Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review.

PubMed

Ding, Zhenyang; Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-04-03

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Distributed spatial information integration based on web service

NASA Astrophysics Data System (ADS)

Tong, Hengjian; Zhang, Yun; Shao, Zhenfeng

2008-10-01

Spatial information systems and spatial information in different geographic locations usually belong to different organizations. They are distributed and often heterogeneous and independent from each other. This leads to the fact that many isolated spatial information islands are formed, reducing the efficiency of information utilization. In order to address this issue, we present a method for effective spatial information integration based on web service. The method applies asynchronous invocation of web service and dynamic invocation of web service to implement distributed, parallel execution of web map services. All isolated information islands are connected by the dispatcher of web service and its registration database to form a uniform collaborative system. According to the web service registration database, the dispatcher of web services can dynamically invoke each web map service through an asynchronous delegating mechanism. All of the web map services can be executed at the same time. When each web map service is done, an image will be returned to the dispatcher. After all of the web services are done, all images are transparently overlaid together in the dispatcher. Thus, users can browse and analyze the integrated spatial information. Experiments demonstrate that the utilization rate of spatial information resources is significantly raised thought the proposed method of distributed spatial information integration.

Distributed spatial information integration based on web service

NASA Astrophysics Data System (ADS)

Tong, Hengjian; Zhang, Yun; Shao, Zhenfeng

2009-10-01

Spatial information systems and spatial information in different geographic locations usually belong to different organizations. They are distributed and often heterogeneous and independent from each other. This leads to the fact that many isolated spatial information islands are formed, reducing the efficiency of information utilization. In order to address this issue, we present a method for effective spatial information integration based on web service. The method applies asynchronous invocation of web service and dynamic invocation of web service to implement distributed, parallel execution of web map services. All isolated information islands are connected by the dispatcher of web service and its registration database to form a uniform collaborative system. According to the web service registration database, the dispatcher of web services can dynamically invoke each web map service through an asynchronous delegating mechanism. All of the web map services can be executed at the same time. When each web map service is done, an image will be returned to the dispatcher. After all of the web services are done, all images are transparently overlaid together in the dispatcher. Thus, users can browse and analyze the integrated spatial information. Experiments demonstrate that the utilization rate of spatial information resources is significantly raised thought the proposed method of distributed spatial information integration.

Spatially continuous distributed fiber optic sensing using optical carrier based microwave interferometry.

PubMed

Huang, Jie; Lan, Xinwei; Luo, Ming; Xiao, Hai

2014-07-28

This paper reports a spatially continuous distributed fiber optic sensing technique using optical carrier based microwave interferometry (OCMI), in which many optical interferometers with the same or different optical path differences are interrogated in the microwave domain and their locations can be unambiguously determined. The concept is demonstrated using cascaded weak optical reflectors along a single optical fiber, where any two arbitrary reflectors are paired to define a low-finesse Fabry-Perot interferometer. While spatially continuous (i.e., no dark zone), fully distributed strain measurement was used as an example to demonstrate the capability, the proposed concept may also be implemented on other types of waveguide or free-space interferometers and used for distributed measurement of various physical, chemical and biological quantities.

A component-based, integrated spatially distributed hydrologic/water quality model: AgroEcoSystem-Watershed (AgES-W) overview and application

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components. The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the addition of nitrogen (N) and sediment modeling compo...

The spatial distribution of cropland carbon transfer in Jilin province during 2014

NASA Astrophysics Data System (ADS)

Cai, Xintong; Meng, Jian; Li, Qiuhui; Gao, Shuang; Zhu, Xianjin

2018-01-01

Cropland carbon transfer (CCT, gC yr-1) is an important component in the carbon budget of terrestrial ecosystems. Analyzing the value of CCT and its spatial variation would provide a data basis for assessing the regional carbon balance. Based on the data from Jilin statistical yearbook 2015, we investigated the spatial variation of CCT in Jilin province during 2014. Results suggest that the CCT of Jilin province was 30.83 TgC, which exhibited a decreasing trend from the centre to the border but the west side was higher than the east. The magnitude of carbon transfer per area (MCT), which showed a similar spatial distribution with CCT, was the dominating component of CCT spatial distribution. The spatial distribution of MCT was jointly affected by that of the ratio of planting area to regional area (RPR) and carbon transfer per planting area (CTP), where RPR and CTP contributed 65.55% and 34.5% of MCT spatial distribution, respectively. Therefore, CCT in Jilin province spatially varied, which made it highly needed to consider the difference in CCT among regions when we assessing the regional carbon budget.

Mapping the spatial distribution of global anthropogenic mercury atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Wilson, Simon J.; Steenhuisen, Frits; Pacyna, Jozef M.; Pacyna, Elisabeth G.

This paper describes the procedures employed to spatially distribute global inventories of anthropogenic emissions of mercury to the atmosphere, prepared by Pacyna, E.G., Pacyna, J.M., Steenhuisen, F., Wilson, S. [2006. Global anthropogenic mercury emission inventory for 2000. Atmospheric Environment, this issue, doi:10.1016/j.atmosenv.2006.03.041], and briefly discusses the results of this work. A new spatially distributed global emission inventory for the (nominal) year 2000, and a revised version of the 1995 inventory are presented. Emissions estimates for total mercury and major species groups are distributed within latitude/longitude-based grids with a resolution of 1×1 and 0.5×0.5°. A key component in the spatial distribution procedure is the use of population distribution as a surrogate parameter to distribute emissions from sources that cannot be accurately geographically located. In this connection, new gridded population datasets were prepared, based on the CEISIN GPW3 datasets (CIESIN, 2004. Gridded Population of the World (GPW), Version 3. Center for International Earth Science Information Network (CIESIN), Columbia University and Centro Internacional de Agricultura Tropical (CIAT). GPW3 data are available at http://beta.sedac.ciesin.columbia.edu/gpw/index.jsp). The spatially distributed emissions inventories and population datasets prepared in the course of this work are available on the Internet at www.amap.no/Resources/HgEmissions/

Soil nutrients influence spatial distributions of tropical tree species.

PubMed

John, Robert; Dalling, James W; Harms, Kyle E; Yavitt, Joseph B; Stallard, Robert F; Mirabello, Matthew; Hubbell, Stephen P; Valencia, Renato; Navarrete, Hugo; Vallejo, Martha; Foster, Robin B

2007-01-16

The importance of niche vs. neutral assembly mechanisms in structuring tropical tree communities remains an important unsettled question in community ecology [Bell G (2005) Ecology 86:1757-1770]. There is ample evidence that species distributions are determined by soils and habitat factors at landscape (<10(4) km(2)) and regional scales. At local scales (<1 km(2)), however, habitat factors and species distributions show comparable spatial aggregation, making it difficult to disentangle the importance of niche and dispersal processes. In this article, we test soil resource-based niche assembly at a local scale, using species and soil nutrient distributions obtained at high spatial resolution in three diverse neotropical forest plots in Colombia (La Planada), Ecuador (Yasuni), and Panama (Barro Colorado Island). Using spatial distribution maps of >0.5 million individual trees of 1,400 species and 10 essential plant nutrients, we used Monte Carlo simulations of species distributions to test plant-soil associations against null expectations based on dispersal assembly. We found that the spatial distributions of 36-51% of tree species at these sites show strong associations to soil nutrient distributions. Neutral dispersal assembly cannot account for these plant-soil associations or the observed niche breadths of these species. These results indicate that belowground resource availability plays an important role in the assembly of tropical tree communities at local scales and provide the basis for future investigations on the mechanisms of resource competition among tropical tree species.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

Ladar imaging detection of salient map based on PWVD and Rényi entropy

NASA Astrophysics Data System (ADS)

Xu, Yuannan; Zhao, Yuan; Deng, Rong; Dong, Yanbing

2013-10-01

Spatial-frequency information of a given image can be extracted by associating the grey-level spatial data with one of the well-known spatial/spatial-frequency distributions. The Wigner-Ville distribution (WVD) has a good characteristic that the images can be represented in spatial/spatial-frequency domains. For intensity and range images of ladar, through the pseudo Wigner-Ville distribution (PWVD) using one or two dimension window, the statistical property of Rényi entropy is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on PWVD and Rényi entropy is proposed. After that, target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.

Within-field spatial distribution of Megacopta cribraria (Hemiptera: Plataspidae) in soybean (Fabales: Fabaceae).

PubMed

Seiter, Nicholas J; Reay-Jones, Francis P F; Greene, Jeremy K

2013-12-01

The recently introduced plataspid Megacopta cribraria (F.) can infest fields of soybean (Glycine max (L.) Merrill) in the southeastern United States. Grid sampling in four soybean fields was conducted in 2011 and 2012 to study the spatial distribution of M. cribraria adults, nymphs, and egg masses. Peak oviposition typically occurred in early August, while peak levels of adults occurred in mid-late September. The overall sex ratio was slightly biased at 53.1 ± 0.2% (SEM) male. Sweep samples of nymphs were biased toward late instars. All three life stages exhibited a generally aggregated spatial distribution based on Taylor's power law, Iwao's patchiness regression, and spatial analysis by distance indices (SADIE). Interpolation maps of local SADIE aggregation indices showed clusters of adults and nymphs located at field edges, and mean densities of adults were higher in samples taken from field edges than in those taken from field interiors. Adults and nymphs were often spatially associated based on SADIE, indicating spatial stability across life stages.

Implementing an SIG based platform of application and service for city spatial information in Shanghai

NASA Astrophysics Data System (ADS)

Yu, Bailang; Wu, Jianping

2006-10-01

Spatial Information Grid (SIG) is an infrastructure that has the ability to provide the services for spatial information according to users' needs by means of collecting, sharing, organizing and processing the massive distributed spatial information resources. This paper presents the architecture, technologies and implementation of the Shanghai City Spatial Information Application and Service System, a SIG based platform, which is an integrated platform that serves for administration, planning, construction and development of the city. In the System, there are ten categories of spatial information resources, including city planning, land-use, real estate, river system, transportation, municipal facility construction, environment protection, sanitation, urban afforestation and basic geographic information data. In addition, spatial information processing services are offered as a means of GIS Web Services. The resources and services are all distributed in different web-based nodes. A single database is created to store the metadata of all the spatial information. A portal site is published as the main user interface of the System. There are three main functions in the portal site. First, users can search the metadata and consequently acquire the distributed data by using the searching results. Second, some spatial processing web applications that developed with GIS Web Services, such as file format conversion, spatial coordinate transfer, cartographic generalization and spatial analysis etc, are offered to use. Third, GIS Web Services currently available in the System can be searched and new ones can be registered. The System has been working efficiently in Shanghai Government Network since 2005.

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds

NASA Astrophysics Data System (ADS)

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K.

2018-04-01

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement.

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

Spatial dynamics of the invasive defoliator amber-marked birch leafminer across the Anchorage landscape

Treesearch

J.E. Lundquist; R.M. Reich; M. Tuffly

2012-01-01

The amber-marked birch leafminer has caused severe infestations of birch species in Anchorage, AK, since 2002. Its spatial distribution has been monitored since 2006 and summarized using interpolated surfaces based on simple kriging. In this study, we developed methods of assessing and describing spatial distribution of the leafminer as they vary from year to year, and...

