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ISPRS Int. J. Geo-Inf., Volume 3, Issue 2 (June 2014), Pages 391-867

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Open AccessArticle A Dynamic GIS as an Efficient Tool for Integrated Coastal Zone Management
ISPRS Int. J. Geo-Inf. 2014, 3(2), 391-407; doi:10.3390/ijgi3020391
Received: 19 September 2013 / Revised: 26 February 2014 / Accepted: 5 March 2014 / Published: 26 March 2014
Cited by 2 | PDF Full-text (2359 KB) | HTML Full-text | XML Full-text
Abstract
This contribution addresses both the role of geographical information in participatory research of coastal zones, and its potential to bridge the gap between research and coastal zone management. Over a one year period, heterogeneous data (spatial, temporal, qualitative and quantitative) were obtained [...] Read more.
This contribution addresses both the role of geographical information in participatory research of coastal zones, and its potential to bridge the gap between research and coastal zone management. Over a one year period, heterogeneous data (spatial, temporal, qualitative and quantitative) were obtained which included the process of interviews, storing in a spatio-temporal database. The GIS (Geographic Information System) produced temporal snapshots of daily human activity patterns allowing it to map, identify and quantify potential space-time conflicts between activities. It was furthermore used to facilitate the exchange of ideas and knowledge at various levels: by mapping, simulation, GIS analysis and data collection. Results indicated that both captured data and the participatory workshop added real value to management and therefore it was deemed well managed by stakeholders. To incorporate a dynamic GIS would enhance pro-active integrated management by opening the path for better discussions whilst permitting management simulated scenarios. Full article
(This article belongs to the Special Issue Coastal GIS)
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Open AccessArticle The Application of WebGIS Tools for Visualizing Coastal Flooding Vulnerability and Planning for Resiliency: The New Jersey Experience
ISPRS Int. J. Geo-Inf. 2014, 3(2), 408-429; doi:10.3390/ijgi3020408
Received: 2 October 2013 / Revised: 5 March 2014 / Accepted: 10 March 2014 / Published: 26 March 2014
Cited by 3 | PDF Full-text (1077 KB) | HTML Full-text | XML Full-text
Abstract
While sea level rise is a world-wide phenomenon, mitigating its impacts is a local decision-making challenge that is going to require site-specific remedies. Faced with a variety of conflicting mandates and uncertainty as to appropriate responses, local land use planners and managers [...] Read more.
While sea level rise is a world-wide phenomenon, mitigating its impacts is a local decision-making challenge that is going to require site-specific remedies. Faced with a variety of conflicting mandates and uncertainty as to appropriate responses, local land use planners and managers need place-based decision support tools. With the increasing availability of high-resolution digital elevation models and the advancing speed and sophistication of web-based mapping, a number of web geographic information systems (GIS) tools have been developed to map and visualize what areas of a coastal landscape will potentially be flooded under different scenarios of sea level rise. This paper presents a case study of one such WebGIS application, NJFloodMapper (www.NJFloodMapper.org), with a focus on the user-centered design process employed to help our target audience of coastal decision-makers in the state of New Jersey, USA, access and understand relevant geographic information concerning sea level rise and exposure to coastal inundation, as well as assess the vulnerability of key infrastructure, populations and natural resources within their communities. We discuss the success of this approach amidst the broader context of the application of WebGIS tools in this arena. Due to its flexible design and user-friendly interface, NJFloodMapper has been widely adopted by government and non-governmental agencies in the state to assess coastal flooding exposure and vulnerability in the aftermath of a recent destructive coastal storm. However, additional decision support tools are needed to help coastal decision-makers translate the place-based information into concrete action plans aimed at promoting more resilient coastal land use decisions. Full article
(This article belongs to the Special Issue Coastal GIS)
Open AccessArticle Small Reservoir Distribution, Rate of Construction, and Uses in the Upper and Middle Chattahoochee Basins of the Georgia Piedmont, USA, 1950–2010
ISPRS Int. J. Geo-Inf. 2014, 3(2), 460-480; doi:10.3390/ijgi3020460
Received: 2 January 2014 / Revised: 3 March 2014 / Accepted: 14 March 2014 / Published: 1 April 2014
Cited by 4 | PDF Full-text (1435 KB) | HTML Full-text | XML Full-text
Abstract
Construction of small reservoirs affects ecosystem processes in numerous ways including fragmenting stream habitat, altering hydrology, and modifying water chemistry. While the upper and middle Chattahoochee River basins within the Southeastern United States Piedmont contain few natural lakes, they have a high [...] Read more.
