Abstract: Cities are complex systems composed of numerous interacting components that evolve over... more Abstract: Cities are complex systems composed of numerous interacting components that evolve over multiple spatio-temporal scales. Consequently, no single data source is sufficient to satisfy the information needs required to map, monitor, model, and ultimately understand and manage our interaction within such urban systems. Remote sensing technology provides a key data source for mapping such environments, but is not sufficient for fully understanding them. In this article we provide a condensed urban perspective of critical geospatial technologies and techniques: (i) Remote Sensing; (ii) Geographic Information Systems; (iii) object-based image analysis; and (iv) sensor webs, and recommend a holistic integration of these technologies within the language of open geospatial consortium (OGC) standards in-order to more fully understand urban systems. We then discuss the potential of this integration and conclude that this extends the monitoring and mapping options beyond “hard infrastr...
In Austria about half of the entire area (46 %) is covered by forests. The majority of these are ... more In Austria about half of the entire area (46 %) is covered by forests. The majority of these are highly managed and controlled in growth. But besides timber production forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among climatic, ecological, social and economic dimensions of forests require technologies for monitoring both the state and the development of forests. This comprises forest structure, species and age composition and, forest integrity in general. Assessing forest structure for example enables forest managers and natural risk engineers to evaluate whether a forest can fulfil its protective function or not. Traditional methods for assessing forest structure like field inventories and aerial photo interpretation are intrinsically limited in providing spatially continuous information over a large area. The Centre for Geoinformatics (Z_GIS) in collaboratio...
Although typically small in terms of their spatial footprint, landslide hazards are relatively fr... more Although typically small in terms of their spatial footprint, landslide hazards are relatively frequent in Northern Iran. We assess landslide susceptibility for the nearly 20.000 km2 large study area of the Urmia lake basin which is dominated by agricultural land use but includes the major settlements areas of the East Azerbaijan province, Iran. Landslide factors are established in form of GIS dataset layers including topography, geology, climatology and land use. After pre-processing all data layers are standardized based on a fuzzy logic model. An Analytical Hierarchical Process (AHP) delivers the weights for the GIS-analysis. Datasets are combined by GIS spatial analysis techniques and a landslide susceptibility map of the study area is created. An existing inventory of known landslides within the case study area was compared with the resulting susceptibility map. We found that high susceptible zones cover about 4.47% (944 km2) of the total area whereby geological outcrops of sed...
ISPRS International Journal of Geo-Information, 2018
Around the globe, Geographic Information Systems (GISs) are well established in the daily workflo... more Around the globe, Geographic Information Systems (GISs) are well established in the daily workflow of authorities, businesses and non-profit organisations. GIS can effectively handle spatial entities and offer sophisticated analysis and modelling functions to deal with space. Only a small fraction of the literature in Geographic Information Science—or GIScience in short—has advanced the development of place, addressing entities with an ambiguous boundary and relying more on the human or social attributes of a location rather than on crisp geographic boundaries. While the GIScience developments support the establishment of the digital humanities, GISs were never designed to handle subjective or vague data. We, an international group of authors, juxtapose place and space in English language and in several other languages and discuss potential consequences for Geoinformatics and GIScience. In particular, we address the question of whether linguistic and cultural settings play a role in...
ISPRS International Journal of Geo-Information, 2018
Parks are essential public places and play a central role in urban livability. However, tradition... more Parks are essential public places and play a central role in urban livability. However, traditional methods of investigating their attractiveness, such as questionnaires and in situ observations, are usually time- and resource-consuming, while providing less transferable and only site-specific results. This paper presents an improved methodology of using social media (Twitter) data to extract spatial and temporal patterns of park visits for urban planning purposes, along with the sentiment of the tweets, focusing on frequent Twitter users. We analyzed the spatiotemporal park visiting behavior of more than 4000 users for almost 1700 parks, examining 78,000 tweets in London, UK. The novelty of the research is in the combination of spatial and temporal aspects of Twitter data analysis, applying sentiment and emotion extraction for park visits throughout the whole city. This transferable methodology thereby overcomes many of the limitations of traditional research methods. This study co...
ISPRS International Journal of Geo-Information, 2017
A challenge in regional inequality is to identify the relative influence of objective neighborhoo... more A challenge in regional inequality is to identify the relative influence of objective neighborhood context on subjective citizens’ attitudes and experiences of place. This paper first presents six groups of hierarchal neighborhoods in optimizing public service inequality (PSI) indicators based on census blocks collected in Quito, Ecuador. Multilevel models were then applied to understand the relative influence of neighborhood-level PSI on citizens’ perceptions of place, including individual-level perceptions of neighborhood social cohesion and neighborhood safety, and self-perceived health status. Our results show that the internal variability of the individual perceptions that is explained by neighborhood context is strongly influenced by the scale of neighborhood units. A spatial consistency between objective neighborhood context and subjective individual perception of place plays a crucial role in propagating mixed-methods approaches (qualitative-quantitative) and improves the sp...