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

The role of experience in location estimation: Target distributions shift location memory biases.

PubMed

Lipinski, John; Simmering, Vanessa R; Johnson, Jeffrey S; Spencer, John P

2010-04-01

Research based on the Category Adjustment model concluded that the spatial distribution of target locations does not influence location estimation responses [Huttenlocher, J., Hedges, L., Corrigan, B., & Crawford, L. E. (2004). Spatial categories and the estimation of location. Cognition, 93, 75-97]. This conflicts with earlier results showing that location estimation is biased relative to the spatial distribution of targets [Spencer, J. P., & Hund, A. M. (2002). Prototypes and particulars: Geometric and experience-dependent spatial categories. Journal of Experimental Psychology: General, 131, 16-37]. Here, we resolve this controversy by using a task based on Huttenlocher et al. (Experiment 4) with minor modifications to enhance our ability to detect experience-dependent effects. Results after the first block of trials replicate the pattern reported in Huttenlocher et al. After additional experience, however, participants showed biases that significantly shifted according to the target distributions. These results are consistent with the Dynamic Field Theory, an alternative theory of spatial cognition that integrates long-term memory traces across trials relative to the perceived structure of the task space. Copyright 2009 Elsevier B.V. All rights reserved.

Research on reconstructing spatial distribution of historical cropland over 300 years in traditional cultivated regions of China

NASA Astrophysics Data System (ADS)

Yang, Xuhong; Jin, Xiaobin; Guo, Beibei; Long, Ying; Zhou, Yinkang

2015-05-01

Constructing a spatially explicit time series of historical cultivated land is of upmost importance for climatic and ecological studies that make use of Land Use and Cover Change (LUCC) data. Some scholars have made efforts to simulate and reconstruct the quantitative information on historical land use at the global or regional level based on "top-down" decision-making behaviors to match overall cropland area to land parcels using land arability and universal parameters. Considering the concentrated distribution of cultivated land and various factors influencing cropland distribution, including environmental and human factors, this study developed a "bottom-up" model of historical cropland based on constrained Cellular Automaton (CA). Our model takes a historical cropland area as an external variable and the cropland distribution in 1980 as the maximum potential scope of historical cropland. We selected elevation, slope, water availability, average annual precipitation, and distance to the nearest rural settlement as the main influencing factors of land use suitability. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. This paper applies the model to a traditional cultivated region in China and reconstructs its spatial distribution of cropland during 6 periods. The results are shown as follows: (1) a constrained CA is well suited for simulating and reconstructing the spatial distribution of cropland in China's traditional cultivated region. (2) Taking the different factors affecting spatial pattern of cropland into consideration, the partitioning of the research area effectively reflected the spatial differences in cropland evolution rules and rates. (3) Compared with "HYDE datasets", this research has formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format. We conclude that our reconstruction is closer to the actual change pattern of the traditional cultivated region in China.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Spatial distribution of soil organic carbon and total nitrogen based on GIS and geostatistics in a small watershed in a hilly area of northern China.

PubMed

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0-20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km(2)) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.

Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China

PubMed Central

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km2) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed. PMID:24391791

Research on key technologies for data-interoperability-based metadata, data compression and encryption, and their application

NASA Astrophysics Data System (ADS)

Yu, Xu; Shao, Quanqin; Zhu, Yunhai; Deng, Yuejin; Yang, Haijun

2006-10-01

With the development of informationization and the separation between data management departments and application departments, spatial data sharing becomes one of the most important objectives for the spatial information infrastructure construction, and spatial metadata management system, data transmission security and data compression are the key technologies to realize spatial data sharing. This paper discusses the key technologies for metadata based on data interoperability, deeply researches the data compression algorithms such as adaptive Huffman algorithm, LZ77 and LZ78 algorithm, studies to apply digital signature technique to encrypt spatial data, which can not only identify the transmitter of spatial data, but also find timely whether the spatial data are sophisticated during the course of network transmission, and based on the analysis of symmetric encryption algorithms including 3DES,AES and asymmetric encryption algorithm - RAS, combining with HASH algorithm, presents a improved mix encryption method for spatial data. Digital signature technology and digital watermarking technology are also discussed. Then, a new solution of spatial data network distribution is put forward, which adopts three-layer architecture. Based on the framework, we give a spatial data network distribution system, which is efficient and safe, and also prove the feasibility and validity of the proposed solution.

Soil nutrients influence spatial distributions of tropical tree species

PubMed Central

John, Robert; Dalling, James W.; Harms, Kyle E.; Yavitt, Joseph B.; Stallard, Robert F.; Mirabello, Matthew; Hubbell, Stephen P.; Valencia, Renato; Navarrete, Hugo; Vallejo, Martha; Foster, Robin B.

2007-01-01

The importance of niche vs. neutral assembly mechanisms in structuring tropical tree communities remains an important unsettled question in community ecology [Bell G (2005) Ecology 86:1757–1770]. There is ample evidence that species distributions are determined by soils and habitat factors at landscape (<104 km2) and regional scales. At local scales (<1 km2), however, habitat factors and species distributions show comparable spatial aggregation, making it difficult to disentangle the importance of niche and dispersal processes. In this article, we test soil resource-based niche assembly at a local scale, using species and soil nutrient distributions obtained at high spatial resolution in three diverse neotropical forest plots in Colombia (La Planada), Ecuador (Yasuni), and Panama (Barro Colorado Island). Using spatial distribution maps of >0.5 million individual trees of 1,400 species and 10 essential plant nutrients, we used Monte Carlo simulations of species distributions to test plant–soil associations against null expectations based on dispersal assembly. We found that the spatial distributions of 36–51% of tree species at these sites show strong associations to soil nutrient distributions. Neutral dispersal assembly cannot account for these plant–soil associations or the observed niche breadths of these species. These results indicate that belowground resource availability plays an important role in the assembly of tropical tree communities at local scales and provide the basis for future investigations on the mechanisms of resource competition among tropical tree species. PMID:17215353

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Spatial modeling of the geographic distribution of wildlife populations: A case study in the lower Mississippi River region

USGS Publications Warehouse

Ji, W.; Jeske, C.

2000-01-01

A geographic information system (GIS)-based spatial modeling approach was developed to study environmental and land use impacts on the geographic distribution of wintering northern pintails (Arias acuta) in the Lower Mississippi River region. Pintails were fitted with backpack radio transmitter packages at Catahoula Lake, LA, in October 1992-1994 and located weekly through the following March. Pintail survey data were converted into a digital database in ARC/INFO GIS format and integrated with environmental GIS data through a customized modeling interface. The study verified the relationship between pintail distributions and major environmental factors and developed a conceptual relation model. Visualization-based spatial simulations were used to display the movement patterns of specific population groups under spatial and temporal constraints. The spatial modeling helped understand the seasonal movement patterns of pintails in relation to their habitat usage in Arkansas and southwestern Louisiana for wintering and interchange situations among population groups wintering in Texas and southeastern Louisiana. (C) 2000 Elsevier Science B.V.

Validation of temporal and spatial consistency of facility- and speed-specific vehicle-specific power distributions for emission estimation: A case study in Beijing, China.

PubMed

Zhai, Zhiqiang; Song, Guohua; Lu, Hongyu; He, Weinan; Yu, Lei

2017-09-01

Vehicle-specific power (VSP) has been found to be highly correlated with vehicle emissions. It is used in many studies on emission modeling such as the MOVES (Motor Vehicle Emissions Simulator) model. The existing studies develop specific VSP distributions (or OpMode distribution in MOVES) for different road types and various average speeds to represent the vehicle operating modes on road. However, it is still not clear if the facility- and speed-specific VSP distributions are consistent temporally and spatially. For instance, is it necessary to update periodically the database of the VSP distributions in the emission model? Are the VSP distributions developed in the city central business district (CBD) area applicable to its suburb area? In this context, this study examined the temporal and spatial consistency of the facility- and speed-specific VSP distributions in Beijing. The VSP distributions in different years and in different areas are developed, based on real-world vehicle activity data. The root mean square error (RMSE) is employed to quantify the difference between the VSP distributions. The maximum differences of the VSP distributions between different years and between different areas are approximately 20% of that between different road types. The analysis of the carbon dioxide (CO 2 ) emission factor indicates that the temporal and spatial differences of the VSP distributions have no significant impact on vehicle emission estimation, with relative error of less than 3%. The temporal and spatial differences have no significant impact on the development of the facility- and speed-specific VSP distributions for the vehicle emission estimation. The database of the specific VSP distributions in the VSP-based emission models can maintain in terms of time. Thus, it is unnecessary to update the database regularly, and it is reliable to use the history vehicle activity data to forecast the emissions in the future. In one city, the areas with less data can still develop accurate VSP distributions based on better data from other areas.

Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.

PubMed

Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C

2014-11-01

Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.

aerosol radiative effects and forcing: spatial and temporal distributions

NASA Astrophysics Data System (ADS)

Kinne, Stefan

2014-05-01

A monthly climatology for aerosol optical properties based on a synthesis from global modeling and observational data has been applied to illustrate spatial distributions and global averages of aerosol radiative impacts. With the help of a pre-industrial reference for aerosol optical properties from global modeling, also the aerosol direct forcing (ca -0.35W/m2 globally and annual averaged) and their spatial and seasonal distributions and contributions by individual aerosol components are estimated. Finally, CCN and IN concentrations associated with this climatology are applied to estimate aerosol indirect effects and forcing.

A log-Weibull spatial scan statistic for time to event data.

PubMed

Usman, Iram; Rosychuk, Rhonda J

2018-06-13

Spatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions. We propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas. We proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

Reserch on Spatial and Temporal Distribution of Color Steel Building Based on Multi-Source High-Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Yang, S. W.; Ma, J. J.; Wang, J. M.

2018-04-01

As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city's image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building's special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.

Geographical distribution patterns of iodine in drinking-water and its associations with geological factors in Shandong Province, China.

PubMed

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-05-19

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran's I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors.

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

Use of UAS remote sensing data to estimate crop ET at high spatial resolution

USDA-ARS?s Scientific Manuscript database

Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

Quantification of root water uptake in soil using X-ray computed tomography and image-based modelling.

PubMed

Daly, Keith R; Tracy, Saoirse R; Crout, Neil M J; Mairhofer, Stefan; Pridmore, Tony P; Mooney, Sacha J; Roose, Tiina

2018-01-01

Spatially averaged models of root-soil interactions are often used to calculate plant water uptake. Using a combination of X-ray computed tomography (CT) and image-based modelling, we tested the accuracy of this spatial averaging by directly calculating plant water uptake for young wheat plants in two soil types. The root system was imaged using X-ray CT at 2, 4, 6, 8 and 12 d after transplanting. The roots were segmented using semi-automated root tracking for speed and reproducibility. The segmented geometries were converted to a mesh suitable for the numerical solution of Richards' equation. Richards' equation was parameterized using existing pore scale studies of soil hydraulic properties in the rhizosphere of wheat plants. Image-based modelling allows the spatial distribution of water around the root to be visualized and the fluxes into the root to be calculated. By comparing the results obtained through image-based modelling to spatially averaged models, the impact of root architecture and geometry in water uptake was quantified. We observed that the spatially averaged models performed well in comparison to the image-based models with <2% difference in uptake. However, the spatial averaging loses important information regarding the spatial distribution of water near the root system. © 2017 John Wiley & Sons Ltd.

