http://www.mdpi.com/journal/ijgi Latest open access articles published in ISPRS Int. J. Geo-Inf. at http://www.mdpi.com/journal/ijgi http://www.mdpi.com/2220-9964/2/2/432 The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis. ISPRS International Journal of Geo-Information 2013-05-21 2 2 Article 10.3390/ijgi2020432 432 455 2220-9964 2013-05-21 doi: 10.3390/ijgi2020432 Matteo Abrate Clara Bacciu Anders Hast Andrea Marchetti Salvatore Minutoli Maurizio Tesconi http://www.mdpi.com/2220-9964/2/2/413 Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations. ISPRS International Journal of Geo-Information 2013-05-21 2 2 Article 10.3390/ijgi2020413 413 431 2220-9964 2013-05-21 doi: 10.3390/ijgi2020413 Wenwen Li Linna Li Michael Goodchild Luc Anselin http://www.mdpi.com/2220-9964/2/2/405 In this paper, we apply a special application of the Rao quadratic diversity for multiscale analysis of land use changes in a mixed agricultural-forest landscape in Central Italy. The proposed approach is similar to a block-size analysis of compositional diversity for which a given landscape is overlaid with a series of square grids composed of increasingly larger boxes. The combination of land cover classes in each box is recorded, and the Rao quadratic diversity is computed for the frequency distribution of the land cover classes at each box-size. Plotting compositional diversity versus box-size provides information on the scale-dependent pattern of the landscape. Since the proposed methodology is not severely influenced by the co-registration accuracy of the underlying data sets, it may prove to be reasonably adequate for analyzing historical data sets of varying resolution and quality, like aerial photographs or categorical maps. ISPRS International Journal of Geo-Information 2013-05-14 2 2 Communication 10.3390/ijgi2020405 405 412 2220-9964 2013-05-14 doi: 10.3390/ijgi2020405 Carlo Ricotta Maria Carranza http://www.mdpi.com/2220-9964/2/2/385 We are developing a geospatial inventory tool that will guide habitat conservation, restoration and coastal development and benefit several stakeholders who seek mitigation and adaptation strategies to shoreline changes resulting from erosion and sea level rise. The ESRI Geoportal Server, which is a type of web portal used to find and access geospatial information in a central repository, is customized by adding a Geoinventory tool capability that allows any shoreline related data to be searched, displayed and analyzed on a map viewer. Users will be able to select sections of the shoreline and generate statistical reports in the map viewer to allow for comparisons. The tool will also facilitate map-based discussion forums and creation of user groups to encourage citizen participation in decisions regarding shoreline stabilization and restoration, thereby promoting sustainable coastal development. ISPRS International Journal of Geo-Information 2013-05-13 2 2 Article 10.3390/ijgi2020385 385 404 2220-9964 2013-05-13 doi: 10.3390/ijgi2020385 Diana Mitsova Frank Wissinger Ann-Margaret Esnard Ravi Shankar Peter Gies http://www.mdpi.com/2220-9964/2/2/371 In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters, which indicated the typical stop-and-go movement pattern in real-world traffic congestion. We found that the sizes of spatio-temporal clusters exhibited a power law distribution. This implies the presence of a scaling property; i.e., they can be naturally divided into a strong hierarchical structure: long time-duration ones (a low percentage) whose values lie above the mean value and short ones (a high percentage) whose values lie below. The spatio-temporal clusters at different levels represented the degree of traffic congestions, for example the higher the level, the worse the traffic congestions. Moreover, the distribution of traffic congestions varied spatio-temporally and demonstrated a multinuclear structure in urban road networks, which suggested there is a correlation to the corresponding internal mobile regularities of an urban system. ISPRS International Journal of Geo-Information 2013-05-10 2 2 Article 10.3390/ijgi2020371 371 384 2220-9964 2013-05-10 doi: 10.3390/ijgi2020371 Xintao Liu Yifang Ban http://www.mdpi.com/2220-9964/2/2/349 The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been undertaken using buffering techniques and statistics, whilst shape metrics, including moments invariant, have been applied to assess polygon matching. The analyses are presented with a user-friendly interface which eases data input, computation and output of results, and assists in interpretation of the comparison. The results show that a comparison of positional and shape characteristics of OS data or GDS data, with those of OSM data, indicates that their integration for large scale mapping applications is not viable. ISPRS International Journal of Geo-Information 2013-04-25 2 2 Article 10.3390/ijgi2020349 349 370 2220-9964 2013-04-25 doi: 10.3390/ijgi2020349 David Fairbairn Maythm Al-Bakri http://www.mdpi.com/2220-9964/2/2/324 Recent profound changes have been observed in the Arctic environment, including record low sea ice extents and high latitude greening. Studying the Arctic and how it is changing is an important element of climate change science. The Tundra, an ecoregion of the Arctic, is directly related to climate change due to its effects on the snow ice feedback mechanism and greenhouse gas cycling. Like all ecoregions, the Tundra border is shifting, yet studies and policies require clear delineation of boundaries. There are many options for ecoregion classification systems, as well as resources for creating custom maps. To help decision makers identify the best classification system possible, we present a review of North American Tundra ecoregion delineations and further explore the methodologies, purposes, limitations, and physical properties of five common ecoregion classification systems. We quantitatively compare the corresponding maps by area using a geographic information system. ISPRS International Journal of Geo-Information 2013-04-08 2 2 Review 10.3390/ijgi2020324 324 348 2220-9964 2013-04-08 doi: 10.3390/ijgi2020324 Kirk Silver Mark Carroll http://www.mdpi.com/2220-9964/2/2/302 This study analyzed more than 50 years of land cover and land use changes in the 260 km2 Koga catchment in North Western Ethiopia. The data used includes 1:50,000 scale aerial photographs, Landsat MSS, TM and ETM images, and ASTER images together with ground truth data collected