Remote Sensing

mosaic of remote sensing activites

feature extractionRemote 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.

change detectionImage-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.

mosaic of drone imagesUnmanned 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.

Projects

drone image of street damage

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.

change in urban ghana

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

Project Description

drone image of building damage

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.

Faculty

Courses