{"id":2580,"date":"2017-12-07T08:10:08","date_gmt":"2017-12-07T08:10:08","guid":{"rendered":"http:\/\/hgf-eda.de\/?page_id=2580"},"modified":"2018-09-13T07:54:50","modified_gmt":"2018-09-13T07:54:50","slug":"2018-2","status":"publish","type":"page","link":"https:\/\/hgf-eda.de\/?page_id=2580","title":{"rendered":"2018"},"content":{"rendered":"

2018<\/strong> |<\/strong> 2017 |<\/strong> <\/a>2016 <\/a>| <\/a>2015 <\/a>|<\/strong><\/a>2014<\/a> |<\/strong> <\/a>2013 – 2012<\/a><\/h3>\n

Biosphere<\/span><\/p>\n

R. Fischer, E. R\u00f6dig, A. Huth: Consequences of a Reduced Number of Plant Functional Types for the Simulation of Forest Productivity. Forests, 9, 460, 2018, doi:10.3390\/f9080460.<\/a><\/p>\n

U. Hiltner, A. Huth, A. Br\u00e4uning, B. H\u00e9rault, R. Fischer: Simulation of succession in a neotropical forest: High selective logging intensities prolong the recovery times of ecosystem functions. Forest Ecology and Management, Vol. 430, pp. 517-525, 2018, doi:10.1016\/j.foreco.2018.08.042.<\/a><\/p>\n

H. Joerg, M. Pardini, I. Hajnsek, K. Papathanassiou: 3-D Scattering Characterization of Agricultural Crops at C-band using SAR Tomography. IEEE Transactions on Geoscience and Remote Sensing,\u00a056(7)<\/span>, 2018, doi:10.1109\/TGRS.2018.2818440.<\/a><\/span><\/span><\/p>\n

H. Joerg, M. Pardini, I. Hajnsek, K. P. Papathanassiou: Sensitivity of SAR Tomography to the Phenological Cycle of Agricultural Crops at X-, C- and L-band. IEEE J. Sel. Top. Appl. Earth Obs., 11(9), 2018,\u00a0doi:10.1109\/JSTARS.2018.2845127<\/a>.<\/p>\n

H. Joerg: Multi-Frequency Polarimetric SAR Tomography for the 3-D Characterization and Monitoring of Agricultural Crops. PhD thesis, ETH Zurich, 2018 doi:10.3929\/ethz-b-000259515<\/a>.<\/p>\n

N. Knapp, A. Huth, F. Kugler, K. Papathanassiou, R. Condit, S. P. Hubbell and R. Fischer: Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches. Remote Sens. 2018, 10(5), 731; doi:10.3390\/rs10050731<\/a>.<\/p>\n

N. Knapp, R. Fischer, A. Huth: Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states. Remote Sensing of Environment, 205, p. 199\u2013209, 2018, doi:10.1016\/j.rse.2017.11.018.<\/a><\/p>\n

M. Pardini, M. Tello Alonso, V. Cazcarra Bes, K. Papathanassiou, I. Hajnsek: L- and P-Band 3-D SAR Reflectivity Profiles vs. Lidar Waveforms: The AfriSAR Case. IEEE JSTARS, 2018, doi: 10.1109\/JSTARS.2018.2847033<\/a><\/p>\n

M. Pardini, K.P. Papathanassiou, F. Lombardini: Impact of Dielectric Changes on L-Band 3-D SAR Reflectivity Profiles of Forest Volumes. IEEE Transactions on Geoscience and Remote Sensing, 2018, doi:10.1109\/TGRS.2018.2850357.<\/a><\/p>\n

M. Pichierri, I. Hajnsek, S. Zwieback, and B. Rabus: On the potential of Polarimetric SAR Interferometry to characterize the biomass, moisture and structure of agricultural crops at L-, C- and X-Bands. Remote Sensing of Env., 204, pp. 596-616, 2018, doi:10.1016\/j.rse.2017.09.039<\/a>.<\/p>\n