through field surveys and community elders’ interviews. Aerial photographs have high spatial resolution but provide lower spectral resolution than satellite data. While most land use/cover change studies compare changes from different spatial scales, this study applied land use/cover classification techniques to bring the data to a relatively similar scale. The data revealed that woody vegetation decreased from 5,576 ha to 3,012 ha from the 1950s to 2010. Most of the deforestation took place between the 1970s and 1980s, but there is an increasing trend since then. No significant changes were observed in the area used for agriculture that comprises the pastures and crop fields since the 1950s, while there is an enormous increase in the area used for settlement, due to a tremendous increase in population from one point in time to another. The bare lands that used to exist in previous years were found to be totally covered with other land cover/use classes and no bare lands were observed in the study area in the year 2010. Population pressure and land use policies were found to be reasons for the changes in land use/cover while soil degradation, decrease in the indigenous woody vegetation and erosion were the observed consequences of the land use/cover changes. ISPRS International Journal of Geo-Information 2013-04-02 2 2 Article 10.3390/ijgi2020302 302 323 2220-9964 2013-04-02 doi: 10.3390/ijgi2020302 Eleni Yeshaneh Wolfgang Wagner Michael Exner-Kittridge Dagnachew Legesse Günter Blöschl http://www.mdpi.com/2220-9964/2/2/276 As open source volunteered geographic information continues to gain popularity, the user community and data contributions are expected to grow, e.g., CloudMade, Apple, and Ushahidi now provide OpenStreetMap© (OSM) as a base layer for some of their mapping applications. This, coupled with the lack of cartographic standards and the expectation to one day be able to use this vector data for more geopositionally sensitive applications, like GPS navigation, leaves potential users and researchers to question the accuracy of the database. This research takes a photogrammetric approach to determining the positional accuracy of OSM road features using stereo imagery and a vector adjustment model. The method applies rigorous analytical measurement principles to compute accurate real world geolocations of OSM road vectors. The proposed approach was tested on several urban gridded city streets from the OSM database with the results showing that the post adjusted shape points improved positionally by 86%. Furthermore, the vector adjustment was able to recover 95% of the actual positional displacement present in the database. To demonstrate a practical application, a head-to-head positional accuracy assessment between OSM, the USGS National Map (TNM), and United States Census Bureau’s Topologically Integrated Geographic Encoding Referencing (TIGER) 2007 roads was conducted. ISPRS International Journal of Geo-Information 2013-04-02 2 2 Article 10.3390/ijgi2020276 276 301 2220-9964 2013-04-02 doi: 10.3390/ijgi2020276 Roberto Canavosio-Zuzelski Peggy Agouris Peter Doucette http://www.mdpi.com/2220-9964/2/2/256 We present the application of Latent Semantic Analysis (LSA) in combination with recommender systems, in order to enhance discovery in geoportals. As a basis for discovery, metadata of spatial data and services, as well as of non-spatial resources, such as documents and scientific papers, is created and registered in the catalogue of the geoportal (semi-)automatically. Links that are not inherent in the data itself are established based on the semantic similarity of its textual content using LSA. This leads to the transition from unstructured data to structured (metadata) information, serving as a basis for the generation of knowledge. The metadata information is integrated into a recommendation system that provides a ranked list showing (1) what other users viewed and (2) the related resources discovered by the LSA workflow as a result. Based on the assumptions that similar texts have something in common and that users are likely to be interested in what other users viewed, recommendations provide a broader, but also more precise, search result; on the one hand, the recommender engine considers additional information; on the other hand, it ranks resources based on the discovery experience of other users and the likeliness of the documents being related to each other. ISPRS International Journal of Geo-Information 2013-03-28 2 2 Article 10.3390/ijgi2020256 256 275 2220-9964 2013-03-28 doi: 10.3390/ijgi2020256 Bernhard Vockner Andreas Richter Manfred Mittlböck http://www.mdpi.com/2220-9964/2/1/237 Congenital Malformations (CM) impose a heavy burden on families and society. Identification of spatial patterns of CM is useful for understanding the epidemiology of this public health issue. In Israel, about 1,000,000 births and 25,000 CM cases at 37 groups were geocoded during 2000–2006. These were geo-analyzed using global-Moran’s-I statistics. Eight groups demonstrated geospatial heterogeneity and were further analyzed at both the census tract (Local Indicator of Spatial Association (LISA) and hot spot analyses) and street levels (spatial scan statistics with two population threshold sizes). The positional definition of results is further discussed in relevance to possible exposure to teratogenic sources in the region. Limitations of data and methods used are presented as well. ISPRS International Journal of Geo-Information 2013-03-19 2 1 Article 10.3390/ijgi2010237 237 255 2220-9964 2013-03-19 doi: 10.3390/ijgi2010237 Keren Agay-Shay Yona Amitai Chava Peretz Shai Linn Michael Friger Ammatzia Peled http://www.mdpi.com/2220-9964/2/1/220 We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and object-based approaches. All pairs of species were separable based on spectral reflectance values in at least one band, with Peltophorum pterocarpum being most distinct from other species. Object-based approaches were consistently superior to pixel-based methods, which were particularly low in accuracy for tree species with small canopy sizes, such as Cocos nucifera and Roystonea regia. There was a strong and significant correlation between the number of trees determined on the ground and from object-based classification. Overall, object-based approaches appear capable of discriminating the six most common species in a challenging urban environment, with substantial heterogeneity of tree canopy sizes. ISPRS