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Manuela Hirschmugl
Manuela Hirschmugl
Joanneum Research & University of Graz
Verified email at joanneum.at
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Cited by
Year
An international comparison of individual tree detection and extraction using airborne laser scanning
H Kaartinen, J Hyyppä, X Yu, M Vastaranta, H Hyyppä, A Kukko, ...
Remote Sensing 4 (4), 950-974, 2012
5492012
Single tree detection in very high resolution remote sensing data
M Hirschmugl, M Ofner, J Raggam, M Schardt
Remote Sensing of Environment 110 (4), 533-544, 2007
2172007
Methods for mapping forest disturbance and degradation from optical earth observation data: A review
M Hirschmugl, H Gallaun, M Dees, P Datta, J Deutscher, N Koutsias, ...
Current Forestry Reports 3, 32-45, 2017
792017
Global change research in the Carpathian mountain region
AB Gurung, A Bokwa, W Che³micki, M Elbakidze, M Hirschmugl, P Hostert, ...
Mountain Research and Development 29 (3), 282-288, 2009
782009
Use of SAR and optical time series for tropical forest disturbance mapping
M Hirschmugl, J Deutscher, C Sobe, A Bouvet, S Mermoz, M Schardt
Remote Sensing 12 (4), 727, 2020
682020
Mapping forest degradation due to selective logging by means of time series analysis: Case studies in Central Africa
M Hirschmugl, M Steinegger, H Gallaun, M Schardt
Remote Sensing 6 (1), 756-775, 2014
672014
Mapping tropical rainforest canopy disturbances in 3D by COSMO-SkyMed spotlight InSAR-stereo data to detect areas of forest degradation
J Deutscher, R Perko, K Gutjahr, M Hirschmugl, M Schardt
Remote sensing 5 (2), 648-663, 2013
512013
Combined use of optical and synthetic aperture radar data for REDD+ applications in Malawi
M Hirschmugl, C Sobe, J Deutscher, M Schardt
Land 7 (4), 116, 2018
322018
Derivation of forest parameters from UltracamD data
M Hirschmugl
na, 2008
222008
Reflectance of various snow types: measurements, modeling, and potential for snow melt monitoring
JI Peltoniemi, J Suomalainen, T Hakala, J Näränen, E Puttonen, ...
Light Scattering Reviews 5: Single Light Scattering and Radiative Transfer …, 2010
202010
Humid tropical forest monitoring with multi-temporal L-, C-and X-band SAR data
J Deutscher, K Gutjahr, R Perko, H Raggam, M Hirschmugl, M Schardt
2017 9th International Workshop on the Analysis of Multitemporal Remote …, 2017
162017
„Pansharpening “-Methoden für digitale, sehr hochauflösende Fernerkundungsdaten
M Hirschmugl, H Gallaun, R Perko, M Schardt
na, 2005
162005
An international comparison of individual tree detection and extraction using airborne laser scanning. Remote Sens. 4, 950–974
H Kaartinen, J Hyyppä, X Yu, M Vastaranta, H Hyyppä, A Kukko, ...
142012
Combined use of SAR and optical time series data for near real-time forest disturbance mapping
M Hirschmugl, J Deutscher, KH Gutjahr, C Sobe, M Schardt
2017 9th International Workshop on the Analysis of Multitemporal Remote …, 2017
132017
A near real-time method for forest change detection based on a structural time series model and the Kalman filter
M Puhm, J Deutscher, M Hirschmugl, A Wimmer, U Schmitt, M Schardt
Remote Sensing 12 (19), 3135, 2020
122020
3D stereo mapping by means of UltracamD data
M Ofner, M Hirschmugl, H Raggam, M Schardt
Proceedings of the Workshop on 3D Remote Sensing in Forestry, Vienna …, 2006
122006
Viability and sustainability assessment of bioenergy value chains on underutilised lands in the EU and Ukraine
C Khawaja, R Janssen, R Mergner, D Rutz, M Colangeli, L Traverso, ...
Energies 14 (6), 1566, 2021
102021
Pan-European mapping of underutilized land for bioenergy production
M Hirschmugl, C Sobe, C Khawaja, R Janssen, L Traverso
Land 10 (2), 102, 2021
102021
The assessment of forest parameters by combined LiDAR and satellite data over Alpine regions–EUFODOS Implementation in Austria/Hodnotenie parametrov lesa kombináciou LIDAR-u a …
M Schardt, K Granica, M Hirschmugl, J Deutscher, M Mollatz, ...
Central European Forestry Journal 61 (1), 3-11, 2015
102015
Review on the possibilities of mapping old-growth temperate forests by remote sensing in Europe
M Hirschmugl, C Sobe, A Di Filippo, V Berger, H Kirchmeir, ...
Environmental Modeling & Assessment 28 (5), 761-785, 2023
92023
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