Construction of small reservoirs affects ecosystem processes in numerous ways including fragmenting stream habitat, altering hydrology, and modifying water chemistry. While the upper and middle Chattahoochee River basins within the Southeastern United States Piedmont contain few natural lakes, they have a high density of small reservoirs (more than 7500 small reservoirs in the nearly 12,000 km2 basin). Policymakers and water managers in the region have little information about small reservoir distribution, uses, or the cumulative inundation of land cover caused by small reservoir construction. Examination of aerial photography reveals the spatiotemporal patterns and extent of small reservoir construction from 1950 to 2010. Over that 60 year timeframe, the area inundated by water increased nearly six fold (from 19 reservoirs covering 0.16% of the study area in 1950 to 329 reservoirs covering 0.95% of the study area in 2010). While agricultural practices were associated with reservoir creation from 1950 to 1970, the highest rates of reservoir construction occurred during subsequent suburban development between 1980 and 1990. Land cover adjacent to individual reservoirs transitioned over time through agricultural abandonment, land reforestation, and conversion to development during suburban expansion. The prolific rate of ongoing small reservoir creation, particularly in newly urbanizing regions and developing counties, necessitates additional attention from watershed managers and continued scientific research into cumulative environmental impacts at the watershed scale. Full article
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Open AccessArticle Effects of Pansharpening on Vegetation Indices
ISPRS Int. J. Geo-Inf. 2014, 3(2), 507-522; doi:10.3390/ijgi3020507
Received: 6 February 2014 / Revised: 10 March 2014 / Accepted: 19 March 2014 / Published: 2 April 2014
Cited by 4 | PDF Full-text (1169 KB) | HTML Full-text | XML Full-text
Abstract
This study evaluated the effects of image pansharpening on Vegetation Indices (VIs), and found that pansharpening was able to downscale single-date and multi-temporal Landsat 8 VI data without introducing significant distortions in VI values. Four fast pansharpening methods—Fast Intensity-Hue-Saturation (FIHS), Brovey Transform [...] Read more.
This study evaluated the effects of image pansharpening on Vegetation Indices (VIs), and found that pansharpening was able to downscale single-date and multi-temporal Landsat 8 VI data without introducing significant distortions in VI values. Four fast pansharpening methods—Fast Intensity-Hue-Saturation (FIHS), Brovey Transform (BT), Additive Wavelet Transform (AWT), and Smoothing Filter-based Intensity Modulation (SFIM)—and two VIs—Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR)—were tested. The NDVI and SR formulas were both found to cause some spatial information loss in the pansharpened multispectral (MS) bands, and this spatial information loss from VI transformations was not specific to Landsat 8 imagery (it will occur for any type of imagery). BT, SFIM, and other similar pansharpening methods that inject spatial information from the panchromatic (Pan) band by multiplication, lose all of the injected spatial information after the VI calculations. FIHS, AWT, and other similar pansharpening methods that inject spatial information by addition, lose some spatial information from the Pan band after VI calculations as well. Nevertheless, for all of the single- and multi-date VI images, the FIHS and AWT pansharpened images were more similar to the higher resolution reference data than the unsharpened VI images were, indicating that pansharpening was effective in downscaling the VI data. FIHS best enhanced the spectral and spatial information of the single-date and multi-date VI images, followed by AWT, and neither significantly over- or under-estimated VI values. Full article
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Open AccessArticle GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method
ISPRS Int. J. Geo-Inf. 2014, 3(2), 523-539; doi:10.3390/ijgi3020523
Received: 21 November 2013 / Revised: 10 March 2014 / Accepted: 19 March 2014 / Published: 2 April 2014
Cited by 6 | PDF Full-text (1106 KB) | HTML Full-text | XML Full-text
Abstract
The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW) approach was used to combine these [...] Read more.
The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW) approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece). This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale. Full article
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Open AccessArticle Land Cover Heterogeneity Effects on Sub-Pixel and Per-Pixel Classifications
ISPRS Int. J. Geo-Inf. 2014, 3(2), 540-553; doi:10.3390/ijgi3020540
Received: 1 January 2014 / Revised: 3 March 2014 / Accepted: 17 March 2014 / Published: 3 April 2014
Cited by 1 | PDF Full-text (953 KB) | HTML Full-text | XML Full-text
Abstract
Per-pixel and sub-pixel are two common classification methods in land cover studies. The characteristics of a landscape, particularly the land cover itself, can affect the accuracies of both methods. The objectives of this study were to: (1) compare the performance of sub-pixel [...] Read more.
