. "Geographic Information Science"@en . . "Remote Sensing"@en . . "Environmental sciences"@en . . "English"@en . . "Fundamentals of remote sensing"@en . . "6.0" . "### Working language\n\nPortuguese and English\n\n### Goals\n\nThis UC aims to introduce the basic concepts of Remote Sensing (RD), which will serve as the basis for the frequency of specific UC DR, from the 2nd semester of the 1st year.\n\nPretend that students:\n\n1) Acquire basic knowledge about the physical principles of remote sensing, in particular about radiometry and the interaction of radiation with the atmosphere and the Earth's surface.\n\n2) Get to know the immense potential of remote sensing in Earth observation.\n\n3) Get to know the main characteristics of the orbits of Remote Sensing satellites.´\n\n4) Get to know the vast set of satellite data available and be able to identify the most suitable one for solving a given problem.\n\n5) Know the specific characteristics of microwave sensors versus optical and thermal sensors, advantages and tolerances of each type.\n\n### Learning outcomes and skills\n\nStudents must:\n\n1) Be able to identify the strengths and limitations of remote sensing in Earth observation, in particular: the physical principles of remote sensing; the main characteristics of DR satellite orbits and how they affect the ability to acquire DR data; main satellites and sensors and their characteristics..\n\n2) Know the vast set of available satellite data and be able to identify the most appropriate one to solve a given problem.\n\n### Working mode\n\nin person\n\n### Program\n\n1\\. Introduction to Remote Sensing.\ntwo\\. Energy sources and radiometric concepts\n3\\. Interaction of energy with the atmosphere\n4\\. Interaction of energy with the Earth's surface\n5\\. Orbits of remote sensing satellites.\n6\\. Earth Observation Satellites\n6.1 Characteristics of satellites and sensors; Types of Sensors.\n6.2 Environmental satellites\n6.3 Oceanographic satellites\n6.4 Weather satellites\n6.5 High resolution satellites (spatial and/or spectral)\n7\\. Microwave sensors.\n\n### Mandatory Bibliography\n\nJensen John R.; [Remote sensing of the environment](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000285191 \"Remote sensing of the environment (Abre numa nova janela)\"). ISBN: 0-13-188950-8 \nLillesand, T.M., Kiefer, R.W.; Remote Sensing and Image Interpretation, John Wiley and Sons, 7th Edition,, 2015 \nRees, W. G; Physical Principles of Remote Sensing, University of Cambridge, 3rd Edition , 2013 \nProst Gary L.; [Remote sensing for geoscientists](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000297467 \"Remote sensing for geoscientists (Abre numa nova janela)\"). ISBN: 978-1-4665-6175-5 ebook \n\n### Complementary Bibliography\n\nRichards, J.A., Jia, X; Remote Sensing Digital Image Analysis - An Introduction, Fifth Edition, Springer-Verlag, 2013 \nGonzalez, R.C., Woods, R.E. ; Digital Image Processing, Addison-Wesley, 2008 \n\n### Teaching methods and learning activities\n\nTheoretical content classes are given based on Power Point presentations. In the practical classes, it is proposed to solve exercises that aim to apply and complement the knowledge given in the theoretical ones, especially those referring to points 2) and 5) of the program. At the beginning of each class, a period will be reserved for students to raise questions about the content of the previous class, thus trying to encourage continuous and regular study.\n\nSince the objectives of this UC are the transmission of basic knowledge of Remote Sensing, it does not include the use of any type of software, this component being covered by the UC Digital Image Processing and Computing for Remote Sensing.\n\n### Type of evaluation\n\nEvaluation by final exam (100%)\n\n### Occupation Components\n\nSelf-study (hours): 120.00\n\nFrequency of classes (hours): 42.00\n\n**Total:**: 162.00\n\n### Get Frequency\n\nClass attendance is mandatory. Students may lose attendance if they exceed the number of absences provided by law.\n\n### Final classification calculation formula\n\nAssessment is carried out in a final exam (EF), with two components: Theoretical (T) and Practical (P).\n\nFinal: CF=T \\*0.7 + P\\*0.3.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479403" . . "Presential"@en . "TRUE" . . "Image processing and analysis"@en . . "6.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n\n### Goals\n\nThe objective of this curricular unit is to present the main concepts and techniques of Digital Image Processing (PDI) with emphasis on images acquired by remote sensing sensors.\n\n### Learning outcomes and skills\n\nIt is intended that students:\n\n\\- Know and understand the main concepts and methods used in remote sensing image processing.\n\n\\- Be able to select and use the appropriate PDI tools to extract relevant information from remote sensing images.\n\n\\- Be able to apply the knowledge acquired in the effective analysis of simulated and experimental data, using advanced computational means.\n\n### Working mode\n\nIn person\n\n### Program\n\n1\\. Basic concepts of digital image processing.\ntwo\\. Spot operations / Image calibration.\n3\\. Spatial Filters / Noise Reduction.\n4\\. Color representation models.\n5\\. Image segmentation.\n6\\. Morphological Operations.\n7\\. Geometric Corrections / Image referencing.\n8\\. Multi-Spectral Imaging / Principal Components.\n9\\. Classification of multi-spectral images.\n10\\. Clustering / Unsupervised sorting.\n11\\. Operations in frequency space.