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Dr. Peter Hofmann, Dipl.-Geogr.

Geoinformatik
Fernerkundung
Object-basierte Bildanalyse (OBIA)
Spatial-AI
Unmanned Areal Systems (UAS)

Zentrum für angewandte Forschung

Institut für angewandte Informatik - Technologie Campus Freyung

Wissenschaftlicher Mitarbeiter

Wiss. Mitarbeiter

TCF

08551/91764-15

Publikationen

Sortierung:

Zeitschriftenartikel

Peter Hofmann

Multinationale Unternehmen in Schottland.

In: Wirtschaftsraum, Ressourcen, Umwelt (WRU) (vol. 8) , pg. 54-58

(1996)

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Hochschulschrift

Peter Hofmann

Die Anwendung fernerkundlicher Daten und Methoden im Geomarketing, untersucht am Beispiel einer KFA-1000-Aufnahme von München.

Ludwig-Maximilians-Universität, München. Institu für Wirtschafts- und Sozialgeographie, Fakultät für Geowissenschaften/Department für Geographie

(1997)

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Zeitschriftenartikel

Peter Hofmann
W. Reinhardt

The extraction of GIS features from high resolution imagery using advanced methods based on additional contextual information-first experiences.

In: International Archives of Photogrammetry and Remote Sensing (vol. 33) , pg. 376-383

(2000)

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Monographie

M. Baatz
M. Heynen
Peter Hofmann
I. Lingenfelder
M. Mimier
A. Schape
M. Weber
G. Willhauck

eCognition User Guide 2.0: Object oriented image analysis.

Definiens Imaging GmbH, München

(2001)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

Detecting urban features from IKONOS data using an object-oriented approach.

pg. 79-91

(2001)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

Detecting informal settlements from IKONOS image data using methods of object oriented image analysis-an example from Cape Town (South Africa).

In:
C. Jürgens

Regensburg: Universität Regensburg/Institut für Geographie pg. 41-42

(2001)

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Zeitschriftenartikel

Peter Hofmann

Detecting buildings and roads from IKONOS data using additional elevation information.

In: GeoBIT/GIS (vol. 6) , pg. 28-33

(2001)

Abstract anzeigen

Using high resolution imagery such as IKONOS data should make it possible to detect man-made-features such as buildings and roads more easily than with conventional satellite image data. However, due to the higher spatial resolution of IKONOS data, an automatic or semiautomatic detection of such features based only on their spectral characteristics can become difficult, especially in heterogeneous areas such as dense urban areas (see Bauer, T. & Steinnocher, K. in this issue). A typical problem in urban remote sensing is the handling of shadows. Using a DEM and additional semantic information can help to detect such cases and to manage them adequately. Furthermore, when using an additional DEM, significant elevation information of questionable objects can be used to identify their shape. As eCognition is able to use an arbitrary number of channels for the image segmentation and classification, the DEM was used for the initial segmentation and for the subsequent object classification. Thereby, the influence of the DEM on the object generation can be controlled by adjusting the channels' weights. Based upon the underlying concepts of eCognition to generate and classify image objects, different strategies have been developed.

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Monographie

M. Baatz
U. Benz
S. Dehghani
M. Heynen
A. Höltje
Peter Hofmann
I. Lingenfelder
M. Mimler
M. Sohlbach
M. Weber

eCognition user guide.

Definiens Imaging GmbH, München

(2004)

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Zeitschriftenartikel

U. Benz
Peter Hofmann
G. Willhauck
I. Lingenfelder
M. Heynen

Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information.

In: ISPRS Journal of Photogrammetry and Remote Sensing (vol. 58) , pg. 239-258

(2004)

DOI: 10.1016/j.isprsjprs.2003.10.002

Abstract anzeigen

Remote sensing from airborne and spaceborne platforms provides valuable data for mapping, environmental monitoring, disaster management and civil and military intelligence. However, to explore the full value of these data, the appropriate information has to be extracted and presented in standard format to import it into geo-information systems and thus allow efficient decision processes. The object-oriented approach can contribute to powerful automatic and semi-automatic analysis for most remote sensing applications. Synergetic use to pixel-based or statistical signal processing methods explores the rich information contents. Here, we explain principal strategies of object-oriented analysis, discuss how the combination with fuzzy methods allows implementing expert knowledge and describe a representative example for the proposed workflow from remote sensing imagery to GIS. The strategies are demonstrated using the first object-oriented image analysis software on the market, eCognition, which provides an appropriate link between remote sensing imagery and GIS.