Per-pixel and sub-pixel are two common classification methods in land cover studies. The characteristics of a landscape, particularly the land cover itself, can affect the accuracies of both methods. The objectives of this study were to: (1) compare the performance of sub-pixel vs. per-pixel classification methods for a broad heterogeneous region; and (2) analyze the impact of land cover heterogeneity (i.e., the number of land cover classes per pixel) on both classification methods. The results demonstrated that the accuracy of both per-pixel and sub-pixel classification methods were generally reduced by increasing land cover heterogeneity. Urban areas, for example, were found to have the lowest accuracy for the per-pixel method, because they had the highest heterogeneity. Conversely, rural areas dominated by cropland and grassland had low heterogeneity and high accuracy. When a sub-pixel method was used, the producer’s accuracy for artificial surfaces was increased by more than 20%. For all other land cover classes, sub-pixel and per-pixel classification methods performed similarly. Thus, the sub-pixel classification was only advantageous for heterogeneous urban landscapes. Both creators and users of land cover datasets should be aware of the inherent landscape heterogeneity and its potential effect on map accuracy. Full article
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Open AccessArticle A Hierarchical Approach to Optimizing Bus Stop Distribution in Large and Fast Developing Cities
ISPRS Int. J. Geo-Inf. 2014, 3(2), 554-564; doi:10.3390/ijgi3020554
Received: 19 February 2014 / Revised: 31 March 2014 / Accepted: 3 April 2014 / Published: 14 April 2014
Cited by 4 | PDF Full-text (672 KB) | HTML Full-text | XML Full-text
Abstract
Public transit plays a key role in shaping the transportation structure of large and fast growing cities. To cope with high population and employment density, such cities usually resort to multi-modal transit services, such as rail, BRT and bus. These modes are [...] Read more.
Public transit plays a key role in shaping the transportation structure of large and fast growing cities. To cope with high population and employment density, such cities usually resort to multi-modal transit services, such as rail, BRT and bus. These modes are strategically connected to form an effective transit network. Among the transit modes, bus stops need to be properly deployed to maintain an acceptable walking accessibility. This paper presents a hierarchical process for optimizing bus stop locations in the context of fast growing multi-modal transit services. Three types of bus stops are identified hierarchically, which includes connection stops, key stops and ordinary stops. Connection stops are generated manually to connect with other transit facilities. Key stops and ordinary stops are optimized with coverage models that are respectively weighted by network centrality measure and potential demand. A case study in a Chinese city suggests the hierarchical approach may generate more effective stop distribution. Full article
(This article belongs to the Special Issue GIS for Sustainable Urban Transport)
Open AccessArticle GIS-Based Analytical Tools for Transport Planning: Spatial Regression Models for Transportation Demand Forecast
ISPRS Int. J. Geo-Inf. 2014, 3(2), 565-583; doi:10.3390/ijgi3020565
Received: 2 January 2014 / Revised: 20 March 2014 / Accepted: 25 March 2014 / Published: 15 April 2014
Cited by 5 | PDF Full-text (1105 KB) | HTML Full-text | XML Full-text
Abstract
Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the [...] Read more.
Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets. Full article
(This article belongs to the Special Issue GIS for Sustainable Urban Transport)
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Open AccessArticle A Conceptual Flash Flood Early Warning System for Africa, Based on Terrestrial Microwave Links and Flash Flood Guidance
ISPRS Int. J. Geo-Inf. 2014, 3(2), 584-598; doi:10.3390/ijgi3020584
Received: 30 December 2013 / Revised: 26 March 2014 / Accepted: 3 April 2014 / Published: 22 April 2014
Cited by 4 | PDF Full-text (638 KB) | HTML Full-text | XML Full-text
Abstract
A conceptual flash flood early warning system for developing countries is described. The system uses rainfall intensity data from terrestrial microwave communication links and the geostationary Meteosat Second Generation satellite, i.e., two systems that are already in place and operational. Flash [...] Read more.
