Development and implementation of a new Masters Programme in ...

The Photogrammetric Journal of Finland, Vol. 25, No. 1, 2016 Doi:10.17690/016251.1

Accepted 20.12.2016

DEVELOPMENT AND IMPLEMENTATION OF A NEW MASTERS PROGRAMME IN GEOINFORMATICS AT AALTO UNIVERSITY, FINLAND Petri Rönnholm1, Henrik Haggrén1 1

Aalto University, Department of Built Environment, Finland [email protected], [email protected]

ABSTRACT A major renovation in teaching geoinformatics has been made at Aalto University, Finland. In this article, the development process and courses in the new Master in Geoinformatics are described from the perspective of photogrammetry and laser scanning. However, the new curriculum includes teaching in photogrammetry, laser scanning, remote sensing, geodesy, cartography, and geoinformation techniques, covering all aspects of the surveying sciences. The teaching language in all courses is English, allowing international students to participate. In addition, the new curriculum is part of the Nordic Master in Cold Climate Engineering. The students participating in this masters get a double degree. Aalto University grants the degree of Master of Science (Technology), and the Technical University of Denmark grants the degree of Master of Science in Earth and Space Physics and Engineering. 1. INTRODUCTION Aalto University in Finland was founded in 2010, merging three previously independent universities: the Helsinki University of Technology, the Helsinki School of Economics, and the University of Art and Design Helsinki. Aalto University is divided into six schools: School of Arts, Design and Architecture, School of Chemical Technology, School of Business, School of Electrical Engineering, School of Engineering, and School of Science. Our discipline is included in the School of Engineering. According to the strategy of 2012, the national mission of Aalto University is to support Finland’s success and contribute to Finnish society, its internationalization and competitiveness by educating responsible, broad-minded experts to act as society’s visionaries and change agents. As far as this resulted in the design of the new degree programs within the applied and polytechnic sciences, the aim was to strengthen the fundamental knowledge and to limit specific and practice-oriented professional skills. The ultimate goal has been to renew technologies by scientific research and to train broad-minded experts with a comprehensive understanding of complex subjects without resistance from earlier best practices (Aalto University, 2012). Aalto University has been active in renovating old study programmes and structures. As a result, both the Bachelor’s and the Master’s programmes in the School of Engineering have recently been reorganised. The current development has significantly affected the teaching of geoinformatics, consisting of photogrammetry, laser scanning, remote sensing, geodesy, cartography, and geoinformation techniques (the term geomatics was replaced with geoinformatics in the new system). The previous study programme was established in 2005, 1

when the curriculum of Geomatics was started (Junnilainen et al., 2006). That study programme included both the Bachelor’s (180 ECTS) and the Master’s (120 ECTS) levels and was already fulfilling the requirements of the Bologna agreement (European Ministers of Education, 1999). The 3-year Bachelor’s programme continued fluently to the 2-year Master’s programme (Figure 1). The main teaching language was Finnish. However, the presence of international exchange students was taken into account in such a way that, in practice, all courses could be passed in English.

Figure 1. The curriculum of Geomatics in 2005. The red line indicates the study path of geoinformatics during the five years of geomatics education. During the Bachelor’s programme, the geoinformatics-related course contents counted for about 80 credits (Haggrén et al., 2006). The renovation started with the Bachelor’s programmes. The new programmes started in 2013 and the old ones were ended. As a result, Geomatics lost its own Bachelor’s programme. Instead we currently belong in the Bachelor’s programme of Energy and Environmental Technology. The annual intake is approximately 90 students. From this Bachelor’s programme, students can continue to the Master’s programmes of Energy Technology, Geoinformatics, Geoengineering, or Water and Environmental Engineering. In other words, these Master’s programmes compete with each other in order to get students in their programmes. The Master’s programme of Geoinformatics includes teaching in photogrammetry, laser scanning, geodesy, remote sensing, cartography, and geoinformation techniques covering all aspects of surveying sciences. Combining many disciplines in one Bachelor’s programme makes for limited space for teaching Geoinformatics. Only one of our courses is mandatory for all students in this Bachelor’s programme. In addition, there are two elective courses available. The courses are listed in Table 1. Even if our own courses are few, other courses also support our discipline. For example, in the course Computer-Aided Tools in Engineering, it is possible to learn the basic use of ArcGIS and CAD software. There is also an elective minor in Computation and Modelling in Engineering, which includes relevant courses in geoinformatics. Consequently, the amount of course contents related to geoinformatics has dropped from 80 credits in the previous Bachelor’s programme to about 15-20 credits. 2

