ISPRS Int. J. Geo-Inf., Volume 5, Issue 8 (August 2016) – 21 articles

Banagrass is a biomass crop candidate for ethanol production in the State of Hawaii. This study examines: (i) whether enough banagrass can be produced to meet Hawaii’s renewable fuel target of 20% highway fuel demand produced with renewable sources by 2020 and (ii) at what cost. This study proposes to locate suitable land areas for banagrass production and ethanol processing, focusing on the two largest islands in the state of Hawaii—Hawaii and Maui. The results suggest that the 20% target is not achievable by using all suitable land resources for banagrass production on both Hawaii and Maui. A total of about 74,224,160 gallons, accounting for 16.04% of the state’s highway fuel demand, can be potentially produced at a cost of $6.28/gallon. Lower ethanol cost is found when using a smaller production scale. The lowest cost of $3.31/gallon is found at a production processing capacity of about 9 million gallons per year (MGY), which meets about 2% of state demand. This cost is still higher than the average imported ethanol price of $3/gallon. Sensitivity analysis finds that it is possible to produce banagrass-based ethanol on Hawaii Island at a cost below the average imported ethanol price if banagrass yield increases of at least 35.56%. Full article

Uncertainty in thematic maps has been tested mainly in maps with discrete or fuzzy classifications based on spectral data. However, many ecosystem maps in tropical countries consist of discrete polygons containing information on various ecosystem properties such as vegetation cover, soil, climate, geomorphology and biodiversity. The combination of these properties into one class leads to error. We propose a probability-based sampling design with two domains, multiple stages, and stratification with selection of primary sampling units (PSUs) proportional to the richness of strata present. Validation is undertaken through field visits and fine resolution remote sensing data. A pilot site in the center of the Colombian Andes was chosen to validate a government official ecosystem map. Twenty primary sampling units (PSUs) of 10 × 15 km were selected, and the final numbers of final sampling units (FSUs) were 76 for the terrestrial domain and 46 for the aquatic domain. Our results showed a confidence level of 95%, with the accuracy in the terrestrial domain varying between 51.8% and 64.3% and in the aquatic domain varying between 75% and 92%. Governments need to account for uncertainty since they rely on the quality of these maps to make decisions and guide policies. Full article

Until now, road network generalization has mainly been applied to the task of generalizing from one fixed source scale to another fixed target scale. These actions result in large differences in content and representation, e.g., a sudden change of the representation of road segments from areas to lines, which may confuse users. Therefore, we aim at the continuous generalization of a road network for the whole range, from the large scale, where roads are represented as areas, to mid- and small scales, where roads are represented progressively more frequently as lines. As a consequence of this process, there is an intermediate scale range where at the same time some roads will be represented as areas, while others will be represented as lines. We propose a new data model together with a specific data structure where for all map objects, a range of valid map scales is stored. This model is based on the integrated and explicit representation of: (1) a planar area partition; and (2) a linear road network. This enables the generalization process to include the knowledge and understanding of a linear network. This paper further discusses the actual generalization options and algorithms for populating this data structure with high quality vario-scale cartographic content. Full article

Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1) It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2) It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency. Full article

Soil moisture plays an important role in understanding climate change and hydrology, and L-band passive microwave radiometers have been verified as effective tools for monitoring soil moisture. This paper proposes a novel, simplified algorithm for bare surface soil moisture retrieval using L-band radiometer. The algorithm consists of two sub-algorithms: a surface emission model and a soil moisture retrieval model. In analyses of the advanced integral equation model (AIEM) simulated database, the surface emission model was developed to diminish the effects of surface roughness using dual-polarization surface reflectivity. The soil moisture retrieval model, which was calibrated using the Dobson simulated database, is based on the relationship between the adjusted real refractive index $N_r$ and the volumetric soil moisture. Soil moisture can be determined via a numerical solution that uses several freely available input parameters: dual-polarization microwave brightness temperature, surface temperature, and the contents of sand and clay. The results showed good agreement with the input soil moisture values simulated by the AIEM model, with root mean square errors (RMSEs) lower than 3% at all incidence angles. The algorithm was then verified based on data from the four-year L-band experiments conducted at Beltsville Agricultural Research Center (BARC) test sites, achieving RMSEs of 4.3% and 3.4% at 40° and 50°, respectively. These results indicate that the simplified algorithm proposed in this paper shows a very good accuracy in soil moisture retrieval. Additionally, the algorithm exhibits a better performance for the large incidence angle radiometers in L-band such as those produced by the Soil Moisture Active and Passive (SMAP). Full article

