Successful completion of this course will provide the following learning outcomes:

A basic understanding of the physics of electromagnetic energy that underlie the
acquisition, analysis and application of remote sensing data, including aerial
photographs, airborne and satellite optical digital images and thermal/microwave
digital imagery.

An appreciation of remote sensing information content and ethical issues of privacy
and proper use of remote sensing data.

An awareness of the concepts and application of scale, coordinate systems, geometric
and thematic accuracy, uncertainty and thematic content.

An understanding of the historical development of remote sensing technology, 
national and international remote sensing programs and its integration in geographic
information systems.

A greater cognizance of the importance of remote sensing in our daily lives and the
crucial role it can play in monitoring environmental change, assessing human impacts
and influencing policy decision-making.


This course meets the following General Education Abilities by accomplishing the
specific learning objectives listed below:

Communicate effectively through writing.  This is met by a series of writing 
assignments associated with supplemental reading and data analysis.
 
Communicate effectively through speech.  This is met by oral presentations, 
discussion leading, and classroom participation.

Computer Literacy is addressed through course administration, student-faculty 
electronic interaction, data analysis activities and assignments, and exposure to 
GIS technologies.
 
Critical Thinking is central to the learning objectives of this class, and are 
developed through homework assignments, lecture, classroom discussion, and inquiry-
based learning efforts.

Moral Reasoning (Ethics) is an important element of this course, as it considers 
ethical guidelines for use of remote sensing technologies and considers the role of 
mapping sciences in economic development and human welfare.   Moral reasoning is 
developed through lectures, writing assignments, classroom discussion, and inquiry-
based learning activities.

Fundamentals of the electromagnetic spectrum; radiance
Raster data structure and representation
Lab 1: Intro to Digital Image Processing
Photographic systems
Aerial photograph geometry; scanning; resolving power; scale 
Lab 2: Scale measurements and scanning
Digital Photogrammetry: geometric correction, image rectification, polynomials,
orthoimage generation
Visual interpretation of image data
Lab 3: Analysis of imaging spectrometer data: spectral response of features in
remotely sensed images
Applications of visual interpretation of image data
Multispectral, thermal, hyperspectral remote sensing overview
Lab 4: Accessing remotely sensed  data via the worldwide web
Remote sensor scanners geometry; orbits; stereo
Thermal and hyperspectral imagery
Lab 5: Multispectral/hyperspectral satellite images 
Remote sensing systems: history
Landsat
Lab 6: Landsat TM and ETM+; Rectification 
SPOT  and high resolution commercial satellite systems
NASA’s Earth Observing System 
Lab 7: On-screen compilation of land use/land cover from Landsat TM 
data search and retrieval
Digital image processing: georeferencing; polynomial  transformations; data formats
Image enhancement, contrast manipulation, pan-sharpening
Lab 8: Image enhancement; pan-sharpening
Spatial feature manipulation: filtering
Multi-image manipulation: ratios, NDVI
Lab 9: Image filtering, ratios
Supervised image classification: theory, methods, classifiers
Supervised classification: training and implementation
Lab 10: Supervised classification of Landsat TM
Unsupervised classification
Hybrid classification; mixed pixels; output; post-classification smoothing;
hyperspectral classification
Lab 11: Unsupervised classification; post-classification processing
Classification accuracy assessment
Change detection; data merging and integration
Lab 12: Change detection and accuracy assessment
Contextual classification
Stereo image data and DEM generation
Lab 13: DEM generation from ASTER stereo image data; terrain visualization 
Radar, SRTM, microwave systems
Lidar and applications