Students may register for cross-listed courses in the department of choice.
The objective of this course is to provide students with an understanding of the spatial sciences, how they are applied for problem solving in a wide variety of fields, and what opportunities are available to professionals in the spatial sciences.
Identification and evaluation of natural and cultural features on aerial photographs; methods for extracting information concerning land use, vegetative cover, surface and structural features, urban/industrial patterns and archaeological sites. Cross-listed with GEOG 398.
Remote Sensing for the management of renewable natural resources; use of aerial photography and satellite imagery to detect, identify and monitor forest, range, and agricultural resources; utilize remotely sensed data as input to computerized information management systems.
Advanced topics in Geographic Information Systems (GIS) to solve natural resource problems; manipulation of raster data types; three-dimensional modeling; emphasis on geoprocessing as it relates to applied projects, particularly with habitat suitability models; field and lab use of Global Positioning Systems (GPS); Internet-based GIS modeling.
Also cross-listed as AGSM 461 (currently AGSM 489), BAEN 651
Systems approach to the integration of spatial and attribute data to study the capture, analysis, manipulation, and portrayal of land-based resource data; data types/formats and GIS design; integration of GIS/remote sensing; hardware/software; systems networking.
The objective of this course is to give students a greater understanding of advanced GIS topics. Knowledge gained in this course will give students the tools required to solve complex natural resource issues. This will be accomplished by providing experience in spatial analysis, environmental modeling, and geostatistical analysis. Students will also be exposed to internet based mapping - a technology used to disseminate spatial data.
Primary focus is placed on sensors, digital image processing, interpretation, and analysis for a broad range of applications in natural resources management. The course emphasizes a hands-on learning environment, including theoretical and conceptual underpinnings in both aerial and satellite remote sensing.
Advanced techniques for information extraction using airborne and satellite imagery; active and passive sensors characteristics; customizing and developing image processing tools for remote sensing applications for a broad range of sensors and applications.
This course is intended for graduate student with little or no previous experience with formal programming languages. Students entering graduate-level remote sensing and GIS programs come from a wide array of undergraduate programs, many of which require only the completion of a computer literacy course for graduation. To make maximum use of any type of analytical software often requires that the user "think outside of the box" - that they coax programs into doing things that the designers of the program had not thought of or had chosen not to include. Also, even when the desired functionality is included with the software, it is often necessary to perform the same task on many different objects. The ability to automate such repetitious and tedious tasks often results in substantial increases in efficiency (and coincident decrease in tedium and boredom).
A macro is a program, often a very small program, that is written to run from within a larger program package. At this time Visual Basic for Applications (VBA) is the macro programming language of choice in a large number of program packages. This includes most Microsoft products, ArcGIS, and ERDAS. In time, this may change and other languages may come to dominate. That won't matter - once you have learned one programming language it is easy to pick up another because the concepts are the same in all languages.
This class is an introduction of the theory and practice of spatial statistics as applied to the natural resources. Spatial analyses will focus primarily on kriging, point processes, and lattice data.