Table 1. Courses in Geoinformatics at the Bachelor’s level. Course

ECTS

Teaching year

Geoinformation in Environmental Modelling

5

mandatory

2nd year

Surveying and Observing the Environment

5

elective

2nd year

Management of Environmental Data and Information

5

elective

3rd year

The new two-year Master’s programme in Geoinformatics started in September 2016. The students have two options for acceptance in this Master’s programme. The basic track comes from the Bachelor’s programme of Energy and Environmental Technologies at Aalto University. The other track is available for students coming from outside Aalto University. Once a year, they can apply to the Master’s programme of Geoinformatics if they have a qualifying degree from a university or a university of applied sciences. The maximum intake of non-Aalto University students is 20. In September 2016, 24 students started studying in the new Master’s programme in Geoinformatics. Six students had graduated from the Bachelor’s programme of Aalto University and the rest were accepted through the second track. In addition, there were some students who were continuing their studies in the previous study programme in Geomatics. They will be automatically transferred to the new Master’s programme in autumn 2017 if they have not graduated. The first students from the new programme will graduate in spring 2018. Since autumn 2017, Aalto University will charge a tuition fee from students coming from countries outside the EU and EEA. This will also apply to the Master’s programme in Geoinformatics. The tuition fee will be reviewed annually, and in the academic year 2017-2018 it will be 15,000 € per year. However, it is possible to apply for a scholarship from Aalto University Scholarship programme or from other scholarship programmes. More information about these alternatives can be read from http://www.aalto.fi/en/studies/fees_and_scholarships/. Scholarships are granted on the basis of academic merits. The aim of this paper is to describe the development process and the implementation of the new Master’s programme in Geoinformatics from the perspective of photogrammetry and laser scanning. Also, the Nordic Master programme in Cold Climate Engineering (http://www.coldclimate-master.org) will be highlighted, because our courses are available for students who select its Space track: Mapping and navigation. This programme leads to a double degree given by two Nordic universities. 2. DEVELOPING A NEW MASTER’S PROGRAMME The programme development started 1 1/2 years before the starting date of the new Master’s programme. During the development phase, several meetings were arranged. In practice, all professors (4) and senior university lecturers (2) were participating in the meetings. In some meetings, the student delegates were also invited to give their insight to the development process. In these meetings, the curriculum was analysed from many perspectives. For example, Figure 2 illustrates an attempt to compress the core contents, similarities and relationships between photogrammetry, laser scanning and remote sensing. The purpose of this work was to envision

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the most important topics, as well as to later find similarities and connections with geodesy, cartography and geoinformation techniques.

Figure 2. A chart of the compressed core content focusing on photogrammetry and remote sensing. After initial discussions, it was decided to make all core contents visible to all professors and senior university lecturers. The idea behind this was to find and extract those contents that were somehow in common in all fields. Also, this process significantly helped to identify which contents each student should learn and thus should be placed in mandatory courses. Naturally, also those contents that could be saved for elective courses become visible. In addition, the creation of courses that covered complete processes throughout several fields of geoinformatics become possible. All core contents of the curriculum were organized in a matrix with post-it stickers. The rows of the matrix represented the level of learning. Here we applied Bloom’s taxonomy (Krathwohl, 2002). The columns represented the following categories: data acquisition, modelling, analysis, applications, and visualization. At this point, some core contents could not yet be categorized accurately to one level of learning, which caused a bit fuzzy appearance of the matrix. Along the process, we noticed that some core contents appeared more than once written by different persons. In such cases, they were combined into larger groups. This phase required several iterations. The core contents matrix is illustrated in Figure 3.