A. Rammig, J. Heinke, F. Hofhansl, H. Verbeeck, T. R. Baker, B. Christoffersen, P. Ciais, H. De Deurwaerder, K. Fleischer, D. Galbraith, M. Guimberteau, A. Huth, M. Johnson, B. Krujit, F. Langerwisch, P. Meir, P. Papastefanou, G. Sampaio, K. Thonicke, C. von Randow, C. Zang, E. R\u00f6dig: A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region. Geosci. Model Dev. Discuss., 2018, doi:10.5194\/gmd-2018-182.<\/a><\/p>\n

E. R\u00f6dig, M. Cuntz, A. Rammig, R. Fischer, F. Taubert, A. Huth: The importance of forest structure for carbon fluxes of the Amazon rainforest. Environ. Res. Lett., 13(5), 2018, doi:10.1088\/1748-9326\/aabc61<\/a>.<\/p>\n

E. R\u00f6dig: Simulating carbon stocks and fluxes of the Amazon rainforest: a journey across temporal and spatial scales. PhD-Thesis, Uni Osnabr\u00fcck, 2018.<\/p>\n

R. Taubert, R. Fischer, J. Groeneveld, S. Lehmann, S.M. Michael, E. R\u00f6dig, T. Wiegand, A. Huth: Global patterns of tropical forest fragmentation. Nature, 554, pp. 519\u2013522, 2018, doi:10.1038\/nature25508<\/a>.<\/p>\n

M. Tello, V. Cazcarra-Bes, M. Pardini, K. Papathanassiou: Forest Structure Characterization From SAR Tomography at L-Band. IEEE J. Sel. Top. Appl. Earth Obs., 2018, doi:10.1109\/JSTARS.2018.2859050.<\/a><\/p>\n

Geosphere<\/span><\/p>\n

J. Neelmeijer, T. Sch\u00f6ne, R. Dill, V. Klemann, M. Motagh: Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data\u2014A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series. Remote Sensing, 10(3), 2018, doi:10.3390\/rs10030462<\/a>.<\/p>\n

N. Richter, J.T. Salzer, E. de Zeeuw-van Dalfsen, D. Perissin, T.R. Walter: Constraints on the geomorphological evolution of the nested summit craters of L\u00e1scar volcano from high spatio-temporal resolution TerraSAR-X interferometry. Bulletin of Volcanology, 80(21), 2018, doi:10.1007\/s00445-018-1195-3<\/a>.<\/p>\n

Hydrosphere<\/span><\/p>\n

V. Brancato, I. Hajnsek: Analyzing the Influence of Wet Biomass Changes in Polarimetric Differ-ential SAR Interferometry at L-Band. IEEE JSTARS, 2018, doi:10.1109\/JSTARS.2018.2805775<\/a>.<\/p>\n

V. Brancato: The Influence of Soil Moisture, Agricultural Vegetation and Rain Interception in Differential SAR Interferometry. Dissertation, ETH Zurich, 2018. doi:10.3929\/ethz-b-000239184<\/a>.<\/p>\n

S. R. Lutz, R. Krieg, C. M\u00fcller, M. Zink, K. Kn\u00f6ller, L. Samaniego, R. Merz: Spatial Patterns of Water Age: Using Young Water Fractions to Improve the Characterization of Transit Times in Contrasting Catchments. Water Resources Research, 54(7), 2018, doi:10.1029\/2017WR022216<\/a><\/p>\n

C. Montzka, K. R\u00f6tzer, H. R. Bogena, N. Sanchez, H. Vereecken: A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability. Remote Sensing, 10(3), 427, 2018, doi:10.3390\/rs10030427<\/a>.<\/p>\n

M. Schr\u00f6n, S. Zacharias, G. Womack, M. K\u00f6hli, D. Desilets, S.E. Oswald, J. Bumberger, H. Mollenhauer, S. K\u00f6gler, P. Remmler, M. Kasner, A. Denk, P. Dietrich: Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment . Geosci. Instrum. Method. Data Syst. Discuss, 7, pp. 83-99, 2018, doi:10.5194\/gi-7-83-2018<\/a>.<\/p>\n

