Introduces students to the nature and practice of science in physical and human geography, including practical methods for research productivity, professional, societal and ethical obligations of scientists, the philosophy of science, and the scientific literature. Students will prepare and critically evaluate research proposals.

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Multivariate statistical method applications to spatial problems. Linear and non-linear correlation and regression, factor analysis, cluster analysis. Spatial statistics including: trend surfaces, sequences, point distributions. Applications orientation.

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The intersection of human and biophysical systems from the vantage point of the impact of human actions on the environment are examined. The impact of the biophysical environment on humans is also discussed.

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This class provides an examination of land cover and land use change science, addressing the causes, impacts and projection of change. Key concepts of land use science are presented and recent research papers and case studies are reviewed. Class consists of lectures, invited presentations and individual student projects and presentations.

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The course will be a lab practical. Students will be introduced to the image processing steps required for characterizing land cover extent and change. Key components of land cover characterization, including image interpretation, algorithm implementation, feature space selection, thematic output definition, and scripting will be discussed and implemented.

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An advanced graduate level introduction to the effects of geography on economic activities and the effects of economic incentives, institutions, and activities on the nature and sustainability of human and environmental geographic systems.

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Biogeographical topics of global significance, including a consideration of measurement techniques, and both descriptive and mechanistic modeling. Topics may include: scale in biogeography, biodiversity, carbon geography, climate and vegetation, interannual variability in the biosphere, land cover, global biospheric responses to climate change, NASA's Mission to Planet Earth and Earth Observation System. The class focuses on both natural and athropogenic controls, impacts of biography on climate and ecosystem services and different methods in biogeography.

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Detailed examination of land remote sensing instruments, observatories and resultant measurements in the optical portion of the EM spectrum. Includes computer-based exercises that examine the importance of data geo-registration and radiometric calibration in land measurements.

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Biophysical principles, phenomena and processes underlying multispectra remote sensing in the optical portion of the EM spectrum. Includes computer-based exercises that explore the biophysical basis of land patterns and dynamics observed in remote sensing data.

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Comprehensive instruction is provided in the advanced use of a commercial programming language and analysis tool used for scientific programming and data visualization, with an emphasis on applications in geography and remote sensing or GIS.

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This course will provide an introduction to modern econometric techniques in general and spatial econometrics in particular. It is designed for senior and graduate students of geography department who may have relatively limited background in statistics, mathematics, and econometrics but are keen to learn this ‘difficult’ subject. This course will use the popular open source statistical computer language R. Its focus is on using statistical computing to produce analytical reports for real-world applications, research papers, and dissertations.

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Designed as an introduction to mobile GIS, to the programming concepts underlying mobile GIS development, and more importantly, to the design and implementation of a mobile GIS application. Covers how to develop, test, and publish mobile GIS native apps working across two mobile platforms: Android and iOS. This course will also try to leverage the capabilities of JavaScript, Swift, Google maps, ArcGIS Server and runtime SDK to developing and publishing mobile GIS web apps.

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Also offered on the Interactive Video Network. Contact the MEES department for more information.

This course considers various ways of understanding interactions and feedback loops between human and natural systems. We begin with core readings on coupled systems, then proceed into different methods for researching such systems. Students will gain fundamental understandings of this emerging area, opportunities to "'practice" appropriate methodological approaches, and a chance to conduct their own research.

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Restriction: Open to GEOG, GIS, and ENSP-Coastal, Land Use, Global majors only. The aim of the course is to familiarize the student with the fundamentals of geospatial representations, such as spatial indexes and network data structures, and with techniques for manipulating geospatial information for geographic information systems, for spatially-based, for spatially-based decision systems and location-based services.

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Lab sections will occasionally meet in LEF 1136 or LEF 1138. Students must pay a $40.00 lab materials fee.

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Students will learn to use open source GIS tools like QGIS, GeoServer and PostGIS to collect, store, analyze, serve and visualize spatial data on the web (e.g., OpenStreetMap Data). This course will help students understand the backend of web mapping services like Google map, Bing Map etc. by using open source GIS server to build Google Map-like web mapping services, including data services (WFS), visualization services (WMS), and processing services(WPS). Previous exposure to GIS environment and basic concepts of web server will be helpful but not required for learning in this course.

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This course is intended as a survey of the theory and methods pertaining to social networks. Class time will be devoted to learning principles, theoretical perspectives, and appropriate software packages (mainly those in R) for designing a study for gathering network data, and analyzing those data. The readings are a combination of introductory-level material, classic, scholarly readings in the field, and empirical studies that apply social network analytic techniques to topics relevant to the social sciences as a whole.

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