Google Earth Plug-in Research Articles

SketchUp and Sketchfab: Tools for Teaching with 3D

SketchUp and Sketchfab: Tools for Teaching with 3D

Caracterização dos bancos de areia causados pelo assoreamento na Boca da Barra do Canal do Linguado em Balneário Barra do Sul

Este estudo foi realizado no Canal do Linguado, localizado norte estado de Santa Catarina (SC). O delineamento de estudo acondiciona-se em área consolidada no município de Balneário Barra do Sul (SC) para mapear áreas suscetíveis à processos de assoreamento, contempla o Canal do Linguado que vai da Br 280 até a Boca da Barra, local onde o canal encontra a saída para o mar. O processamento das imagens foi efetuado no software Qgis por meio do plugin Quick Map Services e Google Earth.

THE PROCESS OF DIGITIZING OF OLD GLOBE

Abstract. This paper describes the process of digitalization of old globes that brings with it the possibility to use globes in their digital form. Created digital models are available to the general public through modern technology in the Internet network. This gives an opportunity to study old globes located in various historical collections, and prevent damage of the originals. Another benefit of digitization is also a possibility of comparing different models both among themselves and with current map data by increasing the transparency of individual layers. Digitization is carried out using special device that allows digitizing globes with a diameter ranging from 5 cm to 120 cm. This device can be easily disassembled, and it is fully mobile therefore the globes can be digitized in the place of its storage. Image data of globe surface are acquired by digital camera firmly fastened to the device. Acquired image data are then georeferenced by using a method of complex adjustment. The last step of digitization is publication of the final models that is realized by two ways. The first option is in the form of 3D model through JavaScript library Cesium or Google Earth plug-in in the Web browser. The second option is as a georeferenced map using Tile Map Service.

THE PROCESS OF DIGITIZING OF OLD GLOBE

This paper describes the process of digitalization of old globes that brings with it the possibility to use globes in their digital form. Created digital models are available to the general public through modern technology in the Internet network. This gives an opportunity to study old globes located in various historical collections, and prevent damage of the originals. Another benefit of digitization is also a possibility of comparing different models both among themselves and with current map data by increasing the transparency of individual layers. <br><br> Digitization is carried out using special device that allows digitizing globes with a diameter ranging from 5 cm to 120 cm. This device can be easily disassembled, and it is fully mobile therefore the globes can be digitized in the place of its storage. Image data of globe surface are acquired by digital camera firmly fastened to the device. Acquired image data are then georeferenced by using a method of complex adjustment. The last step of digitization is publication of the final models that is realized by two ways. The first option is in the form of 3D model through JavaScript library Cesium or Google Earth plug-in in the Web browser. The second option is as a georeferenced map using Tile Map Service.

Moving KML geometry elements within Google Earth

During the process of modeling and visualizing geospatial information on the Google Earth virtual globe, there is an increasing demand to carry out such operations as moving geospatial objects defined by KML geometry elements horizontally or vertically. Due to the absence of the functionality and user interface for performing the moving transformation, it is either hard or impossible to interactively move multiple geospatial objects only using the existing Google Earth desktop application, especially when the data sets are in large volume. In this paper, we present a general framework and associated implementation methods for moving multiple KML geometry elements within Google Earth. In our proposed framework, we first load KML objects into the Google Earth plug-in, and then extract KML geometry elements from the imported KML objects. Subsequently, we interactively control the movement distance along a specified orientation by employing a custom user interface, calculate the transformed geographic location for each KML geometry element, and adjust geographic coordinates of the points in each KML objects. And finally, transformed KML geometry elements can be displayed in Google Earth for 3D visualization and spatial analysis. A key advantage of the proposed framework is that it provides a simple, uniform and efficient user interface for moving multiple KML geometry elements within Google Earth. More importantly, the proposed framework and associated implementations can be conveniently integrated into other customizable Google Earth applications to support interactively visualizing and analyzing geospatial objects defined by KML geometry elements.

