Remote Sensing, Image Processing & Analysis: Remote sensing of the environment pertains to the capture of data about earth surface features and phenomena without being in contact with them, normally with sensors on aircraft and satellites. Image and other remotely sensed data can be corrected, enhanced, and interpreted with the aid of computer image processing systems. Human interpreters and computer-assisted image analysis routines are capable of extracting information from remotely sensed data, often in the forms of maps.
Image-based Change Detection: Remotely sensed images captured over time by sensors on aircraft or satellites enable information about changes in earth surface features and phenomena to be extracted. This is facilitated by image processing routines that co-align these multi-temporal images and then extract change information, or enable updating of maps and GIS layers.
Unmanned Aerial Vehicle: Also known as unmanned aircraft systems (UAS) or drones, unmanned aerial vehicles (UAV) enable flexible, low altitude imaging of earth surface features. In particular, UAV images captured with large amounts of overlap between adjacent images enable 3-D models of both ground and vertical feature (e.g., structures and plants) surfaces.
Development of a Remote Sensing Network for Time-Sensitive Detection of Fine Scale Damage to Transportation Infrastructure
The focus of this study is on assessing damage to transportation infrastructure following a major hazard event. The premise is that some transportation infrastructure (such as bridges which impact transportation options), are so critical to saving human lives and supporting emergency response actions that near real-time information on the damage status of such infrastructure is essential and yet may be difficult to ascertain in a timely manner with conventional, ground observations and sensor networks. We hypothesize that the solution to this post-hazard information access challenge is to design flexible, ready-to-deploy, time-sensitive remote sensing systems (TSRSS) based on a network of airborne platforms and digital cameras. The key is to determine which transportation infrastructure types and damage are truly “critical” and then to design and pre-plan low-cost TSRSS that meets maximum time to delivery and minimum information reliability requirements of decision makers. Team members are interacting with and surveying transportation infrastructure managers to determine these timeliness and reliability requirements, as well as estimating and attempting to optimize time to delivery and reliability characteristics of the TSRSS through tool development, simulation and empirical testing of the components of end-to-end TSRSS.
The Urban Transition in Ghana and Its Relation to Land Cover and Land Use Change Through Analysis of Multi-scale and Multi-temporal Satellite Image Data
Optimization of Remote Sensing Networks for Time-sensitive Detection of Fine Scale Damage to Critical Infrastructure Leave geography site
The focus of this study is on assessing damage to infrastructure following a major hazard event using airborne remote sensing. The premise is that some infrastructure, particular in cities, is so critical to saving human lives and supporting emergency response actions that near real-time information on the damage status of such infrastructure is essential and yet may be difficult to ascertain with conventional, ground observations and sensor networks. We hypothesize that the solution to this post-hazard information access challenge is to design flexible, ready-to-deploy, time-sensitive remote sensing systems (TSRSS) based on a network of airborne platforms and digital cameras. Our team is collaborating on research pertaining to important elements of end-to-end TSRSS that supports post-disaster assessment of damage to critical infrastructure and allocation of emergency response resources.
- GEOG 576: Advanced Watershed Analysis
- GEOG 591: Remote Sensing of Environment
- GEOG 591L: Remote Sensing of Environment Laboratory
- GEOG 592: Intermediate Remote Sensing of Environment
- GEOG 592L: Intermediate Remote Sensing of Environment Laboratory
- GEOG 688: Advanced Remote Sensing
- GEOG 688L: Advanced Remote Sensing Laboratory
- GEOG 780: Seminar in Techniques of Spatial Analysis
Theory and techniques in watershed analysis. Use of GIS and statistical programming for analyses of geomorphology, hydrology, and water quality data.
Acquiring and interpreting remotely sensed data of environment. Electromagnetic radiation processes, aerial and satellite imaging systems and imagery. Geographic analysis of selected human, terrestrial, and marine processes and resources.
Practical exercises, introductory processing, visual interpretation and mapping of remotely sensed imagery.
Digital image processing. Thermal infrared and microwave imaging systems and image interpretation principles. Geographic analysis of selected human, terrestrial, oceanographic, and atmospheric processes and resources.
Digital image processing, visual interpretation, mapping of thermal infrared, and microwave imagery.
Sensor systems, image interpretation and geographic applications in thermal infrared and microwave remote sensing. Principles of digital image processing.
Processing and analysis of remotely sensed data. Laboratory training in sensor systems and digital image-processing methods including thermal infrared and microwave data analysis.
Spatial analytic techniques from image processing, remote sensing, geographic information systems, cartography or quantitative methods. May be repeated with new content. See Class Schedule for specific content.