Prof. Clement Atzberger Profile

Prof. Clement Atzberger

Head of Institute at Univ für Bodenkultur Wien

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Author

Publications (9)

Proceedings Article | 25 October 2016 Presentation + Paper

Mapping Prosopis spp. within the Tarach water basin, Turkana, Kenya using Sentinel-2 imagery

Wai-Tim Ng, Markus Immitzer, Matthias Floriansitz, Francesco Vuolo, Luigi Luminari, Chrisgone Adede, Raphael Wahome, Clement Atzberger

Proceedings Volume 9998, 99980L (2016) https://doi.org/10.1117/12.2241279

KEYWORDS: Earth observing sensors, Tolerancing, Remote sensing, Associative arrays, Vegetation, Clouds, Agriculture, Soil science, Atmospheric corrections, Roads

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Proceedings Article | 14 October 2015 Open Access

Mapping areas invaded by Prosopis juliflora in Somaliland on Landsat 8 imagery

Felix Rembold, Ugo Leonardi, Wai-Tim Ng, Hussein Gadain, Michele Meroni, Clement Atzberger

Proceedings Volume 9637, 963723 (2015) https://doi.org/10.1117/12.2193133

KEYWORDS: Agriculture, Vegetation, Landsat, Image classification, Earth observing sensors, Visualization, Remote sensing, Ecosystems, Associative arrays, Image resolution

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Prosopis juliflora is a fast growing tree species originating from South and Central America with a high invasion potential in semi-arid areas around the globe. It was introduced to East Africa for the stabilization of dune systems and for providing fuel wood after prolonged droughts and deforestation in the 1970s and 1980s. In many dry lands in East Africa the species has expanded rapidly and has become challenging to control. The species generally starts its colonization on deep soils with high water availability while in later stages or on poorer soils, its thorny thickets expand into drier grasslands and rangelands. Abandoned or low input farmland is also highly susceptible for invasion as P. juliflora has competitive advantages to native species and is extremely drought tolerant.

In this work we describe a rapid approach to detect and map P. juliflora invasion at country level for the whole of Somaliland. Field observations were used to delineate training sites for a supervised classification of Landsat 8 imagery collected during the driest period of the year (i.e., from late February to early April). The choice of such a period allowed to maximise the spectral differences between P. juliflora and other species present in the area, as P. juliflora tends to maintain a higher vigour and canopy water content than native vegetation, when exposed to water stress.

The results of our classification map the current status of invasion of Prosopis in Somaliland showing where the plant is invading natural vegetation or agricultural areas. These results have been verified for two spatial subsets of the whole study area with very high resolution (VHR) imagery, proving that Landsat 8 imagery is highly adequate to map P. juliflora. The produced map represents a baseline for understanding spatial distribution of P. juliflora across Somaliland but also for change detection and monitoring of long term dynamics in support to P. juliflora management and control activities.

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Proceedings Article | 25 October 2012 Paper

Data service platform for MODIS Vegetation Indices time series processing at BOKU Vienna: current status and future perspectives

Francesco Vuolo, Matteo Mattiuzzi, Anja Klisch, Clement Atzberger

Proceedings Volume 8538, 85380A (2012) https://doi.org/10.1117/12.974857

KEYWORDS: MODIS, Vegetation, Data archive systems, Image processing, Databases, Composites, Image filtering, Satellites, Data processing, Algorithm development

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SPIE Journal Paper | 4 September 2012

Derivation of biophysical variables from Earth observation data: validation and statistical measures

Katja Richter, Tobias Hank, Wolfram Mauser, Clement Atzberger

JARS, Vol. 6, Issue 01, 063557, (September 2012) https://doi.org/10.1117/12.10.1117/1.JRS.6.063557

KEYWORDS: Data modeling, Statistical modeling, Performance modeling, Error analysis, Vegetation, Calibration, Statistical analysis, Biological research, Remote sensing, Process modeling

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Proceedings Article | 7 October 2011 Paper

Goodness-of-fit measures: what do they tell about vegetation variable retrieval performance from Earth observation data

Katja Richter, Tobias Hank, Clement Atzberger, Wolfram Mauser

Proceedings Volume 8174, 81740R (2011) https://doi.org/10.1117/12.897980

KEYWORDS: Error analysis, Data modeling, Vegetation, Statistical modeling, Statistical analysis, Performance modeling, Biological research, Current controlled current source, Remote sensing, Analytical research

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Proceedings Article | 7 October 2011 Paper

Why confining to vegetation indices? Exploiting the potential of improved spectral observations using radiative transfer models

Clement Atzberger, Katja Richter, Francesco Vuolo, Roshanak Darvishzadeh, Martin Schlerf

Proceedings Volume 8174, 81740Q (2011) https://doi.org/10.1117/12.898479

KEYWORDS: Vegetation, Data modeling, Reflectivity, Radiative transfer, Sensors, Neodymium, Current controlled current source, Calibration, Statistical modeling, Inverse problems

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Proceedings Article | 6 October 2011 Paper

Evaluation of time-series and phenological indicators for land cover classification based on MODIS data

Francesco Vuolo, Katja Richter, Clement Atzberger

Proceedings Volume 8174, 81740E (2011) https://doi.org/10.1117/12.898389

KEYWORDS: MODIS, Composites, Satellites, Vegetation, Spatial resolution, Feature selection, Accuracy assessment, Data acquisition, Error analysis, Associative arrays

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Proceedings Article | 7 October 2009 Paper

Geostatistical regularization of inverse models for the retrieval of vegetation biophysical variables

C. Atzberger, K. Richter

Proceedings Volume 7478, 74781O (2009) https://doi.org/10.1117/12.830009

KEYWORDS: Curium, Vegetation, Reflectivity, Agriculture, Radiative transfer, Inverse problems, Solar radiation models, Soil science, Sensors, Satellites

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Proceedings Article | 18 September 2009 Paper

Estimation of inter-annual winter crop area variation and spatial distribution with low resolution NDVI data by using neural networks trained on high resolution images

C. Atzberger, F. Rembold

Proceedings Volume 7472, 747207 (2009) https://doi.org/10.1117/12.830007

KEYWORDS: Image resolution, Neural networks, Spatial resolution, Neurons, Data modeling, Agriculture, Modeling, Temporal resolution, Landsat, Earth observing sensors

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Showing 5 of 9 publications

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