A conceptual flash flood early warning system for developing countries is described. The system uses rainfall intensity data from terrestrial microwave communication links and the geostationary Meteosat Second Generation satellite, i.e., two systems that are already in place and operational. Flash flood early warnings are based on a combination of the Flash Flood Guidance method and a hydrological model. The system will be maintained and operated through a public-private partnership, which includes a mobile telephone operator, a national meteorological service and an emergency relief service. The mobile telephone operator acts as both the supplier of raw input data and the disseminator of early warnings. The early warning system could significantly reduce the number of fatalities due to flash floods, improve the efficiency of disaster risk reduction efforts and play an important role in strengthening the resilience to climate change of developing countries in Africa. This paper describes the system that is currently being developed for Kenya. Full article
Open AccessArticle Geo-Spatial Support for Assessment of Anthropic Impact on Biodiversity
ISPRS Int. J. Geo-Inf. 2014, 3(2), 599-618; doi:10.3390/ijgi3020599
Received: 31 December 2013 / Revised: 1 April 2014 / Accepted: 3 April 2014 / Published: 22 April 2014
Cited by 6 | PDF Full-text (2281 KB) | HTML Full-text | XML Full-text
Abstract
This paper discusses a methodology where geo-spatial analysis tools are used to quantify risk derived from anthropic activities on habitats and species. The method has been developed with a focus on simplification and the quality of standard procedures set on flora and [...] Read more.
This paper discusses a methodology where geo-spatial analysis tools are used to quantify risk derived from anthropic activities on habitats and species. The method has been developed with a focus on simplification and the quality of standard procedures set on flora and fauna protected by the European Directives. In this study case, the DPSIR (Drivers, Pressures, State, Impacts, Responses) is applied using spatial procedures in a geographical information system (GIS) framework. This approach can be inserted in a multidimensional space as the analysis is applied to each threat, pressure and activity and also to each habitat and species, at the spatial and temporal scale. Threats, pressures and activities, stress and indicators can be managed by means of a geo-database and analyzed using spatial analysis functions in a tested GIS workflow environment. The method applies a matrix with risk values, and the final product is a geo-spatial representation of impact indicators, which can be used as a support for decision-makers at various levels (regional, national and European). Full article
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Open AccessArticle Geo-Based Statistical Models for Vulnerability Prediction of Highway Network Segments
ISPRS Int. J. Geo-Inf. 2014, 3(2), 619-637; doi:10.3390/ijgi3020619
Received: 30 December 2013 / Revised: 8 April 2014 / Accepted: 14 April 2014 / Published: 29 April 2014
Cited by 1 | PDF Full-text (733 KB) | HTML Full-text | XML Full-text
Abstract
This study describes four statistical models—Poisson; Negative Binomial; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial—which were devised in order to examine traffic accidents and estimate the best probability estimating model in terms of future risk assessment at interurban road sections. The study was [...] Read more.
This study describes four statistical models—Poisson; Negative Binomial; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial—which were devised in order to examine traffic accidents and estimate the best probability estimating model in terms of future risk assessment at interurban road sections. The study was conducted on four sets of fixed-length sections of the road network: 500, 750, 1000, and 1500 m. The contribution of transportation and spatial parameters as predictors of road accident rates was evaluated for all four data sets separately. In addition, the Empirical Bayes method was applied. This method uses historical accidents information, allowing regression to the mean phenomenon so as to improve model results. The study was performed using Geographic Information System (GIS) software. Other analyses, such as statistical analyses combined with spatial parameters, interactions, and examination of other geographical areas, were also performed. The results showed that the short road sections data sets of 500 and 750 m yielded the most stable models. This allows focused treatment on short sections of the road network as a way to save resources (enforcement; education and information; finance) and potentially gain maximum benefit at minimum investment. It was found that the significant parameters affecting accident rates are: curvature of the road section; the region and traffic volume. An interaction between the region and traffic volume was also found. Full article
Open AccessArticle A Flexible Spatial Framework for Modeling Spread of Pathogens in Animals with Biosurveillance and Disease Control Applications
ISPRS Int. J. Geo-Inf. 2014, 3(2), 638-661; doi:10.3390/ijgi3020638
Received: 2 December 2013 / Revised: 14 April 2014 / Accepted: 25 April 2014 / Published: 9 May 2014
Cited by 2 | PDF Full-text (1264 KB) | HTML Full-text | XML Full-text
Abstract
Biosurveillance activities focus on acquiring and analyzing epidemiological and biological data to interpret unfolding events and predict outcomes in infectious disease outbreaks. We describe a mathematical modeling framework based on geographically aligned data sources and with appropriate flexibility that partitions the modeling [...] Read more.
