GLY 465/565

 Course description:

This course covers the fundamentals of remote sensing (e.g., electromagnetic radiation, description of remote sensing sensors), extraction of geological, biophysical, or land use/land cover information from remote sensing data, and provides guidance as to how remote sensing data can be used to solve environmental and geological problems.  The course provides extensive hands-on training on real-world geologic and environmental projects and data sets. These data sets were collected by the instructor and his research associates over the past 15 years.  Throughout the course, the participants receive rigorous hands-on training on digital image processing techniques (e.g., image enhancement, classification, change detection, etc.) as well.   The students learn how to extract and integrate lithologic and environmental information from a wide range of archival remote sensing data (e.g., Aerial photographs, CORONA, Landsat MSS, TM, SPOT, IKONOS, SIR-C, RADARSAT), real-time remote sensing data (e.g., NOAA, SeaWIFS [UB’s receiving station]), digital elevation models, and maps (geologic, land use, land cover, etc.). 

Part I - Fundamentals, data sources, and image acquisition

History and scope of remote sensing: Concepts of remote sensing, geophysical remote sensing, and milestones.

Electromagnetic radiations: Wave model of electromagnetic energy, matter interaction with atmosphere, matter interaction with terrain, radiance and hemispherical reflectance, absorptance, and transmittance.

Spectroscopy of rocks and minerals and principles of spectroscopy: Causes of absorption, electronic processes, vibrational processes, spectra of miscellaneous minerals and rocks, and scattering processes.

Multispectral and hyperspectral remote sensing: Landsat System, Spot, ASTER, IKONOS, AVHRR, SeaWifs, MISR, and Hyperion.

Active Microwave and Lidar: Geometry of radar images, wavelength, penetration, polarization, SAR, RADARSAT, radar interferometry, LIDAR sensor system, and canopy penetration

Thermal infrared radiation: Thermal infrared radiation properties, thermal radiation laws, and thermal properties of a terrain.

Part II – Analysis of remote sensing data

Radiometric and geometric enhancement: histogram, contrast modification, piecewise linear contrast modification, histogram matching, image smoothing, mean value smoothing, edge detection and enhancement, line detection, shape detection.

Image classifications: Supervised (e.g., maximum likelihood, minimum distance classification, thresholds, parallelepiped) and unsupervised classifications (e.g., delineation of spectral classes, single pass clustering, and clustering by histogram peak selection).

Accuracy assessment: Sources of errors, and measurement of map accuracy.

Part III – Applications

Earth sciences: lithology, structure (faults, folds, suture zones), and plate reconstructions.

Environmental:  land use and land cover change, monitoring sea-shore line erosion, urbanization, fires, and deforestation.

Survey: digital terrain models.

Hydrology: applications of remote sensing in surface runoff modeling and ground water flow modeling

Projects that are conducted in the lab throughout the course: 

(1)     Lithologic mapping using remote sensing data in arid lands

The students use Landsat Thematic Mapper data, Landsat Multispectral scanner data, and ASTER data together with field, petrographic, geochemical, and hemispherical reflectance data to generate a lithologic map for a 600 km² area in the Red Sea Hills.

 (2)     Structural mapping of faults, folds, and suture zones from remote sensing data

The students use the spatial distribution of rock units and their lithologic characteristics (inferred from remote sensing data) together with field and geologic data to produce a regional structural map showing the distribution of suture zones, transcurrent fault systems, and folds.

 (3)     Paleo-reconstructions of continental plates

The students investigate pre-Red Sea reconstructions by generating regional mosaics for the Red Sea coastlines and by correlating the lithologies and structures cropping along the Red Sea coastlines. The students determine the optimum reconstruction of the plates prior to the Red Sea opening some twenty million years ago by rotating (in spherical coordinates) one of the plates around a pole that aligns the structural and lithologic elements on either side of the Red Sea.

 (4)     Monitoring deforestation in Madagascar

The students co-register and examine archival satellite data acquired over Madagascar to monitor and quantify the progression of deforestation throughout the past three decades. The participants analyze remote sensing data in conjunction with other relevant data sets including digital topography, population, distribution of roads, and urban centers to identify the dominant factors controlling deforestation.

 (5)     Development of digital terrain models

The students generate a regional digital terrain model from a data collection of twenty pairs of stereo ASTER scenes.

 (6)     Water quality of lake Erie from receiving station data

Students use real-time satellite data (SeaWifs, AVHRR) to extract water quality parameters (e.g., turbidity, chlorophyll, total dissolved solids) downloaded from the recently acquired receiving station at UB.  The students correlate findings from temporal satellite data to detect and monitor the spatial and temporal variations in the water quality of Lake Erie. 

Textbooks:

 Campbell, J., 2002, Introduction to Remote Sensing, Third Edition, Guilford Press, New York, 620 pp.  (required)

 Jensen, J.R., Remote Sensing of the Environment, Prentice Hall, New Jersey, 544 pp., (optional)

 Jensen, J.R., 1996, Introductory Digital Image Processing, a Remote Sensing Perspective, Second Edition, Prentice Hall, New Jersey, 318 pp. (optional)

Grading:

 50% Assignments/projects

40% (quizzes, mid term exam, final exam)

10% attendance