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Zeitschriftenartikel

M. Baatz
U. Benz
S. Dehghani
M. Heynen
A. Höltje
Peter Hofmann
I. Lingenfelder
M. Mimler
M. Sohlbach
M. Weber

eCognition professional user guide 4.

In: Munich: Definiens-Imaging , pg. 72

(2004)

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Hochschulschrift

Peter Hofmann

Übertragbarkeit von Methoden und Verfahren in der objektorientierten Bildanalyse-das Beispiel informelle Siedlungen.

Universität Salzburg, Salzburg, Österreich.

(2005)

Hochschulschrift

Peter Hofmann

Übertragbarkeit von Methoden und Verfahren in der objektorientierten Bildanalyse - das Beispiel informelle Siedlungen.

Universität Salzburg, Salzburg, Österreich.

(2005)

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Beitrag in Sammelwerk/Tagungsband

M. Ridd
E. Bjorgo
L. Camp
D. Card
J. Chung
E. Dudley-Murphy
R. Gillies
J. Hipple
M. Hernandez
Peter Hofmann

Documenting Dynamics of Human Settlements (Chapter 10).

In:
A. Rencz
J. Hipple
M. Ridd

New York: John Wiley & Sons

(2005)

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Beitrag in Sammelwerk/Tagungsband

T. Blaschke
Peter Hofmann
I. Georg
E. Schöpfer
D. Tiede
S. Lang
M. Möller
E. Araújo
H. Kux

Möglichkeiten und Grenzen der Fernerkundung für das Monitoring und Safeguarding informeller Siedlungen: Eine Synthese.

In:
E. Seyfert

pg. 361-374

(2007)

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Zeitschriftenartikel

Peter Hofmann
P. Lohmann
S. Müller

Concepts of an object-based change detection process chain for GIS update.

In: International Archives of Photogrammetry and Remote Sensing (vol. 37) , pg. 305-312

(2008)

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Zeitschriftenartikel

O. Buescher
O. Buck
P. Lohmann
Peter Hofmann
S. Mueller
R. Schenkel
C. Weise

Change Detection for Updating DeCOVER Object Classes.

In: Photogrammetrie, Fernerkundung, Geoinformation (PFG) , pg. 395-407

(2008)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
P. Lohmann
S. Müller

Change Detection by Object-Based Change Indications.

In:
European Association of Remote Sensing Laboratories

vol. 8 pg. 4-7

(2008)

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Zeitschriftenartikel

O. Büscher
O. Buck
P. Lohmann
Peter Hofmann
S. Müller
R. Schenkel
C. Weise

Einsatz von Change Detection Methoden zur Fortführung von DeCOVER Objektarten.

In: Photogrammetrie, Fernerkundung, Geoinformation (PFG) , pg. 397-408

(2008)

Abstract anzeigen

Change Detection for Updating DeCOVER Object Classes. Advancing technical means - just consider the current satellite systems RapidEye or TerraSAR-X - aswell as new Euro-peanlegislationsuch as the Water Framework Directive or INSPIRE bringing new reporting obligations, lead to continuously increasing geoinformation demand by administrative authorities. Existing geospatial information systems such as the German Authoritative Topographic and Cartographic Information System (ATKIS@)or the Euopean CORINE Land Cover (CLC) can not fully meet this demand, bringing the focus to current studies and developments to update and refne these geodata he project aim is to develop a concept to establish and update land cover and land use information via geospatial web services based on up-to-date remote sensing information. This article presents the fundamental aspects and latest results of the DeCOVER project, such as the sequential processing chain. It focuses on the developed change detection methodology, which is an integral part of DeCOVER. Diferent change indicators are implemented based on a comparison ofthe input satellite data ofdiferent dates. These indicators in combination with a transition-probability-matrix are used to limit the new possible classes and control the subsequent recursive processing to verify the indicated changes according to the probabilities of change. The results of the proposed object-based change detection process chain are compared to change-detection results obtained by completelyvisual interpretation. Finally all results are assembled to aresultant change indication map.