ABSTRACT This research presents a semi-automated object-based image analysis (OBIA) methodology f... more ABSTRACT This research presents a semi-automated object-based image analysis (OBIA) methodology for landslide delineation and change detection analysis from multi-temporal satellite images for a study area in North-West Iran. The approach applies fuzzy set theory for rule based classification while systematically utilizing advantages of membership functionalities in OBIA, both for the spatial and spectral information dimensions of landslides. Several fuzzy logic membership functions are employed to combine spectral analysis, shape analysis and textural measurements using gray-level co-occurrence matrix (GLCM). Objects are generated by applying multi-resolution segmentation in a sequence of feature selection and object classification steps applied to different satellite imagery (IRS-1D, SPOT-5 and ALOS PalSar) together with slope and flow direction derivatives from a digital elevation model and topographically-oriented gray level co-occurrence matrices. After the generation and optimization of the multi-resolution image segmentation a fuzzy rule object based classification is performed and 42 spatial and spectral parameters for detecting landslides in the study area are identified. Fuzzy membership values for 11 membership functions are calculated by using 20 landslide objects as training data which are taken from a landslide inventory database. We employ six different operators for the object based classifications and compare the accuracies of the resulting landslide maps based on a Fuzzy Synthetic Evaluation (FSE) approach and by using the landslide inventory database. Results of this research demonstrate that that the accuracy of fuzzy rule based classification is significantly affected by the choice of the fuzzy operators. In this respect, FSE turns out to be particularly appropriate to assess the accuracy of fuzzy based classifications.
During March and April 2010 aerosol inventories from four large cities in Pakistan were assessed ... more During March and April 2010 aerosol inventories from four large cities in Pakistan were assessed in terms of particle size distributions (N), mass (M) concentrations, and particulate matter (PM) concentrations. These M and PM concentrations were obtained for Karachi, Lahore, Rawalpindi, and Peshawar from N concentrations using a native algorithm based on the Grimm model 1.109 dust monitor. The results have confirmed high N, M and PM concentrations in all four cities. They also revealed major contributions to the aerosol concentrations from the re-suspension of road dust, from sea salt aerosols, and from vehicular and industrial emissions. During the study period the 24 hour average PM(10) concentrations for three sites in Karachi were found to be 461 μg m(-3), 270 μg m(-3), and 88 μg m(-3), while the average values for Lahore, Rawalpindi and Peshawar were 198 μg m(-3), 448 μg m(-3), and 540 μg m(-3), respectively. The corresponding 24 hour average PM(2.5) concentrations were 185 μg m(-3), 151 μg m(-3), and 60 μg m(-3) for the three sites in Karachi, and 91 μg m(-3), 140 μg m(-3), and 160 μg m(-3) for Lahore, Rawalpindi and Peshawar, respectively. The low PM(2.5)/PM(10) ratios revealed a high proportion of coarser particles, which are likely to have originated from (a) traffic, (b) other combustion sources, and (c) the re-suspension of road dust. Our calculated 24 hour averaged PM(10) and PM(2.5) concentrations at all sampling points were between 2 and 10 times higher than the maximum PM concentrations recommended by the WHO guidelines. The aerosol samples collected were analyzed for crustal elements (Al, Fe, Si, Mg, Ca) and trace elements (B, Ba, Cr, Cu, K, Na, Mn, Ni, P, Pb, S, Sr, Cd, Ti, Zn and Zr). The averaged concentrations for crustal elements ranged from 1.02 ± 0.76 μg m(-3) for Si at the Sea View location in Karachi to 74.96 ± 7.39 μg m(-3) for Ca in Rawalpindi, and averaged concentrations for trace elements varied from 7.0 ± 0.75 ng m(-3) for B from the SUPARCO location in Karachi to 17.84 ± 0.30 μg m(-3) for Na at the M. A. Jinnah Road location, also in Karachi.
Abstract: Cities are complex systems composed of numerous interacting components that evolve over... more Abstract: Cities are complex systems composed of numerous interacting components that evolve over multiple spatio-temporal scales. Consequently, no single data source is sufficient to satisfy the information needs required to map, monitor, model, and ultimately understand and manage our interaction within such urban systems. Remote sensing technology provides a key data source for mapping such environments, but is not sufficient for fully understanding them. In this article we provide a condensed urban perspective of critical geospatial technologies and techniques: (i) Remote Sensing; (ii) Geographic Information Systems; (iii) object-based image analysis; and (iv) sensor webs, and recommend a holistic integration of these technologies within the language of open geospatial consortium (OGC) standards in-order to more fully understand urban systems. We then discuss the potential of this integration and conclude that this extends the monitoring and mapping options beyond “hard infrastr...