Knowledge of the German building stock is largely based on census data and annual construction statistics. Despite the wide range of statistical data, they are constrained in terms of temporal, thematic and spatial resolution, and hence do not satisfy all requirements of spatial planning and research. In this paper, we describe a new workflow for data integration that allows the quantification of the structure and dynamic of national building stocks by analyzing authoritative geodata. The proposed workflow has been developed, tested and demonstrated exemplarily for the whole country of Germany. We use nationwide and commonly available authoritative geodata products such as building footprint and address data derived from the real estate cadaster and land use information from the digital landscape model. The processing steps are (1) data preprocessing; (2) the calculation of building attributes; (3) semantic enrichment of the building using a classification tree; (4) the intersection with spatial units; and finally (5) the quantification and cartographic visualization of the building structure and dynamic. Applying the workflow to German authoritative geodata, it was possible to describe the entire building stock by 48 million polygons at different scale levels. Approximately one third of the total building stock are outbuildings. The methodological approach reveals that 62% of residential buildings are detached, 80% semi-detached and 20% terraced houses. The approach and the novel database will be very valuable for urban and energy modeling, material flow analysis, risk assessment and facility management. Full article

Absolute orientation is an important method in the field of photogrammetry. The technique is used to transform points between a local coordinate reference system and a global (geodetic) reference system. The classical transformation method uses a single set of similarity transformation parameters. However, the root mean square error (RMSE) of the classical method is large, especially for large-scale aerial photogrammetry analyses in which the points used are triangulated through free-net bundle adjustment. To improve the transformation accuracy, this study proposes a novel absolute orientation method in which the transformation uses various sets of local similarities. A Triangular Irregular Network (TIN) model is applied to divide the Ground Control Points (GCPs) into numerous triangles. Local similarities can then be computed using the three vertices of each triangle. These local similarities are combined to formulate the new transformation based on a weighting function. Both simulated and real data sets were used to assess the accuracy of the proposed method. The proposed method yields significantly improved plane and z-direction transformed point accuracies compared with the classical method. On a real data set with a mapping scale of 1:30,000 for a 53 km × 35 km study area, the plane and z RMSEs can be reduced from 1.2 m and 12.4 m to 0.4 m and 3.2 m, respectively. Full article

Increasing coastal space resource utilization (CSRU) activities and their impact on coastal environments has been recognized as a critical coastal zone stressor. Consequently, the need for sustainable and valid CSRU management has been highlighted. In this study, a highly-intelligent prototype decision-aided system for CSRU was developed. In contrast with existing coastal decision-aided systems, this system is aimed at the management of CSRU, providing reliable and dynamic numerical simulation, analysis, and aided decision making for real coastal engineering based on a self-developed fully automatic numerical program. It was established on multi-tier distributed architecture based on Java EE. The most efficient strategies for spatial data organization, automatic coastal numerical programs, and impact assessment modules are demonstrated. In addition, its integrated construction involving the addition of a new coastal project on the webpage, its one-click numerical prediction of coastal environmental impacts, assessments based on numerical results, and its aided decision-making capabilities are addressed. The system was applied to Ningbo Sea, China, establishing the Ningbo CSRU Decision Support System. Two projects were demonstrated: one reclamation project and one land-based outlet planning case. Results indicated that these projects had detrimental effects on local coastal environments. Therefore, the approvals of these projects were not recommended. Full article

This paper investigates the effect of four driving forces, including elevation, slope, distance to drainage and distance to major roads, on urban expansion in five Saudi Arabian cities: Riyadh, Jeddah, Makkah, Al-Taif and Eastern Area. The prediction of urban probabilities in the selected cities based on the four driving forces is generated using a logistic regression model for two time periods of urban change in 1985 and 2014. The validation of the model was tested using two approaches. The first approach was a quantitative analysis by using the Relative Operating Characteristic (ROC) method. The second approach was a qualitative analysis in which the probable urban growth maps based on urban changes in 1985 is used to test the performance of the model to predict the probable urban growth after 2014 by comparing the probable maps of 1985 and the actual urban growth of 2014. The results indicate that the prediction model of 2014 provides a reliable and consistent prediction based on the performance of 1985. The analysis of driving forces shows variable effects over time. Variables such as elevation, slope and road distance had significant effects on the selected cities. However, distance to major roads was the factor with the most impact to determine the urban form in all five cites in both 1985 and 2014. Full article