Beitrag in Sammelwerk/Tagungsband

C. Heipke
Peter Hofmann
P. Lohmann
S. Müller

Concepts of an Object-Based Change Detection Process Chain for GIS Update.

In:
International Society for Photogrammetry and Remote Sensing

(2008)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

Detecting informal settlements using methods of object-based image analysis.

Presentation at Expert Group on Slum Identification Using Geo-Information Technology.

pg. 21-23

(2008)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
J. Strobl
T. Blaschke
H. Kux

Detecting informal settlements from Quickbird data in Rio de Janeiro using an object based approach.

In:
G. Hay
T. Blaschke
S. Lang

Berlin, Heidelberg: Springer pg. 531-553

DOI: 10.1007/978-3-540-77058-9_29

(2008)

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Beitrag in Sammelwerk/Tagungsband

P. Lohmann
Peter Hofmann
S. Müller

Updating GIS by object-based change detection.

In:
J. Schiewe
U. Michel

pg. 81-86

(2008)

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Beitrag in Sammelwerk/Tagungsband

R. Marschallinger
S. Golaszewski
J. Kraus
M. Kronbichler
A. Kunz
Peter Hofmann

Multiple Sclerosis: a Multidisciplinary Approach to the Analysis, 4D Modeling and Spatiotemporal Simulation of Lesion Pattern Evolution.

(2009)

Beitrag in Sammelwerk/Tagungsband

G. Atay
J. Wegner
P. Lohmann
Peter Hofmann
U. Sörgel

Comparison of pixel based and feature based fusion of high resolution optical and SAR imagery.

In:
D. Maktav

Turkey: IOS Press pg. 214-219

(2009)

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Beitrag in Sammelwerk/Tagungsband

A. Nazarkulova
J. Strobl
Peter Hofmann

Green Spaces in Bishkek - A Satellite Perspective.

(2010)

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Beitrag in Sammelwerk/Tagungsband

R. Marschallinger
Peter Hofmann

The application of object based image analysis to petrographic micrographs.

In:
J. Díaz
A. Méndez-Vilas

Badajoz: Formatex Research Center pg. 1526-1532

(2010)

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Zeitschriftenartikel

Peter Hofmann
J. Strobl
A. Nazarkulova

Mapping green spaces in Bishkek—how reliable can spatial analysis be?.

In: Remote Sensing (vol. 3) , pg. 1088-1103

(2011)

DOI: 10.3390/rs3061088

Abstract anzeigen

Within urban areas, green spaces play a critically important role in the quality of life. They have remarkable impact on the local microclimate and the regional climate of the city. Quantifying the ‘greenness’ of urban areas allows comparing urban areas at several levels, as well as monitoring the evolution of green spaces in urban areas, thus serving as a tool for urban and developmental planning. Different categories of vegetation have different impacts on recreation potential and microclimate, as well as on the individual perception of green spaces. However, when quantifying the ‘greenness’ of urban areas the reliability of the underlying information is important in order to qualify analysis results. The reliability of geo-information derived from remote sensing data is usually assessed by ground truth validation or by comparison with other reference data. When applying methods of object based image analysis (OBIA) and fuzzy classification, the degrees of fuzzy membership per object in general describe to what degree an object fits (prototypical) class descriptions. Thus, analyzing the fuzzy membership degrees can contribute to the estimation of reliability and stability of classification results, even when no reference data are available. This paper presents an object based method using fuzzy class assignments to outline and classify three different classes of vegetation from GeoEye imagery. The classification result, its reliability and stability are evaluated using the reference-free parameters Best Classification Result and Classification Stability as introduced by Benz et al. in 2004 and implemented in the software package eCognition (www.ecognition.com). To demonstrate the application potentials of results a scenario for quantifying urban ‘greenness’ is presented.

