The notion of “3D GIS” has been gaining momentum in the geospatial industry for a few years now. Realistic 3D vector data, Building Information Modeling (BIM), 3D terrain and imagery are all important components of building a GIS infrastructure that goes beyond two dimensions. The convergence of GIS, photogrammetry and remote sensing data, tools and methods has now matured to the point of making integrated 3D GIS applications a reality.
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This is a winner paper from our 2012 ERDAS IMAGINE-DigitalGlobe Geospatial Challenge. Howard’s work has implications for predicting daily movement patterns of all mobile animals, as high-resolution imagery and subpixel analysis in conjunction with habitat modeling represent significant improvements to previous attempts to link species occurrence or animal behavior with environmental variables.
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IMAGINE Objective provides tools for feature extraction, update and change detection, enabling geospatial data layers to be created and maintained using remotely sensed imagery. IMAGINE Objective combines inferential learning with expert knowledge in a true object-oriented feature extraction environment.
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This paper describes the algorithm used to further automate the workflow to triangulate images from the multi-line Aerial Digital Sensor ADS from Leica Geosystems. Up to now many parts of the triangulation process have been successfully automated like point measurement, bundle adjustment with automatic blunder removal, automatic variance components estimation and automatic selection of self-calibration parameters. What still requires human interaction is the quality analysis. The key to full automation in triangulation is the quality control.
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Converting a large number of image tiles in Lizardtech’s MrSID format (or any other raster format) to another format such as JPEG 2000 is an easy task using the Batch tool available in IMAGINE Essentials.
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This paper was submitted as part of the 2012 ERDAS IMAGINE-DigitalGlobe Geospatial Challenge. Satellite remotely-sensed data has been applied to estimate water depth in the clear and shallow water area. In this study, we use Quickbird and WorldView-2 imagery for bathymetric mapping around Itu Aba Island, located in the center of South China Sea (SCS). A linear model is applied to estimate water depths. The result show that the error of water depth estimated from Quickbird imagery is about 9.7% around Pratas Island. The model is also applied to map the water depth around Itu Aba Island with Quickbird and WorldView-2 images. A more changeable depth is found from WorldView-2 image than that from Quickbird. It implies that the coastal blue band in WorldView-2 imagery may retrieve more information.
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Many countries have organizations responsible for collecting, surveying, processing, analyzing and publishing geospatial information for specified areas. These organizations have an official mandate or simply a crucial need to make their data available to private or public users, individuals or organizations.
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Change detection is used to highlight or identify significant differences in imagery acquired at different times; playing an important role in the lifecycle of GIS features and providing the capability to update feature data based on new imagery.
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This paper was submitted as part of the 2012 ERDAS IMAGINE-DigitalGlobe Geospatial Challenge. Remote sensing and Geographical Information Sciences has contributed a lot towards site specific to global level vegetation and earth surface monitoring. Different Analyses are carried out for WorldView-2, SPOT 5 and Terra/Aqua Satellites datasets. High spectral and spatial resolution satellite data is sometime constrained by its optimum visualization and interpretation. Optimum Index Factor for improved visualization in case of SPOT5 is observed to be less consistent for optimum data visualization as compared to WorldView-2 data.
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The landscape of the village of Nohfelden in the southwestern state Saarland in Germany is dominated by the tower of an old castle complex. With photogrammetry and three-dimensional, computer based visualization available inIMAGINE VirtualGIS®, this castle can be virtually rebuilt.
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For years, spatial data has been replicated and hosted on multiple security domains for users with different clearances. The emergence of label secure database technology, sophisticated high assurance security appliances and changes in security make it possible to avoid such costly implementations, drastically reducing mission latency.
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ERDAS APOLLO Image Manager possesses the market differentiating capability to develop a complex data model of massive volumes of gridded data and deliver the data through a single, interoperable web service URL. This piece describes the data modeling and security features of ERDAS APOLLO Image Manager, and provides working examples of data modeling techniques.
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For ERDAS IMAGINE 2011, ERDAS Inc. has developed a new algorithm for change detection between two co-registered images acquired at different dates. This algorithm, named Discriminant Function Change (DFC), characterizes the natural distribution of spectral clusters in the data space of one image, then uses a discriminant function to measure probability of change of the pixels in the other image.
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Many enterprises suffer from the lack of a central repository for staff members and partners to quickly discover each other’s knowledge of a given locale. The Enterprise Wikimapia solution leverages the concepts pioneered by www.wikimapia.org, along with the Open Geospatial Consortium (OGC) concepts of transactional web feature service (WFS-T) and gazetteer (WFS-G).
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As a comprehensive data management and distribution solution to manage and rapidly serve massive volumes of data to a large number of users, ERDAS APOLLO meets the basic need to inventory and share geospatial data. On top of handling extensive volumes of dynamic and static images, it also easily delivers feature data, terrain and virtually any digital object, all while maintaining a consistently high level of performance.
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