Identify the key academic disciplines that contributed to the development of GIS&T
Evaluate the role that the Quantitative Revolution in geography played in the development of GIS
Describe the major research foci in GIS and related fields in the 1970s, 1980s, 1990s, and 2000s
Evaluate the importance of the NCGIA and UCGIS in coalescing GIScience as a sub-field of GIS&T
Discuss the contributions of early academic centers of GIS&T research and development (e.g., Harvard Laboratory for Computer Graphics, UK Experimental Cartography Unit)
Agent-based models are dynamic simulation models that provide insight into complex geographic systems. Individuals are represented as agents that are encoded with goal-seeking objectives and decision-making behaviors to facilitate their movement through or changes to their surrounding environment. The collection of localized interactions amongst agents and their environment over time leads to emergent system-level spatial patterns. In this sense, agent-based models belong to a class of bottom-up simulation models that focus on how processes unfold over time in ways that produce interesting, and at times surprising, patterns that we observe in the real world.
Differentiate supervised classification from unsupervised classification
Describe the sequence of tasks involved in the geometric correction of the Advanced Very High Resolution Radiometer (AVHRR) Global Land Dataset
Compare pixel-based image classification methods with segmentation techniques
Explain how to enhance contrast of reflectance values clustered within a narrow band of wavelengths
Describe an application of hyperspectral image data
Produce pseudocode for common unsupervised classification algorithms, including chain method, ISODATA method, and clustering
Calculate a set of filtered reflectance values for a given array of reflectance values and a digital image filtering algorithm
Describe a situation in which filtered data are more useful than the original unfiltered data
Perform a manual unsupervised classification given a two-dimensional array of reflectance values and ranges of reflectance values associated with a given number of land cover categories
Compare and contrast spatial statistical analysis, spatial data analysis, and spatial modeling
Compare and contrast the methods of analyzing aggregate data as opposed to methods of analyzing a set of individual observations
Define the terms spatial analysis, spatial modeling, geostatistics, spatial econometrics, spatial statistics, qualitative analysis, map algebra, and network analysis
Differentiate between geostatistics and spatial statistics
Discuss situations when it is desirable to adopt a spatial approach to the analysis of data
Explain what is added to spatial analysis to make it spatio-temporal analysis
Explain what is special (i.e., difficult) about geospatial data analysis and why some traditional statistical analysis techniques are not suited to geographic problems
Outline the sequence of tasks required to complete the analytical process for a given spatial problem
Compare and contrast spatial statistics and map algebra as two very different kinds of data analysis
FC-31 - Academic origins