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Figure 3. The core contents analysis of the curriculum with post-it stickers. The number of new courses was decided on taking into account the teaching resources, the general curriculum structure, and suggestions of personnel. Initial names of courses were given and the division into mandatory and elective courses was suggested. At this point, it was decided which courses would benefit combining more than one field of geoinformatics into single courses. Because the initial names of courses were known, it was possible to create a timetable for teaching. Figure 4 presents how courses were distributed to the teaching periods. This kind of planning can ensure that not too many courses are in one period. At Aalto University, there are two periods in the autumn semester and three periods in the spring semester. Also, some links were drawn between courses to identify the relationships and possible prerequisites of courses. The core contents were distributed evenly to new courses. We took into account continuity and connections to other courses as well as the timing of courses. At this phase, we tried to limit the amount of core contents attached to a single course in order to prevent overloaded courses. According to the core contents, a short description was written from each course illustrating the course contents and learning aims. Because a similar renovation process was ongoing throughout Aalto University, there were organized meetings, guidance sessions and workshops in which individual professors or senior university lecturers participated. These sessions gave new insights and greatly assisted the development process. 5

Figure 4. The planning of the course order and relationships between courses. After the initial courses and their descriptions were completed, a meeting with stakeholders was arranged. In this meeting, delegates of companies, municipalities and research centres were present, giving valuable comments and sharing their perspective about what should be taught in our curriculum in order to serve their needs. The meeting was very interactive, and participants contributed in small groups to all fields included in the Master in Geoinformatics. As a result, we got feedback on which bases the contents of courses were fine-tuned. Overall, the participants were satisfied with our initial suggestion of courses and study structure. Figure 5 is taken from the meeting. Figure 6 illustrates one of the results of one group's work.

Figure 5. Meeting with stakeholders.

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Figure 6. Stakeholders grouped, analysed and commented on the planned courses and their contents. Finally, the suggestions for all course contents were ready. For each course, a responsible teacher was nominated. Responsible teachers in co-operation with other lecturers of the course finalized course names and course descriptions. After the official acceptance of the curriculum and courses, the actual implementation phase began, which is still ongoing. During the writing of this paper, only six mandatory courses of the curriculum were already given. 3. MASTER IN GEOINFORMATICS The new programme, Master in Geoinformatics (120 ECTS), was launched in autumn 2016. The main structure contains 30 ECTS of mandatory major studies, 30 ECTS of elective major studies, 30 ECTS of freely elective studies (can also be a minor), and Master’s Thesis (30 ECTS) (Figure 7). All this is designed in such a way that the degree can be achieved in two years. All courses are given in English, which allows international students to participate. The courses that are mandatory for all students of geoinformatics are given in the first autumn semester. These courses aim to ensure an even and sufficient background to all students to understand the complete view and basics of geoinformatics. In addition, these courses teach in practice many skills that are expected from higher education. These skills are not only related to substance, but also to critical thinking, co-operation, group work, programming, and scientific writing, just to name a few. The courses for the first semester are presented in Table 2.

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Major studies, mandatory for all students (30 ECTS)

Major studies, elective courses (30 ECTS)

Elective studies (can be a minor) (30 ECTS)

Master’s Thesis (30 ECTS)

Figure 7. The structure of Master in Geoinformatics. Table 2. Mandatory courses of Master in Geoinformatics. All courses are given in the 1st semester (autumn). Course

Period

GIS-E1010 Geodesy and Positioning (5 ECTS)

1 (autumn)

GIS-E1020 From Measurements to Maps (5 ECTS)

1 (autumn)

GIS-E1030 Introduction to Spatial Methods (5 ECTS)

1 (autumn)

GIS-E1040 Photogrammetry, Laser Scanning and Remote Sensing (5 ECTS)

2 (autumn)

GIS-E1050 Visualization of Geographic Information (5 ECTS)

2 (autumn)

