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Imagery
The imagery software products are now available through the subsidiary GeoGenesis, Inc. The areas of software specialization include: imagery structure, data preparation tools, modeling and validation, and management systems. Likewise, these themes serve as the foundations for the current four products:
- GeoGenesis® -
- Serving as the core application of the suite, GeoGenesis® is an imagery processing and content generation workstation giving you complete control over your data. Using GeoGenesis you can rapidly orthorectify aerial and satellite imagery one at a time or in batch mode. In addition, GeoGenesis provides you the ability to perform bundle adjustment on multiple images assisted by automated tie point selection between overlapping images. GeoGenesis includes pan-sharpening capabilities to fuse high-resolution panchromatic imagery with lower resolution color imagery. The GeoGenesis mosaicking capabilities allow you to combine multiple images into a single orthomosaic, and our radiometric balancing capabilities help eliminate any visible seams using either color or grayscale source date. Geared totally for production applications, GeoGenesis is the tool of choice for your imagery processing and production needs.
- The totally FREE GeoGenesisLE™ -
- GeoGenesisLE™ is a free geospatial data viewer allowing you to display imagery, elevation, and vector data with an easy to use graphical user interface. Using GeoGenesisLE you can quickly view single or multi-band satellite and aerial imagery with simple band selection menus to display natural color and false color views of the scene. You may also overlay geospatial vector data onto underlying imagery and elevation data. In addition to rapid panning and zooming capabilities, GeoGenesisLE provides you the ability to convert and save imagery from NITF format to GeoTIFF while maintaining important registration information including RPC data for commercial satellite imagery. Whether displaying or converting data, GeoGenesisLE will be the tool you turn to.
- OmniDEM™ -
- If you need accurate and up-to-date digital terrain elevation data, then OmniDEM™ is your solution. Digital Elevation Models (DEMs) are essential to a variety of geospatial production applications, such as GIS, digital terrain database generation, orthorectification, and watershed analysis. OmniDEM provides you the ability to efficiently extract accurate elevation models from stereoscopic imagery as well as full editing capability to refine existing DEMs. The OmniDEM easy to use interface unlocks the secret to generating accurate DEMs from overlapping satellite and aerial imagery.
- FeatureXTract™ -
- FeatureXTract™ is a geospatial site-modeling system composed of both automated and semi-automated tools. These allow you to rapidly extract 3D buildings and related features from aerial and satellite imagery. FeatureXTract employs a simple split-screen interface eliminating the need for active stereo displays in 3D feature extraction. Using FeatureXTract you can quickly extract accurate 3D site models even on a laptop and export them for use in a variety of applications, including digital terrain database generation. With FeatureXTract, building an urban environment is now simple, rapid, and most importantly accurate.
The GeoGenesis, Inc. website has complete descriptions of the products accordingly.
Contacting Us
For more information on these imagery processing products, please use our contacts page or email/call Mr. Eric Lester, Senior VP, elester@iavo-rs.com, or 919-433-2400.
Behavioral
The behavioral sciences division is in the intermediate stages of developing a software and services portfolio, which focuses on three main areas of original research and software development:
- Behavioral and Decision Modeling
- Social Network Analysis
- Geospatial Analysis of Human Phenomena
The current product portfolio consists of multiple complimentary software programs:
- ISRModeler™ – A causal modeling application suite which uses path analysis, structural equation modeling and growth mixture models.
- CulturalISR™ – An advanced behavioral modeling software suite which offers three new applications, discrete time hazard modeling, multi- latent group structural equations modeling, and hidden Markov processes application .
- PrismaCSN™ – A hybrid methodology using the EM Algorithm, Quadratic Discriminate Analysis, SEM and the Genetic Algorithm to understand and manipulate behavior of complex social networks.
- CMSEM™ – A modeling tool using Bayesian network models, latent variable models and error models in order to detect and expose hidden enemy networks.
- TempusTEC™– A modeling tool that analyzes how particular responses encourage or disrupt event chains and cause shifts in the decision making processes using Markov chain models.
ISRModeler™
ISRModeler™ is a causal modeling application suite that focuses on analyzing latent attributes of actors and processes within a battlespace, which directly and indirectly influence tactical level interactions and dynamics. ISRModeler uses the following applications:
- Path Effects Models: Drives basis of theory for further analysis and data collection. Path effects is a simple method to understand what nodes and variables are connected.
- Structural Equation Models: Statistical analysis using above nodes/variables to determine coefficients and quantitative relationships between each.
