DISA

Centre for Data Intensive Sciences and Applications

Workshop (May 4th, 2023) on Self-supervised deep learning in EO-based forest inventory – ESA RepreSent project and Forest Thematic Exploitation Platform (F-TEP)

2023-04-27

Deep learning (DL) and computer vision are rapidly gaining popularity in forest inventory. However, the scarcity of available reference data limits the effective use of DL tools. Self-supervised learning (SSL) and weakly-supervised learning aim to solve this bottleneck by enabling better utilization of available EO data to effectively train DL models.

We invite you to attend an online workshop, where we will present and discuss several deep learning models suitable for forest mapping with satellite remote sensing data, that were created within the ESA funded RepreSent project (2022-2023) on Representation learning for Copernicus Sentinel data. The developed models enable forest mapping and monitoring by significantly reducing the amount of reference data typically required for deep learning model training. A selected set of tools has also been implemented on Forestry TEP to facilitate the quick adoption of developed methodologies in the downstream sector and for potential use as benchmark methodologies.

The workshop targets AI4EO researchers who are interested in the forestry sector, as well as foresters who wish to explore the broader applications of DL and SSL in their academic research or operational forest management.

Please inform about your participation using this link https://forms.office.com/e/GFKbeZ29jQ

Participation to the workshop is free.

The online workshop will be organized on MS Teams, and further details will be sent to registered participants.

Preliminary agenda – the online workshop starts at 10 am EEST (Finland time zone), May 4th 2023

10:00 am (EEST) Welcome and ESA RepreSent project introduction Matthieu Molinier, Oleg Antropov, VTT, Corneliu Octavian Dumitru, DLR
10:05 Forest inventory using EO data Jukka Miettinen, Tuomas Häme, VTT
10:15 Self-supervised and weakly-supervised Learning in Earth Observation ESA Represent consortium
10:25

10min + 5min Q&A

MoCo & MAML models in forest mapping using Copernicus Sentinel-2 and Sentinel-1 data Lloyd Hughes, Marc Russwurm,

Devis Tuia, EPFL

10:40

10min +5 min Q&A

UNet+ models with multi-source EO data Oleg Antropov, VTT
10:55

10 min +5 min Q&A

DCVA approaches for forest change detection using Sentinel-2 images Ridvan Kuzu, DLR
11:10 Break (5 mn)
11:15

20 min +5 min Q&A

F-TEP introduction: Status and tools overview Jukka Miettinen, Renne Tergujeff, VTT
11:40

20 min + 5 min Q&A

F-TEP service demonstrations including SSL Lauri Seitsonen, VTT
12:05 F-TEP developer’s perspective Lauri Seitsonen, VTT
12:15 Concluding remarks Oleg Antropov, Matthieu Molinier, VTT

Please forward this invitation to your colleagues who might be interested in these topics.

We look forward to meeting you at the workshop.

Oleg Antropov, Matthieu Molinier, VTT and the ESA RepreSent team

KvarkenSat Innovation Challenge 2022 on Sustainable Forestry

2022-02-10

The DISA forestry group invites you to KvarkenSat Innovation Challenge 2022 on Sustainable Forestry that will start in next week with a pre-hackathon followed by the hackathon using space-based data helping to combat climate change!

Acceptance based on submission, the best submissions may be approved early.

The challenges

Climate change brings about major changes affecting us all. Extreme weather events become more frequent and especially the amount of rainfall increases in Northern Europe, one contributor being the warmer winters. New species of both vegetation and animals enter new areas while the existing species might have even major changes in their habitats. These lead to new challenges in the forestry industry. We are looking for ideas and solutions combining existing knowledge and datasets with space-based data and datasets based on satellite measurements, in four particular themes including soil moisture, spruce bark beetles, forest ground damage and the forest value chain.

Who can apply?