In Austria about half of the entire area (46 %) is covered by forests. The majority of these are ... more In Austria about half of the entire area (46 %) is covered by forests. The majority of these are highly managed and controlled in growth. But besides timber production forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among climatic, ecological, social and economic dimensions of forests require technologies for monitoring both the state and the development of forests. This comprises forest structure, species and age composition and, forest integrity in general. Assessing forest structure for example enables forest managers and natural risk engineers to evaluate whether a forest can fulfil its protective function or not. Traditional methods for assessing forest structure like field inventories and aerial photo interpretation are intrinsically limited in providing spatially continuous information over a large area. The Centre for Geoinformatics (Z_GIS) in collaboratio...
Although typically small in terms of their spatial footprint, landslide hazards are relatively fr... more Although typically small in terms of their spatial footprint, landslide hazards are relatively frequent in Northern Iran. We assess landslide susceptibility for the nearly 20.000 km2 large study area of the Urmia lake basin which is dominated by agricultural land use but includes the major settlements areas of the East Azerbaijan province, Iran. Landslide factors are established in form of GIS dataset layers including topography, geology, climatology and land use. After pre-processing all data layers are standardized based on a fuzzy logic model. An Analytical Hierarchical Process (AHP) delivers the weights for the GIS-analysis. Datasets are combined by GIS spatial analysis techniques and a landslide susceptibility map of the study area is created. An existing inventory of known landslides within the case study area was compared with the resulting susceptibility map. We found that high susceptible zones cover about 4.47% (944 km2) of the total area whereby geological outcrops of sed...
ISPRS International Journal of Geo-Information, 2018
Around the globe, Geographic Information Systems (GISs) are well established in the daily workflo... more Around the globe, Geographic Information Systems (GISs) are well established in the daily workflow of authorities, businesses and non-profit organisations. GIS can effectively handle spatial entities and offer sophisticated analysis and modelling functions to deal with space. Only a small fraction of the literature in Geographic Information Science—or GIScience in short—has advanced the development of place, addressing entities with an ambiguous boundary and relying more on the human or social attributes of a location rather than on crisp geographic boundaries. While the GIScience developments support the establishment of the digital humanities, GISs were never designed to handle subjective or vague data. We, an international group of authors, juxtapose place and space in English language and in several other languages and discuss potential consequences for Geoinformatics and GIScience. In particular, we address the question of whether linguistic and cultural settings play a role in...
ISPRS International Journal of Geo-Information, 2018
Parks are essential public places and play a central role in urban livability. However, tradition... more Parks are essential public places and play a central role in urban livability. However, traditional methods of investigating their attractiveness, such as questionnaires and in situ observations, are usually time- and resource-consuming, while providing less transferable and only site-specific results. This paper presents an improved methodology of using social media (Twitter) data to extract spatial and temporal patterns of park visits for urban planning purposes, along with the sentiment of the tweets, focusing on frequent Twitter users. We analyzed the spatiotemporal park visiting behavior of more than 4000 users for almost 1700 parks, examining 78,000 tweets in London, UK. The novelty of the research is in the combination of spatial and temporal aspects of Twitter data analysis, applying sentiment and emotion extraction for park visits throughout the whole city. This transferable methodology thereby overcomes many of the limitations of traditional research methods. This study co...
ISPRS International Journal of Geo-Information, 2017
A challenge in regional inequality is to identify the relative influence of objective neighborhoo... more A challenge in regional inequality is to identify the relative influence of objective neighborhood context on subjective citizens’ attitudes and experiences of place. This paper first presents six groups of hierarchal neighborhoods in optimizing public service inequality (PSI) indicators based on census blocks collected in Quito, Ecuador. Multilevel models were then applied to understand the relative influence of neighborhood-level PSI on citizens’ perceptions of place, including individual-level perceptions of neighborhood social cohesion and neighborhood safety, and self-perceived health status. Our results show that the internal variability of the individual perceptions that is explained by neighborhood context is strongly influenced by the scale of neighborhood units. A spatial consistency between objective neighborhood context and subjective individual perception of place plays a crucial role in propagating mixed-methods approaches (qualitative-quantitative) and improves the sp...