Gis-Based Spatial Statistical Analysis of College Graduates Employment

NASA Astrophysics Data System (ADS)

Tang, R.

2012-07-01

It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

Estimating recharge rates with analytic element models and parameter estimation

USGS Publications Warehouse

Dripps, W.R.; Hunt, R.J.; Anderson, M.P.

2006-01-01

Quantifying the spatial and temporal distribution of recharge is usually a prerequisite for effective ground water flow modeling. In this study, an analytic element (AE) code (GFLOW) was used with a nonlinear parameter estimation code (UCODE) to quantify the spatial and temporal distribution of recharge using measured base flows as calibration targets. The ease and flexibility of AE model construction and evaluation make this approach well suited for recharge estimation. An AE flow model of an undeveloped watershed in northern Wisconsin was optimized to match median annual base flows at four stream gages for 1996 to 2000 to demonstrate the approach. Initial optimizations that assumed a constant distributed recharge rate provided good matches (within 5%) to most of the annual base flow estimates, but discrepancies of >12% at certain gages suggested that a single value of recharge for the entire watershed is inappropriate. Subsequent optimizations that allowed for spatially distributed recharge zones based on the distribution of vegetation types improved the fit and confirmed that vegetation can influence spatial recharge variability in this watershed. Temporally, the annual recharge values varied >2.5-fold between 1996 and 2000 during which there was an observed 1.7-fold difference in annual precipitation, underscoring the influence of nonclimatic factors on interannual recharge variability for regional flow modeling. The final recharge values compared favorably with more labor-intensive field measurements of recharge and results from studies, supporting the utility of using linked AE-parameter estimation codes for recharge estimation. Copyright ?? 2005 The Author(s).

The Role of Experience in Location Estimation: Target Distributions Shift Location Memory Biases

ERIC Educational Resources Information Center

Lipinski, John; Simmering, Vanessa R.; Johnson, Jeffrey S.; Spencer, John P.

2010-01-01

Research based on the Category Adjustment model concluded that the spatial distribution of target locations does not influence location estimation responses [Huttenlocher, J., Hedges, L., Corrigan, B., & Crawford, L. E. (2004). Spatial categories and the estimation of location. "Cognition, 93", 75-97]. This conflicts with earlier results showing…

Design & implementation of distributed spatial computing node based on WPS

NASA Astrophysics Data System (ADS)

Liu, Liping; Li, Guoqing; Xie, Jibo

2014-03-01

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds.

PubMed

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K

2018-04-27

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations

USGS Publications Warehouse

Starr, James C.; Torgersen, Christian E.

2015-01-01

We compared the assemblage structure, spatial distributions, and habitat associations of mountain whitefish (Prosopium williamsoni) morphotypes and size classes. We hypothesised that morphotypes would have different spatial distributions and would be associated with different habitat features based on feeding behaviour and diet. Spatially continuous sampling was conducted over a broad extent (29 km) in the Calawah River, WA (USA). Whitefish were enumerated via snorkelling in three size classes: small (10–29 cm), medium (30–49 cm), and large (≥50 cm). We identified morphotypes based on head and snout morphology: a pinocchio form that had an elongated snout and a normal form with a blunted snout. Large size classes of both morphotypes were distributed downstream of small and medium size classes, and normal whitefish were distributed downstream of pinocchio whitefish. Ordination of whitefish assemblages with nonmetric multidimensional scaling revealed that normal whitefish size classes were associated with higher gradient and depth, whereas pinocchio whitefish size classes were positively associated with pool area, distance upstream, and depth. Reach-scale generalised additive models indicated that normal whitefish relative density was associated with larger substrate size in downstream reaches (R2 = 0.64), and pinocchio whitefish were associated with greater stream depth in the reaches farther upstream (R2 = 0.87). These results suggest broad-scale spatial segregation (1–10 km), particularly between larger and more phenotypically extreme individuals. These results provide the first perspective on spatial distributions and habitat relationships of polymorphic mountain whitefish.

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques.

PubMed

Chen, Tao; Niu, Rui-qing; Wang, Yi; Li, Ping-xiang; Zhang, Liang-pei; Du, Bo

2011-08-01

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.

RipleyGUI: software for analyzing spatial patterns in 3D cell distributions

PubMed Central

Hansson, Kristin; Jafari-Mamaghani, Mehrdad; Krieger, Patrik

2013-01-01

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers. PMID:23658544

An fMRI study of sex differences in regional activation to a verbal and a spatial task.

PubMed

Gur, R C; Alsop, D; Glahn, D; Petty, R; Swanson, C L; Maldjian, J A; Turetsky, B I; Detre, J A; Gee, J; Gur, R E

2000-09-01

Sex differences in cognitive performance have been documented, women performing better on some phonological tasks and men on spatial tasks. An earlier fMRI study suggested sex differences in distributed brain activation during phonological processing, with bilateral activation seen in women while men showed primarily left-lateralized activation. This blood oxygen level-dependent fMRI study examined sex differences (14 men, 13 women) in activation for a spatial task (judgment of line orientation) compared to a verbal-reasoning task (analogies) that does not typically show sex differences. Task difficulty was manipulated. Hypothesized ROI-based analysis documented the expected left-lateralized changes for the verbal task in the inferior parietal and planum temporal regions in both men and women, but only men showed right-lateralized increase for the spatial task in these regions. Image-based analysis revealed a distributed network of cortical regions activated by the tasks, which consisted of the lateral frontal, medial frontal, mid-temporal, occipitoparietal, and occipital regions. The activation was more left lateralized for the verbal and more right for the spatial tasks, but men also showed some left activation for the spatial task, which was not seen in women. Increased task difficulty produced more distributed activation for the verbal and more circumscribed activation for the spatial task. The results suggest that failure to activate the appropriate hemisphere in regions directly involved in task performance may explain certain sex differences in performance. They also extend, for a spatial task, the principle that bilateral activation in a distributed cognitive system underlies sex differences in performance. Copyright 2000 Academic Press.

Spatial distribution of 214Po ions in the electrostatic collection.

PubMed

Barlas, E; Bayrak, A; Emirhan, E; Haciomeroglu, S; Ozben, C S

2013-10-01

A low cost Si-PIN photodiode-based radon monitor was successfully designed and produced to monitor precursory earthquake indicators in the Northern Anatolian Fault Line. The spatial distribution of (214)Po ions was determined by comparing the 7.69 MeV (214)Po peak in the MCA spectrum and the Geant4 energy distribution of alpha particles at various detector source distances. Copyright © 2013 Elsevier Ltd. All rights reserved.

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

USGS Publications Warehouse

Wallace, C.S.A.; Marsh, S.E.

2005-01-01

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

Temporal and spatial distribution of Microcystis biomass and genotype in bloom areas of Lake Taihu.

PubMed

Guan, Dong-Xing; Wang, Xingyu; Xu, Huacheng; Chen, Li; Li, Pengfu; Ma, Lena Q

2018-06-26

Cyanobacterial blooms as a global environmental issue are of public health concern. In this study, we investigated the spatial (10 sites) and temporal (June, August and October) variations in: 1) their biomass based on chlorophyll-a (chl-a) concentration, 2) their toxic genotype based on gene copy ratio of mcyJ to cpcBA, and 3) their cpcBA genotype composition of Microcystis during cyanobacterial bloom in Lake Taihu. While spatial-temporal variations were found in chl-a and mcyJ/cpcBA ratio, only spatial variation was observed in cpcBA genotype composition. Samples from northwestern part had a higher chl-a, but mcyJ/cpcBA ratio didn't vary among the sites. High chl-a was observed in August, while mcyJ/cpcBA ratio and genotypic richness increased with time. The spatial variations in chl-a and mcyJ/cpcBA ratio and temporal variation in cpcBA genotype were correlated negatively with dissolved N and positively with dissolved P. Spatial distribution of Microcystis biomass was positively correlated with nitrite and P excluding October, but no correlation was found for spatial distribution of mcyJ/cpcBA ratio and cpcBA genotype. Spatial distribution of toxic and cpcBA genotypes may result from horizontal transport of Microcystis colonies, while spatial variation in Microcystis biomass was probably controlled by both nutrient-mediated growth and horizontal transport of Microcystis. The temporal variation in Microcystis biomass, toxic genotype and cpcBA genotype composition were related to nutrient levels, but cause-and-effect relationships require further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Stochastic characteristics of different duration annual maximum rainfall and its spatial difference in China based on information entropy

NASA Astrophysics Data System (ADS)

Li, X.; Sang, Y. F.

2017-12-01

Mountain torrents, urban floods and other disasters caused by extreme precipitation bring great losses to the ecological environment, social and economic development, people's lives and property security. So there is of great significance to floods prevention and control by the study of its spatial distribution. Based on the annual maximum rainfall data of 60min, 6h and 24h, the paper generate long sequences following Pearson-III distribution, and then use the information entropy index to study the spatial distribution and difference of different duration. The results show that the information entropy value of annual maximum rainfall in the south region is greater than that in the north region, indicating more obvious stochastic characteristics of annual maximum rainfall in the latter. However, the spatial distribution of stochastic characteristics is different in different duration. For example, stochastic characteristics of 60min annual maximum rainfall in the Eastern Tibet is smaller than surrounding, but 6h and 24h annual maximum rainfall is larger than surrounding area. In the Haihe River Basin and the Huaihe River Basin, the stochastic characteristics of the 60min annual maximum rainfall was not significantly different from that in the surrounding area, and stochastic characteristics of 6h and 24h was smaller than that in the surrounding area. We conclude that the spatial distribution of information entropy values of annual maximum rainfall in different duration can reflect the spatial distribution of its stochastic characteristics, thus the results can be an importantly scientific basis for the flood prevention and control, agriculture, economic-social developments and urban flood control and waterlogging.

Informed herbivore movement and interplant communication determine the effects of induced resistance in an individual-based model.