GIS-E1060 Spatial Analytics (5 ECTS)

2 (autumn)

From a set of elective courses, the students select enough courses to get 30 ECTS. Elective courses define how students emphasize their studies. However, these courses can also be included in freely elective courses. Therefore, it is actually possible to select all courses available. The list of elective courses is presented in Table 3. At Aalto University, an academic advising system is established for both the Bachelor’s and Master’s levels. This means that each student has a staff member as an academic advisor. Academic advisors meet personally with each student twice a year. The advantage of the academic advising system is that each student has someone who follows their progress and informs them about important steps in the studies. The system makes it easy for students to approach staff and get help when needed.

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Table 3. Elective courses of Master in Geoinformatics. Course

Year

Period

GIS-E3010 Least-Squares Methods in Geoscience (5 ECTS)

1st

3 (spring)

GIS-E3020 Digital Image Processing and Feature Extraction (5 ECTS)

1st

3 (spring)

GIS-E4010 Topographic Information Management (5 ECTS)

1st

3 (spring)

GIS-E3030 Advanced Laser Scanning (5 ECTS)

1st

4 (spring)

GIS-E3040 Advanced Photogrammetry (5 ECTS)

1st

4 (spring)

GIS-E5020 GNSS Technologies (5 ECTS)

1st

4 (spring)

GIS-E3050 Advanced Remote Sensing (5 ECTS)

1st

5 (spring)

GIS-E5010 Earth System Geodesy (5 ECTS)

1st

5 (spring)

GIS-E4020 Advanced Spatial Analytics (5 ECTS)

1st

5 (spring)

GIS-E6010 Project Course (10 ECTS)

2nd

1-2 (autumn)

4. HIGHLIGHTS OF THE NEW MASTER IN GEOINFORMATICS This chapter gives some highlights about the new curriculum. The focus is on those parts that have already been implemented and given. Chapter 4.1 describes the orientation event in the first week of the academic year 2016-2017 for new students. Chapters 4.2 through 4.4 describe some course content implemented in the first autumn semester from the perspective of photogrammetry and laser scanning. 4.1

Orientation event

The new master’s curricula at Aalto University are ambitious in promoting an academic culture of creativity and entrepreneurship as well as preparing students during the two years for entering professional life (Aalto University, 2012). This challenges teachers and researchers to create a learning-centred culture and readdress their teaching methods, to improve the mentoring of students for their commitment, and to initiate and open new interaction with stakeholders. Therefore a special orientation event was arranged for new students where they could meet with both the academic staff and the potential employers. This was also the first opportunity for the stakeholders to start head-hunting for new and talented employees or for the students to reinforce their own entrepreneurship and vision of possible start-ups. In addition, the student association in geoinformatics, Poligoni (http://poligoni.ayy.fi/?file=IN%20ENGLISH), was highly visible and participated in organizing the event. The orientation event lasted two days, during which the students got familiar with each other and with the teaching and research staff. One aim of the orientation event was to guide the students fluently to their studies and direct their interest in the fields within geoinformatics. The students created groups in which they were asked to reflect upon following questions: 9

Describe your vision of your professional profile through 2025. What kinds of tasks do you expect will become relevant or important in the future? What about your own interests? What are your intentions about specialization in a profession? What are your current professional and interdisciplinary networks? Synergy options? What are your expectations of this Master’s Programme? The group assignment was given on the first day of the orientation event, and the results were discussed the following day. Figure 8 highlights one result of the group work.

Figure 8. The result of a student group work. The afternoon of the first day was dedicated to companies and research centres. We got many presentations from the delegates, and the students got an impressive overview of the current state of labour markets and future prospects. After the presentations, students were able to discuss with the presenters during a longer coffee break. As the final happening of the day, there were guided tours to get familiar with our facilities and research staff. Both the students and delegates gave much positive feedback when they were able to see our devices and staff in action. 4.2

From Measurements to Maps

The course From Measurements to Maps gives a theoretical and practical overview of mapping processes, including the establishment of the coordinate frame, data acquisition, data processing, and map design and compilation. In the process, geodetic, photogrammetric, remote sensing, and cartographic methods are applied.