\n\n### Mandatory Bibliography\n\nRichards J.A. Jia X.; [Remote Sensing Digital Image Analysis](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000227774 \"Remote Sensing Digital Image Analysis (Opens in a new window)\")\nGonzalez Rafael C.; [Digital image processing](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000260721 \"Digital image processing (Opens in a new window)\"). ISBN: 0-13-008519-7\nRafael C. Gonzalez; [Digital image processing using MATLAB](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000278836 \"Digital image processing using MATLAB (Opens in a new window)\"). ISBN: 0-13-008519-7\n\n### Complementary Bibliography\n\nSzeliski, R.; Computer Vision: Algorithms and Applications, Springer, 2010\nSonka Milan; [Image processing, analysis, and machine vision](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000281201 \"Image processing, analysis, and machine vision (Opens in a new window )\"). ISBN: 0-495-08252-X\n\n### Teaching methods and learning activities\n\nThe TP classes are used in part for the presentation of theoretical material, illustrated with varied examples, and there is another part dedicated to the execution of small practical (computational) projects. The “Other” type classes are used to support the realization of practical computational work as well as clarify any doubts that students may have.\n\n### Software\n\nSNAP\nMATLAB\n\n### Type of evaluation\n\nDistributed evaluation with final exam\n\n### Assessment Components\n\nOral test: 20.00%\n\nWritten work: 30.00%\n\nPractical or project work: 50.00%\n\n**Total:**: 100.00\n\n### Occupation Components\n\nSelf-study: 60.00 hours\nFrequency of classes: 42.00 hours\nProject development: 40.00 hours\nWritten work: 20.00 hours\n\n**Total:**: 162.00\n\n### Get Frequency\n\nRealization of Practical Works, with the delivery of the respective reports within the established deadlines, and with a classification of not less than 40% of the corresponding quotation (8 values in the 0-20 scale).\nStudents may have to answer questions related to the practical work carried out, during classes or in an oral exam.\n\n### Final classification calculation formula\n\nThe final classification will be determined based on the performance in practical work (50%) and in an individual mini-project (50%), none of these components being able to be less than 40% of the corresponding quotation (8 values in the 0-20 scale).\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479404" . . "Presential"@en . "TRUE" . . "Statistics applied to science and engineering"@en . . "6.0" . "### Working language\n\nEnglish\n_Note: Note that the working language will be English, and students can always ask questions in Portuguese._\n\n### Goals\n\n1\\. Enable the student for regression analysis involving continuous or discrete responses (generalized linear models)\ntwo\\. Implement statistical analyzes in suitable software\n3\\. Promoting a critical spirit in a data analysis process (data collection, modelling, interpretation of results, ...)\n\n### Learning outcomes and skills\n\nAt the end of the curricular unit, it is intended that students:\na) acquire knowledge about the organized collection of information\nb) learn statistical techniques and models commonly used in data processing\nc) know how to correctly choose the statistical models learned for concrete problems\nd) know how to apply and implement the models studied in R\ne) acquire a critical spirit and ability to interpret the results obtained.\n\n### Working mode\n\nIn person\n\n### Prerequisites (prior knowledge) and co-requisites (concurrent knowledge)\n\nPrior knowledge of random variables and probability distributions, sample statistics, confidence intervals and hypothesis testing is required. These are the usual contents of an introductory curricular unit to Probability and Statistics in higher education. A brief review of this matter will be carried out.\n\n### Program\n\n0\\. Brief review of inference-based techniques. statistics - confidence intervals and hypothesis tests\n1- Introduction to programming language in software environment **R.**\ntwo\\. Pearson correlation and Spearman correlation.\n3\\. Simple linear regression.\n4\\. Multiple linear regression. Model, parameter estimation, hypothesis tests for coefficients, confidence intervals, prediction intervals, determination coefficient, multicollinearity, model selection methods, model comparison, diagnosis.\n5\\*. Analysis of variance - ANOVA: 1 and 2 factors.\n6\\*. Generalized linear models. Logistic regression.\n\\*Only one subject will be studied, from 5. to 6.\n\n### Mandatory Bibliography\n\nRita Gaio; Notes written by the teacher\n\n### Complementary Bibliography\n\nISBN: 1-58488-029-5\nISBN: 0-387-95475-9\nISBN: 978-0-521-86116-8\nISBN: 0-387-95187-3\nISBN: 0-387-95284-5\nISBN: 1-58488-325-1\nISBN: 0-387-98218-3\nJulian Faraway; Linear Models with R, Taylor and Francis, 2009. ISBN: 1584884258\nJulian Faraway; Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Chapman & Hall/CRC Texts in Statistical Science, 2006. ISBN: 158488424X\n\n### Teaching methods and learning activities\n\nTheoretical-practical classes with different examples of application of techniques and statistical models presented in a computational laboratory. The software used is R.\n\n### Software\n\nR Project\n\n### Key words\n\nPhysical Sciences > Mathematics > Statistics\n\n### Type of evaluation\n\nDistributed evaluation with final exam\n\n### Assessment Components\n\nTest: 37.50%\nWritten work: 25.00%\nExam: 37.50%\n\n**Total:**: 100.00\n\n### Occupation Components\n\nSelf-study: 110.00 hours\nFrequency of classes: 42.00 hours\nWritten work: 10.00 hours\n\n**Total:**: 162.00\n\n### Get Frequency\n\nThere is no lack of frequency.\n\n### Final classification calculation formula\n\n1\\. The work consists of a written report and an oral presentation. Carrying out the work is optional.\n \ntwo\\. The grade of the work cannot be improved.\n \n3\\. The evaluation of the normal season will include the classification of two tests (T1 and T2), each with a quotation of 10 points. The T2 test will take place on the day designated for the exam of the normal season.