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Georg Bareth
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2020 – today
- 2023
- [j30]Clara Oliva Gonçalves Bazzo
, Bahareh Kamali, Christoph Hütt
A Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV. Remote. Sens. 15(3): 639 (2023) - [c9]Georg Bareth, Christoph Hütt, Alexander Jenal
Spectral Evaluation of Hyperspectral Remote Sensing Data Using UAV-derived VIS/NIR/SWIR Imaging Data and Polygon Grids. IGARSS 2023: 1945-1948 - [c8]Alexander Jenal
A New Multispectral VNIR/SWIR Imaging System for UAVs to Monitor Crop Traits. IGARSS 2023: 4635-4637 - 2022
- [j29]Ulrike Lussem
Herbage Mass, N Concentration, and N Uptake of Temperate Grasslands Can Adequately Be Estimated from UAV-Based Image Data Using Machine Learning. Remote. Sens. 14(13): 3066 (2022) - 2021
- [j28]Alexander Jenal
Investigating the Potential of a Newly Developed UAV-Mounted VNIR/SWIR Imaging System for Monitoring Crop Traits - A Case Study for Winter Wheat. Remote. Sens. 13(9): 1697 (2021) - 2020
- [j27]Christoph Hütt
Fusion of Sentinel-1 with Official Topographic and Cadastral Geodata for Crop-Type Enriched LULC Mapping Using FOSS and Open Data. ISPRS Int. J. Geo Inf. 9(2): 120 (2020)
2010 – 2019
- 2019
- [j26]Shanyu Huang, Yuxin Miao
In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages. Remote. Sens. 11(16): 1847 (2019) - [j25]Nora Tilly
Estimating Nitrogen from Structural Crop Traits at Field Scale - A Novel Approach Versus Spectral Vegetation Indices. Remote. Sens. 11(17): 2066 (2019) - [j24]Alexander Jenal
Development of a VNIR/SWIR Multispectral Imaging System for Vegetation Monitoring with Unmanned Aerial Vehicles. Sensors 19(24): 5507 (2019) - 2018
- [j23]Christian Willmes
CRC806-KB: A Semantic MediaWiki Based Collaborative Knowledge Base for an Interdisciplinary Research Project. Data 3(4): 44 (2018) - [j22]Sebastian Brocks
Estimating Barley Biomass with Crop Surface Models from Oblique RGB Imagery. Remote. Sens. 10(2): 268 (2018) - 2017
- [j21]Guido Waldhoff, Ulrike Lussem, Georg Bareth:
Multi-Data Approach for remote sensing-based regional crop rotation mapping: A case study for the Rur catchment, Germany. Int. J. Appl. Earth Obs. Geoinformation 61: 55-69 (2017) - [j20]Daniel Becker
Investigating the Influence of Different DEMs on GIS-Based Cost Distance Modeling for Site Catchment Analysis of Prehistoric Sites in Andalusia. ISPRS Int. J. Geo Inf. 6(2): 36 (2017) - [j19]Christian Willmes, Daniel Becker, Jan Verheul, Yasa Yener, Mirijam Zickel, Andreas Bolten, Olaf Bubenzer, Georg Bareth:
PaleoMaps: SDI for paleoenvironment GIS data. Int. J. Spatial Data Infrastructures Res. 12 (2017) - [j18]Shanyu Huang
Potential of RapidEye and WorldView-2 Satellite Data for Improving Rice Nitrogen Status Monitoring at Different Growth Stages. Remote. Sens. 9(3): 227 (2017) - [j17]Frank Thonfeld
In Memoriam: Gunter Menz. Remote. Sens. 9(3): 274 (2017) - [j16]Christian Willmes
High Resolution Köppen-Geiger Classifications of Paleoclimate Simulations. Trans. GIS 21(1): 57-73 (2017) - 2016
- [j15]Christoph Hütt
Best Accuracy Land Use/Land Cover (LULC) Classification to Derive Crop Types Using Multitemporal, Multisensor, and Multi-Polarization SAR Satellite Images. Remote. Sens. 8(8): 684 (2016) - 2015
- [j14]Juliane Bendig
Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley. Int. J. Appl. Earth Obs. Geoinformation 39: 79-87 (2015) - [j13]Quanying Zhao, Victoria I. S. Lenz-Wiedemann
Investigating Within-Field Variability of Rice from High Resolution Satellite Imagery in Qixing Farm County, Northeast China. ISPRS Int. J. Geo Inf. 4(1): 236-261 (2015) - [j12]Andreas Burkart, Helge Aasen
Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer. Remote. Sens. 7(1): 725-746 (2015) - [j11]Shanyu Huang
Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China. Remote. Sens. 7(8): 10646-10667 (2015) - [j10]Nora Tilly
Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass. Remote. Sens. 7(9): 11449-11480 (2015) - [j9]Nora Tilly
Correction: Tilly, N. et al. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass. Remote Sens. 2015, 7, 11449-11480. Remote. Sens. 7(12): 17291-17296 (2015) - 2014
- [j8]Martin L. Gnyp
Development and implementation of a multiscale biomass model using hyperspectral vegetation indices for winter wheat in the North China Plain. Int. J. Appl. Earth Obs. Geoinformation 33: 232-242 (2014) - [j7]Kang Yu
Investigation of Leaf Diseases and Estimation of Chlorophyll Concentration in Seven Barley Varieties Using Fluorescence and Hyperspectral Indices. Remote. Sens. 6(1): 64-86 (2014) - [j6]Juliane Bendig
Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging. Remote. Sens. 6(11): 10395-10412 (2014) - [j5]Yinkun Yao
In-Season Estimation of Rice Nitrogen Status With an Active Crop Canopy Sensor. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(11): 4403-4413 (2014) - [j4]Christian Willmes
Building Research Data Management Infrastructure using Open Source Software. Trans. GIS 18(4): 496-509 (2014) - [c7]Helge Aasen
Towards robust vegetation indices: The multi-correlation matrix strategy. WHISPERS 2014: 1-4 - [c6]Martin Leon Gnyp, Kang Yu
Estimating biomass of rice in farmers' fields by red-edge indices. WHISPERS 2014: 1-4 - 2013
- [j3]Wolfgang Koppe, Martin Gnyp
Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data. Int. J. Appl. Earth Obs. Geoinformation 21: 568-576 (2013) - 2012
- [j2]Constanze Curdt
Scientific Research Data Management for Soil-Vegetation-Atmosphere Data - The TR32DB. Int. J. Digit. Curation 7(2): 68-80 (2012) - [c5]Dirk Hoffmeister, Nora Tilly, Juliane Bendig, Constanze Curdt, Georg Bareth:
Detektion von Wachstumsvariabilität in vier Zuckerrübensorten durch multi-temporales terrestrisches Laserscanning. GIL Jahrestagung 2012: 135-138 - 2011
- [c4]Liangliang Jia, Zihui Yu, Fei Li, Martin Gnyp
Nitrogen Status Estimation of Winter Wheat by Using an IKONOS Satellite Image in the North China Plain. CCTA (2) 2011: 174-184
2000 – 2009
- 2009
- [j1]Georg Bareth:
GIS- and RS-based spatial decision support: structure of a spatial environmental information system (SEIS). Int. J. Digit. Earth 2(2): 134-154 (2009) - [c3]Constanze Curdt, Dirk Hoffmeister, Guido Waldhoff, Georg Bareth:
Implementierung eines Projektdatenmanagements für das interdisziplinäre Forschungsprojekt TR32 "Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation". GIL Jahrestagung 2009: 37-40 - [c2]Guido Waldhoff, Constanze Curdt, Dirk Hoffmeister, Georg Bareth:
Multi-Daten Ansatz für verbesserte Landnutzungsanalysen - Fallstudie Rur-Einzugsgebiet. GIL Jahrestagung 2009: 181-184 - [c1]Martin L. Gnyp
Hyperspactral data analysis of nitrogen fertilization effects on winter wheat using spectrometer in North China Plain. WHISPERS 2009: 1-4
1990 – 1999
- 1999
- [b1]Georg Bareth:
Emissionen klimarelevanter Gase aus der Landwirtschaft - regionale Darstellung und Abschätzung unter Nutzung von GIS am Beispiel des württembergischen Allgäus. Universität Hohenheim, 1999, pp. I-IX, 1-208 - [p1]Georg Bareth:
Emissionen klimarelevanter Gase aus der Landwirtschaft. Ausgezeichnete Informatikdissertationen 1999: 9-21
Coauthor Index
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