Modern cities are dense with very tall buildings, which often leads to features of interest (FOIs, e.g., relevant roads and associated landmarks) being occluded by clusters of buildings. Thus, from any given point of view, users can see only a small area of the city. However, it is currently an important technical problem to maintain the visibility of FOIs while preserving the urban shapes and spatial relationships between features. In this paper, we present a novel automatic visualization method to generate occlusion-free views for FOIs in real time. Our method integrates with three effective cartographic schemes: route broadening, building displacement, and building scaling, using an optimization framework A series of distortion energies are presented to preserve the urban resemblance, considering the view position and the urban features based on spatial cognition to maintain spatial and temporal coherence. Our approach can be used to visualize large urban environments at interactive framerates in which the visibility of the occluded FOIs is maximized while the deformation of the landscape’s shape is minimized. Using this approach, the visual readability of such 3D urban maps can be much improved. Full article

Monitoring urban growth and measuring urban sprawl is essential for improving urban planning and development. In this paper, we introduce a supervised approach for the delineation of urban areas using commonly available topographic data and commercial GIS software. The method uses a supervised parameter optimization approach along with buffer-based quality measuring method. The approach was developed, tested and evaluated in terms of possible usage in monitoring built-up areas in spatial science at a very fine-grained level. Results show that built-up area boundaries can be delineated automatically with higher quality compared to the settlement boundaries actually used. The approach has been applied to 166 settlement bodies in Germany. The study shows a very efficient way of extracting settlement boundaries from topographic data and maps and contributes to the quantification and monitoring of urban sprawl. Moreover, the findings from this study can potentially guide policy makers and urban planners from other countries. Full article

With the advance of the World-Wide Web (WWW) technology, people can easily share content on the Web, including geospatial data and web services. Thus, the “big geospatial data management” issues start attracting attention. Among the big geospatial data issues, this research focuses on discovering distributed geospatial resources. As resources are scattered on the WWW, users cannot find resources of their interests efficiently. While the WWW has Web search engines addressing web resource discovery issues, we envision that the geospatial Web (i.e., GeoWeb) also requires GeoWeb search engines. To realize a GeoWeb search engine, one of the first steps is to proactively discover GeoWeb resources on the WWW. Hence, in this study, we propose the GeoWeb Crawler, an extensible Web crawling framework that can find various types of GeoWeb resources, such as Open Geospatial Consortium (OGC) web services, Keyhole Markup Language (KML) and Environmental Systems Research Institute, Inc (ESRI) Shapefiles. In addition, we apply the distributed computing concept to promote the performance of the GeoWeb Crawler. The result shows that for 10 targeted resources types, the GeoWeb Crawler discovered 7351 geospatial services and 194,003 datasets. As a result, the proposed GeoWeb Crawler framework is proven to be extensible and scalable to provide a comprehensive index of GeoWeb. Full article

The implementation of sustainable land policies is in need of monitoring methods that go beyond a mere description of the proportion values of land use classes. The annual statistical surface area report on actual land utilization (German: “Bodenfläche nach Art der tatsächlichen Nutzung”), published by the statistical offices of the German federal states and the federation, provides information on a set of pre-defined land use classes for municipalities, districts and federal states. Due to its surveying method of summing up usage information from cadastral registers, it is not possible to determine previous and subsequent usages of land parcels. Hence, it is hard to precisely indicate to what extent particular land use classes contribute to the settlement area increase. Nevertheless, this information is crucial to the understanding of land use change processes, which is needed for a subsequent identification of driving forces. To overcome this lack of information, a method for the spatial and quantitative determination of previous and subsequent land usages has been developed, implemented and tested. It is based on pre-processed land use data for different time slices, which are derived from authoritative geo-topographical base data. The developed method allows for the identification of land use changes considering small geometric shifts and changes in the underlying data model, which can be adaptively excluded from the balance. Full article

The Göttingen eResearch Alliance is presented as a case study for establishing institutional support for research data management within the context of the Göttingen Campus, a particular alliance of several research institutes at Göttingen. The cross-cutting, “horizontal” approach of the Göttingen eResearch Alliance, established by two research-oriented infrastructure providers, a research library and a computing and IT competence center, aims to coordinate Campus-led activities to establish sustainable and innovative services to support all phases of the research data life cycle. In this article, the core activities of the first phase aimed at developing a modular approach to provide support for research data management to researchers will be described. It closes with lessons learned and an outlook on future activities. Full article

