Rapid advancements in remote sensing and sensor network technologies have transformed our ability to measure and observe the natural and built environment. Today, remote sensing systems are mounted on piloted and unpiloted craft operating from space, air, land and sea. Sensor networks enable spatially distributed measurement of physical and environmental conditions. Collectively, these sensor capabilities provide a wealth of near real time earth observations at local, regional, and global scales. These data streams are then fed into data processing and analysis chains to discover meaningful patterns and extract new knowledge (analytics) about how our environment and society evolve at scales of interest.
Geospatial Sensing and Analytics (GSA) is an integrative field of research concerned with the exploitation of sensed geo-observations to measure and track spatially dynamic environmental and social phenomenon; it is further concerned with the development of computational tools and data-driven analytics to transform these observations into actionable knowledge to guide science and decision making. TAMU-CC faculty are recognized innovators in GSA science including emergent 3D sensing modalities, remote sensing with unmanned aircraft systems (UAS), sensor networks for coastal-environmental informatics, multi-sensor data fusion and processing, spatial data mining, GIS for spatial analytics, and geographic forecasting with machine learning.
Geospatial Computer Science is a field that involves the tasks of acquiring, modeling, processing, visualizing, managing and utilizing geospatial data. It is a demanding task in terms of computer science power and storage. Such tasks have traditionally been performed using high-performance servers or desktops. The rapid development of mobile technologies is now offering us a unique opportunity to perform Geospatial Computer Science tasks in mobile devices with their increasing computer science capability, abundance of built-in sensors, support for developing application software and abundant availability to the general public. Mobile Geospatial Computer Science is an emerging and exciting field with many challenges and opportunities. Research areas include: ubiquitous positioning, mobile sensing, context awareness, mobile Geographic Information System (GIS), mobile Location-Based Service (LBS) and location-based mobile gaming. The Geospatial Computer Science Lab (GCL) and the Innovation in computer science Research Labs (iCORE) offer state-of-the-art research environments and facilities, e.g., Google glass, smartphones, high-precision GPS/INS system, and laser scanner system, to facilitate research in this area.
Unmanned Systems have broad implications for our society, the economy, and for existing remote sensing businesses. In the air, on the ground, or underwater, unmanned systems are extending human capabilities in difficult or dangerous situations, enabling humans to see, to understand, and to act decisively. At present, unmanned systems are being used responsibly, for example, in precision agriculture, scientific research, search and rescue operations, surveying wildlife, hazardous environments, nuclear reactors inspection, and homeland security. The GSCS program prepares students on the design, development, and implementation of original solutions for using unmanned systems in Geospatial Computer Science research. Task-based navigation strategies, embedded computer science and sensors, mobile sensor networks, and development of novel unmanned platforms for specific applications, are among the research areas addressed in our program. TAMU-CC is the leading organization for the Lone Star UAS Center of Excellence and Innovation (LSUASC), one of the six Federal Aviation Administration (FAA)-designated Unmanned Aircraft Systems (UAS) test sites in the United States. Equipment, facilities, and unmanned platforms available in TAMU-CC enable the experimental validation of Geospatial Computer Science research.