Biosurveillance activities focus on acquiring and analyzing epidemiological and biological data to interpret unfolding events and predict outcomes in infectious disease outbreaks. We describe a mathematical modeling framework based on geographically aligned data sources and with appropriate flexibility that partitions the modeling of disease spread into two distinct but coupled levels. A top-level stochastic simulation is defined on a network with nodes representing user-configurable geospatial “patches”. Intra-patch disease spread is treated with differential equations that assume uniform mixing within the patch. We use U.S. county-level aggregated data on animal populations and parameters from the literature to simulate epidemic spread of two strikingly different animal diseases agents: foot-and-mouth disease and highly pathogenic avian influenza. Results demonstrate the capability of this framework to leverage low-fidelity data while producing meaningful output to inform biosurveillance and disease control measures. For example, we show that the possible magnitude of an outbreak is sensitive to the starting location of the outbreak, highlighting the strong geographic dependence of livestock and poultry infectious disease epidemics and the usefulness of effective biosurveillance policy. The ability to compare different diseases and host populations across the geographic landscape is important for decision support applications and for assessing the impact of surveillance, detection, and mitigation protocols. Full article
Open AccessArticle Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images
ISPRS Int. J. Geo-Inf. 2014, 3(2), 693-712; doi:10.3390/ijgi3020693
Received: 26 February 2014 / Revised: 14 April 2014 / Accepted: 25 April 2014 / Published: 9 May 2014
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Abstract
Health and development are intricately related. Although India has made significant progress in the last few decades in the health sector and overall growth in GDP, there are still large regional differences in both health and development. The main objective of this [...] Read more.
Health and development are intricately related. Although India has made significant progress in the last few decades in the health sector and overall growth in GDP, there are still large regional differences in both health and development. The main objective of this paper is to develop techniques for the prediction of health indicators for all the districts of India and examine the correlations between health and development. The level of electrification and district domestic product (DDP) are considered as two fundamental indicators of development in this research. These data, along with health metrics and the information from two nighttime satellite images, were used to propose the models. These successfully predicted the health indicators with less than a 7%–10% error. The chosen health metrics, such as crude birth rate (CBR) and maternal mortality rate (MMR), were mapped for the whole country at the district level. These metrics showed very strong correlation with development indicators (correlation coefficients ranging from 0.92 to 0.99 at the 99% confidence interval). This is the first attempt to use Visible Infrared Imaging Radiometer Suite (VIIRS) (satellite) imagery in a socio-economic study. This paper endorses the observation that areas with a higher DDP and level of electrification have overall better health conditions. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
Open AccessArticle Canadian Forest Fires and the Effects of Long-Range Transboundary Air Pollution on Hospitalizations among the Elderly
ISPRS Int. J. Geo-Inf. 2014, 3(2), 713-731; doi:10.3390/ijgi3020713
Received: 3 March 2014 / Revised: 22 April 2014 / Accepted: 5 May 2014 / Published: 20 May 2014
Cited by 3 | PDF Full-text (956 KB) | HTML Full-text | XML Full-text
Abstract
In July 2002, lightning strikes ignited over 250 fires in Quebec, Canada, destroying over one million hectares of forest. The smoke plume generated from the fires had a major impact on air quality across the east coast of the U.S. Using data [...] Read more.
In July 2002, lightning strikes ignited over 250 fires in Quebec, Canada, destroying over one million hectares of forest. The smoke plume generated from the fires had a major impact on air quality across the east coast of the U.S. Using data from the Medicare National Claims History File and the U.S. Environmental Protection Agency (EPA) National air pollution monitoring network, we evaluated the health impact of smoke exposure on 5.9 million elderly people (ages 65+) in the Medicare population in 81 counties in 11 northeastern and Mid-Atlantic States of the US. We estimated differences in the exposure to ambient PM2.5—airborne particulate matter with aerodynamic diameter of ≤2.5 µm—concentrations and hospitalizations for cardiovascular, pulmonary and injury outcomes, before and during the smoke episode. We found that there was an associated 49.6% (95% confidence interval (CI), 29.8, 72.3) and 64.9% (95% CI, 44.3–88.5) increase rate of hospitalization for respiratory and cardiovascular diagnoses, respectively, when the smoke plume was present compared to before the smoke plume had arrived. Our study suggests that rapid increases in PM2.5 concentrations resulting from wildfire smoke can impact the health of elderly populations thousands of kilometers removed from the fires. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
Open AccessArticle Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico
ISPRS Int. J. Geo-Inf. 2014, 3(2), 732-749; doi:10.3390/ijgi3020732
Received: 24 March 2014 / Revised: 23 April 2014 / Accepted: 29 April 2014 / Published: 20 May 2014
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Abstract
Using a geographic transect in Central Mexico, with an elevation/climate gradient, but uniformity in socio-economic conditions among study sites, this study evaluates the applicability of three widely-used remote sensing (RS) products to link weather conditions with the local abundance of the dengue [...] Read more.