- Growth Mixture Models: Sophisticated data analysis method to understand the why or how of a group of data or social network connections.
Platform: XP, extendable to Unix and LINUX
Projected User Profile: Social scientists, intelligence analysts, effects-based operations personnel, human behavioral modelers.
CulturalISR™
CulturalISR™ is an advanced socio-temporal performance modeling and simulation framework which integrate the strengths of human behavioral social scientific theories with advanced quantitative abilities to clearly and succinctly forecast the decision-making of individuals-of-interest. These three models are the main components in CulturalISR:
- Discrete Time Hazard Models (DTHM) – a model of simultaneous and serial decision-making that accounts for sources of variation in the temporal patterning of decision-based behavior.
- Multi-Latent Group Structural Equation Modeling (MLGSEM) – a non- linear structural analysis capability to examine observed and latent aspects of data at the group-level, with specific emphasis on cross-cultural attributes.
- Hidden Markov Processes Application (HMPA) – an application of Hidden Markov Models and similar models that uses available data on social structure, observed events and statistical decision-models to generate accurate predictions on social aggregate behavior and intent.
Platform: XP, extendable to Unix and LINUX
Projected User Profile: Social scientists, field officers, intelligence analysts, effects-based operations personnel, human behavioral modelers.
PrismaCSN™
PrismaCSN™ (CSN: Complex Social Network) is a hybrid methodology that harnesses the strengths of several data analysis processes that produce plans of action for how to best interact with complex social networks, discovering how to alter the actions of its interrelated members to generate new behavioral patterns which are consistent with mission planning objectives. This robust modeling framework and software tool will make the integration of these proven and innovative methods available at the tactical level by introducing a user-oriented, automated system comprised of five primary tools:
- Feature Space Definition (FSD): The process of determining relevant observable and latent variables, then quantifying these high-resolution metrics for use in probability models.
- Expectation Maximization Classification of Actors (EMCA): Algorithmic prediction using observable and latent variables to estimate missing data to determine the probability of an actor’s classification within a social network as ‘good’ or ‘bad’.
- Quadratic Discriminant Analysis (QDA): Statistical classification of a node’s characteristic vectors, which separates a class surface into two planes by finding a best-fit threshold, thus distinguishing ‘good’ from ‘bad’.
- Causal Model (CM): Using structural equation modeling to understand the system of interrelated effects of variable manipulation within a feature space.
- Applied Genetic Algorithm (AGA): Identifying best-fit variable manipulations metrics to apply within a social network for desired outcome.
Platform: XP, extendable to Unix and LINUX
Projected User Profile: Social network scientists, social scientists, intelligence analysts, effects-based operations personnel, human behavioral modelers.
CMSEM™
CMSEM™ (Computational Multi-level Structural Equations Model) A modeling tool using Bayesian network models, latent variable models and error models in order to detect and expose hidden enemy networks, specifically for use in large sets of communication data:
- Bayesian Networks: The process of determining interdependencies among network data in observable enemy behavior.
- Error Models: These models account for the uncertainty that is present in communications data.
- Causal Models: Using latent variable modeling in order to understand the system of interrelated effects of variables within a dataset.
Platform: XP, extendable to Unix and LINUX
Projected User Profile: social scientists, communications network analysts, intelligence analysts, effects-based operations personnel, human behavioral modelers.
TempusTEC™
TempusTEC™ (Tracking Event Chains) will analyze how blue force response changes the way in which adversarial groups decide to carry out future acts of violence – thus being able to quantify and predict how particular responses encourage or disrupt event chains and cause shifts in the decision making processes. These analytical methods will allow intelligence officers to create an environment in which our military is able to manipulate and anticipate adversarial responses.
- Estimation of Markov Chain Models -Estimation of Statistical Parameters of relationships between Markov chain events and finding the most accurate combination of latent and categorical variables (human, social, cultural, behavioral, etc.) to predict adversarial response.
- Parsing Event Chains -Classification of event chains as belonging to a particular group, series of events or person.
- Model Translation - Using model estimation numbers and formatting these results into actionable data.
- Evaluating Predictive Capability – Forecasting future events and checking the models against previous event chains to determine accuracy.
Platform: XP, extendable to Unix and LINUX
Projected User Profile: social scientists, communications network analysts, intelligence analysts, effects-based operations personnel, human behavioral modelers.
Contacting Us
For more information on these behavioral sciences products, please use our contacts page or email/call Ms. Jenn Carter, Division Director, jcarter@iavo-rs.com, or 919-433-2400.
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