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
R. Marschallinger
M. Unterwurzacher
F. Zobl

Designation of marble provenance: State-of-the-art rock fabric characterization in thin sections by object based image analysis.

In:
International Association for Mathematical Geosciences

pg. 1-14

(2011)

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Zeitschriftenartikel

R. Marschallinger
Peter Hofmann
G. Daxner-Höck
R. Ketcham

Solid modeling of fossil small mammal teeth.

In: Computers & Geosciences (vol. 37) , pg. 1364-1371

(2011)

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Zeitschriftenartikel

Peter Hofmann
T. Blaschke
J. Strobl

Quantifying the robustness of fuzzy rule sets in object-based image analysis.

In: International Journal of Remote Sensing (vol. 32) , pg. 7359-7381

(2011)

DOI: 10.1080/01431161.2010.523727

Abstract anzeigen

Object-based image analysis (OBIA) has become very popular since the turn of the century. For high-resolution situations, in particular, where the objects of interest are larger than pixels, methods have been developed that build on image segmentation and on the further classification of objects rather than on pixels. Many studies have shown that OBIA methods are, in principle, more transferable and reapplicable to other images. To obtain comparable results by reapplying a given rule set on (slightly) changed conditions, the rule set must either be able to adapt to the changed conditions or it must be parameterized for manual adaptation. In this context, a rule set can be seen as the more robust the less it has to be changed, and vice versa. In this article we introduce a new method to evaluate the robustness of a rule set. The main assumption is that the amount of necessary adaptations can be measured in conjunction with the quality of classification achieved. We demonstrate that the method introduced is able to (1) evaluate the robustness of a rule set and (2) identify crucial elements of a rule set that need to be reparameterized.

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
R. Marschallinger
G. Daxner-Höck

3D Volumen-Modellierung fossiler Kleinsäugerzähne mittels Mikro-Computertomographie und objektbasierter Bildanalyse.

(2011)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
T. Blaschke

Object based change detection using temporal linkages.

pg. 634-638

(2012)

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Beitrag in Sammelwerk/Tagungsband

R. Marschallinger
S. Golaszewski
A. Kunz
Peter Hofmann
J. Kraus

Some Brainwork: Geostatistics for Fingerprinting MS Lesion Patterns in Space and Time.

(2013)

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Zeitschriftenartikel

Peter Hofmann
R. Marschallinger
M. Unterwurzacher
F. Zobl

Marble provenance designation with Object Based Image Analysis: State-of-the-art rock fabric characterization from petrographic micrographs.

In: Austrian Journal of Earth Sciences (vol. 106/2) , pg. 40-49

(2013)

Abstract anzeigen

The designation of marble provenance plays an important role in Cultural History, Archeology and Geosciences in general. In the multidisciplinary approach to explore marble provenance, petrography plays a key role. This paper presents a novel method for automatic image analysis of marble micrographs: Object Based Image Analysis (OBIA), via the incorporation of petrographic expert knowledge, enables the reliable extraction of mineral grains and yields a wealth of quantitative shape and texture measures. A work flow is introduced for extracting mineral shape characteristics from marble micrographs, comprising data acquisition, pre-processing and Object Based Image Analysis. Therefore verifiable parameters and analysis supply marble provenance research particularly for multiple sample analysis in an efficient and timely manner.

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Zeitschriftenartikel

T. Blaschke
G. Hay
M. Kelly
S. Lang
Peter Hofmann
E. Addink
R. Queiroz Feitosa
van der Meer, F.
van der Werff, H.
F. van Coillie
D. Tiede

Geographic Object-Based Image Analysis – Towards a new paradigm.

In: ISPRS Journal of Photogrammetry and Remote Sensing (vol. 87) , pg. 180-191

(2014)

DOI: 10.1016/j.isprsjprs.2013.09.014

Abstract anzeigen

The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

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Zeitschriftenartikel

C. Leitner
Peter Hofmann
R. Marschallinger

3D-modeling of deformed halite hopper crystals by Object Based Image Analysis.