\n \n4\\. The evaluation of the appeal period will only include a final exam, which will focus on all the contents of the curricular unit. The classifications of the T1 and T2 tests will not be considered here.\n \n5\\. Evaluation formula in the **regular season**: There are two evaluation formulas, depending on whether or not the curricular unit's work/project is delivered.\n \na) For students who **turn in work**:\na1) T1+T2: weight of 13 or 15 (in 20); work: weight of 7 or 5 (in 20)\nOf the two evaluation components, the one in which the student had the best rating (on a scale of 0-20) has, for that student, the maximum weight indicated above. The worst component has, for that student, the minimum weight indicated above.\na2) In order to pass, the student must obtain a classification greater than 20% in each of the components (tests and work).\n \nb) For students who **do not turn in the work**:\nIn this case, only the test scores count; however, the student's final classification will never be higher than 16, even with a higher grade in the tests.\n \n6\\. Evaluation formula in **appeal season**: There are two evaluation formulas, depending on the delivery or not of the work/curricular unit project.\n \na) For students who **turn in work**:\na1) resource exam: weight of 13 or 15 (out of 20); work: weight of 7 or 5 (in 20)\nOf the two evaluation components, the one in which the student had the best rating (on a scale of 0-20) has, for that student, the maximum weight indicated above. The worst component has, for that student, the minimum weight indicated above.\na2) In order to pass, the student must obtain a classification greater than 20% in each of the components (exam and work).\n \nb) For students who **do not turn in the work**:\nIn this case, only the exam score counts; however, the final classification of the student will never exceed 16 points, even if he/she has a higher grade in the exam.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479406" . . "Presential"@en . "TRUE" . . "Computing for remote sensing"@en . . "6.0" . "### Working language\n\nPortuguese and English\n\n### Goals\n\nIt is intended that students acquire skills and knowledge of programming/scientific computing that will allow them to develop tools and applications dedicated to the areas of Remote Sensing (RD).\n\n### Learning outcomes and skills\n\nThe program covers the Python language as a programming language, as well as the use of scientific computing libraries for manipulation and visualization of geospatial information for the development of applications.\n\n### Working mode\n\nIn person\n\n### Prerequisites (prior knowledge) and co-requisites (concurrent knowledge)\n\nNo prerequisites.\n\n### Program\n\nIntroduction to the Python language\n\nIntroduction to the command line for interactive computing – IPython\n\nData Types (variables of type int, float, byte…, strings, lists, dictionaries…)\n\nControl flow (loops, if-then conditions)\n\nCode organization (functions, modules, packages)\n\nFile writing and reading, data input-output\n\nIntroduction to the _numpy_ module\n\nUnderstand data structuring with N-dimensions\n\narray creation\n\nArray indexing, joining and cutting with indexes, masks\n\nBasic operations and manipulation of N-dimensional arrays\n\nIntroduction to the 2D visualization module – _matplotlib_\n\nControl of colors, axes and legends\n\nCreating scatter, line, and bar charts\n\nStatistical graphs, histograms\n\nLevel curves, 2.5D visualization\n\nSub-figures, graphic organization\n\nIntroduction to the _s__ci__p__y_ module for scientific computing\n\ntrigonometric functions\n\nstatistical functions\n\nLinear Algebra, vectors and matrices\n\nLinear, polynomial and spline interpolation\n\ndata input-output\n\nVisualization of georeferenced information – _b__asemap_ and _c__artopy_\n\nmap creation\n\ncartographic projections\n\nCoastlines, political boundaries, land-sea, lakes and rivers\n\nMapping of vector information through shapefiles\n\nData structuring in time series and dataframes – module _p__andas_\n\nData input-output in pandas\n\nStructured information 1D (series) and 2D (dataframes)\n\nData organization, aggregation and indexing criteria\n\nComputing and analyzing information in pandas\n\nControl of dates and times, module _astropy_\n\n2D visualization and matplotlib integrated in Pandas\n\nMulti-dimensional arrays and datasets with _pandas_ and _xarray_\n\nInput-output of structured information in netCDF\n\nData indexing and selection\n\nExtraction and manipulation of variables\n\nStatistical analysis by dimensions and time series\n\nReorganization and visualization\n\n### Mandatory Bibliography\n\nMark Lutz; [Programming Python](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000228063 \"Programming Python (Opens in a new window)\"). ISBN: 0-596-00085-5\n\n### Complementary Bibliography\n\nMark Lutz; [Python pocket reference](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000189758 \"Python pocket reference (Opens in a new window)\"). ISBN: 978-1-56592-500-7\nMatt A. Wood; [Python and Matplotlib essentials for scientists and engineers](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000855875 \"Python and Matplotlib essentials for scientists and engineers (Opens in a new window )\"). ISBN: 978-1-62705-619-9\nHans Peter Langtangen; [A primer on scientific programming with Python](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000291612 \"A primer on scientific programming with Python (Opens in a new window)\" ). ISBN: 978-3-642-02474-0\n\n### Teaching methods and learning activities\n\nClasses are based on Powerpoint presentations and Notebooks with practical exercises exemplifying the use of the various modules addressed.