International Journal of Geo-Information 2013-03-13 2 1 Article 10.3390/ijgi2010220 220 236 2220-9964 2013-03-13 doi: 10.3390/ijgi2010220 Shivani Agarwal Lionel Vailshery Madhumitha Jaganmohan Harini Nagendra http://www.mdpi.com/2220-9964/2/1/201 PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS), Web Service Definition Language (WSDL)/Simple Object Access Protocol (SOAP)). The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations. ISPRS International Journal of Geo-Information 2013-03-11 2 1 Article 10.3390/ijgi2010201 201 219 2220-9964 2013-03-11 doi: 10.3390/ijgi2010201 Pietro Zambelli Sören Gebbert Marco Ciolli http://www.mdpi.com/2220-9964/2/1/155 In this paper we describe a recently developed algorithm called Topological Weighted Centroid (TWC). TWC takes locations of an event of interest and analyzes the possible associated dynamics using the ideas of free energy and entropy. This novel mathematical tool has been applied to a real world example, the epidemic outbreak caused by Escherichia coli that occurred in Germany in 2011, to point out the real source of the outbreak. Other four examples of application to other epidemic spreads are described: Chikungunya fever of 2007 in Italy; Foot and mouth disease of 1967 in England; Cholera of 1854 in London; and the Russian influenza of 1889–1890 in Sweden. Comparisons have been made with other already published algorithms: Rossmo Algorithm, NES, LVM, Mexican Prob. The TWC results are significantly superior in comparison with other algorithms according to four independent indexes: distance from the peak, sensitivity, specificity and searching area. They are consistent with the idea that the spread of infectious disease is not random but follows a progression based on inherent, but as yet undiscovered, mathematical laws. The TWC method could provide an additional powerful tool for the investigation of the early stages of an epidemic and novel simulation methods for understanding the process through which a disease is spread. ISPRS International Journal of Geo-Information 2013-03-11 2 1 Article 10.3390/ijgi2010155 155 200 2220-9964 2013-03-11 doi: 10.3390/ijgi2010155 Massimo Buscema Enzo Grossi Alvin Bronstein Weldon Lodwick Masoud Asadi-Zeydabadi Roberto Benzi Francis Newman http://www.mdpi.com/2220-9964/2/1/135 Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query) is our novel mobile spatial interaction (MSI) prototype that acts as a next-generation base for human interaction within such geospatial sensor web environments/urban landscapes. It filters information using “Hidden Query Removal” functionality that intelligently refines the search space by calculating the geometry of a three dimensional visibility shape (Vista space) at a user’s current location. This 3D shape then becomes the query “window” in a spatial database for retrieving information on only those objects visible within a user’s actual 3D field-of-view. 3DQ reduces information overload and serves to heighten situation awareness on constrained commercial off-the-shelf devices by providing visibility space searching as a mobile web service. The effects of variations in mobile spatial search techniques in terms of query speed vs. accuracy are evaluated and presented in this paper. ISPRS International Journal of Geo-Information 2013-03-08 2 1 Article 10.3390/ijgi2010135 135 154 2220-9964 2013-03-08 doi: 10.3390/ijgi2010135 Junjun Yin James Carswell http://www.mdpi.com/2220-9964/2/1/110 The overall objective of the study is to generate information for an enhanced land use planning with respect to flood hazards. The study assesses the potential impact of climate change by simulating a dam break scenario in a high intensity rainfall event and evaluates the vulnerability risk in the downstream region by integrating ArcGIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS) technologies. In the past century, the evidence of climate changes are observed in terms of increase in high intensity rainfall events. These events are of high concern, as increased inflow rates may increase the probability of a dam failure, leading to higher magnitude flooding events involving multiple consequences. The 100 year historical rainfall data for the central Mississippi region reveals an increased trend in the intensity of rainfall rates after the 1970s. With more than 10% of high hazard dams in the central region, the damage can be far accumulative. The study determines occurrence of the high intensity rainfall event in the past 100 years for central Mississippi and simulates a Ross Barnett Reservoir dam break scenario and evaluates the vulnerability risks due to inundation in the immediate downstream region, which happens to be the State Capital. The results indicate that the inundation due to a Ross Barnett Reservoir failure under high intensity rainfall event is comparable to a catastrophic flood event experienced by the region in 1979, which almost equals a 200-year flood magnitude. The results indicate that the extent and depth of flood waters poses a significant destructive threat to the state capital, inundating various infrastructural and transportation networks. ISPRS International Journal of Geo-Information 2013-03-04 2 1 Article 10.3390/ijgi2010110 110 134 2220-9964 2013-03-04 doi: 10.3390/ijgi2010110 Sudha Yerramilli http://www.mdpi.com/2220-9964/2/1/94 Several studies attempt to describe changes in the spatial patterns of forests over time, resorting to the comparison of landscape pattern indices (LPI), but new methods for quantifying landscape differences in a statistical context are necessary. In this paper, we quantified and assessed the statistical significance of the forests pattern changes, which have occurred since the end of WWII in Central Italy (Isernia). To do this; based on the proportion of forest cover (pi) and contagion (H) of three land cover maps (1954–1981–2006); we generated 100 forest maps with predictable results through the midpoint displacement algorithm. Then, for both observed and simulated maps, we computed a set of LPI (number of patches, cohesion, largest forest patch index and area weighted mean shape index) and we derived their empirical distributions; finally, we compared the empirical distributions using the non-parametric Kruskal-Wallis test. Our results show significant changes in the spatial pattern of forests and underline the process of natural forest re-growth, which, in the area, is constrained by “remnants” of traditional activities. The