In: Computers & Geosciences (vol. 73) , pg. 61-70

(2014)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

Defining robustness measures for OBIA framework: A case study for detecting informal settlements.

In:
Q. Weng

Boca Raton, FL: CRC Press vol. Chapter 16 pg. 303-324

DOI: 10.1201/b17012-21

(2014)

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Zeitschriftenartikel

Peter Hofmann
P. Lettmayer
T. Blaschke
M. Belgiu
S. Wegenkittl
R. Graf
T. Lampoltshammer
V. Andrejchenko

ABIA – A Conceptual Framework for Agent Based Image Analysis.

In: South-Eastern European Journal of Earth Observation and Geomatics (vol. 3) , pg. 125-130

(2014)

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Beitrag in Sammelwerk/Tagungsband

C. Leitner
Peter Hofmann
R. Marschallinger

3D-Modeling of deformed halite hopper crystals: Object based image analysis and support vector machine, a first evaluation.

pg. 5210

(2014)

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Zeitschriftenartikel

R. Marschallinger
S. Golaszewski
A. Kunz
M. Kronbichler
G. Ladurner
Peter Hofmann
E. Trinka
M. McCoy
J. Kraus

Usability and Potential of Geostatistics for Spatial Discrimination of Multiple Sclerosis Lesion Patterns.

In: Journal of Neuroimaging (Experimental Laboratory Research) (vol. 24) , pg. 278-86

(2014)

DOI: 10.1111/jon.12000

Abstract anzeigen

BACKGROUND AND PURPOSE In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. METHODS We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. RESULTS By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. CONCLUSIONS This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives.

Zeitschriftenartikel

M. Belgiu
B. Hofer
Peter Hofmann

Coupling formalized knowledge bases with object-based image analysis.

In: Remote Sensing Letters (vol. 5) , pg. 530-538

(2014)

DOI: 10.1080/2150704X.2014.930563

Abstract anzeigen

Object-based image analysis (OBIA) is a widely used method for knowledge-based interpretation of very high resolution imagery. It relies on expert knowledge to classify the desired classes from the imagery at hand. The definition of classes is subjective, usually project-specific and not shared with the community. Ontologies as a form of knowledge representation technique are acknowledged as solution to establish and document class definitions independently of an OBIA framework. However, ontologies have not yet been strongly integrated in this image analysis framework. This paper presents a method to automatically integrate ontologies in OBIA. The method has been implemented as a tool to be used with the eCognition® software (Trimble, Sunnyvale, CA, USA). A case study was conducted for classifying the land cover classes defined by the Environment Agency of Austria in the Land Information System Austria (LISA) project using WorldView-2 image. The strength of this approach is the direct integration of ontologies into the OBIA process, which reduces the effort necessary to define the classes for image analysis and simultaneously reduces its subjectivity.

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Zeitschriftenartikel

Peter Hofmann
D. Tiede

Image Segmentation Based on Hexagonal Sampling Grids.

In: South-Eastern European Journal of Earth Observation and Geomatics (vol. 3) , pg. 173-178

(2014)

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Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
H. Taubenböck
C. Werthmann

Monitoring and Modelling of Informal Settlements – a Review on Recent Developments and Challenges.

In:
Institute of Electrical and Electronics Engineers Inc.

(2015)

Zeitschriftenartikel

A. Dudkiewicz
Boxall, A. B. A.
Q. Chaudhry
K. Mølhave
K. Tiede
Peter Hofmann
Linsinger, T. P. J.

Uncertainties of size measurements in electron microscopy characterization of nanomaterials in foods.

In: Food Chemistry (vol. 176) , pg. 472-479

(2015)

DOI: 10.1016/j.foodchem.2014.12.071

Abstract anzeigen

Electron microscopy is a recognized standard tool for nanomaterial characterization, and recommended by the European Food Safety Authority for the size measurement of nanomaterials in food. Despite this, little data have been published assessing the reliability of the method, especially for size measurement of nanomaterials characterized by a broad size distribution and/or added to food matrices. This study is a thorough investigation of the measurement uncertainty when applying electron microscopy for size measurement of engineered nanomaterials in foods. Our results show that the number of measured particles was only a minor source of measurement uncertainty for nanomaterials in food, compared to the combined influence of sampling, sample preparation prior to imaging and the image analysis. The main conclusion is that to improve the measurement reliability, care should be taken to consider replications and matrix removal prior to sample preparation.