The hackathon is open to students, teachers, researchers and start-ups in teams of 3-5 persons. Relevant expertise to participate include: space and satellite data, machine learning and neural networks, computer science, positioning systems, automation, image processing/recognition, engineering, logistics, business/communications and forestry.

Awards

The three best proposals across all of the themes will be awarded a cash prize (over 100 000SEK) and possible continuation/acceleration within start-ups and innovation programs.

Pre-Hack Webinar

To get familiar with the hackathon, meet the mentors and partners, and participate in Q&A-session join our webinar on 15 February at 13.00 (14.00 Finnish time).

Link to the join the webinar: https://bit.ly/KvarkenSatWebinar

More information about the hackathon: https://ultrahack.org/kvarkensat-innovation-challenge-2022

Meet Speaker Anna-Lena Axelsson from The Forest Data Lab

2020-11-27

During the Big Data Conference on December 3-4, 2020 we will have several interesting invited speakers, one of them is Anna-Lena Axelsson from The Forest Data Lab .

Anna-Lena Axelsson will talk about The National Forest Data Lab, an open platform that promotes co-creation and data-driven innovation within the forest sector. The platform builds upon existing data, infrastructure and collaboration between two strong players within management, analysis and curation of forest related data; the Swedish Forest Agency and the Swedish University of Agricultural Sciences (SLU). The main users and collaborators are companies and public authorities but also academia and research institutes. The presentation will focus on a number of use cases that demonstrate the value of open data and services for data-driven innovation in the forest sector. The Lab also arrange seminars, networking and training events. Currently The Forest Data Lab participate in the new version of Hack for Sweden 365, which is an innovation competition related to public open data.

Anna-Lena Axelsson. Foto: Linnea Lutto

Foto: Linnea Lutto

Anna-Lena Axelsson works with development of external collaboration and coordinates the forest environmental monitoring and assessment program at the Swedish University of Agricultural Sciences. She is one of the initiators of the National Forest Data Lab.

Don’t miss out on the opportunity to listen to him and take part of the conference by signing up here by December 1st.

Meet Keynote: Erik Willén – Big Data applications in Forestry

2020-11-20

During the Big Data Conference on December 3-4, 2020 we will have several interesting Keynote speakers, one of them is Erik Willén, who is Process Manager at Skogforsk, in Uppsala, Sweden

During the conference he will speak about how Swedish forestry is using and producing vast amount of data for planning, during operations and transportation to the industry. The presentation focus on the enablers for digitalization in Swedish forestry and their current status. The most important data collection and processing as well as several applications in operational use and in applied R&D will be presented.

Erik Willén, SKogforsk

Don’t miss out on the opportunity to listen to him and take part of the conference by signing up here by December 1st.

Meet Keynote: Håkan Olsson – Remote Sensing provides Big Data for assessment of our forest resources

2020-11-19

During the Big Data Conference on December 3-4, 2020 we will have several interesting Keynote speakers, one of them is Håkan Olsson is professor in forest remote sensing at the Swedish University of Agricultural sciences. He leads the data acquisition work package in the research programme Mistra Digital Forest. He is also a member in the steering group for the ongoing national laser scanning for forest resource assessment, and a member of the national council for geodata (Geodatarådet).

Håkan Olsson

During his talk he focus on that there is an increasing stream of remote sensing data that together with digital techniques can be used for assessment of forest resources. Satellites provides frequent images that can be compared and used for forest damage assessment. Airborne laser scanners provide 3D point clouds that in combination with field surveyed reference data are used operationally for producing nationwide and accurate maps with data about the forest on raster cell level. The sensors develops rapidly and provides data with higher resolution, making assessments of single trees realistic. Among the current research frontiers are: combining single tree data from airborne sensors with stem shape data from sensors carried by man or vehicles; automated classification of tree species; assessment of forest growth from repeated sensor data acquisitions. The ultimate goal is to assimilate all new data into a continuously updated model of the forest resources.

Don’t miss out on the opportunity to listen to him and take part of the conference by signing up here by December 1st.