adopted approach could be extended to a large ensemble of landscapes and spatial scales and could become a standard procedure when comparing patterns in time. ISPRS International Journal of Geo-Information 2013-03-01 2 1 Article 10.3390/ijgi2010094 94 109 2220-9964 2013-03-01 doi: 10.3390/ijgi2010094 Ludovico Frate Maria Carranza http://www.mdpi.com/2220-9964/2/1/82 The National Spatial Data Infrastructure (NSDI) is defined as the technologies, policies and people necessary to promote sharing of geospatial data throughout all levels of government, the private and non-profit sectors and the academic community. The US Census Bureau is the federal agency lead for administrative units data, one of the seven data themes identified by the NSDI framework. The administrative unit is a unit with administrative responsibilities. These units are organized as nodes/lines/areas feature data. The OpenGIS Geography Markup Language (GML) is the XML grammar to express the geographic features. This study at the US Census Bureau investigates how the general-purpose GML standard could be leveraged and extended to describe the most comprehensive geographic dataset with national coverage in the US. Challenges and problems in dealing with data volume, GML document structure, GML schema design and GML document naming are analyzed, followed by proposed solutions proven for feasibility. Our results show that one key point in making a successful GML deployment for NSDI is to reflect the characteristics of the geographic data through a carefully designed GML schema, structure and organization. The lessons learned may be useful to others transforming NSDI framework data and other large geospatial datasets into GML structures. ISPRS International Journal of Geo-Information 2013-02-18 2 1 Article 10.3390/ijgi2010082 82 93 2220-9964 2013-02-18 doi: 10.3390/ijgi2010082 Lingling Guo http://www.mdpi.com/2220-9964/2/1/67 While OGC’s WFS facilitates disseminating heterogeneous spatial data over the Web and allows feature-level geospatial information sharing and synchronization, performance issues challenge the efficient and effective utilization of WFS for disaster response. Literature shows that obtaining spatial information becomes very slow when querying WFS systems from large geospatial databases over the Internet. Solutions on how to improve the WFS system performance so that spatial data can be delivered to disaster responders within a reasonable amount of time are needed. This paper proposes a parallel approach based on Voronoi diagram indexing and data/task parallelism for improving the query performance of WFS systems for disaster applications. Experimental results show that the parallel approach can significantly improve the response time needed to process the spatial queries from a massive volume of spatial data for disaster response. ISPRS International Journal of Geo-Information 2013-02-06 2 1 Article 10.3390/ijgi2010067 67 81 2220-9964 2013-02-06 doi: 10.3390/ijgi2010067 Chuanrong Zhang Tian Zhao Weidong Li http://www.mdpi.com/2220-9964/2/1/50 The environment affects agriculture, via soils, weather, etc. and agriculture affects the environment locally at farm level and via its impact on climate change. Locating agriculture within its spatial environment is thus important for farmers and policy makers. Within the EU countries collect detailed farm data to understand the technical and financial performance of farms; the Farm Accountancy Data Network. However, knowledge of the spatial-environmental context of these farms is reported at gross scale. In this paper, Irish farm accounting data is geo-referenced using address matching to a national address database. An analysis of the geographic distribution of the survey farms, illustrated through a novel 2D ranked pair plot of the coordinates, compared to the national distribution of farms shows a trend in the location of survey farms that leads to a statistical difference in the climatic variables associated with the farm. The farms in the survey have significantly higher accumulated solar radiation values than the national average. As a result, the survey may not be representative spatially of the pattern of environment x farm system. This could have important considerations when using FADN data in modelling climate change impacts on agri-economic performance. ISPRS International Journal of Geo-Information 2013-02-06 2 1 Article 10.3390/ijgi2010050 50 66 2220-9964 2013-02-06 doi: 10.3390/ijgi2010050 Stuart Green Cathal O'Donoghue http://www.mdpi.com/2220-9964/2/1/27 At present it is common to use geographic information system (GIS) applications to assess runoff generation. One of these GIS-based tools to generate maps of dominant runoff processes is the so called GIS-DRP approach. The tool, which has been developed mainly based on agricultural areas, uses commonly available input data like a digital elevation model (DEM), geological information as well as land use information. The aim of this study is to test, validate and improve this GIS-DRP method for forested and silviculture areas. Hence, soil-hydrologic investigations and several mapping techniques of dominant runoff processes were conducted on 25 test-plots in four forested catchments in Rhineland-Palatinate (Germany) and the Grand Duchy of Luxembourg. By comparing the results of the mapping techniques and those of the test plots, weak points in the original GIS-DRP method were detected. Subsequently, it was possible to enhance the GIS-DRP approach by incorporating new discharge relevant parameters like topsoil sealing, extreme weather events and semipermeability of the substratum. Moreover, the improved GIS-DRP approach can be widely used in different landscapes and for different fields of application. The adapted method can now support foresters and decision makers in forestry planning, answer questions concerning the landscape water balance and peripheral water retention or provide extra information for sustainable forest planning in times of a changing climate. ISPRS International Journal of Geo-Information 2013-01-31 2 1 Article 10.3390/ijgi2010027 27 49 2220-9964 2013-01-31 doi: 10.3390/ijgi2010027 Marco Hümann Christoph Müller http://www.mdpi.com/2220-9964/2/1/1 The Sensor Web is a growing phenomenon where an increasing number of sensors are collecting data in the physical world, to be made available over the Internet. To help realize the Sensor Web, the Open Geospatial Consortium (OGC) has developed