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This course introduces both photogrammetry and laser scanning from the aerial perspective. The course included six assignments. The photogrammetric assignment was about mapping and map updating processes with aerial images. The assignment started with converting building vectors, downloaded from the File Service of Open Data provided by the National Land Survey of Finland (https://tiedostopalvelu.maanmittauslaitos.fi/tp/kartta?lang=en), from the GML format to the Microstation design file format with FME WorkBench software (http://www.safe.com/). The purpose was to later superimpose these vectors onto aerial images for stereoscopic examination. The next phase was the selection of the area of interest from the larger area (see Figure 9). Because data was complete (i.e. it included all building vectors), the students were asked to remove a couple of buildings. Later, the students were asked to map these building vectors photogrammetrically.

Figure 9. The selection of building vectors from the area of interest. The next phase was done with Z/I Imagestation, a digital stereo workstation. The process included the main steps of the photogrammetric mapping process. The known interior orientation was set to the aerial camera (DMC, type I). Tie points between images were measured for a block of three aerial images. Also, known ground control and checkpoints were measured from images. Aerial triangulation was performed, solving the exterior orientations of images and the 3D coordinates of tie points. Stereo models were created, as well as epipolar images needed for stereoscopic measurements. The building vectors were superimposed in the epipolar images for a stereoscopic examination. The non-measured (deleted) building vectors were easy to detect by visual inspection. These buildings were interactively mapped from stereo images (Figure 10). The vectors were measured to the footing of buildings, as required for the Finnish National Database.

Figure 10. Photogrammetric mapping of building vectors.

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All building vectors from the area of interest were converted from the Microstation design file format to the ESRI shapefile format with FME WorkBench software. This shapefile was used later in a cartographic assignment in which all data (including the data that students had actually measured by themselves) were combined as a final map. The laser scanning assignment was dedicated to the processing of airborne laser scanning data. In this exercise, two different data sets were given. The first one included four crossing flying strips of unprocessed laser scanning data. The second data set, covering the campus area, was downloaded from the File Service of Open Data provided by the National Land Survey of Finland. The aim of this exercise was to learn processing and classification of airborne laser scanning data. As the output, the students created contour lines of the area of interest. This data was also included in the final map in ArcGIS. For this assignment, software by TerraSolid Oy was applied (Microstation environment). Processing steps required the use of TerraScan, TerraMatch and TerraModel. The students learned basic data handling operations and visualizations of laser point clouds. The first data set also contained trajectory data that was assigned to raw laser scans. In order to make a strip adjustment, the ground points were classified. Noise points and low points were removed, and the surface points were smoothed. In this phase, the students learned how to create macros for batch processing. A strip adjustment removed the misalignment between laser scanning strips. After the strip adjustment, all laser points were classified by class as ground, low vegetation, medium vegetation, and high vegetation. In this area, there were no buildings. From the ground class, several terrain model representations were created, such as a triangulated irregular network (TIN), a grid model, and contour lines. The skills that were learned with the first data set were applied to the second data set. In that case, data was already pre-processed and classified (Figure 11). Therefore, only the creation of contour lines was required. These contour lines were converted from the Microstation design files to the ESRI shapefile format with FME WorkBench software. In ArcGIS, the contour lines were smoothed before adding to the final map.

Figure 11. Pre-classified ground points and the selection of the area of interest. 12

4.3

Introduction to Spatial Methods

The course Introduction to Spatial Methods introduces various mathematical, statistical and computational methods in their spatial forms. The contents of the course cover processing, analysis and quality issues of spatial data including measures of autocorrelation, spatial statistics, convolution, spatial interpolation, data classification, clustering methods, geometric problem solving, spatial algorithms, as well as quality concepts and measures. The course included three programming assignments and three hands-on sessions. The first programming assignment aimed to practice interpolation methods. The creation of orthophotos was selected as the framework. By means of interpolation, this case is almost perfect because, firstly, the height values of the pixels of the orthophoto need to be interpolated from an irregular laser point cloud. Secondly, the colour values of the pixels of the orthophoto are interpolated from the regular grid of the aerial image. Therefore, both main interpolation cases are needed. The input data of the assignment is illustrated in Figure 12.

