| Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture E Honkavaara, H Saari, J Kaivosoja, I Pölönen, T Hakala, P Litkey, ... Remote Sensing 5 (10), 5006-5039, 2013 | 572 | 2013 |
| A novel machine learning method for estimating biomass of grass swards using a photogrammetric canopy height model, images and vegetation indices captured by a drone N Viljanen, E Honkavaara, R Näsi, T Hakala, O Niemeläinen, J Kaivosoja Agriculture 8 (5), 70, 2018 | 206 | 2018 |
| Estimating biomass and nitrogen amount of barley and grass using UAV and aircraft based spectral and photogrammetric 3D features R Näsi, N Viljanen, J Kaivosoja, K Alhonoja, T Hakala, L Markelin, ... Remote Sensing 10 (7), 1082, 2018 | 172 | 2018 |
| Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system E Honkavaara, J Kaivosoja, J Mäkynen, I Pellikka, L Pesonen, H Saari, ... ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2012 | 107 | 2012 |
| Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry RA Oliveira, R Näsi, O Niemeläinen, L Nyholm, K Alhonoja, J Kaivosoja, ... Remote Sensing of Environment 246, 111830, 2020 | 96 | 2020 |
| Spectral imaging from UAVs under varying illumination conditions T Hakala, E Honkavaara, H Saari, J Mäkynen, J Kaivosoja, L Pesonen, ... International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2013 | 86 | 2013 |
| Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV I Pölönen, H Saari, J Kaivosoja, E Honkavaara, L Pesonen Remote sensing for agriculture, ecosystems, and hydrology XV 8887, 141-149, 2013 | 79 | 2013 |
| Automatic control of farming operations based on spatial web services J Kaivosoja, M Jackenkroll, R Linkolehto, M Weis, R Gerhards Computers and electronics in agriculture 100, 110-115, 2014 | 52 | 2014 |
| A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data J Kaivosoja, L Pesonen, J Kleemola, I Pölönen, H Salo, E Honkavaara, ... Remote Sensing for Agriculture, Ecosystems, and Hydrology XV 8887, 118-127, 2013 | 45 | 2013 |
| Cropinfra–An Internet-based service infrastructure to support crop production in future farms LA Pesonen, FKW Teye, AK Ronkainen, MO Koistinen, JJ Kaivosoja, ... Biosystems engineering 120, 92-101, 2014 | 43 | 2014 |
| Visible, very near IR and short wave IR hyperspectral drone imaging system for agriculture and natural water applications H Saari, A Akujärvi, C Holmlund, H Ojanen, J Kaivosoja, A Nissinen, ... The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2017 | 34 | 2017 |
| Reference measurements in developing UAV systems for detecting pests, weeds, and diseases J Kaivosoja, J Hautsalo, J Heikkinen, L Hiltunen, P Ruuttunen, R Näsi, ... Remote sensing 13 (7), 1238, 2021 | 33 | 2021 |
| Cropinfra research data collection platform for ISO 11783 compatible and retrofit farm equipment J Backman, R Linkolehto, M Koistinen, J Nikander, A Ronkainen, ... Computers and Electronics in Agriculture 166, 105008, 2019 | 24 | 2019 |
| Estimating grass sward quality and quantity parameters using drone remote sensing with deep neural networks K Karila, R Alves Oliveira, J Ek, J Kaivosoja, N Koivumäki, P Korhonen, ... Remote Sensing 14 (11), 2692, 2022 | 22 | 2022 |
| GNSS error simulator for farm machinery navigation development J Kaivosoja, R Linkolehto Computers and Electronics in Agriculture 119, 166-177, 2015 | 20 | 2015 |
| Silage grass sward nitrogen concentration and dry matter yield estimation using deep regression and RGB images captured by UAV R Alves Oliveira, J Marcato Junior, C Soares Costa, R Näsi, N Koivumäki, ... Agronomy 12 (6), 1352, 2022 | 14 | 2022 |
| Assessment of various remote sensing technologies in biomass and nitrogen content estimation using an agricultural test field R Näsi, N Viljanen, J Kaivosoja, T Hakala, M Pandžić, L Markelin, ... The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2017 | 14 | 2017 |
| Assessment of RGB and hyperspectral UAV remote sensing for grass quantity and quality estimation RA Oliveira, R Näsi, O Niemeläinen, L Nyholm, K Alhonoja, J Kaivosoja, ... The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2019 | 11 | 2019 |
| Different remote sensing data in relative biomass determination and in precision fertilization task generation for cereal crops J Kaivosoja, R Näsi, T Hakala, N Viljanen, E Honkavaara International Conference on Information and Communication Technologies in …, 2017 | 10 | 2017 |
| High-precision estimation of grass quality and quantity using UAS-based VNIR and SWIR hyperspectral cameras and machine learning RA Oliveira, R Näsi, P Korhonen, A Mustonen, O Niemeläinen, ... Precision Agriculture 25 (1), 186-220, 2024 | 9 | 2024 |
