Παρακολούθηση
Fabian Ewald Fassnacht
Fabian Ewald Fassnacht
Professor, Freie Universität Berlin
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα fu-berlin.de - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
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
9472016
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
4132014
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
4042014
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
2432019
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
2422019
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
2182014
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
1802016
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
1792014
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
1362020
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
1352017
Forest structure modeling with combined airborne hyperspectral and LiDAR data
H Latifi, F Fassnacht, B Koch
Remote Sensing of Environment 121, 10-25, 2012
1312012
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
1082019
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
1062015
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
1052015
The spectral variability hypothesis does not hold across landscapes
S Schmidtlein, FE Fassnacht
Remote sensing of environment 192, 114-125, 2017
1012017
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
992017
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
972020
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
962024
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
942015
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
922019
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