Figure 12. Aerial image and a laser point cloud as an input for the orthophoto creation. This assignment included programming in Matlab. To make the task possible for the student who didn't have much programming experience, a template was given in which the basic functionalities were pre-programmed and only four sub-functions needed to be implemented: inverse distance weighting interpolation, collinearity equations, transformation from camera coordinates to image coordinates, and bilinear interpolation. The second programming assignment did not relate to photogrammetry or laser scanning, but the third programming assignment was about implementation of k-nn and kmeans classification algorithms with R programming language (https://www.r-project.org/about.html). These two methods are examples of supervised and unsupervised classification, respectively. Even if the input data of this assignment was related to geoinformation techniques, these methods can be applied also for the classification of remote sensing data, laser scanning point clouds or photogrammetrically derived 3D data. The assignment illustrated how to establish feature vectors, and how k-nn and kmeans methods function and differ from each other. 4.4

Photogrammetry, Laser Scanning and Remote Sensing

The course Photogrammetry, Laser Scanning and Remote Sensing gives theoretical background on photogrammetric, laser scanning and remote sensing measurements. Measuring processes include calibration, mathematical sensor models, data pre-processing, data analysis, data 13

integration, and visualization. In addition, the course highlights implementations of modern data acquisition instruments. Both photogrammetry and laser scanning in this course are illustrated mainly from the terrestrial perspective. The course contains five mandatory assignments and one voluntary assignment. The voluntary assignment was a practical data acquisition with a FARO Focus3D 120S terrestrial laser scanner. This assignment was not mandatory because the students from the Bachelor’s programme at Aalto University have already had a similar assignment. In addition, some of the non-Aalto University students might also have previous experiences of collecting data with terrestrial laser scanners. The photogrammetric assignment included close-range tasks. A camera was calibrated with iWitness software. The calibration targets are illustrated in Figure 13. Camera calibration parameters were applied to two modelling tasks. Firstly, a wooden box was modelled with iWitness (Figure 14), and then the deformation of a test object (Figure 15) was accurately detected. All the measurements were done in iWitness except the deformation detection which was performed in Matlab. Again, a template was given and the students needed to complete the code in order to get correct results.

Figure 13. Calibration targets for iWitness calibration process.

Figure 14. Camera positions and the virtual model of the wooden box that was measured photogrammetrically. 14

Figure 15. By rotating two screws, it is possible to deform the front surface of this test object. The laser scanning assignment gives an overview of processing terrestrial laser scanning data. Input data included two terrestrial laser scans from different scanning locations. As the device was FARO Focus3D 120S, Faro Scene software was utilized. The assignment started with creating the project, importing data sets, and pre-processing of the data. Data registration was done with both the Iterative Closest Point Algorithm and by utilizing reference spheres (see Figure 16). Also, the use of 3D Views and clipping boxes were practiced (Figure 17). The floor was selected and exported in PTS format.

Figure 16. Detected reference spheres for the registration of laser scans.

Figure 17. Practicing the use of a clipping box. The flatness of the floor was examined in CloudCompare, which is freeware for processing laser data. A plane was fitted to the floor. Then the point cloud was decimated and a mesh model of it was created. This mesh model was compared with the average plane of data, which revealed where the floor was flat and where differences existed. 15