open standards to standardize the communication protocols for sharing sensor data. Spatial Data Infrastructures (SDIs) are systems that have been developed to access, process, and visualize geospatial data from heterogeneous sources, and SDIs can be designed specifically for the Sensor Web. However, there are problems with interoperability associated with a lack of standardized naming, even with data collected using the same open standard. The objective of this research is to automatically group similar sensor data layers. We propose a methodology to automatically group similar sensor data layers based on the phenomenon they measure. Our methodology is based on a unique bottom-up approach that uses text processing, approximate string matching, and semantic string matching of data layers. We use WordNet as a lexical database to compute word pair similarities and derive a set-based dissimilarity function using those scores. Two approaches are taken to group data layers: mapping is defined between all the data layers, and clustering is performed to group similar data layers. We evaluate the results of our methodology. ISPRS International Journal of Geo-Information 2013-01-30 2 1 Article 10.3390/ijgi2010001 1 26 2220-9964 2013-01-30 doi: 10.3390/ijgi2010001 Ben Knoechel Chih-Yuan Huang Steve Liang http://www.mdpi.com/2220-9964/1/3/333 Existing models of spatial relations do not consider that different concepts exist on different levels in a hierarchy and in turn that the spatial relations in a given scene are a function of the specific concepts considered. One approach to determining the existence of a particular spatial relation is to compute the corresponding high level concepts explicitly using map generalization before inferring the existence of the spatial relation in question. We explore this idea through the development of a model of the spatial relation “enters” that may exist between a road and a housing estate. ISPRS International Journal of Geo-Information 2012-12-13 1 3 Article 10.3390/ijgi1030333 333 350 2220-9964 2012-12-13 doi: 10.3390/ijgi1030333 Padraig Corcoran Peter Mooney Michela Bertolotto http://www.mdpi.com/2220-9964/1/3/315 The OpenStreetMap (OSM) project, a well-known source of freely available worldwide geodata collected by volunteers, has experienced a consistent increase in popularity in recent years. One of the main caveats that is closely related to this popularity increase is different types of vandalism that occur in the projects database. Since the applicability and reliability of crowd-sourced geodata, as well as the success of the whole community, are heavily affected by such cases of vandalism, it is essential to counteract those occurrences. The question, however, is: How can the OSM project protect itself against data vandalism? To be able to give a sophisticated answer to this question, different cases of vandalism in the OSM project have been analyzed in detail. Furthermore, the current OSM database and its contributions have been investigated by applying a variety of tests based on other Web 2.0 vandalism detection tools. The results gathered from these prior steps were used to develop a rule-based system for the automated detection of vandalism in OSM. The developed prototype provides useful information about the vandalism types and their impact on the OSM project data. ISPRS International Journal of Geo-Information 2012-11-22 1 3 Article 10.3390/ijgi1030315 315 332 2220-9964 2012-11-22 doi: 10.3390/ijgi1030315 Pascal Neis Marcus Goetz Alexander Zipf http://www.mdpi.com/2220-9964/1/3/294 Delineation of commuting regions has always been based on statistical units, often municipalities or wards. However, using these units has certain disadvantages as their land areas differ considerably. Much information is lost in the larger spatial base units and distortions in self-containment values, the main criterion in rule-based delineation procedures, occur. Alternatively, one can start from relatively small standard size units such as hexagons. In this way, much greater detail in spatial patterns is obtained. In this paper, regions are built by means of intrazonal maximization (Intramax) on the basis of hexagons. The use of geoprocessing tools, specifically developed for the processing of commuting data, speeds up processing time considerably. The results of the Intramax analysis are evaluated with travel-to-work area constraints, and comparisons are made with commuting fields, accessibility to employment, commuting flow density and network commuting flow size. From selected steps in the regionalization process, a hierarchy of nested commuting regions emerges, revealing the complexity of commuting patterns. ISPRS International Journal of Geo-Information 2012-11-14 1 3 Article 10.3390/ijgi1030294 294 314 2220-9964 2012-11-14 doi: 10.3390/ijgi1030294 Martin Landré http://www.mdpi.com/2220-9964/1/3/272 A planning support system for land consolidation has been developed that has, at its heart, an expert system called LandSpaCES (Land Spatial Consolidation Expert System) which contains a “design module” that generates alternative land redistributions under different scenarios and an “evaluation module” which integrates GIS with multi-criteria decision making for assessing these alternatives. This paper introduces the structural framework of the latter module which has been applied using a case study in Cyprus. Two new indices are introduced: the “parcel concentration coefficient” for measuring the dispersion of parcels; and the “landowner satisfaction rate” for predicting the acceptance of the land redistribution plan by the landowners in terms of the location of their new parcels. These two indices are used as criteria for the evaluation of the land redistribution alternatives and are transferable to any land consolidation project. Moreover, a modified version of the ratio estimation procedure, referred to as the “qualitative rating method” for assigning weights to the evaluation criteria, is presented, along with a set of non-linear value functions for standardizing the performance scores of the alternatives and incorporating expert knowledge for five evaluation criteria. The application of the module showed that it is a powerful new tool for the evaluation of alternative land redistribution plans that could be implemented in other countries after appropriate adjustments. A broader contribution has also been made to spatial planning processes, which might follow the methodology