| Stand density estimators based on individual tree detection and stochastic geometry K Kansanen, J Vauhkonen, T Lähivaara, L Mehtätalo Canadian journal of forest research 46 (11), 1359-1366, 2016 | 32 | 2016 |
| Lmfor: Functions for forest biometrics L Mehtätalo, K Kansanen R package version 1, 2015 | 26 | 2015 |
| Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching K Kansanen, J Vauhkonen, T Lähivaara, A Seppänen, M Maltamo, ... ISPRS journal of photogrammetry and remote sensing 152, 66-78, 2019 | 23 | 2019 |
| lmfor: functions for Forest biometrics. R package version 1.2 L Mehtatalo, K Kansanen | 14 | 2019 |
| Modelling and real-time analysis of critical infrastructure using discrete event systems on graphs S Puuska, K Kansanen, L Rummukainen, J Vankka 2015 IEEE International Symposium on Technologies for Homeland Security (HST …, 2015 | 8 | 2015 |
| Horvitz-Thompson–like estimation with distance-based detection probabilities for circular plot sampling of forests K Kansanen, P Packalen, M Maltamo, L Mehtätalo Biometrics 77 (2), 715-728, 2021 | 7 | 2021 |
| Refining and evaluating a Horvitz–Thompson-like stand density estimator in individual tree detection based on airborne laser scanning K Kansanen, P Packalen, T Lähivaara, A Seppänen, J Vauhkonen, ... Canadian journal of forest research 52 (4), 527-538, 2022 | 4 | 2022 |
| Estimation of forest stand characteristics using individual tree detection, stochastic geometry and a sequential spatial point process model L Mehtätalo, A Yazigi, K Kansanen, P Packalen, T Lähivaara, M Maltamo, ... International Journal of Applied Earth Observation and Geoinformation 112 …, 2022 | 3 | 2022 |
| Using stochastic geometry and sequential spatial point process model for estimation of stand density based on ALS-itd L Mehtätalo, A Yazigi, K Kansanen, P Packalen, T Lähivaara, M Maltamo, ... Proceedings of the SilviLaser Conference 2021, 2021 | 1 | 2021 |
| Package ‘lmfor’ L Mehtatalo, K Kansanen, ML Mehtatalo | 1 | 2015 |
| Correcting TLS Estimation for Shading by Other Trees Using a Horvitz-Thompson-like Estimator K Kansanen, P Packalen, M Maltamo, L Mehtätalo Proceedings of the SilviLaser Conference 2021, 2021 | | 2021 |
| Horvitz-Thompson-like estimators based on stochastic geometry for forest remote sensing K Kansanen Itä-Suomen yliopisto, 2020 | | 2020 |
| Stokastiset differentiaaliyhtälöt ja stokastinen Lorenzin systeemi KPP Kansanen Itä-Suomen yliopisto, 2012 | | 2012 |
| Finding hidden trees in remote sensing of forests by using stochastic geometry, sequential spatial point processes and the HT-like estimator L Mehtätalo, K Kansanen, A Yazigi | | |
| Estimation of forest characteristics using airborne laser scanning: could stochastic geometry help? L Mehtätalo, K Kansanen | | |
Lauri MehtätaloNatural Resources Institute Finland (Luke)Verified email at luke.fi