\n\n### Software\n\nPython interpreter\nvirtualbox\n\n### Type of evaluation\n\nEvaluation by final exam\n\n### Assessment Components\n\nExam: 100.00%\n\n**Total:**: 100.00\n\n### Occupation Components\n\nSelf-study: 50.00 hours\nFrequency of classes: 50.00 hours\n\n**Total:**: 100.00\n\n### Get Frequency\n\nClass attendance is mandatory.\nStudents may lose attendance if they exceed the number of absences provided by law.\n\n### Final classification calculation formula\n\nFinal exam (100%).\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479402" . . "Presential"@en . "TRUE" . . "Geographic information systems"@en . . "6.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n_Note: Portuguese_\n\n### Goals\n\nNecessary theoretical bases for students to deal with representations of cartographic data in a computational environment and for the use and implementation of a GIS.\n\n### Learning outcomes and skills\n\nStudents should know the differences between raster and vector data models, and the advantages and disadvantages of each model. They should also know how to analyze GIS data from simple and spatial searches.\n\n### Working mode\n\nIn person\n\n### Program\n\n1\\. Principles and fundamentals of Geographic Information Systems.\ntwo\\. Vector data: acquisition, manipulation and analysis operations with environmental data.\n3\\. Open Source GIS Software. Some examples of applications.\n4\\. Geographic databases.\n5\\. Raster data: acquisition, manipulation and analysis operations with environmental data.\n6\\. Three-dimensional terrain analysis: digital terrain models.\n7\\. Examples of GIS applications.\n8\\. Principles of geostatistics.\n\n### Mandatory Bibliography\n\nLongley Paul A.070; [Geographic information systems and science](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000279522 \"Geographic information systems and science (Opens in a new window)\"). ISBN: 9780470870013\n\n### Teaching methods and learning activities\n\nSome TP classes of the curricular unit are of a more theoretical nature and others of a more practical nature, with the performance of various exercises in GIS software. In the “Other” classes, doubts will be answered about the various topics of the program and support will be given to carrying out practical computational work.\nThe teaching means include the audiovisual material for the presentation of the classes as well as the various GIS software (proprietary and open source).\n\n### Software\n\nQGIS\nArcGIS\n\n### Type of evaluation\n\nDistributed evaluation with final exam\n\n### Assessment Components\n\nExam: 60.00%\nLaboratory work: 40.00%\n\n**Total:**: 100.00%\n\n### Occupation Components\n\nFrequency of classes: 50.00 hours\nLaboratory work: 50.00 hours\n\n**Total:**: 100.00 hours\n\n### Get Frequency\n\nAttendance in 75% of classes.\n\n### Final classification calculation formula\n\nThe evaluation will be carried out through a practical evaluation in a computational environment (corresponds to 40% of the final classification) and a final written exam. Students must have a minimum of 8 values in each of the assessment components. The classification of the subject has a weight of 60% for the written exam (T) and 40% for the practical evaluation (P).\nThe final classification will be: CF=T \\*0.6 + P\\*0.4.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479405" . . "Presential"@en . "TRUE" . . "Gnss applications"@en . . "3.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n\n### Goals\n\nUnderstand the operating principles of GNSS systems (Global Navigation Satellite Systems).\n\n### Learning outcomes and skills\n\nA. Know the characteristics of the current GNSS (Global Navigation Satellite Systems), identify their limitations, and acquire the necessary knowledge to determine positions and speeds.\n\nB. Identify and understand issues that may affect GNSS observations and how to overcome them.\n\nC. Knowing the advantages, and necessity, of integrating GNSS with other sensors and identifying the most appropriate solutions depending on the type of application and the desired positional accuracy.\n\nD. Realize that in science what, for some, is noise, for others, can be a valuable source of data, which allows the acquisition of relevant information for various areas of Earth and Space sciences.\n\n### Working mode\n\nIn person\n\n### Prerequisites (prior knowledge) and co-requisites (concurrent knowledge)\n\n\\- Elementary knowledge of Reference Systems\n \n\\- Orbits\n\n### Program\n\n1\\. Introduction to global positioning techniques: evolution and basic concepts, operating principles, types of observables, error sources.\n\ntwo\\. Methodologies to eliminate and model errors in the determination of positions and velocities.\n\n3\\. GNSS integration with other sensors. Practical examples of application in remote sensing.\n\n4\\. Methods for advanced analysis of long series of temporal data. Applications in Geosciences.\n\n5\\. Ionosphere: introduction and basic concepts. Influence on the accuracy of GNSS measurements. Use of GNSS data to characterize the state of the ionosphere and identify disturbances.\n\n6\\. Reflected signals: applications of GNSS reflectometry.\n\n### Mandatory Bibliography\n\nSanz Subirana Jaume; [GNSS data processing](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000296749 \"GNSS data processing (Opens in a new window)\"). ISBN: 978-92-9221-886-7\n\n### Complementary Bibliography\n\nGroves Paul D.; [Principles of GNSS, inertial, and multisensor integrated navigation systems](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000291643 \"Principles of GNSS, inertial, and multisensor integrated navigation systems (Opens in a new window)\"). ISBN: 978-1-58053-244-6\n\n### Teaching methods and learning activities\n\nClasses include theoretical exposition but also oral presentations by students. Students must write and deliver a report corresponding to the work they have presented.