and innovations presented in this paper. ISPRS International Journal of Geo-Information 2012-11-09 1 3 Article 10.3390/ijgi1030272 272 293 2220-9964 2012-11-09 doi: 10.3390/ijgi1030272 Demetris Demetriou Linda See John Stillwell http://www.mdpi.com/2220-9964/1/3/256 In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems. ISPRS International Journal of Geo-Information 2012-11-02 1 3 Article 10.3390/ijgi1030256 256 271 2220-9964 2012-11-02 doi: 10.3390/ijgi1030256 Günther Sagl Martin Loidl Euro Beinat http://www.mdpi.com/2220-9964/1/3/242 Changes to stems caused by natural forces and timber harvesting constitute an essential input for many forestry-related applications and ecological studies, especially forestry inventories based on the use of permanent sample plots. Conventional field measurement is widely acknowledged as being time-consuming and labor-intensive. More automated and efficient alternatives or supportive methods are needed. Terrestrial laser scanning (TLS) has been demonstrated to be a promising method in forestry field inventories. Nevertheless, the applicability of TLS in recording changes in the structure of forest plots has not been studied in detail. This paper presents a fully automated method for detecting changes in forest structure over time using bi-temporal TLS data. The developed method was tested on five densely populated forest plots including 137 trees and 50 harvested trees in point clouds. The present study demonstrated that 90 percent of tree stem changes could be automatically located from single-scan TLS data. These changes accounted for 92 percent of the changed basal area. The results indicate that the processing of TLS data collected at different times to detect tree stem changes can be fully automated. ISPRS International Journal of Geo-Information 2012-10-26 1 3 Article 10.3390/ijgi1030242 242 255 2220-9964 2012-10-26 doi: 10.3390/ijgi1030242 Xinlian Liang Juha Hyyppä Harri Kaartinen Markus Holopainen Timo Melkas http://www.mdpi.com/2220-9964/1/3/228 Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Smoothing-Filter-Based-Intensity Modulation (SFIM) algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve more of the spatial information of the higher resolution panchromatic image band (i.e., IHS and BT) led to more spatially-accurate segmentations, while pansharpening algorithms that minimize the distortion of spectral information of the lower resolution multispectral image bands (i.e., SFIM) led to more spectrally-accurate image segments. Based on these findings, we developed a new IHS-SFIM combination approach, specifically for object-based image analysis (OBIA), which combined the better spatial information of IHS and the more accurate spectral information of SFIM to produce image segments with very high spatial and spectral accuracy. ISPRS International Journal of Geo-Information 2012-10-16 1 3 Article 10.3390/ijgi1030228 228 241 2220-9964 2012-10-16 doi: 10.3390/ijgi1030228 Brian Johnson Ryutaro Tateishi Nguyen Hoan http://www.mdpi.com/2220-9964/1/2/209 In Brazil, plantations of exotic species such as Eucalyptus have expanded substantially in recent years, due in large part to the great demand for cellulose and wood. The combination of the steep slopes in some of these regions, such as the municipalities located close to the Serra do Mar and Serra da Mantiqueira, and the soil exposure that occurs in some stages in the Eucalyptus cultivation cycle, can cause landslides. The use of a geographic information system (GIS) assists with the identification of areas that are susceptible to landslides, and one of the GIS tools used is the spatial inference technique. In this work, the landslide susceptibility of areas occupied by Eucalyptus plantations in different stages of development in municipalities in the state of São Paulo was examined. Eight thematic maps were used, and, the fuzzy gamma technique was used for data integration and the generation of susceptibility maps, in which scenarios were created with different gamma values for the dry and rainy seasons. The results for areas planted with Eucalyptus were compared with those obtained for other land uses and covers. In the moderate and high susceptibility classes, the pasture is the land use type that presented the greatest susceptibility, followed by new Eucalyptus plantations and urban areas. ISPRS International Journal of Geo-Information 2012-09-12 1 2 Article 10.3390/ijgi1020209 209 227 2220-9964 2012-09-12 doi: 10.3390/ijgi1020209 Vanessa Canavesi Regina Célia dos Santos Alvalá http://www.mdpi.com/2220-9964/1/2/186 Crowdsourced geodata has been proven to be a rich and major data source for environmental simulations and analysis, as well as the visualization of spatial phenomena. With the increasing size and complexity of public buildings, such as universities or hotels, there is also an increasing demand for information about indoor spaces. Trying to stimulate this growing demand, both researchers and Volunteered Geographic Information (VGI) communities envision to extend established communities towards indoors. It has already been showcased that VGI from OpenStreetMap (OSM) can be utilized for different applications in Spatial Data Infrastructures (SDIs) as well as for simple shortest path computations inside buildings. The here presented research now tries to utilize crowdsourced indoor geodata for more complex indoor routing scenarios of multiple users. Essentially, it will be investigated if, and to what extent, the available data can be utilized for performing indoor evacuation simulations with the simulation framework MATSim. That is, this paper investigates the suitability of crowdsourced indoor information from OSM (IndoorOSM) for evacuation simulations. Additionally, the applicability of MATSim for agent-based indoor evacuation simulations is conducted. The paper discusses the automatic generation simulation-related data, and provides experimental results for two different evacuation scenarios. Furthermore, limitations of the IndoorOSM data and the MATSim framework for indoor evacuation simulations are elaborated and discussed. ISPRS International Journal of Geo-Information 2012-08-29 1 2 Article 10.3390/ijgi1020186 186 208 2220-9964 2012-08-29 doi: 10.3390/ijgi1020186 Marcus Goetz Alexander Zipf http://www.mdpi.com/2220-9964/1/2/166 This paper discusses the use of spatial data for risk and natural disaster management. The importance of remote-sensing (RS), Geographic Information