communication and dissemination, modelling, and decision support (Yu and Gong 2012).…”

Section: Virtual Globes For the Exploration Of Crowdsourced Geo-datamentioning

confidence: 99%

“…Key factors which enabled the birth of virtual globes include the development of high-performance graphics cards for 3D visualization (mainly driven by the video game industry), the evolution of Internet bandwidth, the increased availability of high-resolution satellite imagery (Yu and Gong 2012) and the advancements in the field of global spatial grids (Sahr et al 2003). The success of virtual globes must be certainly attributed to Google Earth, 1 which since its release in 2005 has gained an astonishing popularity among the general public.…”

Section: Virtual Globes As the New Generation Visualization Platformsmentioning

confidence: 99%

New Generation Platforms for Exploration of Crowdsourced Geo-Data

Brovelli

Minghini

Zamboni

2018

Earth Observation Open Science and Innovation

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This chapter addresses two recent topics in the field of geo-information, the former more technological and the latter more scientific. On one side, there is an emerging trend of visualizing data and their changes in space and time through multidimensional geospatial clients and/or virtual globes. In the most advanced cases, these are not simply plain viewers but also allow analysis of the data by acting as "multidimensional intelligent geo-viewers". On the other side, citizen science is providing a great momentum to the possibility of lay people taking part in scientific development. It is a new, citizen-centred paradigm which, in most cases, takes advantage of the individual and collective augmented capability of sensing the surrounding world through the sensors that we wear. The "citizen sensors" will consciously contribute to this development, either through volunteered geographic information or by being themselves an unconscious part of the data analytics, which makes use of geo-crowdsourced data to extract information in order to create a higher level understanding of natural and manmade phenomena. This chapter seeks to outline the Web technological solutions for visualizing and analyzing such data, through a summary of the current state of the art and the original applications developed by the authors.

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Google Earth as a virtual globe tool for Earth science applications at the global scale: progress and perspectives

Cited by 295 publications

References 67 publications

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping

Dominant soil map in ‘Las Batuecas-Sierra De Francia’ and ‘Quilamas’ nature parks (Central System, Salamanca, Spain)

New Generation Platforms for Exploration of Crowdsourced Geo-Data

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