\n\n### Type of evaluation\n\nDistributed evaluation with final exam\n\n### Assessment Components\n\nPresentation/discussion of a scientific work: 20.00%\nExam: 80.00%\n\n**Total:**: 100.00%\n\n### Occupation Components\n\nFrequency of classes: 21.00 Hours\nSelf-study: 40.00 hours\nLaboratory work: 20.00 hours\n\n**Total:**: 81.00\n\n### Get Frequency\n\nStudents cannot exceed the maximum number of absences from theoretical-practical classes, in accordance with the legislation in force at FCUP:\n\n### Final classification calculation formula\n\nThe final classification (EF) results from the performance in the Theoretical Exam (ET) and Presentations and Reports (AR)\n\nThe final classification will be: CF= ET \\*0.8 + AR\\*0.2\n\nMinimum: 50% in the written exam and 50% in the Presentations and Report\n\nNOTE: Classification superior to 15 points in the theoretical exam will only be attributed after carrying out a complementary oral test.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479386" . . "Presential"@en . "TRUE" . . "Remote sensing and gis software"@en . . "3.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n\n### Goals\n\nIn this Curricular Unit it is intended that students acquire skills and knowledge within the scope of the computational development of new tools/applications in the areas of remote sensing and GIS. More specifically:\n\n1. Know the graphical environment of the software to be used.\n2. Use of GIS and Remote Sensing tools.\n3. Acquire training on geospatial libraries and programming paradigms involved.\n4. Automating algorithms for data processing and analysis.\n\n### Learning outcomes and skills\n\nDuring contact with the software and available tools, the student will be encouraged to know, explore and question the functioning of the software with the monitoring of the code presented in the python-_notebook_ and its implementation, contributing to the consolidation of knowledge; classes using software and script development will allow the student to finalize the creation of an application/tool, integrating all the concepts learned so far within the scope of the Curricular Unit.\n\n### Working mode\n\nIn person\n\n### Program\n\n2. Exploration of spatial data modules: GDAL/OGR.\n \n4. Introduction to QGIS software.\n * Exploitation of remote sensing oriented tools integrated in QGIS.\n * Semi automatic classification plugin.\n * Orfeo-Toolbox.\n\n * Introduction to PyQt4 library and QGIS API (qgis.gui and qgis.core).\n * Official framework for creating applications in QGIS software.\n * Importation of algorithms from the Processing Toolbox framework.\n \n6. Introduction to GRASS-GIS software (vector and raster layers; layer properties; visualization of geospatial information; geprocessing; manipulation of multispectral images).\n \n8. Introduction to processing SAR Image products with ESA-SNAP. Radiometric calibration, noise reduction with application of filters and multilook technique, geometric correction. Integration of the final product in GRASS-GIS for geospatial analysis.\n \n\n### Mandatory Bibliography\n\nLawhead, J.; QGIS Python Programming Cookbook, 2015\nMarkus Neteler, Helena Mitasova; Open Source GIS: A GRASS GIS Approach, Springer, 2010\nGary Sherman; Desktop GIS: Mapping the Planet with Open Source Tools, Pragmatic Bookshelf, 2008\n\n### Teaching methods and learning activities\n\nClasses are taught with an essentially practical component and complemented with a theoretical context that will be presented in _the form of worksheets integrated between the different software_, where students follow the material interactively and implement it using the QGIS, GRASS software -GIS and ESA-SNAP.\n\nAssessment is carried out at the end of the program with a practical exam where problems are posed and students must think/reflect and implement a solution. This assessment is carried out with the support of the interactive _notebook_ provided in class.\n\nPractical exam – 100%\n\n### Software\n\nQGIS\nGRASS-GIS\n\n### Type of evaluation\n\nEvaluation by final exam\n\n### Assessment Components\n\nExam: 100.00%\n**Total:**: 100.00%\n\n### Occupation Components\n\nFrequency of classes: 21.00 hours\nSelf-study: 60.00 hours\n\n**Total:**: 81.00 hours\n\n### Get Frequency\n\nFrequency is obtained by taking a final exam.\n\n### Final classification calculation formula\n\nFinal exam.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479387" . . "Presential"@en . "TRUE" . . "Seminars in remote sensing"@en . . "3.0" . "### Working language\n\nPortuguese and English\n\n### Goals\n\nThe objective of this UC is to provide students with a cycle of Lectures on various specialty topics that are not covered in the remaining UC of the CE. These Lectures are intended to be a training and didactic complement and will be delivered predominantly by specialists, either researchers (national or foreign who travel to Porto within the scope of projects. or collaborations with the CE teaching staff), or professionals from companies with activities linked to the DR. Former students of the Masters in Remote Sensing at FCUP, which operated between 2000 and 2007, whose activity is linked to DR, will also be invited, with the aim of transmitting their academic and professional experience to students.\n\n### Learning outcomes and skills\n\nAt the end of the UC, it is intended that students have broadened their knowledge to other domains of DR, contacted researchers and professionals with different experiences, broadened their critical and analytical sense, as well as their ability to carry out autonomous work.