Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 12 Responsible Consumption and Production -
SDG 15 Life on Land
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Collaborations and top research areas from the last five years
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HaQuPrA: Harnessing Quantum for Practical Applications
Seppänen, K. (Manager), Lönnqvist, A. (Owner), Kilpi, J. (CoPI), Reittu, H. (Participant), Muff, J. (Participant), Apilo, O. (Participant) & Hieta-aho, E. (Participant)
1/02/26 → 31/07/28
Project: Business Finland project
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COHQCA: Combinatorial optimization with hybrid quantum-classical algorithms
Seppänen, K. (Manager), Kilpi, J. (Participant), Reittu, H. (Participant), Hieta-aho, E. (Participant), Rautell, M. (Participant), Kotovirta, V. (Participant), Ollikainen, V. (Participant), Chen, T. (Participant), Apilo, O. (Participant) & Lönnqvist, A. (Owner)
1/07/23 → 31/12/25
Project: Business Finland project
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MULTICO: Autonomous Sensing using Satellites, Multicopters, Sensors and Actuators
Lönnqvist, A. (Manager), Rantakari, P. (Participant), Näsilä, A. (Participant) & Korkalo, O. (Participant)
1/04/20 → 30/10/22
Project: Business Finland project
Research output
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A Novel Semisupervised Contrastive Regression Framework for Forest Inventory Mapping With Multisensor Satellite Data
Ge, S., Gu, H., Su, W., Lönnqvist, A. & Antropov, O., 31 May 2023, In: IEEE Geoscience and Remote Sensing Letters. 20, 5 p., 2502705.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access7 Link opens in a new tab Citations (Scopus) -
Deep Learning Models in Forest Mapping Using Multitemporal SAR and Optical Satellite Data
Ge, S., Gu, H., Su, W., Praks, J., Lonnqvist, A. & Antropov, O., 28 Sept 2022, IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE Institute of Electrical and Electronic Engineers, p. 5688-5691 (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 2022-July).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
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Deep neural networks with transfer learning for forest variable estimation using sentinel-2 imagery in boreal forest
Astola, H., Seitsonen, L., Halme, E., Molinier, M. & Lönnqvist, A., 18 Jun 2021, In: Remote Sensing. 13, 12, 2392.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile54 Link opens in a new tab Citations (Scopus)388 Downloads (Pure) -
Mapping Forest Thinning, Systemic and Selective Logging Operations Using Various Imaging Modes of X-Band SAR Images
Antropov, O., Lönnqvist, A., Rauste, Y., Kortelainen, K. & Häme, T., 16 Jul 2021, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. IEEE Institute of Electrical and Electronic Engineers, p. 6272-6275 4 p. 9554477Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
2 Link opens in a new tab Citations (Scopus) -
Classification of Wide-Area SAR Mosaics: Deep Learning Approach for Corine Based Mapping of Finland Using Multitemporal Sentinel-1 Data
Antropov, O., Rauste, Y., Šćepanović, S., Ignatenko, V., Lönnqvist, A. & Praks, J., 17 Feb 2020, 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020: Proceedings. IEEE Institute of Electrical and Electronic Engineers, p. 4283-4286 9323855. (IEEE International Geoscience and Remote Sensing Symposium Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
5 Link opens in a new tab Citations (Scopus)