Dynamic WIFI-Based Indoor Positioning in 3D Virtual World

Abstract. A web-based system based on the 3DTown project was proposed using Google Earth plug-in that brings information from indoor positioning devices and real-time sensors into an integrated 3D indoor and outdoor virtual world to visualize the dynamics of urban life within the 3D context of a city. We addressed limitation of the 3DTown project with particular emphasis on video surveillance camera used for indoor tracking purposes. The proposed solution was to utilize wireless local area network (WLAN) WiFi as a replacement technology for localizing objects of interest due to the wide spread availability and large coverage area of WiFi in indoor building spaces. Indoor positioning was performed using WiFi without modifying existing building infrastructure or introducing additional access points (AP)s. A hybrid probabilistic approach was used for indoor positioning based on previously recorded WiFi fingerprint database in the Petrie Science and Engineering building at York University. In addition, we have developed a 3D building modeling module that allows for efficient reconstruction of outdoor building models to be integrated with indoor building models; a sensor module for receiving, distributing, and visualizing real-time sensor data; and a web-based visualization module for users to explore the dynamic urban life in a virtual world. In order to solve the problems in the implementation of the proposed system, we introduce approaches for integration of indoor building models with indoor positioning data, as well as real-time sensor information and visualization on the web-based system. In this paper we report the preliminary results of our prototype system, demonstrating the system's capability for implementing a dynamic 3D indoor and outdoor virtual world that is composed of discrete modules connected through pre-determined communication protocols.

Vegetation Database of Oak Communities in Turkey

In Turkey, approximately 20,000 vegetation releves do exist in total. However, there is no central database for Turkish vegetation releves at present (2011). I started building the Vegetation Database of Oak Communities in Turkey (GIVD ID AS-TR-002) from published and unpublished data such as master and PhD theses, reports and articles in local and international journals. In total, 1,181 releves were entered in TURBOVEG format for oak vegetation releves, including woodlands and forests. Plots were georeferenced using the Google Earth plugin integrated in the TURBOVEG software. Typical header data, such as altitude or aspect were entered when available. Most of the releves belong to the vegetation classes Quercetea ilicis and Quercetea pubescentis.

Vegetation Database of the Grassland Communities in Anatolia

In Turkey approximately 20,000 vegetation releves do exist. However, there is no central database for Turkish vegetation releves. We started building a vegetation database based on grassland vegetation releves from published and unpublished data from Turkey. The database contains dune, steppic, alpine and subalpine grassland vegetation. Approximately 1,878 releves have been entered in TURBOVEG format. Plots were georeferenced using the Google Earth plugin integrated in the TURBOVEG software. Typical header data were entered when available. Most of the releves belong to the classes Astragalo-Brometea and DaphnoFestucetea. This report describes the available content in the Vegetation Database of the Grassland Communities in Anatolia (GIVD ID AS-TR-001).

Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT) for Collecting Land-Use/Land-Cover Reference Data

Web-based applications that integrate geospatial information, or the geoweb, offer exciting opportunities for remote sensing science. One such application is a Web‑based system for automating the collection of reference data for producing and verifying the accuracy of land-use/land-cover (LULC) maps derived from satellite imagery. Here we describe the capabilities and technical components of the Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT), a collaborative browser-based tool for “crowdsourcing” interpretation of reference data from high resolution imagery. The principal component of VIEW-IT is the Google Earth plug-in, which allows users to visually estimate percent cover of seven basic LULC classes within a sample grid. The current system provides a 250 m square sample to match the resolution of MODIS satellite data, although other scales could be easily accommodated. Using VIEW-IT, a team of 23 student and 7 expert interpreters collected over 46,000 reference samples across Latin America and the Caribbean. Samples covered all biomes, avoided spatial autocorrelation, and spanned years 2000 to 2010. By embedding Google Earth within a Web-based application with an intuitive user interface, basic interpretation criteria, distributed Internet access, server-side storage, and automated error-checking, VIEW-IT provides a time and cost efficient means of collecting a large dataset of samples across space and time. When matched with predictor variables from satellite imagery, these data can provide robust mapping algorithm calibration and accuracy assessment. This development is particularly important for regional to global scale LULC mapping efforts, which have traditionally relied on sparse sampling of medium resolution imagery and products for reference data. Our ultimate goal is to make VIEW-IT available to all users to promote rigorous, global land-change monitoring.