PubMed

Rubin, Ilan N; Ellner, Stephen P; Kessler, André; Morrell, Kimberly A

2015-09-01

1. Plant induced resistance to herbivory affects the spatial distribution of herbivores, as well as their performance. In recent years, theories regarding the benefit to plants of induced resistance have shifted from ideas of optimal resource allocation towards a more eclectic set of theories that consider spatial and temporal plant variability and the spatial distribution of herbivores among plants. However, consensus is lacking on whether induced resistance causes increased herbivore aggregation or increased evenness, as both trends have been experimentally documented. 2. We created a spatial individual-based model that can describe many plant-herbivore systems with induced resistance, in order to analyse how different aspects of induced resistance might affect herbivore distribution, and the total damage to a plant population, during a growing season. 3. We analyse the specific effects on herbivore aggregation of informed herbivore movement (preferential movement to less-damaged plants) and of information transfer between plants about herbivore attacks, in order to identify mechanisms driving both aggregation and evenness. We also investigate how the resulting herbivore distributions affect the total damage to plants and aggregation of damage. 4. Even, random and aggregated herbivore distributions can all occur in our model with induced resistance. Highest levels of aggregation occurred in the models with informed herbivore movement, and the most even distributions occurred when the average number of herbivores per plant was low. With constitutive resistance, only random distributions occur. Damage to plants was spatially correlated, unless plants recover very quickly from damage; herbivore spatial autocorrelation was always weak. 5. Our model and results provide a simple explanation for the apparent conflict between experimental results, indicating that both increased aggregation and increased evenness of herbivores can result from induced resistance. We demonstrate that information transfer from plants to herbivores, and from plants to neighbouring plants, can both be major factors in determining non-random herbivore distributions. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China

PubMed Central

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-01-01

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran’s I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors. PMID:24852390

Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

The Spatially-Distributed Agroecosystem-Watershed (Ages-W) Hydrologic/Water Quality (H/WQ) model for assessment of conservation effects

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...

[Multivariate geostatistics and GIS-based approach to study the spatial distribution and sources of heavy metals in agricultural soil in the Pearl River Delta, China].

PubMed

Cai, Li-mei; Ma, Jin; Zhou, Yong-zhang; Huang, Lan-chun; Dou, Lei; Zhang, Cheng-bo; Fu, Shan-ming

2008-12-01

One hundred and eighteen surface soil samples were collected from the Dongguan City, and analyzed for concentration of Cu, Zn, Ni, Cr, Pb, Cd, As, Hg, pH and OM. The spatial distribution and sources of soil heavy metals were studied using multivariate geostatistical methods and GIS technique. The results indicated concentrations of Cu, Zn, Ni, Pb, Cd and Hg were beyond the soil background content in Guangdong province, and especially concentrations of Pb, Cd and Hg were greatly beyond the content. The results of factor analysis group Cu, Zn, Ni, Cr and As in Factor 1, Pb and Hg in Factor 2 and Cd in Factor 3. The spatial maps based on geostatistical analysis show definite association of Factor 1 with the soil parent material, Factor 2 was mainly affected by industries. The spatial distribution of Factor 3 was attributed to anthropogenic influence.

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

PubMed

Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

2016-11-28

We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

PubMed Central

Pham, Tuan D.

2014-01-01

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi.

PubMed

Zhou, Lei; Yang, Shan; Wang, Shuguang; Xiong, Liyang

2017-01-01

Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies.

Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi

PubMed Central

Zhou, Lei; Yang, Shan; Wang, Shuguang

2017-01-01

Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies. PMID:28278284

A Geospatial Information Grid Framework for Geological Survey.

PubMed

Wu, Liang; Xue, Lei; Li, Chaoling; Lv, Xia; Chen, Zhanlong; Guo, Mingqiang; Xie, Zhong

2015-01-01

The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper.

A Geospatial Information Grid Framework for Geological Survey

PubMed Central

Wu, Liang; Xue, Lei; Li, Chaoling; Lv, Xia; Chen, Zhanlong; Guo, Mingqiang; Xie, Zhong

2015-01-01

The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper. PMID:26710255

Image Quality Assessment Using the Joint Spatial/Spatial-Frequency Representation

NASA Astrophysics Data System (ADS)

Beghdadi, Azeddine; Iordache, Răzvan

2006-12-01

This paper demonstrates the usefulness of spatial/spatial-frequency representations in image quality assessment by introducing a new image dissimilarity measure based on 2D Wigner-Ville distribution (WVD). The properties of 2D WVD are shortly reviewed, and the important issue of choosing the analytic image is emphasized. The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.

Alcohol beverage control, privatization and the geographic distribution of alcohol outlets

PubMed Central

2012-01-01

Background With Pennsylvania currently considering a move away from an Alcohol Beverage Control state to a privatized alcohol distribution system, this study uses a spatial analytical approach to examine potential impacts of privatization on the number and spatial distribution of alcohol outlets in the city of Philadelphia over a long time horizon. Methods A suite of geospatial data were acquired for Philadelphia, including 1,964 alcohol outlet locations, 569,928 land parcels, and school, church, hospital, park and playground locations. These data were used as inputs for exploratory spatial analysis to estimate the expected number of outlets that would eventually operate in Philadelphia. Constraints included proximity restrictions (based on current ordinances regulating outlet distribution) of at least 200 feet between alcohol outlets and at least 300 feet between outlets and schools, churches, hospitals, parks and playgrounds. Results Findings suggest that current state policies on alcohol outlet distributions in Philadelphia are loosely enforced, with many areas exhibiting extremely high spatial densities of outlets that violate existing proximity restrictions. The spatial model indicates that an additional 1,115 outlets could open in Philadelphia if privatization was to occur and current proximity ordinances were maintained. Conclusions The study reveals that spatial analytical approaches can function as an excellent tool for contingency-based “what-if” analysis, providing an objective snapshot of potential policy outcomes prior to implementation. In this case, the likely outcome is a tremendous increase in alcohol outlets in Philadelphia, with concomitant negative health, crime and quality of life outcomes that accompany such an increase. PMID:23170899

Multistage Spatial Property Based Segmentation for Quantification of Fluorescence Distribution in Cells

NASA Astrophysics Data System (ADS)

Zhang, Guangyun; Jia, Xiuping; Pham, Tuan D.; Crane, Denis I.

2010-01-01

The interpretation of the distribution of fluorescence in cells is often by simple visualization of microscope-derived images for qualitative studies. In other cases, however, it is desirable to be able to quantify the distribution of fluorescence using digital image processing techniques. In this paper, the challenges of fluorescence segmentation due to the noise present in the data are addressed. We report that intensity measurements alone do not allow separation of overlapping data between target and background. Consequently, spatial properties derived from neighborhood profile were included. Mathematical Morphological operations were implemented for cell boundary extraction and a window based contrast measure was developed for fluorescence puncta identification. All of these operations were applied in the proposed multistage processing scheme. The testing results show that the spatial measures effectively enhance the target separability.

Valid approximation of spatially distributed grain size distributions - A priori information encoded to a feedforward network

NASA Astrophysics Data System (ADS)

Berthold, T.; Milbradt, P.; Berkhahn, V.

2018-04-01

This paper presents a model for the approximation of multiple, spatially distributed grain size distributions based on a feedforward neural network. Since a classical feedforward network does not guarantee to produce valid cumulative distribution functions, a priori information is incor porated into the model by applying weight and architecture constraints. The model is derived in two steps. First, a model is presented that is able to produce a valid distribution function for a single sediment sample. Although initially developed for sediment samples, the model is not limited in its application; it can also be used to approximate any other multimodal continuous distribution function. In the second part, the network is extended in order to capture the spatial variation of the sediment samples that have been obtained from 48 locations in the investigation area. Results show that the model provides an adequate approximation of grain size distributions, satisfying the requirements of a cumulative distribution function.

Effect of random inhomogeneities in the spatial distribution of radiation-induced defect clusters on carrier transport through the thin base of a heterojunction bipolar transistor upon neutron irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Puzanov, A. S.; Obolenskiy, S. V., E-mail: obolensk@rf.unn.ru; Kozlov, V. A.

We analyze the electron transport through the thin base of a GaAs heterojunction bipolar transistor with regard to fluctuations in the spatial distribution of defect clusters induced by irradiation with a fissionspectrum fast neutron flux. We theoretically demonstrate that the homogeneous filling of the working region with radiation-induced defect clusters causes minimum degradation of the dc gain of the heterojunction bipolar transistor.

Distributed optical fiber vibration sensor based on spectrum analysis of Polarization-OTDR system.

PubMed

Zhang, Ziyi; Bao, Xiaoyi

2008-07-07

A fully distributed optical fiber vibration sensor is demonstrated based on spectrum analysis of Polarization-OTDR system. Without performing any data averaging, vibration disturbances up to 5 kHz is successfully demonstrated in a 1km fiber link with 10m spatial resolution. The FFT is performed at each spatial resolution; the relation of the disturbance at each frequency component versus location allows detection of multiple events simultaneously with different and the same frequency components.

Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006.

PubMed

Liu, Chunxiao; Liu, Qiyong; Lin, Hualiang; Xin, Benqiang; Nie, Jun

2014-01-01

Guangdong Province is the area most seriously affected by dengue fever in China. In this study, we describe the spatial distribution of dengue fever in Guangdong Province from 2001 to 2006 with the objective of informing priority areas for public health planning and resource allocation. Annualized incidence at a county level was calculated and mapped to show crude incidence, excess hazard, and spatial smoothed incidence. Geographic information system-based spatial scan statistics was conducted to detect the spatial distribution pattern of dengue fever incidence at the county level. Spatial scan cluster analyses suggested that counties around Guangzhou City and Chaoshan Region were at increased risk for dengue fever (P < .01). Some spatial clusters of dengue fever were found in Guangdong Province, which allowed intervention measures to be targeted for maximum effect.

Research on the Spatial-Temporal Distribution Pattern of the Network Attention of Fog and Haze in China

NASA Astrophysics Data System (ADS)

Weng, Lingyan; Han, Xugao

2018-01-01

Understanding the spatial-temporal distribution pattern of fog and haze is the base to deal with them by adjusting measures to local conditions. Taking 31 provinces in China mainland as the research areas, this paper collected data from Baidu index on the network attention of fog and haze in relevant areas from 2011 to 2016, and conducted an analysis of their spatial-temporal distribution pattern by using autocorrelation analysis. The results show that the network attention of fog and haze has an overall spatial distribution pattern of “higher in the eastern and central, lower in the western China”. There are regional differences in different provinces in terms of network attention. Network attention of fog and haze indicates an obvious geographical agglomeration phenomenon, which is a gradual enlargement of the agglomeration area of higher value with a slight shrinking of those lower value agglomeration areas.

[Assessment on ecological security spatial differences of west areas of Liaohe River based on GIS].

PubMed

Wang, Geng; Wu, Wei

2005-09-01

Ecological security assessment and early warning research have spatiality; non-linearity; randomicity, it is needed to deal with much spatial information. Spatial analysis and data management are advantages of GIS, it can define distribution trend and spatial relations of environmental factors, and show ecological security pattern graphically. The paper discusses the method of ecological security spatial differences of west areas of Liaohe River based on GIS and ecosystem non-health. First, studying on pressure-state-response (P-S-R) assessment indicators system, investigating in person and gathering information; Second, digitizing the river, applying fuzzy AHP to put weight, quantizing and calculating by fuzzy comparing; Last, establishing grid data-base; expounding spatial differences of ecological security by GIS Interpolate and Assembly.

Scene-based nonuniformity correction using local constant statistics.