System (GIS) and Global Navigation Satellite System (GNSS) data is stressed by comparing studies of the use of these technologies for natural disaster management. Spatial data sharing is discussed in the context of the establishment of Spatial Data Infrastructures (SDIs) for natural disasters. Some examples of SDI application in disaster management are analyzed, and the need for participation from organizations and governments to facilitate the exchange of information and to improve preventive and emergency plans is reinforced. Additionally, the potential involvement of citizens in the risk and disaster management process by providing voluntary data collected from volunteered geographic information (VGI) applications is explored. A model relating all of the spatial data-sharing aspects discussed in the article was suggested to elucidate the importance of the issues raised. ISPRS International Journal of Geo-Information 2012-08-07 1 2 Review 10.3390/ijgi1020166 166 185 2220-9964 2012-08-07 doi: 10.3390/ijgi1020166 Luiz A. Manfré Eliane Hirata Janaína B. Silva Eduardo J. Shinohara Mariana A. Giannotti Ana Paula C. Larocca José A. Quintanilha http://www.mdpi.com/2220-9964/1/2/146 The OpenStreetMap (OSM) project, founded in 2004, has gathered an exceptional amount of interest in recent years and counts as one of the most impressive sources of Volunteered Geographic Information (VGI) on the Internet. In total, more than half a million members had registered for the project by the end of 2011. However, while this number of contributors seems impressive, questions remain about the individual contributions that have been made by the project members. This research article contains several studies regarding the contributions by the community of the project. The results show that only 38% (192,000) of the registered members carried out at least one edit in the OSM database and that only 5% (24,000) of all members actively contributed to the project in a more productive way. The majority of the members are located in Europe (72%) and each member has an activity area whose size may range from one soccer field up to more than 50 km2. In addition to several more analyses conducted for this article, predictions will be made about how this newly acquired knowledge can be used for future research. ISPRS International Journal of Geo-Information 2012-07-27 1 2 Article 10.3390/ijgi1020146 146 165 2220-9964 2012-07-27 doi: 10.3390/ijgi1020146 Pascal Neis Alexander Zipf http://www.mdpi.com/2220-9964/1/2/120 Several tasks in urban and architectural design are today undertaken in a geospatial context. Building Information Models (BIM) and geospatial technologies offer 3D data models that provide information about buildings and the surrounding environment. The Industry Foundation Classes (IFC) and CityGML are today the two most prominent semantic models for representation of BIM and geospatial models respectively. CityGML has emerged as a standard for modeling city models while IFC has been developed as a reference model for building objects and sites. Current CAD and geospatial software provide tools that allow the conversion of information from one format to the other. These tools are however fairly limited in their capabilities, often resulting in data and information losses in the transformations. This paper describes a new approach for data integration based on a unified building model (UBM) which encapsulates both the CityGML and IFC models, thus avoiding translations between the models and loss of information. To build the UBM, all classes and related concepts were initially collected from both models, overlapping concepts were merged, new objects were created to ensure the capturing of both indoor and outdoor objects, and finally, spatial relationships between the objects were redefined. Unified Modeling Language (UML) notations were used for representing its objects and relationships between them. There are two use-case scenarios, both set in a hospital: “evacuation” and “allocating spaces for patient wards” were developed to validate and test the proposed UBM data model. Based on these two scenarios, four validation queries were defined in order to validate the appropriateness of the proposed unified building model. It has been validated, through the case scenarios and four queries, that the UBM being developed is able to integrate CityGML data as well as IFC data in an apparently seamless way. Constraints and enrichment functions are used for populating empty database tables and fields. The motivation scenarios also show the needs and benefits of having an integrated approach to the modeling of indoor and outdoor spatial features. ISPRS International Journal of Geo-Information 2012-07-17 1 2 Article 10.3390/ijgi1020120 120 145 2220-9964 2012-07-17 doi: 10.3390/ijgi1020120 Mohamed El-Mekawy Anders Östman Ihab Hijazi http://www.mdpi.com/2220-9964/1/2/108 For most of the last decade, the south-western portion of the United States has experienced a severe and enduring drought. This has caused serious concerns about water supply and management in the region. In this research, 30 orthorectified Landsat satellite images from the United States Geological Service (USGS) Earth Explorer archive were analyzed for the 1972 to 2009 period. The images encompassed Lake Mead (a major reservoir in this region) and were examined for changes in water surface area. Decadal lake area minimums/maximums were achieved in 1972/1979, 1981/1988, 1991/1998, and 2009/2000. The minimum lake area extent occurred in 2009 (356.4 km2), while the maximum occurred in 1998 (590.6 km2). Variable trends in water level and lake area were observed throughout the analysis period, however progressively lower values were observed since 2000. The Landsat derived lake areas show a very strong relationship with actual measured water levels at the Hoover Dam. Yearly water level variations at the dam vary minimally from the satellite derived estimates. A complete (yearly) record of satellite images may have helped to reduce the slight deviations in the time series. ISPRS International Journal of Geo-Information 2012-06-26 1 2 Article 10.3390/ijgi1020108 108 119 2220-9964 2012-06-26 doi: 10.3390/ijgi1020108 K. Wayne Forsythe Barbara Schatz Stephen J. Swales Lisa-Jen Ferrato David M. Atkinson http://www.mdpi.com/2220-9964/1/1/89 This paper explores the patterns of human activities within a geographical space by adopting the taxicab static points which refer to the