5. NORDIC MASTER IN COLD CLIMATE ENGINEERING The Nordic Master in Cold Climate Engineering is a new programme funded by the Nordic Council of Ministers. Currently, the partner universities are Aalto University, Technical University of Denmark (DTU), and Norwegian University of Science and Technology. This international Master’s programme includes three main study tracks: Land Track, focusing on Arctic Geoengineering; Sea Track, including Arctic Ships and Offshore Structures; and Space Track, teaching Mapping and Observing the Arctic. From our perspective, the Space Track is the most interesting, especially the Mapping and Navigation part of it. In this track, it is possible to do a double degree programme, in which students get two degree titles: Aalto University grants the degree of Master of Science (Technology) and DTU grants the title of Master of Science in Earth and Space Physics and Engineering. The first students were accepted in the Nordic Master in Cold Climate Engineering in September 2016. The specialization of Mapping and Navigation can be started either at Aalto University or at DTU. Both alternatives include one-year studies at both universities. Table 4 lists available courses and study semesters when the programme is started at Aalto University. Table 5 presents the case when studies are started at DTU. Table 4. Courses in the Nordic Master in Cold Climate Engineering when studying is started at Aalto University. Aalto University 1st year Semester 1 Semester 2 Least-squares methods in Geodesy and Geoscience (5 ECTS) Positioning (5 ECTS) Earth system geodesy (5 Introduction to Spatial Methods (5 ECTS)

ECTS) Advanced laser scanning (5 ECTS)

From Measurements to Maps (5 ECTS)

Plus elective courses to gain a total of 30 ECTS for the semester:

Photogrammetry, Digital image processing and Laser Scanning and feature extraction (5 ECTS) Remote Sensing (5 Advanced photogrammetry (5 ECTS) ECTS) Visualization of Advanced remote sensing (5 Geographic ECTS) Information (5 ECTS) Topographic Information Management (5 ECTS) Spatial Analytics (5 ECTS) Advanced Spatial Analytics (5 ECTS) GNSS Technologies (5 ECTS) 16

DTU 2nd year Semester 1 Measurement technologies in Earth and Space Physics (10 ECTS) Synthesis in Earth and Space Physics (10 ECTS) Technology, Economics, Management and Organization (10 ECTS)

Semester 2 Master's Thesis (30 ECTS)

Table 5. Courses in the Nordic Master in Cold Climate Engineering when studying is started at DTU. DTU 1 year st

Semester 1 Measurement technologies in Earth and Space Physics (10 ECTS) Data analysis and modelling in Geoscience and Astrophysics (5 ECTS) Satellite-based Positioning (5 ECTS) Physical Geodesy (5 ECTS)

Semester 2 Geographic Information Systems (5 ECTS) Mapping from Aerial and Satellite Images (5 ECTS) Earth System Science (5 ECTS) The cryosphere (5 ECTS) Technology, economics, management and organisation (10 ECTS)

Data processing methods in Earth and Space Physics (5 ECTS)

Aalto University 2nd year Semester 1 Semester 2 Project Course (10 ECTS) Master's Thesis (30 Plus elective courses to gain ECTS) a total of 30 ECTS for the semester, e.g.: Microwave Remote Sensing (10 ECTS) Geodesy and Positioning (5 ECTS) Introduction to Spatial Methods (5 ECTS) From measurements to maps (5 ECTS) Photogrammetry, laser scanning and remote sensing (5 ECTS) Visualization of Geographic Information (5 ECTS) Spatial Analytics (5 ECTS)

6. CONCLUSIONS The design principles of the new Master’s curricula at Aalto University are highly ambitious. Using less resources and in a shorter time, one should provide students with more fundamental and core-concentrated learning content, enabling them to become responsible and broad-minded experts, who will act as society’s visionaries and change agents. This has resulted in the new twoyear Master’s programme in Geoinformatics. The three-year Bachelor’s programmes at Aalto University are primarily devoted to fundamental studies and less to studies in a specific field of science. The course contents are intentionally limited, compared to the previous five years of studies, e.g., in surveying sciences. We described the development process of the programme in detail. The first programme started in September 2016. The majority of the new students were selected in the second track coming from outside our own Bachelor’s Programme in Energy and Environmental Technologies. This means that the background and basic knowledge of the students is rather diverse. On the other hand, the motivation to study geoinformatics seems to be high, which may somehow compensate for the prerequisites in other competences. The careful planning of the Master’s programme in Geoinformatics ensured that teaching of photogrammetry and laser scanning is now coherent throughout the Master’s programme and 17

