{"id":2924,"date":"2022-01-19T21:24:00","date_gmt":"2022-01-20T00:24:00","guid":{"rendered":"https:\/\/www.ufrgs.br\/ppgsr\/?page_id=2924"},"modified":"2026-07-07T18:30:23","modified_gmt":"2026-07-07T21:30:23","slug":"courses","status":"publish","type":"page","link":"https:\/\/www.ufrgs.br\/ppgsr\/en\/enrollment\/courses\/","title":{"rendered":"Course Descriptions"},"content":{"rendered":"\n<h3 class=\"wp-block-heading has-black-color has-text-color has-link-color wp-elements-9531b8ea3b5cb452c29d78343731c314\">Advanced topics on GNSS for positioning and remote sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">GNSS for ionosphere, GNSS for neutral atmosphere, GNSS Reflectometry, Artificial Intelligence for GNSS.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Genermia Nievinski\u00a0+ employees<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Satellite Agrometeorology<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Description of meteorological and agrometeorological elements; use of remote sensors in the estimation of meteorological and agrometeorological elements; use of remote sensors in crop monitoring; modeling of crop growth and yield parameters; crop forecasting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Denise Cybis Fontana&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Image Analysis Based on Geographic Objects<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Segmentation and clustering of remote sensing images, extraction of textural, spectral and geometric characteristics, classification using parametric and non-parametric methods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Laurindo Antonio Guasselli&nbsp;(Responsible)<\/li>\n\n\n\n<li>Luis Fernando Chimelo Ruiz<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Spatial Analysis<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Spatial Analysis and Geoprocessing (concepts). Computational representations of geographical space. Point Pattern Analysis (Kernel). Interpolation and Numerical Terrain Models. Geostatistical surface analysis. Analysis of Patterns in Area Data: Exploratory analysis, problems of scale and the ecological fallacy. Global spatial regression. Local spatial regression. Introduction to cluster analysis. Introduction to regionalization methods. Dynamic Spatial Modeling<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Marcos Wellausen Dias de Freitas&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing Applications in Geomorphology<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Applications of Remote Sensing data in Geomorphology. In the context of the impact of new technologies on Geomorphology, a comparative analysis of Digital Elevation Models (DEM) will be carried out. Evaluation of morphometric products for geomorphological compartmentalization.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Claudio Wilson Mendes Junior&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Geospatial Database<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Topographic mapping and geodetic references. Geospatial data. Cartographic updating. 3D cartographic representations. Generation of digital models: two and three-dimensional. Quality of geospatial data. Spatial Data Infrastructure (SDI).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Andrea Lopes Iescheck&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Reference Cartography and Geovisualization<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">The production of Reference Mapping. Cartographic projections and the UTM projection system. Brazilian systematic mapping. Cartographic generalization. Cartographic updating. Geoinformation and geoinformation systems. Defining the requirements for a geoinformation system. 3D cartographic representations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Claudia Robbi Sluter&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Spectral Behavior of Targets<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Notions of Radiometry: radiant energy; radiometric quantities; interactions of electromagnetic radiation with terrestrial targets; spectral signatures, measurement of reflectance; optical radiometer. Spectral behavior of vegetation: individual leaf and plant community; vegetation indices. Spectral behavior of minerals, soils and rocks. Spectral behavior of water.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Laurindo Antonio Guasselli&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Detection and Analysis of Changes in Vegetation Cover in Radiometric Space<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Optical spectrum satellite images, formats and numerical processing. Analysis of the acquisition of optical images by the sensor, acquisition geometry and solar illumination. Information processing in radiometric space. Advantages of using radiometric space to analyze and select detection techniques. Variations in data distribution due to lighting geometry, seasonality and effect on change detection. Structural types of vegetation cover and the effect of solar illumination geometry. Radiometric path analysis of thematic and nonthematic changes. Multi-sensor change detection techniques. Transforming continuous data into thematic data, mapping changes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Marcos Wellausen Dias de Freitas&nbsp;(Responsible)<\/li>\n\n\n\n<li>Francisco Dario Maldonado<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Statistics for Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Descriptive Statistics. Basic Probability Theory. Sampling Distributions. Introduction to Statistical Inference. Analysis of Variance. Correlation Analysis. Simple Linear Regression Analysis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Roosevelt de Lara Santos Junior<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Teaching Internship I<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Undergraduate teaching internship in a subject supervised by the supervising Instructor.