\n\n### Working mode\n\nIn person\n\n### Program\n\nSeminars on topics related to the Master's theme, which may be of a more scientific or more technical content, given predominantly by invited national or foreign specialists. Since the master's degree covers a wide range of applications, the possible topics are very wide and will naturally vary from one year to the next.\n\nExamples of possible topics:\n\n\\- Coastal bathymetry with lidar\n\n\\- Sensors on board unmanned aerial vehicles (UAV) and range of applications\n\n\\- Gravimetric Satellites\n\n\\- Innovative applications of integrated GNSSS/INS systems\n\n\\- Remote detection of vegetation\n\n\\- Remote detection of urban areas\n\n\\- etc.\n\n### Mandatory Bibliography\n\nD. Stammer and A. Cazenave, (eds); Satellite Altimetry Over Oceans and Land Surfaces, CRC PressI, 2017. ISBN: 9781498743457\nJackson, C.R., Apel, J.; Synthetic Aperture Radar Marine User’s Manual, available online at http://www.sarusersmanual.com, 2004\nRobinson Ian S.; [Measuring the oceans from space](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000261491 \"Measuring the oceans from space (Opens in a new window)\"). ISBN: 3-540-42647-7\nVaughan Robin A. 340; [Remote sensing applications in meteorology and climatology](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000256498 \"Remote sensing applications in meteorology and climatology (Opens in a new window)\" ). ISBN: 90-277-2502-0\nJones, G.H., Vaughan, R.; Remote sensing of vegetation. Principles, techniques, and applications. , Oxford University Press, Oxford New York, 2010\nFerretti, A.; Satellite InSAR Data – Reservoir Monitoring from Space, EAGE Publications, 2016\n\n### Bibliographic Notes\n\nBibliographic support documents will be provided for each seminar.\n\nExamples of reference books for some areas of application are given.\n\n### Teaching methods and learning activities\n\nThe TP will consist of seminars that will be organized in advance, taking into account the availability of the guests and the relevance of the themes for the EC.\n\nStudents will participate in person to the various Lectures given by national or foreign specialists in the area of DR. After the Lectures, students will be motivated to research one of the topics addressed, under the guidance of the UC professor and/or the specialist who presented the lecture.\n\nIn the “Other” classes, doubts will be answered about the topics covered and support will be given to carrying out individual work.\n \n\n### Type of evaluation\n\nEvaluation by final exam\n\n### Assessment Components\n\nOral test: 30.00%\nWritten work: 70.00%\n\n**Total:**: 100.00%\n\n### Occupation Components\n\nSelf-study: 35.00 hours\nFrequency of classes: 21.00 hours\nResearch work: 25.00 hours\n\n**Total:**: 81.00 hours\n\n### Get Frequency\n\nClass attendance is mandatory. Students may lose attendance if they exceed the number of absences provided by law.\n\n### Final classification calculation formula\n\nThe evaluation is done through an individual work, in article format, on a theme chosen from the list of themes of the various seminars presented. The assessment includes an oral presentation and discussion of the work.\n\nThe classification of the course is the grade of the work carried out with a weighting of 70% for the written work (T) and 30% for the oral discussion (O).\n\nCF=T \\*0.7 + O\\*0.3.\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479388" . . "Presential"@en . "TRUE" . . "Airborne sensors and photogrammetry"@en . . "3.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n\n### Goals\n\nThis UC presents the main concepts related to the acquisition, georeferencing and extraction of geometric information from images obtained by aerial cameras and other sensors, transported by manned aircraft or by UAVs (unmanned aerial vehicles).\n\n### Learning outcomes and skills\n\nIt is intended that students:\n1) Get to know the essentials of aerial photography geometry.\n2) Know the orientation procedures for single optical images and stereoscopic pairs.\n3) Get to know the processes for obtaining three-dimensional information and orthorectification of images.\n4) Perform simple processing of images obtained with UAV.\n5) Understand the geometry of other airborne sensors and understand the need for adequate mathematical models.\n\n### Working mode\n\nIn person\n\n### Program\n\n1\\. Geometry of aerial photography.\ntwo\\. External guidance.\n3\\. Stereoscope pairs, image blocks and aerial triangulation.\n4\\. Automatic image correlation methods.\n5\\. Point clouds and digital surface models.\n6\\. Orthorectification and composition of mosaics.\n7\\. Image processing exercise obtained with UAV.\n8\\. Geometry of other sensors: Lidar, linear sensors and aerial SAR.\n\n### Mandatory Bibliography\n\nBerberan Antonio; [Elements of photogrammetry](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000294337 \"Elements of photogrammetry (Opens in a new window)\"). ISBN: 972-95873-5-3\nWolf Paul R.; [Elements of photogrammetry](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000228090 \"Elements of photogrammetry (Opens in a new window)\"). ISBN: 0-07-292454-3\n\n### Complementary Bibliography\n\nLinder Wilfried; [Digtal photogrammetry](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000280780 \"Digtal photogrammetry (Opens in a new window)\")\nSchenk Toni; [Digital photogrammetry](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000245819 \"Digital photogrammetry (Opens in a new window)\")\n\n### Teaching methods and learning activities\n\nAttendance in 2/3 of classes\n\n### Type of evaluation\n\nEvaluation by final exam\n\n### Assessment Components\n\nExam: 100.00%\n\n**Total:**: 100.00\n\n### Occupation Components\n\nFrequency of classes: 100.00 hours\n\n**Total:**: 100.00 hours\n\n### Get Frequency\n\nSince this is a UC mainly for the transmission of concepts, classes are given based on Power Point presentations and some deductions or calculations on the board. Practical exercises for processing images obtained by UAV with specific software will be launched, with a view to implementing the concepts learned. In the complementary classes of typology “Others”, questions will be clarified and support will be given to carrying out these exercises and analyzing the results.