GEO 507 Course Outline
Professor: Dr. Paul W. Mausel
 
Lectures
Labs
June 15 (Monday) Remote sensing defined, prerequisites for remote sensing overview of applications Intro to MultiSpec, computer images, topo map, selected image interpretation activities.
June 16 (Tuesday) Electromagnetic energy, energy interaction with earth features. Intro to MultiSpec, computer images, topo maps, selected image interpretation activities-continued.
June 17 (Wednesday) Sensors and associated remote sensing data characteristics. Viewing and selected interpretation of various digital images derived from sensors (MSS, TM, SPOT, AVHRR, AVIRIS, digital camera/video, ATLAS, radar, GOES) including aerial/space photography.
June 18 (Thursday) Intro to classification of remotely sensing data (visual and computer). Discuss-data acquisition, preprocessing, and geographic orientation. Intro to computer classification research problem, study area familiarization (ground truth), develop color composite spectral map of the study area and associate with ground truth (topo map).
June 19 (Friday) Introduction to unsupervised classification/cluster analysis. Develop and interpret a low dimensional cluster map (12-15 clusters) of research problem study area.
June 20 (Saturday)  Field visit Field visit to study area to associate earth features with color composite spectral map and cluster map. Take photos with digital camera for possible inclusion in final report.
June 21 (Sunday) No class or lab.
June 22 (Monday) Unsupervised classification--detailed discussion of character, uses, and interpretation of cluster approaches. Detailed cluster development and analysis of study area. Use of clustering in training field development for supervised classification.
June 23 (Tuesday) Supervised classification. Approaches to and development of training fields for supervised classification. Development and testing quality of training fields for supervised classification.
June 24 (Wednesday) Detailed examples of ISURSL basic and applied research projects illustrating computer classification and GIS integration. Conduct supervised classification of study area.
June 25 (Thursday) Detailed examples of ISURSL basic and applied research projects illustrating computer classification and GIS integration (continued). Conduct supervised classification of study area-continued. Assessment of accuracy. Reclassify if needed.
June 26 (Friday) Course review and exam. Submit project report and brief presentation of results of each project.
 

Course Grade Evaluation 

Exam on lectures 40% 
Laboratory exercises 30% 
Project report 30% 




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