. "Remote Sensing"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "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" . . "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 . . . . . . . . . . . . . . . . . . . . .