\n\n### Final classification calculation formula\n\n100% final exam\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479385" . . "Presential"@en . "TRUE" . . "Cartography"@en . . "3.0" . "### Working language\n\nPortuguês - Suitable for English-speaking students\n\n### Goals\n\nThis UC presents the main concepts of coordinate systems associated with the production of cartography, and methods of traditional and digital cartographic representation.\n\n### Learning outcomes and skills\n\nIt is intended that students:\n1) Acquire basic knowledge about geographic referencing systems.\n2) Know the forms of transformations between the different systems of geographic and cartographic coordinates and altimetric systems.\n3) Be capable of converting and transforming coordinates using tools provided by geographic information processing programs.\n4) Know the characteristics of topographic and thematic cartography, whether in analogue or digital form.\n5) Understand the ways of generating maps from remote sensing images and the use of digital cartography combined with images.\n\n### Working mode\n\nIn person\n\n### Program\n\n1\\. Physical phenomena associated with reference systems\ntwo\\. Level, geoid, and ellipsoid surfaces.\n3\\. Geographic coordinate systems and altitude systems\n4\\. Local and global geodetic datum\n5\\. Datum Transformations\n6\\. Cartographic projections: main projections and their geometric properties\n7\\. Configuration of projections. National and European coordinate systems.\n8\\. Cartographic representation: scale, content and degree of generalization of a map\n9\\. Digital cartographic representation: vector chart and image chart\n10\\. Relationships between digital cartography, geographic information and remote sensing.\n\n### Mandatory Bibliography\n\nIliffe Jonathan; [Datums and map projections for remote sensing, GIS, and surveying](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000227756 \"Datums and map projections for remote sensing, GIS , and surveying (Opens in a new window)\"). ISBN: 9781870325288\nGaspar Joaquim Alves; [Charts and cartographic projections](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000274253 \"Charts and cartographic projections (Opens in a new window)\"). ISBN: 972-757-371-1\n\n### Complementary Bibliography\n\nMaling D.H.; [Coordinate systems and map projections](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000227146 \"Coordinate systems and map projections (Opens in a new window)\"). ISBN: 0-08-037234-1\nBugayevskiy Lev M.; [Map projections](http://catalogo.up.pt/F/-?func=find-b&local_base=FCUP&find_code=SYS&request=000227702 \"Map projections (Opens in a new window)\"). ISBN: 0-7484-0304-3\n\n### Teaching methods and learning activities\n\nClasses are based on Power Point presentations and demonstrations of the operation of coordinate transformations in some geographic information processing programs. Practical exercises will be launched with the PROJ.4 library, integrated into the QGIS program, and chart analysis. In type “O” classes, questions about these exercises will be clarified and support will be provided for carrying them out.\n\n### Software\n\nPROJ.4\nQGIS\nArcGIS\n\n### Type of evaluation\n\nEvaluation by final exam\n\n### Assessment Components\n\nExam: 100.00%\n\n**Total:**: 100.00%\n\n### Occupation Components\n\nFrequency of classes: 50.00 hours\n\nLaboratory work: 50.00 hours\n\n**Total:**: 100.00 hours\n\n### Get Frequency\n\nAttendance in 2/3 of classes.\n\n### Final classification calculation formula\n\n100% final exam\n\nMore information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479384" . . "Presential"@en . "TRUE" . . "Altimetry through satellite"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479353" . . "Presential"@en . "FALSE" . . "Applications in agriculture"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479383" . . "Presential"@en . "FALSE" . . "Applications in biology"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479357" . . "Presential"@en . "FALSE" . . "Applications in metheorology and climage changes"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479358" . . "Presential"@en . "FALSE" . . "Coastal applications"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479354" . . "Presential"@en . "FALSE" . . "Forest applications"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479355" . . "Presential"@en . "FALSE" . . "Remote sensing of ocean color and temperature"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479390" . . "Presential"@en . "FALSE" . . "Sar interferometry"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479356" . . "Presential"@en . "FALSE" . . "Ocean sar"@en . . "3.