Zeitschriftenartikel

Peter Hofmann
P. Lettmayer
T. Blaschke
M. Belgiu
S. Wegenkittl
R. Graf
T. Lampoltshammer
V. Andrejchenko

Towards a framework for agent-based image analysis of remote-sensing data.

In: International Journal of Image and Data Fusion (vol. 6) , pg. 115-137

(2015)

DOI: 10.1080/19479832.2015.1015459

Abstract anzeigen

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
V. Andrejchenko
P. Lettmayer
M. Schmitzberger
M. Belgiu
R. Graf
et al.

Agent Based Image Analysis (ABIA) - preliminary research results from an implemented framework.

(2016)

Zeitschriftenartikel

R. Marschallinger
P. Schmidt
Peter Hofmann
C. Zimmer
P. Atkinson
J. Sellner
E. Trinka
M. Mühlau

A MS-lesion pattern discrimination plot based on geostatistics.

In: Brain and Behaviour (vol. 6)

(2016)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
V. Andrejchenko
P. Lettmayer
M. Schmitzberger
M. Gruber
I. Ozan
M. Belgiu
R. Graf
T. Lampoltshammer
S. Wegenkittl

Agent based image analysis (ABIA)-preliminary research results from an implemented framework.

In:
University of Twente

(2016)

Beitrag in Sammelwerk/Tagungsband

G.A.O.P. Costa
Peter Hofmann
P. Happ
R. Feitosa

An object-based meta knowledge model for a distributed image interpretation system.

In:
University of Twente

(2016)

Zeitschriftenartikel

Peter Hofmann

Defuzzification Strategies for Fuzzy Classifications of Remote Sensing Data.

In: Remote Sensing (vol. 8) , pg. 467-490

(2016)

DOI: 10.3390/rs8060467

Abstract anzeigen

The classes in fuzzy classification schemes are defined as fuzzy sets, partitioning the feature space through fuzzy rules, defined by fuzzy membership functions. Applying fuzzy classification schemes in remote sensing allows each pixel or segment to be an incomplete member of more than one class simultaneously, i.e., one that does not fully meet all of the classification criteria for any one of the classes and is member of more than one class simultaneously. This can lead to fuzzy, ambiguous and uncertain class assignation, which is unacceptable for many applications, indicating the need for a reliable defuzzification method. Defuzzification in remote sensing has to date, been performed by “crisp-assigning” each fuzzy-classified pixel or segment to the class for which it best fulfills the fuzzy classification rules, regardless of its classification fuzziness, uncertainty or ambiguity (maximum method). The defuzzification of an uncertain or ambiguous fuzzy classification leads to a more or less reliable crisp classification. In this paper the most common parameters for expressing classification uncertainty, fuzziness and ambiguity are analysed and discussed in terms of their ability to express the reliability of a crisp classification. This is done by means of a typical practical example from Object Based Image Analysis (OBIA).

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

A Fuzzy Belief-Desire-Intention Model for Agent-Based Image Analysis (Chapter 14).

In:
S. Ramakrishnan

IntechOpen

(2017)

Monographie

R. Marschallinger
Peter Hofmann
F. Zobl
A. Klammer
M. Lagger
W. Schubert

ROCKBURST: Devastating micro cracks: researching spontaneous rock failure with rock mechanical testing, μCT, OBIA and geostatistics FFG-BRIDGE Early stage. Marschallinger R, Hofmann P, Zobl F, Klammer A, Lagger M, Schubert W. 2017..

Salzburg, Austria: Geoinformatics, Faculty of Digital and Analytical Sciences, Paris Lodron University of Salzburg

(2017)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
G. Bekkarnayeva

Object-Based Change Detection of Informal Settlements.

