| 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 | 557 | 2016 |
| 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 | 304 | 2014 |
| 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 | 279 | 2014 |
| 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 | 164 | 2014 |
| 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 | 125 | 2014 |
| Forest structure modeling with combined airborne hyperspectral and LiDAR data H Latifi, F Fassnacht, B Koch Remote Sensing of Environment 121, 10-25, 2012 | 116 | 2012 |
| 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 | 107 | 2019 |
| ISS observations offer insights into plant function EN Stavros, D Schimel, R Pavlick, S Serbin, A Swann, L Duncanson, ... Nature Ecology & Evolution 1 (7), 1-5, 2017 | 106 | 2017 |
| 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 | 105 | 2016 |
| 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), 1-9, 2019 | 101 | 2019 |
| 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 | 84 | 2015 |
| 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 | 81 | 2015 |
| 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 | 71 | 2017 |
| 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 | 69 | 2015 |
| 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 | 66 | 2019 |
| Mapping forest biomass from space–Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models T Kattenborn, J Maack, F Faßnacht, F Enßle, J Ermert, B Koch International Journal of Applied Earth Observation and Geoinformation 35 …, 2015 | 66 | 2015 |
| 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 | 59 | 2020 |
| Identification of high nature value grassland with remote sensing and minimal field data S Stenzel, FE Fassnacht, B Mack, S Schmidtlein Ecological indicators 74, 28-38, 2017 | 57 | 2017 |
| Land-use regime shift triggered the recent degradation of alpine pastures in Nyanpo Yutse of the eastern Qinghai-Tibetan Plateau L Li, FE Fassnacht, I Storch, M Bürgi Landscape Ecology 32 (11), 2187-2203, 2017 | 51 | 2017 |
| Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices FE Fassnacht, S Stenzel, AA Gitelson Journal of Plant Physiology 176, 210-217, 2015 | 50 | 2015 |
Teja KattenbornRemote Sensing Centre for Earth System Research (RSC4Earth), Leipzig UniversityVerified email at uni-leipzig.de