PubMed

Zhang, Chao; Zhao, Wenyi

2008-06-01

In scene-based nonuniformity correction, the statistical approach assumes all possible values of the true-scene pixel are seen at each pixel location. This global-constant-statistics assumption does not distinguish fixed pattern noise from spatial variations in the average image. This often causes the "ghosting" artifacts in the corrected images since the existing spatial variations are treated as noises. We introduce a new statistical method to reduce the ghosting artifacts. Our method proposes a local-constant statistics that assumes that the temporal signal distribution is not constant at each pixel but is locally true. This considers statistically a constant distribution in a local region around each pixel but uneven distribution in a larger scale. Under the assumption that the fixed pattern noise concentrates in a higher spatial-frequency domain than the distribution variation, we apply a wavelet method to the gain and offset image of the noise and separate out the pattern noise from the spatial variations in the temporal distribution of the scene. We compare the results to the global-constant-statistics method using a clean sequence with large artificial pattern noises. We also apply the method to a challenging CCD video sequence and a LWIR sequence to show how effective it is in reducing noise and the ghosting artifacts.

Spatial analysis of malaria in Anhui province, China

PubMed Central

Zhang, Wenyi; Wang, Liping; Fang, Liqun; Ma, Jiaqi; Xu, Youfu; Jiang, Jiafu; Hui, Fengming; Wang, Jianjun; Liang, Song; Yang, Hong; Cao, Wuchun

2008-01-01

Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. PMID:18847489

Unbiased estimators for spatial distribution functions of classical fluids

NASA Astrophysics Data System (ADS)

Adib, Artur B.; Jarzynski, Christopher

2005-01-01

We use a statistical-mechanical identity closely related to the familiar virial theorem, to derive unbiased estimators for spatial distribution functions of classical fluids. In particular, we obtain estimators for both the fluid density ρ(r) in the vicinity of a fixed solute and the pair correlation g(r) of a homogeneous classical fluid. We illustrate the utility of our estimators with numerical examples, which reveal advantages over traditional histogram-based methods of computing such distributions.

Skin fluorescence model based on the Monte Carlo technique

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2003-10-01

The novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account spatial distribution of fluorophores following the collagen fibers packing, whereas in epidermis and stratum corneum the distribution of fluorophores assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the NIR spectral region, while fluorescence of sensor layer embedded in epidermis is localized at the adjusted depth. The model is also able to simulate the skin fluorescence spectra.

[Evoked Potential Blind Extraction Based on Fractional Lower Order Spatial Time-Frequency Matrix].

PubMed

Long, Junbo; Wang, Haibin; Zha, Daifeng

2015-04-01

The impulsive electroencephalograph (EEG) noises in evoked potential (EP) signals is very strong, usually with a heavy tail and infinite variance characteristics like the acceleration noise impact, hypoxia and etc., as shown in other special tests. The noises can be described by a stable distribution model. In this paper, Wigner-Ville distribution (WVD) and pseudo Wigner-Ville distribution (PWVD) time-frequency distribution based on the fractional lower order moment are presented to be improved. We got fractional lower order WVD (FLO-WVD) and fractional lower order PWVD (FLO-PWVD) time-frequency distribution which could be suitable for a stable distribution process. We also proposed the fractional lower order spatial time-frequency distribution matrix (FLO-STFM) concept. Therefore, combining with time-frequency underdetermined blind source separation (TF-UBSS), we proposed a new fractional lower order spatial time-frequency underdetermined blind source separation (FLO-TF-UBSS) which can work in a stable distribution environment. We used the FLO-TF-UBSS algorithm to extract EPs. Simulations showed that the proposed method could effectively extract EPs in EEG noises, and the separated EPs and EEG signals based on FLO-TF-UBSS were almost the same as the original signal, but blind separation based on TF-UBSS had certain deviation. The correlation coefficient of the FLO-TF-UBSS algorithm was higher than the TF-UBSS algorithm when generalized signal-to-noise ratio (GSNR) changed from 10 dB to 30 dB and a varied from 1. 06 to 1. 94, and was approximately e- qual to 1. Hence, the proposed FLO-TF-UBSS method might be better than the TF-UBSS algorithm based on second order for extracting EP signal under an EEG noise environment.

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

Modelling the spatial distribution of ammonia emissions in the UK.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Vieno, M; Dore, A J; Misselbrook, T H; Tang, Y S; Sutton, M A

2008-08-01

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

NASA Astrophysics Data System (ADS)

Blanchet, J.; Lehning, M.

2010-12-01

For adequate risk management in mountainous countries, hazard maps for extreme snow events are needed. This requires the computation of spatial estimates of return levels. In this article we use recent developments in extreme value theory and compare two main approaches for mapping snow depth return levels from in situ measurements. The first one is based on the spatial interpolation of pointwise extremal distributions (the so-called Generalized Extreme Value distribution, GEV henceforth) computed at station locations. The second one is new and based on the direct estimation of a spatially smooth GEV distribution with the joint use of all stations. We compare and validate the different approaches for modeling annual maximum snow depth measured at 100 sites in Switzerland during winters 1965-1966 to 2007-2008. The results show a better performance of the smooth GEV distribution fitting, in particular where the station network is sparser. Smooth return level maps can be computed from the fitted model without any further interpolation. Their regional variability can be revealed by removing the altitudinal dependent covariates in the model. We show how return levels and their regional variability are linked to the main climatological patterns of Switzerland.

Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

PubMed

Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

2015-04-08

Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

PubMed

Gangnon, Ronald E

2012-03-01

The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution

PubMed Central

Gangnon, Ronald E.

2011-01-01

Summary The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, while rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. PMID:21762118

Space evolution model and empirical analysis of an urban public transport network

NASA Astrophysics Data System (ADS)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

Advanced data structures for the interpretation of image and cartographic data in geo-based information systems

NASA Technical Reports Server (NTRS)

Peuquet, D. J.

1986-01-01

A growing need to usse geographic information systems (GIS) to improve the flexibility and overall performance of very large, heterogeneous data bases was examined. The Vaster structure and the Topological Grid structure were compared to test whether such hybrid structures represent an improvement in performance. The use of artificial intelligence in a geographic/earth sciences data base context is being explored. The architecture of the Knowledge Based GIS (KBGIS) has a dual object/spatial data base and a three tier hierarchial search subsystem. Quadtree Spatial Spectra (QTSS) are derived, based on the quadtree data structure, to generate and represent spatial distribution information for large volumes of spatial data.

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Katzfuss, M.; Nguyen, H.

2014-12-01

Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Comparison of individual-based model output to data using a model of walleye pollock early life history in the Gulf of Alaska

NASA Astrophysics Data System (ADS)

Hinckley, Sarah; Parada, Carolina; Horne, John K.; Mazur, Michael; Woillez, Mathieu

2016-10-01

Biophysical individual-based models (IBMs) have been used to study aspects of early life history of marine fishes such as recruitment, connectivity of spawning and nursery areas, and marine reserve design. However, there is no consistent approach to validating the spatial outputs of these models. In this study, we hope to rectify this gap. We document additions to an existing individual-based biophysical model for Alaska walleye pollock (Gadus chalcogrammus), some simulations made with this model and methods that were used to describe and compare spatial output of the model versus field data derived from ichthyoplankton surveys in the Gulf of Alaska. We used visual methods (e.g. distributional centroids with directional ellipses), several indices (such as a Normalized Difference Index (NDI), and an Overlap Coefficient (OC), and several statistical methods: the Syrjala method, the Getis-Ord Gi* statistic, and a geostatistical method for comparing spatial indices. We assess the utility of these different methods in analyzing spatial output and comparing model output to data, and give recommendations for their appropriate use. Visual methods are useful for initial comparisons of model and data distributions. Metrics such as the NDI and OC give useful measures of co-location and overlap, but care must be taken in discretizing the fields into bins. The Getis-Ord Gi* statistic is useful to determine the patchiness of the fields. The Syrjala method is an easily implemented statistical measure of the difference between the fields, but does not give information on the details of the distributions. Finally, the geostatistical comparison of spatial indices gives good information of details of the distributions and whether they differ significantly between the model and the data. We conclude that each technique gives quite different information about the model-data distribution comparison, and that some are easy to apply and some more complex. We also give recommendations for a multistep process to validate spatial output from IBMs.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

MONITORING CHANGES IN STRESSED ECOSYSTEMS USING SPATIAL PATTERNS OF ANT COMMUNITIES

EPA Science Inventory

We examined the feasibility of using changes in spatial patterns of ants-distribution on experimental plots as an indicator of response to environmental stress. We produced contour maps based on relative abundances of the three most common genera of ants based on pit-fall trap ca...

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2007) (V. 2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy, and Economics Appalachian State University Boone, NC 28608-2131 USA

2010-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2013.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996) for years prior to 1990 and a variable population distribution for later years (Andres et al. 2016). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production). The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Environmental and biological characteristics of Atlantic bluefin tuna and albacore spawning habitats based on their egg distributions

NASA Astrophysics Data System (ADS)

Reglero, Patricia; Santos, Maria; Balbín, Rosa; Laíz-Carrión, Raul; Alvarez-Berastegui, Diego; Ciannelli, Lorenzo; Jiménez, Elisa; Alemany, Francisco

2017-06-01

Tuna spawning habitats are traditionally characterized using data sets of larvae or gonads from mature adults and concurrent environmental variables. Data on egg distributions have never previously been used since molecular analyses are mandatory to identify tuna eggs to species level. However, in this study we use molecularly derived egg distribution data, in addition to larval data, to characterize hydrographic and biological drivers of the spatial distribution of eggs and larvae of bluefin Thunnus thynnus and albacore tuna Thunnus alalunga in the Balearic Sea, a main spawning area of these species in the Mediterranean. The effects of the hydrography, characterized by salinity, temperature and geostrophic velocity, on the spatial distributions of the eggs and larvae are investigated. Three biological variables are used to describe the productivity in the area: chlorophyll a in the mixed layer, chlorophyll a in the deep chlorophyll maximum and mesozooplankton biomass in the mixed layer. Our results point to the importance of salinity fronts and temperatures above a minimum threshold in shaping the egg and larval distribution of both species. The spatial distribution of the biotic variables was very scattered, and they did not emerge as significant variables in the presence-absence models. However, they became significant when modeling egg and larval abundances. The lack of correlation between the three biotic variables challenges the use of chlorophyll a to describe trophic scenarios for the larvae and suggests that the spatial distribution of resources is not persistent in time. The different patterns in relation to biotic variables across species and stages found in this and other studies indicate a still elusive understanding of the link between trophic levels involving tuna early larval stages. Our ability to improve short-term forecasting and long-term predictions of climate effects on the egg and larval distributions is discussed based on the consistency of the environmentally driven spatial patterns for the two species.