M. Zink, J. Mai, M. Cuntz, L. Samaniego: Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature. Water Resources Research, 54, 2018, doi:10.1002\/2017WR021346<\/a>.<\/p>\n

Cryosphere<\/span><\/p>\n

S. Antonova, H. Sudhaus, T. Strozzi, S. Zwieback, A. K\u00e4\u00e4b, B. Heim, M. Langer, N. Bornemann, J. Boike: Thaw Subsidence of a Yedoma Landscape in Northern Siberia, Measured In Situ and Estimated from TerraSAR-X Interferometry. Remote Sensing, 10(4), 2018, doi:10.3390\/rs10040494<\/a>.<\/p>\n

J. Griebel, W. Dierking: Impact of Sea Ice Drift Retrieval Errors, Discretization and Grid Type on Calculations of Ice Deformation. Remote Sens. 2018, 10(3), 393; doi:10.3390\/rs10030393<\/a>.<\/p>\n

P. Malz, W. Meier, G. Casassa, R. Ja\u00f1a, P. Skvarca, M.H. Braun: Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data. Remote Sens., 10(2), 188, 2018, doi:10.3390\/rs10020188<\/a>.<\/p>\n

A. Parizzi, W. A. Jaber: Estimating Strain and Rotation From Wrapped SAR Interferograms. IEEE Geoscience and Remote Sensing Letters, 2018, doi:10.1109\/LGRS.2018.2838763<\/a><\/p>\n

Seehaus, T., Cook, A., Silva, A. B., and Braun, M. H.: Changes in glacier dynamics at the northern Antarctic Peninsula since 1985, The Cryosphere, 12(2), 2018, doi:10.5194\/tc-12-577-2018<\/a>.<\/p>\n

S. Stettner, A. L. Beamish, A. Bartsch, B. Heim, G. Grosse, A. Roth, H. Lantuit: Monitoring Inter- and Intra-Seasonal Dynamics of Rapidly Degrading Ice-Rich Permafrost Riverbanks in the Lena Delta with TerraSAR-X Time Series. Remote Sens. 2018, 10(1), 51, 2018, doi:10.3390\/rs10010051<\/a>.<\/p>\n

S. Vijay, M. Braun: Early 21st century spatially detailed elevation changes of Jammu and Kashmir glaciers (Karakoram\u2013Himalaya). Global and Planetary Change, 165, pp. 137\u2013146, 2018, doi:10.1016\/j.gloplacha.2018.03.014<\/a>.<\/p>\n

S. Zwieback, S. Kokelj, F. G\u00fcnther, J. Boike, G. Grosse, I. Hajnsek: Sub-seasonal thaw slump mass wasting is not consistently energy limited at the landscape scale The Cryosphere, 12, 549-564, 2018, doi:10.5194\/tc-12-549-2018<\/a>.<\/p>\n

2018<\/strong> |<\/strong> 2017 |<\/strong> <\/a>2016 <\/a>| <\/a>2015 <\/a>|<\/strong><\/a>2014<\/a> |<\/strong> <\/a>2013 – 2012<\/a><\/h3>\n","protected":false},"excerpt":{"rendered":"

2018 | 2017 | 2016 | 2015 |2014 | 2013 – 2012 Biosphere R. Fischer, E. R\u00f6dig, A. Huth: Consequences of a Reduced Number of Plant Functional Types for the Simulation of Forest Productivity. Forests, 9, 460, 2018, doi:10.3390\/f9080460. U. … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":75,"comment_status":"closed","ping_status":"closed","template":"sidebar-page.php","meta":[],"_links":{"self":[{"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/pages\/2580"}],"collection":[{"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/hgf-eda.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2580"}],"version-history":[{"count":24,"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/pages\/2580\/revisions"}],"predecessor-version":[{"id":3050,"href":"https:\/\/hgf-eda.de\/index.php?rest_route=\/wp\/v2\/pages\/2580\/revisions\/3050"}],"wp:attachment":[{"href":"https:\/\/hgf-eda.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2580"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}