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>All<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Planetary Boundary Layer Physics<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Basic concepts about the planetary boundary layer, atmospheric stability. Introduction to the surface energy balance equations. Sensors used to measure turbulent fluxes.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Rita de C\u00e1ssia Marques Alves&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Applied Geodesy<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Measurement methods in geodesy. Terrestrial geodetic measurements, gravity measurements and satellite observations. Geodetic surveys: planimetric network, altimetric network and gravimetric network. Modern geodetic methods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sergio Florencio de Souza&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Geoprocessing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Concepts of geographic information systems (GIS). Components of a GIS Spatial representation of data. Data sources for geoprocessing. Data management. Geographical analysis. GIS modeling.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Laurindo Antonio Guasselli&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Disaster Management<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Disasters; disaster management; prevention, mitigation, preparedness, response, and recovery; countermeasures; hazard, vulnerability, and risk mapping; early warning systems; legislation; case studies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Mauricio Andrades Paix\u00e3o<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Geotechnologies Applied to the Modeling and Simulation of Hydrometeorological Processes<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">General systems theory. Modeling environmental systems. Types of models. Techniques and digital processing of spatial data in GIS. Geotechnologies and their integration with the modeling of hydro-meteorological and environmental processes. Hydrological modeling and simulation. Modeling and simulations in water resources, climatology and meteorology.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Guilherme Garcia de Oliveira&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading has-black-color has-text-color has-link-color wp-elements-893d026f646688ec1c541e2a479e2376\">GNSS Interferometric Reflectometry for Water Level Measurements<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Basic principles of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR). How to run the \u201cgnssrefl\u201d software. GNSS-IR for water level measurements: lakes, rivers, tides.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Google Earth Engine<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Introduction to Google Earth Engine: concept, interface, type of data and available databases; Visualization of maps and images; Spatial and temporal compositions; Indices and time series; Statistical reducers; Obtaining samples; Area calculation; Land use and land cover maps; Classifiers and post-classification filters.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Denise Cybis Fontana&nbsp;(Responsible)<\/li>\n\n\n\n<li>Juliano Schirmbeck<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Integration of GNSS and RPAS (Remotely Piloted Aircraft System) for Mapping<\/h3>\n\n\n\n<p class=\"has-black-color has-text-color has-medium-font-size wp-block-paragraph\">Integration of surveying with GNSS and RPA (Remotely Piloted Aircraft System); Relative positioning methods (Post-processed and RTK); Flight regulation and authorization processes; Complete aerial survey workflow; Implementation of Ground Control Points (GCP) and Checkpoints; Evaluation of the positional accuracy of the final cartographic product; Practice in image processing and product generation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Marciano Carneiro (Instructor)<\/li>\n\n\n\n<li>Alexandre Felipe Bruch (Speaker)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Introduction to GNSS Interferometric Reflectometry<\/h3>\n\n\n\n<p class=\"has-black-color has-text-color has-medium-font-size wp-block-paragraph\">Basic principles of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR). How to run the gnssrefl software. Hydrologic applications. Water level applications. Site installations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Scientific Methodology<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Methodological principles of scientific research. The scientific method. Scientific documentation. Types of scientific research and items in the research project.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Claudia Robbi Sluter&nbsp;<\/li>\n\n\n\n<li>P\u00e9ricles Luiz Pican\u00e7o J\u00fanior<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Spatial Modeling Applied to Environmental Management<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Spatial data sources. Cartographic representation of spatial data. Spatial analysis methods. Change and vulnerability modeling. Case studies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Tatiana Silva da Silva&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing Research<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>All.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Physical Principles of Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Energy and Radiation: Atomic structure, fundamental forces. Production of radiation in its various forms: light, heat, radio waves, high energies. The origin of colors. Black Body Radiation: Wein&#8217;s Law, Stefan-Boltzman&#8217;s Law. Radiation-matter interaction: The photoelectric effect; the quantization of light. The electromagnetic spectrum: typical energy values; continuous spectrum; formation of spectral lines; solar spectrum. Chemical elements, abundances on Earth and in the Universe, isotopes. Radiation theory, spherical coordinates. Thermodynamic equilibrium. Maxwellian velocity distribution. Equilibrium conditions and atmospheric parameters. Light: speed, duality, polarization and coherence; reflection, refraction, optical fibres. Interference. Interferential filters. Laser. Light propagation: extinction and scattering. Lambert&#8217;s law, self-emission. Remote measurements: low and geostationary orbits. Satelliteization. Artificial satellites. Orbit inclinations, coverage of the Earth&#8217;s surface in a given number of orbits.