Three-Dimensional Radiobiologic Dosimetry: Application of Radiobiologic Modeling to Patient-Specific 3-Dimensional Imaging–Based Internal Dosimetry

PubMed Central

Prideaux, Andrew R.; Song, Hong; Hobbs, Robert F.; He, Bin; Frey, Eric C.; Ladenson, Paul W.; Wahl, Richard L.; Sgouros, George

2010-01-01

Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ-absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiologic modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. Methods Three registered SPECT/CT scans were used to generate 3-dimensional images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT scan were provided as input into an EGSnrc-based Monte Carlo calculation: The cumulated activity image was used to define the distribution of decays, and an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a biologically effective dose distribution, which was then used to estimate a single equivalent uniform dose for segmented volumes of interest. Equivalent uniform dose was also calculated from the absorbed dose distribution directly. Results We validate the method using simple models; compare the dose-volume histogram with a previously analyzed clinical case; and give the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for the tumor were 57.7, 58.5, and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8, and 8.3 Gy, respectively. Conclusion The analysis demonstrates the impact of radiobiologic modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose nonuniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy. PMID:17504874

Derivation of spatial patterns of soil hydraulic properties based on pedotransfer functions

USDA-ARS?s Scientific Manuscript database

Spatial patterns in soil hydrology are the product of the spatial distribution of soil hydraulic properties. These properties are notorious for the difficulties and high labor costs involved in measuring them. Often, there is a need to resort to estimating these parameters from other, more readily a...

[Evaluation on spatial structure and rationality of city parks based on goal of disaster prevention: An application of proximal area method in Changchun, China.

PubMed

Li, Xiao Ling; Xiu, Chun Liang; Cheng, Lin; Wang, Nyu Ying

2016-11-18

Urban shelter parks as one of the important urban elements are a main form of emergency shelters for a city. This study evaluated the spatial distribution of urban parks in Changchun City with the proximal area method based on disaster prevention goal. Results showed that the spatial distribution of urban shelter parks was unbalanced, with high concentration in the northwest and low concentration in the southeast. The spatial distribution of urban shelter parks of the same grade was concentrated, but the different grades were scattered. The validity of urban shelter parks was low. More than 50% of the park's per capita refuge area was insufficient. For nearly 40% of the parks, their accessibility was longer than the longest evacuation time. There were significant differences in effectiveness for urban parks of different grades. The urban shelter parks for central disaster prevention were the best, followed by the designated urban shelter parks, whereas urban shelter parks for emergency disaster prevention were the least effective. In view of the layout unreasonable situation of disaster prevention parks in Changchun City, we made following recommendations: the spatial distribution of nesting urban shelter parks with different grades should be used; standards set for urban shelter parks should evolve with population; and the construction of urban shelter parks for emergency disaster prevention should be strengthened.

[Downscaling research of spatial distribution of incidence of hand foot and mouth disease based on area-to-area Poisson Kriging method].

PubMed

Wang, J X; Hu, M G; Yu, S C; Xiao, G X

2017-09-10

Objective: To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources. Methods: The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected. Downscaling interpolation was conducted by using area-to-area Poisson Kriging method. The interpolation results were visualized by using geographic information system (GIS). The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township. Results: In the downscaling interpolation, the range of the fitting semi-variance equation was 20.38 km. Within the range, the incidence had correlation with each other. The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y =1.053 1 x , R (2)=0.99. The incidences at different scale were consistent. Conclusions: The incidence of HFMD had spatial autocorrelation within 20.38 km. When HFMD occurs in one place, it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km. Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.

Nonmydriatic fluorescence-based quantitative imaging of human macular pigment distributions

NASA Astrophysics Data System (ADS)

Sharifzadeh, Mohsen; Bernstein, Paul S.; Gellermann, Werner

2006-10-01

We have developed a CCD-camera-based nonmydriatic instrument that detects fluorescence from retinal lipofuscin chromophores ("autofluorescence") as a means to indirectly quantify and spatially image the distribution of macular pigment (MP). The lipofuscin fluorescence intensity is reduced at all retinal locations containing MP, since MP has a competing absorption in the blue-green wavelength region. Projecting a large diameter, 488 nm excitation spot onto the retina, centered on the fovea, but extending into the macular periphery, and comparing lipofuscin fluorescence intensities outside and inside the foveal area, it is possible to spatially map out the distribution of MP. Spectrally selective detection of the lipofuscin fluorescence reveals an important wavelength dependence of the obtainable image contrast and deduced MP optical density levels, showing that it is important to block out interfering fluorescence contributions in the detection setup originating from ocular media such as the lens. Measuring 70 healthy human volunteer subjects with no ocular pathologies, we find widely varying spatial extent of MP, distinctly differing distribution patterns of MP, and strongly differing absolute MP levels among individuals. Our population study suggests that MP imaging based on lipofuscin fluorescence is useful as a relatively simple, objective, and quantitative noninvasive optical technique suitable to rapidly screen MP levels and distributions in healthy humans with undilated pupils.

Relative importance of population size, fishing pressure and temperature on the spatial distribution of nine Northwest Atlantic groundfish stocks.

PubMed

Adams, Charles F; Alade, Larry A; Legault, Christopher M; O'Brien, Loretta; Palmer, Michael C; Sosebee, Katherine A; Traver, Michele L

2018-01-01

The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963-2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts.

Relative importance of population size, fishing pressure and temperature on the spatial distribution of nine Northwest Atlantic groundfish stocks

PubMed Central

Alade, Larry A.; Legault, Christopher M.; O’Brien, Loretta; Palmer, Michael C.; Sosebee, Katherine A.; Traver, Michele L.

2018-01-01

The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963–2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts. PMID:29698454

GSHR-Tree: a spatial index tree based on dynamic spatial slot and hash table in grid environments

NASA Astrophysics Data System (ADS)

Chen, Zhanlong; Wu, Xin-cai; Wu, Liang

2008-12-01

Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are made possible by high-speed networks and a new generation of Grid middleware that resides between networks and traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the distributed operation, reduplication operation transfer operation of spatial index in the grid environment. The design of GSHR-Tree has ensured the performance of the load balance in the parallel computation. This tree structure is fit for the parallel process of the spatial information in the distributed network environments. Instead of spatial object's recursive comparison where original R tree has been used, the algorithm builds the spatial index by applying binary code operation in which computer runs more efficiently, and extended dynamic hash code for bit comparison. In GSHR-Tree, a new server is assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol which copes with a temporary shortage of storage resources. It uses a distributed balanced binary spatial tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. The application manipulates the GSHR-Tree structure from a node in the grid environment. The node addresses the tree through its image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the servers. In this paper, a spatial index data distribution algorithm that limits the number of servers has been proposed. We improve the storage utilization at the cost of additional messages. The structure of GSHR-Tree is believed that the scheme of this grid spatial index should fit the needs of new applications using endlessly larger sets of spatial data. Our proposal constitutes a flexible storage allocation method for a distributed spatial index. The insertion policy can be tuned dynamically to cope with periods of storage shortage. In such cases storage balancing should be favored for better space utilization, at the price of extra message exchanges between servers. This structure makes a compromise in the updating of the duplicated index and the transformation of the spatial index data. Meeting the needs of the grid computing, GSHRTree has a flexible structure in order to satisfy new needs in the future. The GSHR-Tree provides the R-tree capabilities for large spatial datasets stored over interconnected servers. The analysis, including the experiments, confirmed the efficiency of our design choices. The scheme should fit the needs of new applications of spatial data, using endlessly larger datasets. Using the system response time of the parallel processing of spatial scope query algorithm as the performance evaluation factor, According to the result of the simulated the experiments, GSHR-Tree is performed to prove the reasonable design and the high performance of the indexing structure that the paper presented.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Land quality, sustainable development and environmental degradation in agricultural districts: A computational approach based on entropy indexes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zambon, Ilaria, E-mail: ilaria.zambon@unitus.it; Colantoni, Andrea; Carlucci, Margherita

Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of landmore » sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification. - Highlights: • Spatial heterogeneity is supposed to be associated with degraded areas. • Entropy indexes can inform mitigation strategies against desertification. • Assessing spatial diversification in the degree of land sensitivity to degradation. • Mediterranean rural areas have an evident diversity in agricultural systems. • A diachronic analysis carried out at the Italian agricultural district scale.« less

Remote Sensing-Based Detection and Spatial Pattern Analysis for Geo-Ecological Niche Modeling of Tillandsia SPP. In the Atacama, Chile

NASA Astrophysics Data System (ADS)

Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.

2016-06-01

In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

LASERS IN MEDICINE: Determination of the optical characteristics of turbid media by the laser optoacoustic method

NASA Astrophysics Data System (ADS)

Karabutov, Aleksander A.; Pelivanov, Ivan M.; Podymova, N. B.; Skipetrov, S. E.

1999-12-01

A method, based on the optoacoustic effect for determination of the spatial distribution of the light intensity in turbid media and of the optical characteristics of such media was proposed (and implemented experimentally). A temporal profile of the pressure of a thermo-optically excited acoustic pulse was found to be governed by the absorption coefficient and by the spatial distribution of the light intensity in the investigated medium. The absorption coefficient and the reduced light-scattering coefficient of model turbid water-like media were measured by the optoacoustic method. The results of a direct determination of the spatial light-intensity distribution agreed with a theoretical calculation made in the diffusion approximation.

Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

NASA Astrophysics Data System (ADS)

Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

2012-12-01

Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Characterization and predictability of basin scale SWE distributions using ASO snow depth and SWE retrievals

NASA Astrophysics Data System (ADS)

Bormann, K.; Hedrick, A. R.; Marks, D. G.; Painter, T. H.

2017-12-01

The spatial and temporal distribution of snow water resources (SWE) in the mountains has been examined extensively through the use of models, in-situ networks and remote sensing techniques. However, until the Airborne Snow Observatory (http://aso.jpl.nasa.gov), our understanding of SWE dynamics has been limited due to a lack of well-constrained spatial distributions of SWE in complex terrain, particularly at high elevations and at regional scales (100km+). ASO produces comprehensive snow depth measurements and well-constrained SWE products providing the opportunity to re-examine our current understanding of SWE distributions with a robust and rich data source. We collected spatially-distributed snow depth and SWE data from over 150 individual ASO acquisitions spanning seven basins in California during the five-year operational period of 2013 - 2017. For each of these acquisitions, we characterized the spatial distribution of snow depth and SWE and examined how these distributions changed with time during snowmelt. We compared these distribution patterns between each of the seven basins and finally, examined the predictability of the SWE distributions using statistical extrapolations through both space and time. We compare and contrast these observationally-based characteristics with those from a physically-based snow model to highlight the strengths and weaknesses of the implementation of our understanding of SWE processes in the model environment. In practice, these results may be used to support or challenge our current understanding of mountain SWE dynamics and provide techniques for enhanced evaluation of high-resolution snow models that go beyond in-situ point comparisons. In application, this work may provide guidance on the potential of ASO to guide backfilling of sparse spaceborne measurements of snow depth and snow water equivalent.

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications

PubMed Central

2017-01-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications. PMID:29104259

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications.

PubMed

Miah, Khalid; Potter, David K

2017-11-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications.

Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

2014-03-01

Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

Preliminary surficial geologic map database of the Amboy 30 x 60 minute quadrangle, California

USGS Publications Warehouse

Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.