In order to discuss the impact of land consumption, it is first necessary to localize and quantify the extent of sealed surfaces. Since 2010, the monitoring of land use structures and developments in Germany has been provided by the Monitor of Settlement and Open Space Development at the Leibniz Institute of Ecological Urban and Regional Development (IÖR; IÖR Monitor), a scientific service operated by the Leibniz Institute of Ecological Urban and Regional Development. The IÖR Monitor includes an indicator for soil sealing for the years 2006, 2009 and 2012. Using this new source of data, it is possible for the first time to conduct quantitative studies at the level of Germany’s municipalities with the aim of documenting the extent of soil sealing as a form of spatial classification, as well as to investigate possible correlations with other influential factors. Here, we describe a comprehensive data inspection of soil sealing and potential influential factors. Structural interrelationships are identified under the application of classical and spatial regression methods. Full article

This study uses a large-scale mobile phone dataset to estimate potential demand of bicycle trips in a city. By identifying two important anchor points (night-time anchor point and day-time anchor point) from individual cellphone trajectories, this study proposes an anchor-point based trajectory segmentation method to partition cellphone trajectories into trip chain segments. By selecting trip chain segments that can potentially be served by bicycles, two indicators (inflow and outflow) are generated at the cellphone tower level to estimate the potential demand of incoming and outgoing bicycle trips at different places in the city and different times of a day. A maximum coverage location-allocation model is used to suggest locations of bike sharing stations based on the total demand generated at each cellphone tower. Two measures are introduced to further understand characteristics of the suggested bike station locations: (1) accessibility; and (2) dynamic relationships between incoming and outgoing trips. The accessibility measure quantifies how well the stations could serve bicycle users to reach other potential activity destinations. The dynamic relationships reflect the asymmetry of human travel patterns at different times of a day. The study indicates the value of mobile phone data to intelligent spatial decision support in public transportation planning. Full article

We propose a new segmentation and grouping framework for road map inference from GPS traces. We first present a progressive Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm with an orientation constraint to partition the whole point set of the traces into clusters that represent road segments. A new point cluster grouping algorithm, according to the topological relationship and spatial proximity of the point clusters to recover the road network, is then developed. After generating the point clusters, the robust Locally-Weighted Scatterplot Smooth (Lowess) method is used to extract their centerlines. We then propose to build the topological relationship of the centerlines by a Hidden Markov Model (HMM)-based map matching algorithm; and to assess whether the spatial proximity between point clusters by assuming the distances from the points to the centerline comply with a Gaussian distribution. Finally, the point clusters are grouped according to their topological relationship and spatial proximity to form strokes for recovering the road map. Experimental results show that our algorithm is robust to noise and varied sampling rates. The generated road maps show high geometric accuracy. Full article

To improve the search ability of biogeography-based optimization (BBO), this work proposed an improved biogeography-based optimization based on Affinity Propagation. We introduced the Memetic framework to the BBO algorithm, and used the simulated annealing algorithm as the local search strategy. MBBO enhanced the exploration with the Affinity Propagation strategy to improve the transfer operation of the BBO algorithm. In this work, the MBBO algorithm was applied to IEEE Congress on Evolutionary Computation (CEC) 2015 benchmarks optimization problems to conduct analytic comparison with the first three winners of the CEC 2015 competition. The results show that the MBBO algorithm enhances the exploration, exploitation, convergence speed and solution accuracy and can emerge as the best solution-providing algorithm among the competing algorithms. Full article

Simplification of three-dimensional (3D) buildings is critical to improve the efficiency of visualizing urban environments while ensuring realistic urban scenes. Moreover, it underpins the construction of multi-scale 3D city models (3DCMs) which could be applied to study various urban issues. In this paper, we design a generic yet effective approach for simplifying 3D buildings. Instead of relying on both semantic information and geometric information, our approach is based solely on geometric information as many 3D buildings still do not include semantic information. In addition, it provides an integrated means to treat 3D buildings with either sloped or flat roofs. The two case studies, one exploring simplification of individual 3D buildings at varying levels of complexity while the other, investigating the multi-scale simplification of a cityscape, show the effectiveness of our approach. Full article

In this paper, an automatic approach for zebra crossing extraction and reconstruction from high-resolution aerial images is proposed. In the extraction procedure, zebra crossings are extracted by the JointBoost classifier based on GLCM (Gray Level Co-occurrence Matrix) features and 2D Gabor Features. In the reconstruction procedure, a geometric parameter model based on spatial repeatability relationships is globally fitted to reconstruct the geometric shape of zebra crossings. Additionally, a group of representative experiments is conducted to test the proposed method under interfered conditions, such as zebra crossings covered by pedestrians, shadows and color fading. Furthermore, the performance of the proposed extraction method is compared with the template matching method. Finally, the results show the validation of our proposed method, both in the extraction and reconstruction of zebra crossings. Full article