ABSTRACT This research presents a semi-automated object-based image analysis (OBIA) methodology f... more ABSTRACT This research presents a semi-automated object-based image analysis (OBIA) methodology for landslide delineation and change detection analysis from multi-temporal satellite images for a study area in North-West Iran. The approach applies fuzzy set theory for rule based classification while systematically utilizing advantages of membership functionalities in OBIA, both for the spatial and spectral information dimensions of landslides. Several fuzzy logic membership functions are employed to combine spectral analysis, shape analysis and textural measurements using gray-level co-occurrence matrix (GLCM). Objects are generated by applying multi-resolution segmentation in a sequence of feature selection and object classification steps applied to different satellite imagery (IRS-1D, SPOT-5 and ALOS PalSar) together with slope and flow direction derivatives from a digital elevation model and topographically-oriented gray level co-occurrence matrices. After the generation and optimization of the multi-resolution image segmentation a fuzzy rule object based classification is performed and 42 spatial and spectral parameters for detecting landslides in the study area are identified. Fuzzy membership values for 11 membership functions are calculated by using 20 landslide objects as training data which are taken from a landslide inventory database. We employ six different operators for the object based classifications and compare the accuracies of the resulting landslide maps based on a Fuzzy Synthetic Evaluation (FSE) approach and by using the landslide inventory database. Results of this research demonstrate that that the accuracy of fuzzy rule based classification is significantly affected by the choice of the fuzzy operators. In this respect, FSE turns out to be particularly appropriate to assess the accuracy of fuzzy based classifications.
During March and April 2010 aerosol inventories from four large cities in Pakistan were assessed ... more During March and April 2010 aerosol inventories from four large cities in Pakistan were assessed in terms of particle size distributions (N), mass (M) concentrations, and particulate matter (PM) concentrations. These M and PM concentrations were obtained for Karachi, Lahore, Rawalpindi, and Peshawar from N concentrations using a native algorithm based on the Grimm model 1.109 dust monitor. The results have confirmed high N, M and PM concentrations in all four cities. They also revealed major contributions to the aerosol concentrations from the re-suspension of road dust, from sea salt aerosols, and from vehicular and industrial emissions. During the study period the 24 hour average PM(10) concentrations for three sites in Karachi were found to be 461 μg m(-3), 270 μg m(-3), and 88 μg m(-3), while the average values for Lahore, Rawalpindi and Peshawar were 198 μg m(-3), 448 μg m(-3), and 540 μg m(-3), respectively. The corresponding 24 hour average PM(2.5) concentrations were 185 μg m(-3), 151 μg m(-3), and 60 μg m(-3) for the three sites in Karachi, and 91 μg m(-3), 140 μg m(-3), and 160 μg m(-3) for Lahore, Rawalpindi and Peshawar, respectively. The low PM(2.5)/PM(10) ratios revealed a high proportion of coarser particles, which are likely to have originated from (a) traffic, (b) other combustion sources, and (c) the re-suspension of road dust. Our calculated 24 hour averaged PM(10) and PM(2.5) concentrations at all sampling points were between 2 and 10 times higher than the maximum PM concentrations recommended by the WHO guidelines. The aerosol samples collected were analyzed for crustal elements (Al, Fe, Si, Mg, Ca) and trace elements (B, Ba, Cr, Cu, K, Na, Mn, Ni, P, Pb, S, Sr, Cd, Ti, Zn and Zr). The averaged concentrations for crustal elements ranged from 1.02 ± 0.76 μg m(-3) for Si at the Sea View location in Karachi to 74.96 ± 7.39 μg m(-3) for Ca in Rawalpindi, and averaged concentrations for trace elements varied from 7.0 ± 0.75 ng m(-3) for B from the SUPARCO location in Karachi to 17.84 ± 0.30 μg m(-3) for Na at the M. A. Jinnah Road location, also in Karachi.
Object Based Image Analysis (OBIA) has meanwhile been established as a paradigm for analyzing rem... more Object Based Image Analysis (OBIA) has meanwhile been established as a paradigm for analyzing remotely sensed image data. Although the degree of automation for OBIA methods has increased for several applications, especially in the domain of remote sensing, robust and transferable object-based solutions for automated image analysis of sets of images or even large image archives are still rare. One of the reasons for this lack of robustness and transferability is the high complexity of remote sensing image contents: Especially in Very High Resolution (VHR) remote sensing data, under varying imaging conditions or sensor characteristics, the objects' properties can vary unpredictably. Although earlier work has demonstrated that OBIA rule sets bear a high potential of transferability these rule sets need to be adapted manually in order to receive acceptable results, or the 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 and robotics. The aims of such integration are a) rule sets which can be adapted autonomously according to varying imaging data, and b) image objects which can adapt and adjust themselves in order to best possibly represent the objects of interest in an image. This paper briefly introduces a framework for Agent Based Image Analysis (ABIA) and presents our first research results.
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Papers by Thomas Blaschke