2006-01-01

The surficial geologic map database of the Amboy 30x60 minute quadrangle presents characteristics of surficial materials for an area approximately 5,000 km2 in the eastern Mojave Desert of California. This map consists of new surficial mapping conducted between 2000 and 2005, as well as compilations of previous surficial mapping. Surficial geology units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects occurring post-deposition, and, where appropriate, the lithologic nature of the material. The physical properties recorded in the database focus on those that drive hydrologic, biologic, and physical processes such as particle size distribution (PSD) and bulk density. This version of the database is distributed with point data representing locations of samples for both laboratory determined physical properties and semi-quantitative field-based information. Future publications will include the field and laboratory data as well as maps of distributed physical properties across the landscape tied to physical process models where appropriate. The database is distributed in three parts: documentation, spatial map-based data, and printable map graphics of the database. Documentation includes this file, which provides a discussion of the surficial geology and describes the format and content of the map data, a database 'readme' file, which describes the database contents, and FGDC metadata for the spatial map information. Spatial data are distributed as Arc/Info coverage in ESRI interchange (e00) format, or as tabular data in the form of DBF3-file (.DBF) file formats. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files, and are appropriate for representing a view of the spatial database at the mapped scale.

Symbolic control of visual attention: semantic constraints on the spatial distribution of attention.

PubMed

Gibson, Bradley S; Scheutz, Matthias; Davis, Gregory J

2009-02-01

Humans routinely use spatial language to control the spatial distribution of attention. In so doing, spatial information may be communicated from one individual to another across opposing frames of reference, which in turn can lead to inconsistent mappings between symbols and directions (or locations). These inconsistencies may have important implications for the symbolic control of attention because they can be translated into differences in cue validity, a manipulation that is known to influence the focus of attention. This differential validity hypothesis was tested in Experiment 1 by comparing spatial word cues that were predicted to have high learned spatial validity ("above/below") and low learned spatial validity ("left/right"). Consistent with this prediction, when two measures of selective attention were used, the results indicated that attention was less focused in response to "left/right" cues than in response to "above/below" cues, even when the actual validity of each of the cues was equal. In addition, Experiment 2 predicted that spatial words such as "left/right" would have lower spatial validity than would other directional symbols that specify direction along the horizontal axis, such as "<--/-->" cues. The results were also consistent with this hypothesis. Altogether, the present findings demonstrate important semantic-based constraints on the spatial distribution of attention.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures

PubMed Central

Zavodszky, Maria I.

2017-01-01

Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information). PMID:29190747

Using Historical Atlas Data to Develop High-Resolution Distribution Models of Freshwater Fishes

PubMed Central

Huang, Jian; Frimpong, Emmanuel A.

2015-01-01

Understanding the spatial pattern of species distributions is fundamental in biogeography, and conservation and resource management applications. Most species distribution models (SDMs) require or prefer species presence and absence data for adequate estimation of model parameters. However, observations with unreliable or unreported species absences dominate and limit the implementation of SDMs. Presence-only models generally yield less accurate predictions of species distribution, and make it difficult to incorporate spatial autocorrelation. The availability of large amounts of historical presence records for freshwater fishes of the United States provides an opportunity for deriving reliable absences from data reported as presence-only, when sampling was predominantly community-based. In this study, we used boosted regression trees (BRT), logistic regression, and MaxEnt models to assess the performance of a historical metacommunity database with inferred absences, for modeling fish distributions, investigating the effect of model choice and data properties thereby. With models of the distribution of 76 native, non-game fish species of varied traits and rarity attributes in four river basins across the United States, we show that model accuracy depends on data quality (e.g., sample size, location precision), species’ rarity, statistical modeling technique, and consideration of spatial autocorrelation. The cross-validation area under the receiver-operating-characteristic curve (AUC) tended to be high in the spatial presence-absence models at the highest level of resolution for species with large geographic ranges and small local populations. Prevalence affected training but not validation AUC. The key habitat predictors identified and the fish-habitat relationships evaluated through partial dependence plots corroborated most previous studies. The community-based SDM framework broadens our capability to model species distributions by innovatively removing the constraint of lack of species absence data, thus providing a robust prediction of distribution for stream fishes in other regions where historical data exist, and for other taxa (e.g., benthic macroinvertebrates, birds) usually observed by community-based sampling designs. PMID:26075902

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

PubMed Central

Lam, William H. K.; Li, Qingquan

2017-01-01

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. PMID:29210978

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

PubMed

Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

2017-12-06

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

Deriving movement properties and the effect of the environment from the Brownian bridge movement model in monkeys and birds.

PubMed

Buchin, Kevin; Sijben, Stef; van Loon, E Emiel; Sapir, Nir; Mercier, Stéphanie; Marie Arseneau, T Jean; Willems, Erik P

2015-01-01

The Brownian bridge movement model (BBMM) provides a biologically sound approximation of the movement path of an animal based on discrete location data, and is a powerful method to quantify utilization distributions. Computing the utilization distribution based on the BBMM while calculating movement parameters directly from the location data, may result in inconsistent and misleading results. We show how the BBMM can be extended to also calculate derived movement parameters. Furthermore we demonstrate how to integrate environmental context into a BBMM-based analysis. We develop a computational framework to analyze animal movement based on the BBMM. In particular, we demonstrate how a derived movement parameter (relative speed) and its spatial distribution can be calculated in the BBMM. We show how to integrate our framework with the conceptual framework of the movement ecology paradigm in two related but acutely different ways, focusing on the influence that the environment has on animal movement. First, we demonstrate an a posteriori approach, in which the spatial distribution of average relative movement speed as obtained from a "contextually naïve" model is related to the local vegetation structure within the monthly ranging area of a group of wild vervet monkeys. Without a model like the BBMM it would not be possible to estimate such a spatial distribution of a parameter in a sound way. Second, we introduce an a priori approach in which atmospheric information is used to calculate a crucial parameter of the BBMM to investigate flight properties of migrating bee-eaters. This analysis shows significant differences in the characteristics of flight modes, which would have not been detected without using the BBMM. Our algorithm is the first of its kind to allow BBMM-based computation of movement parameters beyond the utilization distribution, and we present two case studies that demonstrate two fundamentally different ways in which our algorithm can be applied to estimate the spatial distribution of average relative movement speed, while interpreting it in a biologically meaningful manner, across a wide range of environmental scenarios and ecological contexts. Therefore movement parameters derived from the BBMM can provide a powerful method for movement ecology research.

Estimating the spatial distribution of wintering little brown bat populations in the eastern United States

USGS Publications Warehouse

Russell, Robin E.; Tinsley, Karl; Erickson, Richard A.; Thogmartin, Wayne E.; Jennifer A. Szymanski,

2014-01-01

Depicting the spatial distribution of wildlife species is an important first step in developing management and conservation programs for particular species. Accurate representation of a species distribution is important for predicting the effects of climate change, land-use change, management activities, disease, and other landscape-level processes on wildlife populations. We developed models to estimate the spatial distribution of little brown bat (Myotis lucifugus) wintering populations in the United States east of the 100th meridian, based on known hibernacula locations. From this data, we developed several scenarios of wintering population counts per county that incorporated uncertainty in the spatial distribution of the hibernacula as well as uncertainty in the size of the current little brown bat population. We assessed the variability in our results resulting from effects of uncertainty. Despite considerable uncertainty in the known locations of overwintering little brown bats in the eastern United States, we believe that models accurately depicting the effects of the uncertainty are useful for making management decisions as these models are a coherent organization of the best available information.

[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

PubMed

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

Research on the degradation of tropical arable land soil: Part II. The distribution of soil nutrients in eastern part of Hainan Island

NASA Astrophysics Data System (ADS)

Wang, Dengfeng; Wei, Zhiyuan; Qi, Zhiping

Research on the temporal and spatial distribution of soil nutrients in tropical arable land is very important to promote the tropical sustainable agriculture development. Take the Eastern part of Hainan as research area, applying GIS spatial analysis technique, analyzing the temporal and spatial variation of soil N, P and K contents in arable land. The results indicate that the contents of soil N, P and K were 0.28%, 0.20% and 1.75% respectively in 2005. The concentrations of total N and P in arable land soil increased significantly from 1980s to 2005. The variances in contents of soil nutrients were closely related to the application of chemical fertilizers in recent years, and the uneven distribution of soil nutrient contents was a reflection of fertilizer application in research area. Fertilization can be planned based on the distribution of soil nutrients and the spatial analysis techniques, so as to sustain balance of soil nutrients contents.

Statistical Analysis of 3D Images Detects Regular Spatial Distributions of Centromeres and Chromocenters in Animal and Plant Nuclei

PubMed Central

Biot, Eric; Adenot, Pierre-Gaël; Hue-Beauvais, Cathy; Houba-Hérin, Nicole; Duranthon, Véronique; Devinoy, Eve; Beaujean, Nathalie; Gaudin, Valérie; Maurin, Yves; Debey, Pascale

2010-01-01

In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear “compartments”. Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types. PMID:20628576

Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network.

PubMed

Jia, Zhenyi; Zhou, Shenglu; Su, Quanlong; Yi, Haomin; Wang, Junxiao

2017-12-26

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolation and BP neural network methods to estimate the spatial distribution of arsenic (As) and cadmium (Cd) pollution in the study area. Additionally, we introduced a cross-validation method to measure the errors of the estimation results by the two interpolation methods and discussed the accuracy of the information contained in the estimation results. The conclusions are as follows: data distribution characteristics, spatial variability, and mean square errors (MSE) of the different methods showed large differences. Estimation results from BP neural network models have a higher accuracy, the MSE of As and Cd are 0.0661 and 0.1743, respectively. However, the interpolation results show significant skewed distribution, and spatial autocorrelation is strong. Using Kriging interpolation, the MSE of As and Cd are 0.0804 and 0.2983, respectively. The estimation results have poorer accuracy. Combining the two methods can improve the accuracy of the Kriging interpolation and more comprehensively represent the spatial distribution characteristics of metal(loid)s in regional soil. The study may provide a scientific basis and technical support for the regulation of soil metal(loid) pollution.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].

PubMed

Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin

2016-10-01

In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

Changes in the non-Federal land base involving forestry in western Oregon, 1961-94.

Treesearch

Daolan Zheng; Ralph J. Alig

1999-01-01

Temporal and spatial analyses of land use changes on non-Federal lands in western Oregon between 1961 and 1994 were conducted. Two distinct changes in the region were a loss of forest lands and an increase in urban areas. Neither the rates of change over time nor the spatial distribution of land converted to urban use was evenly distributed in the region. The influence...

In vivo measurements of cutaneous melanin across spatial scales: using multiphoton microscopy and spatial frequency domain spectroscopy.

PubMed

Saager, Rolf B; Balu, Mihaela; Crosignani, Viera; Sharif, Ata; Durkin, Anthony J; Kelly, Kristen M; Tromberg, Bruce J

2015-06-01

The combined use of nonlinear optical microscopy and broadband reflectance techniques to assess melanin concentration and distribution thickness in vivo over the full range of Fitzpatrick skin types is presented. Twelve patients were measured using multiphoton microscopy (MPM) and spatial frequency domain spectroscopy (SFDS) on both dorsal forearm and volar arm, which are generally sun-exposed and non-sun-exposed areas, respectively. Both MPM and SFDS measured melanin volume fractions between (skin type I non-sun-exposed) and 20% (skin type VI sun exposed). MPM measured epidermal (anatomical) thickness values ~30-65 μm, while SFDS measured melanin distribution thickness based on diffuse optical path length. There was a strong correlation between melanin concentration and melanin distribution (epidermal) thickness measurements obtained using the two techniques. While SFDS does not have the ability to match the spatial resolution of MPM, this study demonstrates that melanin content as quantified using SFDS is linearly correlated with epidermal melanin as measured using MPM (R² = 0.8895). SFDS melanin distribution thickness is correlated to MPM values (R² = 0.8131). These techniques can be used individually and/or in combination to advance our understanding and guide therapies for pigmentation-related conditions as well as light-based treatments across a full range of skin types.