includes all core aspects. Experiences in autumn 2016 were encouraging, and the new courses seem to function as expected. The orientation event was successful. The fact that the students have diverse backgrounds made additional workload for the teaching staff. But already in the second period, the skills of the students were proven to be more even than in the first period. We are confident that the remaining courses in the curriculum will be as successful as the courses in the autumn semester. We have excellent opportunities to combine recent research with teaching, especially in advanced courses, because of the high-level research of photogrammetry and laser scanning at Aalto University (e.g., https://foto.aalto.fi/memo/) and also at other research centres in Finland, such as the Finnish Geospatial Research Institute (http://www.fgi.fi/fgi/). The drawback of our new curriculum is that there is relatively short time available to learn photogrammetry and laser scanning. This is demanding for both the students and the teaching staff. Limited time resources have also reduced the number of assignments. However, we feel that current exercises in the autumn semester have greatly supported learning. Most of them are new ones focusing on the core skills. These skills can be later utilized in the advanced courses and in the working life. One definitely positive side of the development is that the connections with other fields of geoinformatics are now more obvious than before and there is less unnecessary overlap between courses. Currently, our main concern is to get more resources and especially new tenure positions in order to ensure the long-term continuity of the curriculum. At Aalto University, the tenured positions are not necessarily directly defined by old chairs or by former study programmes, which makes the process thrilling. Because applicants are searched for from the larger field, there is no guarantee that the profile of selected candidate includes, e.g., photogrammetry or laser scanning at all. We believe that our new Master in Geoinformatics is an internationally attractive programme enabling students to become skilled professionals – especially in photogrammetry and laser scanning. It is very possible that our students will become societies’ visionaries and change agents, as Aalto University demands in its strategy. We are proud to welcome all talented students to apply to our Master in Geoinformatics as well as to the Nordic Master in Cold Climate Engineering. 7. ACKNOWLEDGEMENTS Special acknowledgements belong to other professors and senior university lecturers who significantly contributed to the development and implementation of the new Master’s programme: Kirsi Virrantaus, Martin Vermeer, Miina Rautiainen, and Paula Ahonen-Rainio. This article was supported by the Academy of Finland, the Centre of Excellence in Laser Scanning Research, CoE-LaSR (No. 272195) and Strategic Research Council project COMBAT (No. 293389). 8. REFERENCES European Ministers of Education, 1999. The Bologna Declaration on Higher Education. Joint Declaration of the European Ministers of Education Convened in Bologna on 19 June 1999. http://www.magna-charta.org/resources/files/text-of-the-bologna-declaration (accessed 9.11.2016) 18

Junnilainen, H., Haggrén, H., Koistinen, K., Rönnholm, P., 2006. Initiative for International Master Program in Photogrammetry at Helsinki University of Technology, XXIV International FIG Congress, 8-13 October 2006, Münich, Germany. 15 pages. https://www.fig.net/resources/proceedings/fig_proceedings/fig2006/papers/ts34/ts34_01_junnilai nen_etal_0732.pdf (accessed 9.11.2016) Haggrén, H., Junnilainen, H., Koistinen, K., Rönnholm, P., 2006. New academic curriculum in geomatics – Case: Finland, Fifth European GIS Education Seminar September 7-10, 2006, Cracow-Pieniny, Poland http://www.eugises.eu/proceedings2006/index.html (accessed 11.12.2016) Krathwohl, D. R., 2002. A revision of Bloom's taxonomy: An overview. Theory Into Practice. Routledge. 41 (4): 212–218. http://www.tandfonline.com/doi/abs/10.1207/s15430421tip4104_2 (accessed 12.12.2016) Aalto University, 2012. Strategic Development of Aalto University. Edition Jan 2012. http://www.aalto.fi/en/midcom-serveattachmentguid1e4a0910ffec6a4a09111e4a4de336f0d02edfeedfe/aalto-strategy.pdf (accessed 12.12.2016)

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