Using a geographic transect in Central Mexico, with an elevation/climate gradient, but uniformity in socio-economic conditions among study sites, this study evaluates the applicability of three widely-used remote sensing (RS) products to link weather conditions with the local abundance of the dengue virus mosquito vector, Aedes aegypti (Ae. aegypti). Field-derived entomological measures included estimates for the percentage of premises with the presence of Ae. aegypti pupae and the abundance of Ae. aegypti pupae per premises. Data on mosquito abundance from field surveys were matched with RS data and analyzed for correlation. Daily daytime and nighttime land surface temperature (LST) values were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua cloud-free images within the four weeks preceding the field survey. Tropical Rainfall Measuring Mission (TRMM)-estimated rainfall accumulation was calculated for the four weeks preceding the field survey. Elevation was estimated through a digital elevation model (DEM). Strong correlations were found between mosquito abundance and RS-derived night LST, elevation and rainfall along the elevation/climate gradient. These findings show that RS data can be used to predict Ae. aegypti abundance, but further studies are needed to define the climatic and socio-economic conditions under which the correlations observed herein can be assumed to apply. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
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Open AccessArticle A Quality Study of the OpenStreetMap Dataset for Tehran
ISPRS Int. J. Geo-Inf. 2014, 3(2), 750-763; doi:10.3390/ijgi3020750
Received: 8 November 2013 / Revised: 22 April 2014 / Accepted: 8 May 2014 / Published: 22 May 2014
Cited by 7 | PDF Full-text (2425 KB) | HTML Full-text | XML Full-text
Abstract
There has been enormous progress in geospatial data acquisition in the last decade. Centralized data collection, mainly by land surveying offices and local government agencies, has changed dramatically to voluntary data provision by citizens. Among a broad list of initiatives dealing with [...] Read more.
There has been enormous progress in geospatial data acquisition in the last decade. Centralized data collection, mainly by land surveying offices and local government agencies, has changed dramatically to voluntary data provision by citizens. Among a broad list of initiatives dealing with user generated geospatial information, OpenStreetMap (OSM) is one of the most famous crowd-sourced products. It is believed that the quality of collected information remains a valid concern. Therefore, qualitative assessment of OSM data as the most significant instance of volunteered geospatial information (VGI) is a considerable issue in the geospatial information community. One aspect of VGI quality assessment pertains to its comparison with institutionally referenced geospatial databases. This paper proposes a new quality metric for assessment of VGI accuracy and as well as for quality analysis of OSM dataset by evaluating its consistency with that of a reference map produced by Municipality of Tehran, Iran. A gridded map is employed and heuristic metrics such as Minimum Bounding Geometry area and directional distribution (Standard Deviational Ellipse), evaluated for both VGI and referenced data, are separately compared in each grid. Finally, in order to have a specific output as an integrated quality metric for VGI, its consistency with ground-truth data is evaluated using fuzzy logic. The results of this research verify that the quality of OSM maps in the study area is fairly good, although the spatial distribution of uncertainty in VGI varies throughout the dataset. Full article
Open AccessArticle Modeling Properties of Influenza-Like Illness Peak Events with Crossing Theory
ISPRS Int. J. Geo-Inf. 2014, 3(2), 764-780; doi:10.3390/ijgi3020764
Received: 6 February 2014 / Revised: 17 April 2014 / Accepted: 15 May 2014 / Published: 26 May 2014
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Abstract
The concept of “peak event” has been used extensively to characterize influenza epidemics. Current definitions, however, could not maximize the amount of pertinent information about the probabilities of peak events that could be extracted from the generally limited available records. This study [...] Read more.
The concept of “peak event” has been used extensively to characterize influenza epidemics. Current definitions, however, could not maximize the amount of pertinent information about the probabilities of peak events that could be extracted from the generally limited available records. This study proposes a new method of defining peak events and statistically characterizing their properties, including: annual event density, their timing, the magnitude over prescribed thresholds and duration. These properties of peak events are analyzed in five counties of Florida using records from the Influenza-Like Illness Surveillance Network (ILINet). Further, the identified properties of peak events are compared between counties to reveal the geographic variability of influenza peak activity. The results of this study illustrate the proposed methodology’s capacity to aid public health professionals in supporting influenza surveillance and implementing timely effective intervention strategies. Full article
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
Open AccessArticle A Geographical-Based Multi-Criteria Approach for Marine Energy Farm Planning
ISPRS Int. J. Geo-Inf. 2014, 3(2), 781-799; doi:10.3390/ijgi3020781
Received: 13 March 2014 / Revised: 15 May 2014 / Accepted: 15 May 2014 / Published: 26 May 2014
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Abstract
The objective of this paper is to devise a strategy for developing a flexible tool to efficiently install a marine energy farm in a suitable area. The current methodology is applied to marine tidal current, although it can be extended to other [...] Read more.
