| Review of studies on tree species classification from remotely sensed data FE Fassnacht, H Latifi, K Stereńczak, A Modzelewska, M Lefsky, LT Waser, ... Remote sensing of environment 186, 64-87, 2016 | 997 | 2016 |
| Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass FE Fassnacht, F Hartig, H Latifi, C Berger, J Hernández, P Corvalán, ... Remote sensing of environment 154, 102-114, 2014 | 425 | 2014 |
| A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales A Ghosh, FE Fassnacht, PK Joshi, B Koch International Journal of Applied Earth Observation and Geoinformation 26, 49-63, 2014 | 416 | 2014 |
| UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data T Kattenborn, J Lopatin, M Förster, AC Braun, FE Fassnacht Remote sensing of environment 227, 61-73, 2019 | 255 | 2019 |
| Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery T Kattenborn, J Eichel, FE Fassnacht Scientific reports 9 (1), 17656, 2019 | 248 | 2019 |
| Comparison of feature reduction algorithms for classifying tree species with hyperspectral data on three central European test sites FE Fassnacht, C Neumann, M Förster, H Buddenbaum, A Ghosh, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014 | 222 | 2014 |
| Comparing generalized linear models and random forest to model vascular plant species richness using LiDAR data in a natural forest in central Chile J Lopatin, K Dolos, HJ Hernández, M Galleguillos, FE Fassnacht Remote Sensing of Environment 173, 200-210, 2016 | 183 | 2016 |
| Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality FE Fassnacht, H Latifi, A Ghosh, PK Joshi, B Koch Remote Sensing of Environment 140, 533-548, 2014 | 183 | 2014 |
| Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery T Kattenborn, J Eichel, S Wiser, L Burrows, FE Fassnacht, S Schmidtlein Remote Sensing in Ecology and Conservation 6 (4), 472-486, 2020 | 142 | 2020 |
| ISS observations offer insights into plant function EN Stavros, D Schimel, R Pavlick, S Serbin, A Swann, L Duncanson, ... Nature Ecology & Evolution 1 (7), 0194, 2017 | 138 | 2017 |
| Forest structure modeling with combined airborne hyperspectral and LiDAR data H Latifi, F Fassnacht, B Koch Remote Sensing of Environment 121, 10-25, 2012 | 133 | 2012 |
| Remote sensing in forestry: current challenges, considerations and directions FE Fassnacht, JC White, MA Wulder, E Næsset Forestry: An International Journal of Forest Research 97 (1), 11-37, 2024 | 131 | 2024 |
| Differentiating plant functional types using reflectance: which traits make the difference? T Kattenborn, FE Fassnacht, S Schmidtlein Remote Sensing in Ecology and Conservation 5 (1), 5-19, 2019 | 113 | 2019 |
| Forest inventories by LiDAR data: A comparison of single tree segmentation and metric-based methods for inventories of a heterogeneous temperate forest H Latifi, FE Fassnacht, J Müller, A Tharani, S Dech, M Heurich International Journal of Applied Earth Observation and Geoinformation 42 …, 2015 | 109 | 2015 |
| Stratified aboveground forest biomass estimation by remote sensing data H Latifi, FE Fassnacht, F Hartig, C Berger, J Hernández, P Corvalán, ... International Journal of Applied Earth Observation and Geoinformation 38 …, 2015 | 107 | 2015 |
| The spectral variability hypothesis does not hold across landscapes S Schmidtlein, FE Fassnacht Remote sensing of environment 192, 114-125, 2017 | 105 | 2017 |
| Mapping plant species in mixed grassland communities using close range imaging spectroscopy J Lopatin, FE Fassnacht, T Kattenborn, S Schmidtlein Remote Sensing of Environment 201, 12-23, 2017 | 104 | 2017 |
| Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data A Modzelewska, FE Fassnacht, K Stereńczak International journal of applied earth observation and geoinformation 84, 101960, 2020 | 101 | 2020 |
| How canopy shadow affects invasive plant species classification in high spatial resolution remote sensing J Lopatin, K Dolos, T Kattenborn, FE Fassnacht Remote Sensing in Ecology and Conservation 5 (4), 302-317, 2019 | 94 | 2019 |
| Mapping degraded grassland on the Eastern Tibetan Plateau with multi-temporal Landsat 8 data—where do the severely degraded areas occur? FE Fassnacht, L Li, A Fritz International Journal of Applied Earth Observation and Geoinformation 42 …, 2015 | 94 | 2015 |
Teja KattenbornDepartment for Sensor-based Geoinformatics, University of Freiburg在 geosense.uni-freiburg.de 的电子邮件经过验证