(2017)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
M. Hais
M. Heurich
Rainer Pöschl
Stefan Kunze
M. Novak
P. Doležal
S. Grill
M. Davídková
M. Prokýšek
M. Stary
Wolfgang Dorner

3D Hyperspectral and Thermal Analysis of Forest Trees Focusing on Bark Beetle Infestation.

In:
Espace pour le développement
Office national détudes et de recherches aérospatiales
Centre dEtudes Spatiales de la BIOsphère
UMR TETIS

(2018)

Beitrag in Sammelwerk/Tagungsband

Wolfgang Dorner
Luis Ramirez Camargo
Peter Hofmann

Can Geoinformation Help to Better Protect Informal Settlements? - A Concept For the City of Medellín.

In:
T. Tanzi
F. Sunar
M. Chandra
O. Altan

pg. 115-120

DOI: 10.5194/isprs-archives-XLII-3-W8-115-2019

(2019)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann

Multi-agent Systems in Remote Sensing Image Analysis.

In:
A. Rocha
J. van den Herik
L. Steels

pg. 187-185

(2019)

Beitrag in Sammelwerk/Tagungsband

L. Gottsbacher
R. Ketcham
F. Zobl
R. Marschallinger
W. Schubert
A. Klammer
D. Edey
Peter Hofmann

Catching failure in the act: mapping fracture initiation and spreadingusing X-ray tomography.

(2019)

Beitrag in Sammelwerk/Tagungsband

R. Marschallinger
Peter Hofmann
F. Zobl
R. Ketcham
D. Edey
L. Gottsbacher
A. Klammer
W. Schubert

A method and work flow for quantifying Rock Burst in 4D.

(2019)

Beitrag in Sammelwerk/Tagungsband

L. Gottsbacher
A. Klammer
W. Schubert
R. Marschallinger
Peter Hofmann
F. Zobl
R. Ketcham
D. Edey

Combination of Various Laboratory Tests to Investigate Rock Burst.

Paper Number: ISRM-14CONGRESS-2019-198.

(2019)

Beitrag in Sammelwerk/Tagungsband

Z. Dabiri
S. Lang
Peter Hofmann

Laplacian of Gaussian and Gram-Schmidt Image Fusion Using Airborne APEX Hyperspectral and WorldView-2 Panchromatic Image.

(2019)

Zeitschriftenartikel

A. Dudkiewicz
A. Lehner
Q. Chaudhry
K. Molhave
G. Allmaier
K. Tiede
Boxall, A. B. A.
Peter Hofmann
J. Lewis

Development of a sample preparation approach to measure the size of nanoparticle aggregates by electron microscopy.

In: Particuology (vol. 45) , pg. 49-57

(2019)

DOI: 10.1016/j.partic.2018.05.007

Abstract anzeigen

Electron microscopy (EM) is widely used for nanoparticle (NP) sizing. Following an initial assessment of two sample preparation protocols described in the current literature as “unperturbed”, we found that neither could accurately measure the size of NPs featuring a broad size distribution, e.g., aggregates. Because many real-world NP samples consist of aggregates, this finding was of considerable concern. The data showed that the protocols introduced errors into the measurement by either inducing agglomeration artefacts or providing a skewed size distribution towards small particles (skewing artefact). The focus of this work was to develop and apply a mathematical refinement to correct the skewing artefact. This refinement provided a much improved agreement between EM and a reference methodology, when applied to the measurement of synthetic amorphous silica NPs. Further investigation, highlighted the influence of NP chemistry on the refinement. This study emphasised the urgent need for greater and more detailed consideration regarding the sample preparation of NP aggregates to routinely achieve accurate measurements by EM. This study also provided a novel refinement solution applicable to the size characterisation of silica and citrate-coated gold NPs featuring broad size distributions. With further research, this approach could be extended to other NP types

Beitrag in Sammelwerk/Tagungsband

M. Novàk
M. Prokýšek
P. Doležal
M. Hais
S. Gril
M. Davídková
J. Geyer
Peter Hofmann
Rajan Paudyal

Multisensor UAV System for the Forest Monitoring.

pg. 293-296

DOI: 10.1109/ACIT49673.2020.9208993

(2020)

Beitrag in Sammelwerk/Tagungsband

M. Novàk
J. Geyer
M. Prokýšek
M. Hais
S. Gril
M. Davidková
P. Doležal
Peter Hofmann
Rajan Paudyal

Construction of a Multisensor UAV System for Early Detection of Forest Pests.

