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IngenieriaDelTerreno: MAIL301
Management of Marginal Lands and Carbon Sequestration estimation through Remote Sensing and GIS

Management of Marginal Lands and Carbon Sequestration estimation through Remote Sensing and GIS
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The course is targeted to students, researchers, or stakeholders who are interested in the analysis and management of Marginal Lands (MLs). This course is designed in 5 units in which it is expected to transfer the results of the European project “Identifying Marginal Lands in Europe and strengthening their contribution potentialities in a CO2 sequestration strategy (MAIL)”. Project under the European Union's Horizon 2020 Marie Skłodowska-Curie research and innovation program (Grant Agreement No. 823805). All videos are based on the procedures followed in the MAIL project for Europe, which means that some of the procedures described may not be exactly transferable to other parts of the world. The mechanics of the course are simple: follow the learning sequences proposed by the platform by watching the videos and asking the questions and activities that are proposed. In some cases, you will find optional readings that you can read to expand on the subject.
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Duration

5 weeks

About this course

The course is targeted to students, researchers, or stakeholders who are interested in the analysis and management of Marginal Lands (MLs). This course is designed in 5 units in which it is expected to transfer the results of the European project “Identifying Marginal Lands in Europe and strengthening their contribution potentialities in a CO2 sequestration strategy (MAIL)”. Project under the European Union's Horizon 2020 Marie Skłodowska-Curie research and innovation program (Grant Agreement No. 823805). All videos are based on the procedures followed in the MAIL project for Europe, which means that some of the procedures described may not be exactly transferable to other parts of the world. The mechanics of the course are simple: follow the learning sequences proposed by the platform by watching the videos and asking the questions and activities that are proposed. In some cases, you will find optional readings that you can read to expand on the subject.

What will I learn

In this MOOC you will learn: (1) the definition of MLs; (2) a methodological proposal for the identification and classification of MLs; (3) a short review of forest biomass estimation with optical sensors, RADAR, LiDAR; (4) a proposal of carbon calculation; and (5) an introduction to the MLs management application created in GEE in the framework of the project. During the course, we will give you some recommendations for the manipulation of large datasets and we will teach you how to work with the GEE application as a user. All this with the aim that you will be able to better understand the concept of MLs and will be able to analyze large MLs extensions in a fast way. Within the course, you will have questions for self-evaluation after each video, weekly practice, and at the end of the course an exam where you will be asked about the content of the whole course.

Prerequisites

No previous knowledge is required to enroll the course.

Units

  1. Week 1: Definition & descriptions of MLs.
  2. Week 2: Identification & classification of MLs.
  3. Week 3: Biomass estimation from remote sensing data.
  4. Week 4: Carbon storage and accounting.
  5. Week 5: GEE based platform for MLs management.
  6. Final exam

Evaluation

Only the final exam counts for passing the course, the practice and the questions placed after each video serve to reinforce what you have learned but do not count towards your final grade. You have 1 attempt to answer each multiple-choice question. The course will be considered passed if the final score is equal to or higher than 50% of the maximum possible grade. The practices are self-evaluated, although if you think we can give you some comments or if you have many doubts, you can send an email to the corresponding teacher in each section.

Teachers of the course

Charalampos Georgiadis

Charalampos Georgiadis is an Associate Professor at the School of Civil Engineering in the Aristotle University of Thessaloniki. 1997, Diploma Rural and Surveying Engineering (AUTH), 2000, M.sc. Protection, Preservation, and Restoration of Cultural Monuments (AUTH), 2005 PhD Department of Spatial Information Science and Engineering (University of Maine, USA).

His research interests include among others Photogrammetry, Remote Sensing, Cartography, GIS, UAV, Mobile Mapping Systems, 3D modelling, laser scanners, Image processing and analysis, Spatial data analysis. Scientific Responsible or member of research groups in 47 Research projects Funded by National, European or USA Organizations. He has 59 publications in journals and scientific conferences and he is scientific reviewer in 12 Journals.

AUTH

Charalampos Georgiadis
Natalia Verde
Maria Tassopoulou

HOMEOTECH

Lampros Papalampros

IABG

Bettina Felten
Samuel Nyarko

CBK PAN

Michał Krupiński

Cesefor

Fernando Bezares

UPV

Jesús Torralba Pérez
Juan Pedro Carbonell Rivera

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Inscribirse

MOOC es el acrónimo en inglés de Massive Online Open Course (que puede traducirse como Curso masivo abierto online).

Las siglas MOOC se utilizan para referirse a una iniciativa que comenzó en 2011 con un curso de Introducción a la Inteligencia artificial de la Universidad de Stanford en el que se inscribieron 160.000 estudiantes de 190 países, y que se ha convertido ya en un movimiento global al que se han incorporado las mejores universidades del mundo con la creación de diversas plataformas MOOC y miles de cursos que comparten un objetivo: proporcionar acceso gratuito a una formación superior de calidad a cualquiera que tenga una conexión a internet.

Los MOOCs están basados en la integración de tecnologías que existen desde hace tiempo en Internet: el vídeo en red, la evaluación automática a distancia y los foros de preguntas y respuestas en la web. Pero es ahora cuando los usuarios se han acostumbrado a usar el vídeo en red y las redes sociales en su día a día en Internet, lo que facilita que se creen comunidades de alumnos situados en cualquier parte del mundo que comparten conocimientos y experiencias y se ayudan en el proceso de aprendizaje, dándole a la formación online un nuevo enfoque colaborativo. Esto, unido a la disponibilidad de acceso a los cursos MOOC en cualquier momento y desde cualquier lugar en donde se tenga acceso a Internet, ha permitido crear una nueva comunidad global de estudiantes.

Los MOOCs de UPV[X] están diseñados para ayudarte a aprender trabajando a tu ritmo de forma independiente y proporcionarte el apoyo de la comunidad de aprendizaje si te hace falta.

Para ello los MOOCs están estructurados en módulos que suelen corresponder a una semana de trabajo (aunque no siempre es así). Los módulos se estructuran en lecciones con un vídeo, que dura normalmente entre 3 y 10 minutos, y una pregunta de refuerzo al final para ayudarte a fijar su contenido. Las lecciones están orientadas a tratar un concepto (o un número reducido de ellos) de forma que sean lo más atómicas que sea posible.

Los cursos MOOC de UPV[X] pueden tener distintos esquemas de evaluación, pero lo habitual es que al terminar cada módulo haya un examen (normalmente tipo test) que te permitirá comprobar tu evolución y fijar los conocimientos, y que cuenta en cierto porcentaje para la evaluación final. Con ello tendrás una realimentación frecuente de tu progreso que te permitirá ir mejorar tu proceso de aprendizaje.

Al acabar el MOOC habrá a un examen final para evaluar si has alcanzado los objetivos de aprendizaje que contará en un porcentaje mayor para la evaluación final.

En los MOOC también hay un foro de debate moderado por el equipo del curso donde los alumnos pueden consultar sus dudas sobre el contenido del curso y comentar aquellas cosas que les parezcan interesantes. El acceso a una comunidad online de internautas con tus mismos intereses y que están aprendiendo a la vez enriquece la experiencia del curso.

Esperamos sinceramente que disfrutes de nuestros MOOCs y aprendas con nosotros