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Jos\u00e9 Eduardo da Silveira Costa<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Principles for Evaluating the Accuracy of Raster Geospatial Data<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Main quality metrics in geospatial metadata standards and their concepts. Determining the accuracy of raster geospatial data. Sampling schemes and alternatives for obtaining reference data. Determining the accuracy of class maps and quantitative maps. Interpretation of results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Eliseu Jos\u00e9 Weber&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Digital Image Processing in Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Digital images. Attributes in digital images. Corrections in digital images. Geo-referencing. Methods for enhancing and smoothing digital images. Multispectral transformations. Segmentation methods for digital images.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Daniel Capella Zanotta&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Cloud processing of SAR images<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Principles of synthetic aperture radar (SAR) remote sensing. SAR image characteristics and corrections. Javascript programming elements. Processing and classification of Sentinel 1 SAR images in Google Earth Engine (GEE).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Fernando Luis Hillebrand&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Pattern Recognition<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">1- Introduction; review of matrix algebra; eigenvalues and eigenvectors of a matrix; operations on random vectors; linear transformations; the multivariate Gaussian distribution; 2- Basic concepts in Pattern Recognition; spectral, spatial, temporal, context (neighborhood) variables; 3- The statistical concept of decision; Bayesian decision theory; 4- Supervised classification; parametric methods for classification; classifiers; decision functions; linear and quadratic classifiers; methods for estimating parameters; 5- Methods for selecting and extracting variables; objectives; extracting variables for image representation and classification purposes; the Karhunen-Loeve transformation (principal components); transformations in discriminant analysis; measures of separability between classes; divergence, Bhattacharyya distance; 6- Notions on the use of spatial attributes and context (neighborhood) in the process of classifying digital images; 7- Unsupervised classification methods: concept and methods of clustering; main applications of clustering; 8- Notions about non-parametric classifiers; support vector machines (SVM) and neural networks.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Daniel Capella Zanotta&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Artificial Neural Networks for Remote Sensing and Spatial Data Modeling<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Artificial intelligence and machine learning techniques. The definition and structure of an artificial neural network (ANN). General aspects of programming ANN-based models. Modeling and preparing sample data for input into models. Development and application of ANNs in the modeling of remote sensing data and spatial data in general.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Guilherme Garcia de Oliveira&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Satellite reflectometry: Altimetric processing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Introduction. Geometric and physical principles. Observables and altimetric estimation. Sensors and instrumentation. Previous studies. Tide analysis. Pre-processing. Altimetric processing. Post-processing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Scientific Publishing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">The scientific publishing ecosystem. Manuscript preparation and submission. The peer review process. Further issues.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing of the Cryosphere<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Introduction to ice sheets and periglacial environments. Remote sensing of ice cover and permafrost parameters and processes. Field data acquisition. Snow and ice analytical techniques using aerial and orbital remote sensing. Mapping glaciers and periglacial geoforms with satellite images and aerial photographs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ulisses Franz Bremer&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Geodetic Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Satellite positioning, navigation and timing systems. GNSS observables and their sources of error. GNSS applications in meteorology and aeronomy (neutral and ionized atmosphere). GNSS reflectometry.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Geological Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Geological interpretation of remote sensing images. Analysis of the spectral behavior of soils, minerals and rocks in the optical spectrum. Synthetic aperture radar (SAR) images applied to geology. Geomorphometry applied to geological characterization and evolution. Integration of remote sensing and geophysics. Access to databases for geospatial geological data. Remote sensing data processing practices applied to the detection and analysis of geological targets.