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479391" . . "Presential"@en . "FALSE" . . "Submeoscale oceanic and autonomous observing systems"@en . . "6.0" . "Information at: https://sigarra.up.pt/fcup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=479389" . . "Presential"@en . "FALSE" . . "Master in Remote Sensing"@en . . "https://sigarra.up.pt/fcup/en/cur_geral.cur_view?pv_ano_lectivo=2021&pv_curso_id=16781" . "120"^^ . "Presential"@en . "The FCUP Master’s degree in Remote Sensing offers advanced training in Earth observation techniques, analysis and use of geospatial data acquired by sensors deployed on space-borne or aerial platforms. This Programme aims to equip students with skills on the fundamentals of Remote Sensing (RS), the application potential of the various sensors, acquisition techniques, data processing and analysis, and familiarization with various RS and Geographical Information Systems (GIS) data processing tools. Students are expected to be able to use this knowledge in the study of the planet and in solving problems in various fields of application. \nTo this end, the Programme was organised with a common core of curricular units addressing fundamental subjects and a set of optional units that aim to teach specific skills in applications for the study of the ocean, agriculture and forests, coastal zones, climate change, etc. \n\nVídeo de Apresentação: https://youtu.be/_JlMlgmp81U\n\n### Programme structure\n\nThe FCUP MSc in Remote Sensing is a two-year programme organised as follows \n\n* a first year corresponding to a study programme of a set of curricular units (60 ECTS);\n* a second year corresponding to a scientific dissertation or a professional internship with a final report (54 ECTS) plus a supporting curricular unit of 6 ECTS on scientific writing.\n\n### Schedule and teaching language\n\nThe Master's degree runs on a concentrated schedule predominantly on Friday afternoons and on Saturday mornings, attracting students from all over the country, including working students. It is also intended to attract students from other countries, and it is anticipated that classes may be taught in English. \n\n### Employment Prospects\n\nAs this is the only MSc of this type in Portugal, it will respond to the needs of specialized staff in Remote Sensing. The Masters in Remote Sensing will have unique competences to join public institutions or private companies of a technological nature, including space agencies (ESA, EUMETSAT, etc.), with activity in in areas related to the exploitation of Remote Sensing or GIS data, location-based services, thematic mapping, and many others involving the use of georeferenced data. \nIt is also expected that the graduates of this MSc will promote the technological development of the country through the creation of companies of a technological nature and some of them continue their studies for a PhD. \n\n### Entry requirements\n\n1. Hold a higher academic degree in a study programme whose curricula provides students adequate scientific background for Remote Sensing: several branches of Engineering, Environmental Sciences, Informatics, Mathematics, Physics, Geophysics, Geology and related fields.\n2. Hold a foreign higher academic degree in one of the areas described in the previous paragraph.\n3. Hold an academic, scientific or professional curriculum recognized by the scientific committee of the MSc Programme as sufficient to prove capacity to carry out this study program.\n\n### Selection criteria\n\n1\\. Academic curriculum (60%)\n\n* Sub-criterion 1: Training area (20%) \n First degrees with study plans which include scientific background for Remote Sensing will be valued. Background in Mathematics (8%), Informatics / Programming (8%) and Physics (4%) will be considered.\n* Sub-criterion 2: First degree’s grade (40%) \n For candidates who do not yet hold a degree but can obtain it before the end of the registration period, as well as for those who satisfy the condition iii) of entry requirements, the first degree’s grade is replaced by the credit-weighted average of grades in the completed courses.\n\n2\\. Scientific curriculum and professional experience (40%)\n\n* Sub-criterion 1: Technical and/or scientific publications and communications (15%) \n The following aspects will be considered: peer-reviewed papers in scientific journals (10%); other scientific papers (5%);\n* Sub-criterion 2: Participation in research projects (5%)\n* Sub-criterion 3: Professional curriculum (20%) \n The duration and nature of professional activity in areas of relevance to the Master’s programme shall be considered, as follows: relevance of the professional activity (12%); duration of the professional activity (8%).\n\nIn case of equal ratings the following criteria will be adopted:\n\n* First’s degree mark\n* Number of years of professional activity on a relevant field.\n* Number of scientific papers\n* Participation in internships during the first degree, in Remote Sensing topics.\n \n\n### Contacts\n\nCourse Director: m.dr.diretor@fc.up.pt\n\nPostgraduate Section: pos.graduacao@fc.up.pt\n\nAcademic Degree: Master\n\nType of course/cycle of study: Masters Degree \n\nDuration: 4 Semesters\n\n### Study Plan\n\n* The study plan from 2018: https://sigarra.up.pt/fcup/en/cur_geral.cur_planos_estudos_view?pv_plano_id=22922&pv_ano_lectivo=2021&pv_tipo_cur_sigla=&pv_origem=CUR \n\n* All Courses of Study: https://sigarra.up.pt/fcup/en/cur_geral.cur_planos_estudos_list?pv_curso_id=16781&pv_ano_lectivo=2021&pv_tipo_cur_sigla=&pv_origem=CUR \n\n### Certificates\n\n* Master's degree in Remote Sensing (120 ECTS credits)\n* Specialization in Remote Sensing (60 ECTS credits)"@en . . . . "2"@en . "FALSE" . . . "Master"@en . "Thesis" . "1300.00" . "Euro"@en . "3750.00 (International) / 2250.00 (CPLP)" . "Recommended" . "As this is the only MSc of this type in Portugal, it will respond to the needs of specialized staff in Remote Sensing. The Masters in Remote Sensing will have unique competences to join public institutions or private companies of a technological nature, including space agencies (ESA, EUMETSAT, etc.), with activity in in areas related to the exploitation of Remote Sensing or GIS data, location-based services, thematic mapping, and many others involving the use of georeferenced data.\nIt is also expected that the graduates of this MSc will promote the technological development of the country through the creation of companies of a technological nature and some of them continue their studies for a PhD."@en . "1"^^ . "TRUE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . . . . "Portuguese"@en . . "Faculdade de Ciências"@en . .