The objective of this paper is to devise a strategy for developing a flexible tool to efficiently install a marine energy farm in a suitable area. The current methodology is applied to marine tidal current, although it can be extended to other energy contexts with some adaptations. We introduce a three-step approach that searches for marine farm sites and technological solutions. The methodology applied is based on a combination of Geographic Information Systems (GIS), multi-criteria analysis (MCA) and an optimization algorithm. The integration of GIS and MCA is at the core of the search process for the best-suited marine areas, taking into account geographical constraints, such as human activity, pressure on the environment and technological opportunities. The optimization step of the approach evaluates the most appropriate technologies and farm configurations in order to maximize the quantity of energy produced while minimizing the cost of the farm. Three main criteria are applied to finally characterize a location for a marine energy farm: the global cost of the project, the quantity of energy produced and social acceptance. The social acceptance criterion is evaluated by the MCA method, Electre III, while the optimization of the energy cost is approximated by a genetic algorithm. The whole approach is illustrated by a case study applied to a maritime area in North-West France. Full article
(This article belongs to the Special Issue GIS for Renewable Energy)
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Open AccessArticle Development of a GIS-Based Tool for Aquaculture Siting
ISPRS Int. J. Geo-Inf. 2014, 3(2), 800-816; doi:10.3390/ijgi3020800
Received: 1 October 2013 / Revised: 15 May 2014 / Accepted: 26 May 2014 / Published: 10 June 2014
Cited by 1 | PDF Full-text (541 KB) | HTML Full-text | XML Full-text
Abstract
Nearshore aquaculture siting requires the integration of a range of physical, environmental, and social factors. As a result, the information demand often presents coastal managers with a range of complex issues regarding where specific types of aquaculture should be ideally located that [...] Read more.
Nearshore aquaculture siting requires the integration of a range of physical, environmental, and social factors. As a result, the information demand often presents coastal managers with a range of complex issues regarding where specific types of aquaculture should be ideally located that reduce environmental and social impacts. Here we provide a framework and tool for managers faced with these issues that incorporate physical and biological parameters along with geospatial infrastructure. In addition, the development of the tool and underlying data included was undertaken with careful input and consideration of local population concerns and cultural practices. Using Hawaiʻi as a model system, we discuss the various considerations that were integrated into an end-user tool for aquaculture siting. Full article
(This article belongs to the Special Issue Coastal GIS)
Open AccessArticle The Sequential Generation of Gaussian Random Fields for Applications in the Geospatial Sciences
ISPRS Int. J. Geo-Inf. 2014, 3(2), 817-852; doi:10.3390/ijgi3020817
Received: 8 February 2014 / Revised: 21 May 2014 / Accepted: 26 May 2014 / Published: 16 June 2014
Cited by 2 | PDF Full-text (2633 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, [...] Read more.
This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, or multivariate, such as , , and  errors. These realizations enable simulation-based performance assessment and tuning of various geospatial applications. Both homogeneous and non-homogeneous random fields are addressed. The sequential generation is very fast and compared to methods based on Cholesky decomposition of an a priori covariance matrix and Sequential Gaussian Simulation. The multi-grid point covariance matrix is also developed for all the above random fields, essential for the optimal performance of many geospatial applications ingesting data with these types of errors. Full article
Open AccessArticle SIT-REM: An Interoperable and Interactive Web Geographic Information System for Fauna, Flora and Plant Landscape Data Management
ISPRS Int. J. Geo-Inf. 2014, 3(2), 853-867; doi:10.3390/ijgi3020853
Received: 26 February 2014 / Revised: 13 May 2014 / Accepted: 3 June 2014 / Published: 16 June 2014
PDF Full-text (681 KB) | HTML Full-text | XML Full-text
Abstract
The main goal of the SIT-REM project is the design and the development of an interoperable web-GIS environment for the information retrieval and data editing/updating of the geobotanical and wildlife map of Marche Region. The vegetation, plant landscape and faunistic analysis allow [...] Read more.
