Issue link: https://read.dmtmag.com/i/46658
information technology also is breaking down the data access barriers. Increases in data storage solutions, network access and associated standards are enabling rapid data discovery and access. Instead of browsing through data listings and queries, users can interactively connect and browse available libraries. Standards-based protocols enable ad-hoc discovery and information access to support multi-modality analysts. Alert systems notify users of data availability, and the latest feedback-based systems allow users to make requests for future collections. Merge data avail- ability with access to large, historical archives (e.g., Landsat), and the once-isolated geospatial analysts now can rapidly access all the data inputs required. Multi-Modality Exploitation With the barriers to multi-modality data access falling, geospatial analysts can start leveraging the strengths of each sensor's capabilities to deliver superior products in shorter operational timelines. With a wide variety of common-collection datasets, the strengths of each individual sensor modality can be combined to deliver a feature-rich, virtual sensor that enables new possibilities for exploitation and information product availability and accuracy. Although the range of possibilities is endless for multi-modality dataset exploitation, the following examples illustrate the power of this environment: LIDAR and Multispectral Imagery—LIDAR-based feature extraction is a resource-intensive undertak- ing. One method to reduce processing overhead is to use multispectral classification techniques to broadly classify the collection area. Then analysts can use the results of this classification to identify key areas for LIDAR feature extraction and focus processing on these classes. Hyperspectral Imagery and LIDAR—For littoral bathymetric hyperspectral collects, water-column correction is key for observation and image exploita- tion. Co-collected LIDAR data provide accurate depth measurements to improve data calibration and increase overall exploitation abilities. Multi-Modality Attribution Clouds—A modern tech- nique for feature classification is to first identify features and then derive a set of feature attributes. Classification techniques identify unique values of these attributes to identify feature classes across the entire feature set. The addition of other modality datasets adds additional dimensions to the feature attribute set, delivering a higher fidelity to the classification process. As these examples show, the additional informa- tion provided from different modalities opens up advanced levels of data preparation and exploitation. Besides data availability and multi-modality exploi- Users of LIDAR analysis software programs can identify and extract power lines from 3-D data for accurate utility management and right-of-way studies. tation patterns, software tools must support each sensor modality and present a common information model to deliver a common exploitation platform. Greater Exploitation Accuracy and Operational Efficiency The demands being placed on current geospatial systems and the analysts that operate them are inhibiting the ability to reach efficiency, accuracy and timeliness goals. The single-sensor focus of these systems and their associated operational protocols are stifling analysts' capabilities. A solution to this situation is leveraging a holistic approach to analy- sis—leveraging multi-modality data sources for exploitation and information derivation. Today's sensing platforms are deploying multiple sensors, leveraging multiple modalities during a single collection operation. These data are readily available to analysts through modern information technology, which deploys common standards, formats and communication protocols to rapidly make information available throughout the geospatial enterprise. Combined with the latest software tools that support multi-modality exploitation and algorithm development, the struggles of today are eliminated, and multi-modality exploitation becomes the standard operation scenario. We are on the verge of a new era of data exploita- tion capabilities that leverages all available information to derive highly accurate and timely results. Through common data collects, deployment of common-format and protocol standards, and multi-modality exploitation environments, geospatial analysts are empowered to rapidly capture the entire context of an exploitation event and extract high-value information products that meet the requirements of the always-connected, high-activity geospatial enterprise. OCT O BER 2O11 / WWW . GEOPLA CE . C OM 13