In:
N. Shakhovska
M. Medykovskyy

Cham, Switzerland: Springer pg. 1164-1182

(2020)

Beitrag in Sammelwerk/Tagungsband

Peter Hofmann
Nichita Trofanisin
Sebastian Wöllmann

Automatic Delineation of Burned Forest Areas from Satellite Imagery to Analyze and Manage Wildfires.

IEEE pg. 766-771

DOI: 10.1109/ACIT62333.2024.10712578

(2024)

Zeitschriftenartikel

C. Shatto
M. Kiene
Peter Hofmann
A. Walentowitz
V. Wilkens
T. Heuser
F. Weiser

Assessing the recovery of Pinus canariensis stands after wildfires and volcanic eruption on La Palma, Canary Islands.

In: Forest Ecology and Management (vol. 572) , pg. 122317

(2024)

DOI: 10.1016/j.foreco.2024.122317

Abstract anzeigen

The exposure of insular species to local disturbances can influence their evolutionary trajectory resulting in specific adaptations. On the island La Palma, Canary Islands, the archipelago-endemic tree species Pinus canariensis forms forest ecosystems and has been described to be adapted to wildfires. The frequency of these in the recent past, however, is higher due to anthropogenic activities. Recent studies suggest that the species traits might also be an evolutionary response to volcanic outbreaks, consisting of massive sulfur dioxide (SO₂) emissions and ash fall. Several stands of P. canariensis have been exposed to both disturbances, wildfires and volcanic outbreaks, in the recent past. We assess the recovery of P. canariensis after double exposure to these disturbances. P. canariensis recovery was assessed based on Sentintel-2 NDVI images within a 7 km radius of the craters of the Tajogaite volcano that erupted in 2021. Within the same area, wildfires occurred in 2009, 2012 and 2016. We used a Generalized Additive Model (GAM) to assess the recovery of P. canariensis after volcanic and wildfire disturbances. The model shows the P. canariensis forest recovers after the volcanic outbreak with a peak at a distance of 1000–1200 m to the eruption crater, which is in line with our first hypothesis. Our second hypothesis was met with unexpected results, forests exposed to the recent wildfire in 2016 showed an increased recovery, which underlines that P. canariensis exhibits traits related to fire adaptation or might also be the result of stand-specific characteristics such as forest height or local topography. The double pressure of volcanic and forest fire disturbances did not lead to suppressed recovery of the Canary-endemic tree species and highlights the resilience of P. canariensis.

Zeitschriftenartikel

Marc Luger
A. Seidel
Ursula Pähler
Sebastian Schröck
Peter Hofmann
Sebastian Kölbl
K. Drechsler

An Ontology‐Augmented Digital Twin for Fiber‐Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades.

In: Advanced Engineering Materials , pg. 1-19

(2025)

DOI: 10.1002/adem.202401437

Abstract anzeigen

A methodology for establishing a structural digital twin is proposed to facilitate the lifetime prediction of fiber-reinforced polymer (FRP) structures, in this case, a wind turbine rotor blade. The digital twin incorporates production peculiarities and imperfections occurring during the manufacturing process of the FRP component. The methodology involves the computation of process-defined effective elastic properties and residual stresses through numerical simulation of the resin cure cycle. The results are then transferred to a structural finite-element model. By applying local wind conditions to this model, a comprehensive state of stress is obtained. This serves as a basis for a practical evaluation of material fatigue within the composite, leading to the prediction of the component's lifetime. The entire workflow is implemented in a Jupyter-based application that uses an ontology with an appertaining knowledge graph to facilitate the transfer of intermediate results between the observation scales and process steps of the digital twin. In line with the principles of open science, the methodology utilizes open-source software.