The main goal of the SIT-REM project is the design and the development of an interoperable web-GIS environment for the information retrieval and data editing/updating of the geobotanical and wildlife map of Marche Region. The vegetation, plant landscape and faunistic analysis allow the realization of a regional information system for wildlife-geobotanical data. A main characteristic of the SIT-REM is its flexibility and interoperability, in particular, its ability to be easily updated with the insertion of new types of environmental, faunal or socio-economic data and to generate analyses at any geographical (from regional to local) or quantitative level of detail. Different query levels obtain the latter: spatial queries, hybrid query builder and WMSs usable by means of a GIS. SIT-REM has been available online for more than a year and its use over this period has produced extensive data about users’ experiences. Full article
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Open AccessReview Mapping the Potential for Biofuel Production on Marginal Lands: Differences in Definitions, Data and Models across Scales
ISPRS Int. J. Geo-Inf. 2014, 3(2), 430-459; doi:10.3390/ijgi3020430
Received: 20 December 2013 / Revised: 19 February 2014 / Accepted: 27 February 2014 / Published: 1 April 2014
Cited by 13 | PDF Full-text (451 KB) | HTML Full-text | XML Full-text
Abstract
As energy policies mandate increases in bioenergy production, new research supports growing bioenergy feedstocks on marginal lands. Subsequently there has been an increase in published work that uses Geographic Information Systems (GIS) to map the availability of marginal land as a proxy [...] Read more.
As energy policies mandate increases in bioenergy production, new research supports growing bioenergy feedstocks on marginal lands. Subsequently there has been an increase in published work that uses Geographic Information Systems (GIS) to map the availability of marginal land as a proxy for bioenergy crop potential. However, despite the similarity in stated intent among these works a number of inconsistencies remain across studies that make comparisons and standardization difficult. We reviewed a collection of recent literature that mapped bioenergy potential on marginal lands at varying scales, and found that there is no common working definition of marginal land across all of these works. Specifically, we found considerable differences in mapped results that are driven by dissimilarities in definitions, model framework, data inputs, scale and treatment of uncertainty. Most papers reviewed here employed relatively simple GIS overlays of input criteria, distinct thresholds identifying marginal land, and few details describing accuracy and uncertainty. These differences are likely to be major impediments to integration of studies mapping marginal lands for bioenergy production. We suggest that there is future need for spatial modeling of bioenergy, yet further scholarship is needed to compare across countries and scales to understand the global potential for bioenergy crops. Full article
(This article belongs to the Special Issue GIS for Renewable Energy)
Open AccessReview Web GIS-Based Public Health Surveillance Systems: A Systematic Review
ISPRS Int. J. Geo-Inf. 2014, 3(2), 481-506; doi:10.3390/ijgi3020481
Received: 26 November 2013 / Revised: 14 January 2014 / Accepted: 20 March 2014 / Published: 1 April 2014
Cited by 3 | PDF Full-text (807 KB) | HTML Full-text | XML Full-text
Abstract
Web Geographic Information System (Web GIS) has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web [...] Read more.
Web Geographic Information System (Web GIS) has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web GIS-based Public Health Surveillance Systems (WGPHSSs) and assessed them based on 20 indicators adapted from previous studies. The indicators comprehensively cover various aspects of WGPHSS development, including metadata, data, cartography, data analysis, and technical aspects. Our literature search identified 58 relevant journal articles and 27 eligible WGPHSSs. Analyses of results revealed that WGPHSSs were frequently used for infectious-disease surveillance, and that geographical and performance inequalities existed in their development. The latest Web and Web GIS technologies have been used in developing WGPHSSs; however, significant deficiencies in data analysis, system compatibility, maintenance, and accessibility exist. A balance between public health surveillance and privacy concerns has yet to be struck. Use of news and social media as well as Web-user searching records as data sources, participatory public health surveillance, collaborations among health sectors at different spatial levels and among various disciplines, adaption or reuse of existing WGPHSSs, and adoption of geomashup and open-source development models were identified as the directions for advancing WGPHSSs. Full article
(This article belongs to the Special Issue GIS in Public Health)
Open AccessReview GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues
ISPRS Int. J. Geo-Inf. 2014, 3(2), 662-692; doi:10.3390/ijgi3020662
Received: 4 March 2014 / Revised: 24 April 2014 / Accepted: 25 April 2014 / Published: 9 May 2014
Cited by 8 | PDF Full-text (706 KB) | HTML Full-text | XML Full-text
Abstract
In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, [...] Read more.
In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS) is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future research avenues comprise the availability base data and their “geospatial awareness”, the development of a generic and unified data model, the usage of volunteered geographic information (VGI) and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design. Full article
(This article belongs to the Special Issue GIS for Renewable Energy)

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