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Cl\u00f3dis de Oliveira Andrades Filho&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Seminars in Space Geodesy<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Space Geodesy. Satellite Geodesy. Integration with Terrestrial Geodesy. Environmental Geodesy Applications. Geodetic Remote Sensing. Scientific methodology.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Felipe Geremia Nievinski&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing of Vegetation<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Remote sensing of vegetation with basic definitions and applications. Review of theory and data from optical and SAR (radar) remote sensors. Spectral behavior of vegetation, with an introduction to plant structure, physiology (photosynthesis) and phenology. Applications of remote sensing in vegetation mapping and monitoring. Practical classes using an image processing system (SPRING or other). Assessment by 4 Assignments, including exercises, project, article and seminar presentation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Tatiana Mora Kuplich&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Remote Sensing of the Oceans<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Notions of Descriptive Physical Oceanography: physical properties of seawater, definition and analysis of water masses, global and regional ocean circulation. Radiative processes at the ocean-atmosphere interface and heat transport. Concepts of Remote Sensing: physical principles, satellites and sensors. Satellite Oceanography: processes, variables and applications.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Fabricio Sanguinetti Cruz de Oliveira&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Special Topic: Integrating the Ecosystem View into Coastal Vulnerability Assessment<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">An integrated and holistic assessment of coastal vulnerability must include aspects of the physical, biotic and social environment. Current practices are intrinsically flawed because they do not consider social aspects or the ecosystem view or both. Integrating the ecosystem view into coastal vulnerability assessments makes it possible to integrate the different factors that influence the capacity of coastal environments and communities to respond and adapt to climate change and extreme events. The application of remote sensing techniques, GIS and the principles of ecosystem-based management is fundamental to this integration. A better understanding of the factors that generate and influence social and environmental vulnerabilities is necessary to identify the adaptations that are needed to support sustainable development in coastal areas.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Luciana Slomp Esteves&nbsp;<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Special topic: Introduction to Python<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Python programming language. Programming environments. Data types. Identifiers. Variables. Arithmetic and logical expressions. Data collections. Modules. Functions. Graphics. Data input and output. Conditional structures. Repetition structures. NumPy: arrays and vectorization. Pandas: DataFrames. Managing data files. Notebooks. Markdown.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Jos\u00e9 Eduardo da Silveira Costa<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Special Topic: Introduction to Radar Remote Sensing<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">1. Introduction to radar. Types of radar. Acquisition methods used by radar sensors. Weather radar, ground penetrating radar (GPR), SLAR and SAR. 2. Principles of radar remote sensing. Synthetic aperture radar (SAR) and real aperture radar (SLAR). Radar imaging geometry. Characteristics of the signal measured by radar sensors (backscatter). 3. Sensor systems. Space agency data distribution policy. Image catalogs. 4. Radiometric calibration. backscatter from different targets on the Earth&#8217;s surface. 5. Speckle properties and filtering. 6. Geometric corrections in radar images. 7. Classification and segmentation of radar images. 8. development of radar image interpretation projects.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Jean Espinoza<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Special Topic: R Programming Language<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">R: an integrated system for programming, visualization, and scientific data analysis. Concepts of the R programming language. Data structures. Data visualization. Notebooks. Markdown.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Jos\u00e9 Eduardo da Silveira Costa<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Special Topic: Ecosystem-based Spatial Modeling<\/h3>\n\n\n\n<p class=\"has-medium-font-size wp-block-paragraph\">Ecosystems and their services. Ecosystem-based environmental valuation methods. Spatial models of ecosystem services Case studies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instructor(s):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Tatiana Silva da Silva<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Advanced topics on GNSS for positioning and remote sensing GNSS for ionosphere, GNSS for neutral atmosphere, GNSS Reflectometry, Artificial Intelligence for GNSS. Instructor(s): Satellite Agrometeorology Description of meteorological and agrometeorological [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"parent":2893,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2924","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2924","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/comments?post=2924"}],"version-history":[{"count":18,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2924\/revisions"}],"predecessor-version":[{"id":4305,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2924\/revisions\/4305"}],"up":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/pages\/2893"}],"wp:attachment":[{"href":"https:\/\/www.ufrgs.br\/ppgsr\/wp-json\/wp\/v2\/media?parent=2924"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}