locations with zero speed along the tracking trajectory. We report the findings from both aggregated and individual aspects. Results from the aggregated level indicate the following: (1) Human activities exhibit an obvious regularity in time, for example, there is a burst of activity during weekend nights and a lull during the week. (2) They show a remarkable spatial drifting pattern, which strengthens our understanding of the activities in any given place. (3) Activities are heterogeneous in space irrespective of their drifting with time. These aggregated results not only help in city planning, but also facilitate traffic control and management. On the other hand, investigations on an individual level suggest that (4) activities witnessed by one taxicab will have different temporal regularity to another, and (5) each regularity implies a high level of prediction with low entropy by applying the Lempel-Ziv algorithm. ISPRS International Journal of Geo-Information 2012-06-15 1 1 Article 10.3390/ijgi1010089 89 107 2220-9964 2012-06-15 doi: 10.3390/ijgi1010089 Tao Jia Bin Jiang http://www.mdpi.com/2220-9964/1/1/69 Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types). At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable. ISPRS International Journal of Geo-Information 2012-05-29 1 1 Article 10.3390/ijgi1010069 69 88 2220-9964 2012-05-29 doi: 10.3390/ijgi1010069 Marc Wieland Massimiliano Pittore Stefano Parolai Jochen Zschau http://www.mdpi.com/2220-9964/1/1/46 Analysis of spatial and temporal changes of vegetation cover using remote sensing (RS) technology, in conjunction with Geographic Information Systems (GIS), is becoming increasingly important in environmental conservation. The objective of this study was to use RS data and GIS techniques to assess the vegetation cover in 1989 and 2009, in the barangays (smallest administrative units) of the city of San Fernando, La Union, the Philippines, for planning vegetation rehabilitation. Landsat images were used to prepare both the 1989 and 2009 land cover maps, which were then used to detect changes in the vegetation cover for the barangays. In addition to conventional accuracy assessment parameters such as; proportion correct, and standard Kappa index of agreement, two other parameters; quantity, and allocation disagreements were used to assess the accuracy of the land cover classification. Results revealed that there were gains and losses of vegetation cover in most of the barangays, but overall vegetation cover increased by 11% (around 625 ha) based on the original extent of 1989. Those barangays that showed substantial net losses in vegetation cover need to be prioritised for rehabilitation planning. As exemplified in this study, the collection, processing and analysis of relevant RS and GIS information, can facilitate priority-setting in the planning of environmental rehabilitation and conservation by the local government at both city and barangay levels. ISPRS International Journal of Geo-Information 2012-03-13 1 1 Article 10.3390/ijgi1010046 46 68 2220-9964 2012-03-13 doi: 10.3390/ijgi1010046 Ronald C. Estoque Ria S. Estoque Yuji Murayama http://www.mdpi.com/2220-9964/1/1/32 Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid) was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article defines a standard for an improved EASE-Grid 2.0 definition, addressing how the changes rectify issues with the original grid definition. Data distributed using the EASE-Grid 2.0 standard will be easier for users to import into standard software packages and will minimize common reprojection errors that users had encountered with the original EASE-Grid definition. ISPRS International Journal of Geo-Information 2012-03-13 1 1 Article 10.3390/ijgi1010032 32 45 2220-9964 2012-03-13 doi: 10.3390/ijgi1010032 Mary J. Brodzik Brendan Billingsley Terry Haran Bruce Raup Matthew H. Savoie http://www.mdpi.com/2220-9964/1/1/3 The primary objective of this research is to predict and analyze the future urban growth of Dhaka City using the Landsat satellite images of 1989, 1999 and 2009. Dhaka City Corporation (DCC) and its surrounding impact areas have been selected as the study area. At the beginning, a fisher supervised classification method has been applied to prepare the base maps with five land cover classes. In the next stage, three different models have been implemented to simulate the land cover map of Dhaka city of 2009. These have been named as “Stochastic Markov (St_Markov)” Model, “Cellular Automata Markov (CA_Markov)” Model and “Multi Layer Perceptron Markov (MLP_Markov)” Model. Then the best-fitted model has been selected by implementing a method to compare land cover categories in three maps: a reference map of time 1, a reference map of time 2 and a simulation map of time 2. This is how the “Multi Layer Perceptron Markov (MLP_Markov)” Model has been qualified as the most appropriate model for this research. Later, using the MLP_Markov model, the land cover map of 2019 has been predicted. The MLP_Markov model extrapolates that built-up area increases from 46% to 58% of the total study area during 2009–2019. ISPRS International Journal of Geo-Information 2012-02-23 1 1 Article 10.3390/ijgi1010003 3 31 2220-9964 2012-02-23 doi: 10.3390/ijgi1010003 Bayes Ahmed Raquib Ahmed http://www.mdpi.com/2220-9964/1/1/1 All things in our world are related to some location in space and time, and according to Tobler’s first law of geography “everything is related to everything else, but near things are more related than distant things” [1]. Since humans exist they have been contemplating about space and time and have tried to depict and manage the geographic space they live in. We know graphic representations of the land from various regions of the world dating back several thousands of years. The processing and analysis of spatial data has a long history in the disciplines that deal with spatial data such as geography, surveying engineering, cartography, photogrammetry, and remote sensing. Until recently, all these activities have been analog in nature; only since the invention of the computer in the second half of the 20th century and the use of computers for the acquisition, storage, analysis, and display of spatial data starting in the 1960s we speak of geo-information and geo-information systems. [...] ISPRS International Journal of Geo-Information 2011-09-08 1 1 Editorial 10.3390/ijgi1010001 1 2 2220-9964 2011-09-08 doi: 10.3390/ijgi1010001 Wolfgang Kainz