Versatile time-dependent spatial distribution model of sun glint for satellite-based ocean imaging

NASA Astrophysics Data System (ADS)

Zhou, Guanhua; Xu, Wujian; Niu, Chunyue; Zhang, Kai; Ma, Zhongqi; Wang, Jiwen; Zhang, Yue

2017-01-01

We propose a versatile model to describe the time-dependent spatial distribution of sun glint areas in satellite-based wave water imaging. This model can be used to identify whether the imaging is affected by sun glint and how strong the glint is. The observing geometry is calculated using an accurate orbit prediction method. The Cox-Munk model is used to analyze the bidirectional reflectance of wave water surface under various conditions. The effects of whitecaps and the reflectance emerging from the sea water have been considered. Using the moderate resolution atmospheric transmission radiative transfer model, we are able to effectively calculate the sun glint distribution at the top of the atmosphere. By comparing the modeled data with the medium resolution imaging spectrometer image and Feng Yun 2E (FY-2E) image, we have proven that the time-dependent spatial distribution of sun glint areas can be effectively predicted. In addition, the main factors in determining sun glint distribution and the temporal variation rules of sun glint have been discussed. Our model can be used to design satellite orbits and should also be valuable in either eliminating sun glint or making use of it.

The Effect of Velocity Correlation on the Spatial Evolution of Breakthrough Curves in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Massoudieh, A.; Dentz, M.; Le Borgne, T.

2017-12-01

In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies. PMID:26404350

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

NASA Astrophysics Data System (ADS)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups.

PubMed

Capitán, José A; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Nonuniformity correction of imaging systems with a spatially nonhomogeneous radiation source.

PubMed

Gutschwager, Berndt; Hollandt, Jörg

2015-12-20

We present a novel method of nonuniformity correction of imaging systems in a wide optical spectral range by applying a radiation source with an unknown and spatially nonhomogeneous radiance or radiance temperature distribution. The benefit of this method is that it can be applied with radiation sources of arbitrary spatial radiance or radiance temperature distribution and only requires the sufficient temporal stability of this distribution during the measurement process. The method is based on the recording of several (at least three) images of a radiation source and a purposeful row- and line-shift of these sequent images in relation to the first primary image. The mathematical procedure is explained in detail. Its numerical verification with a source of a predefined nonhomogenous radiance distribution and a thermal imager of a predefined nonuniform focal plane array responsivity is presented.

The Spatial Distribution of Attention within and across Objects

PubMed Central

Hollingworth, Andrew; Maxcey-Richard, Ashleigh M.; Vecera, Shaun P.

2011-01-01

Attention operates to select both spatial locations and perceptual objects. However, the specific mechanism by which attention is oriented to objects is not well understood. We examined the means by which object structure constrains the distribution of spatial attention (i.e., a “grouped array”). Using a modified version of the Egly et al. object cuing task, we systematically manipulated within-object distance and object boundaries. Four major findings are reported: 1) spatial attention forms a gradient across the attended object; 2) object boundaries limit the distribution of this gradient, with the spread of attention constrained by a boundary; 3) boundaries within an object operate similarly to across-object boundaries: we observed object-based effects across a discontinuity within a single object, without the demand to divide or switch attention between discrete object representations; and 4) the gradient of spatial attention across an object directly modulates perceptual sensitivity, implicating a relatively early locus for the grouped array representation. PMID:21728455

Compact microwave imaging system to measure spatial distribution of plasma density

NASA Astrophysics Data System (ADS)

Ito, H.; Oba, R.; Yugami, N.; Nishida, Y.

2004-10-01

We have developed an advanced microwave interferometric system operating in the K band (18-27 GHz) with the use of a fan-shaped microwave based on a heterodyne detection system for measuring the spatial distribution of the plasma density. In order to make a simple, low-cost, and compact microwave interferometer with better spatial resolution, a microwave scattering technique by a microstrip antenna array is employed. Experimental results show that the imaging system with the microstrip antenna array can have finer spatial resolution than one with the diode antenna array and reconstruct a good spatially resolved image of the finite size dielectric phantoms placed between the horn antenna and the micro strip antenna array. The precise two-dimensional electron density distribution of the cylindrical plasma produced by an electron cyclotron resonance has been observed. As a result, the present imaging system is more suitable for a two- or three-dimensional display of the objects or stationary plasmas and it is possible to realize a compact microwave imaging system.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

USGS Publications Warehouse

Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.

Spatial correlation-based side information refinement for distributed video coding

NASA Astrophysics Data System (ADS)

Taieb, Mohamed Haj; Chouinard, Jean-Yves; Wang, Demin

2013-12-01

Distributed video coding (DVC) architecture designs, based on distributed source coding principles, have benefitted from significant progresses lately, notably in terms of achievable rate-distortion performances. However, a significant performance gap still remains when compared to prediction-based video coding schemes such as H.264/AVC. This is mainly due to the non-ideal exploitation of the video sequence temporal correlation properties during the generation of side information (SI). In fact, the decoder side motion estimation provides only an approximation of the true motion. In this paper, a progressive DVC architecture is proposed, which exploits the spatial correlation of the video frames to improve the motion-compensated temporal interpolation (MCTI). Specifically, Wyner-Ziv (WZ) frames are divided into several spatially correlated groups that are then sent progressively to the receiver. SI refinement (SIR) is performed as long as these groups are being decoded, thus providing more accurate SI for the next groups. It is shown that the proposed progressive SIR method leads to significant improvements over the Discover DVC codec as well as other SIR schemes recently introduced in the literature.

Remote-sensing supported monitoring of global biodiversity change

NASA Astrophysics Data System (ADS)

Jetz, W.; Tuanmu, M. N.; W, A.; Melton, F. S.; Parmentier, B.; Amatulli, G.; Guzman, A.

2016-12-01

Remote sensing combined with biodiversity observation offers an unrivalled tool for understanding and predicting species distributions and their changes at the planetary scale. I will illustrate recently developed high-resolution remote-sensing based layers targeted for spatiotemporal biodiversity modeling, addressing climate, environment, topography, and habitat heterogeneity. In particular, I will illustrate the development and use of global MODIS-derived environmental layers for biodiversity assessment and change monitoring. Remote-sensing based capture of these putative predictors of biodiversity dynamics provides more a reliable signal than spatially interpolated layers and avoids inflated spatial autocorrelation. The layers result in more accurate models of species occurrence and are more readily able to address the scale of processes underpinning species distributions, e.g. when combined with emerging hierarchical, cross-scale models. I illustrate the multiple ways in which this type of information, based on continuously collected data, supports the prediction of not just spatial but also temporal variation in biodiversity. Using implementations in the Map of Life infrastructure I will showcase new indicators of species distribution and change that demonstrate these new opportunities.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

A 20-year catalog comparing smooth and sharp estimates of slow slip events in Cascadia

NASA Astrophysics Data System (ADS)

Molitors Bergman, E. G.; Evans, E. L.; Loveless, J. P.

2017-12-01

Slow slip events (SSEs) are a form of aseismic strain release at subduction zones resulting in a temporary reversal in interseismic upper plate motion over a period of weeks, frequently accompanied in time and space by seismic tremor at the Cascadia subduction zone. Locating SSEs spatially along the subduction zone interface is essential to understanding the relationship between SSEs, earthquakes, and tremor and assessing megathrust earthquake hazard. We apply an automated slope comparison-based detection algorithm to single continuously recording GPS stations to determine dates and surface displacement vectors of SSEs, then apply network-based filters to eliminate false detections. The main benefits of this algorithm are its ability to detect SSEs while they are occurring and track the spatial migration of each event. We invert geodetic displacement fields for slip distributions on the subduction zone interface for SSEs between 1997 and 2017 using two estimation techniques: spatial smoothing and total variation regularization (TVR). Smoothing has been frequently used in determining the location of interseismic coupling, earthquake rupture, and SSE slip and yields spatially coherent but inherently blurred solutions. TVR yields compact, sharply bordered slip estimates of similar magnitude and along-strike extent to previously presented studied events, while fitting the constraining geodetic data as well as corresponding smoothing-based solutions. Slip distributions estimated using TVR have up-dip limits that align well with down-dip limits of interseismic coupling on the plate interface and spatial extents that approximately correspond to the distribution of tremor concurrent with each event. TVR gives a unique view of slow slip distributions that can contribute to understanding of the physical properties that govern megathrust slip processes.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Research on spatial distribution of photosynthetic characteristics of Winter Wheat

NASA Astrophysics Data System (ADS)

Yan, Q. Q.; Zhou, Q. Y.; Zhang, B. Z.; Han, X.; Han, N. N.; Li, S. M.

2018-03-01

In order to explore the spatial distribution of photosynthetic characteristics of winter wheat leaf, the photosynthetic rate on different parts of leaf (leaf base-leaf middle-leaf apex) and that on each canopy (top layer-middle layer-bottom layer) leaf during the whole growth period of winter wheat were measured. The variation of photosynthetic rate with PAR and the spatial distribution of winter wheat leaf during the whole growth periods were analysed. The results showed that the photosynthetic rate of different parts of winter wheat increased with the increase of PAR, which was showed as leaf base>leaf middle>leaf apex. In the same growth period, photosynthetic rate in different parts of the tablet was showed as leaf middle>leaf base>leaf apex. For the different canopy layer of winter wheat, the photosynthetic rate of the top layer leaf was significantly greater than that of the middle layer and lower layer leaf. The photosynthetic rate of the top layer leaf was the largest in the leaf base position. The photosynthetic rate of leaf of the same canopy layer at different growth stages were showed as tasseling stage >grain filling stage > maturation stage.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Modes in light wave propagating in semiconductor laser

NASA Technical Reports Server (NTRS)

Manko, Margarita A.

1994-01-01

The study of semiconductor laser based on an analogy of the Schrodinger equation and an equation describing light wave propagation in nonhomogeneous medium is developed. The active region of semiconductor laser is considered as optical waveguide confining the electromagnetic field in the cross-section (x,y) and allowing waveguide propagation along the laser resonator (z). The mode structure is investigated taking into account the transversal and what is the important part of the suggested consideration longitudinal nonhomogeneity of the optical waveguide. It is shown that the Gaussian modes in the case correspond to spatial squeezing and correlation. Spatially squeezed two-mode structure of nonhomogeneous optical waveguide is given explicitly. Distribution of light among the laser discrete modes is presented. Properties of the spatially squeezed two-mode field are described. The analog of Franck-Condon principle for finding the maxima of the distribution function and the analog of Ramsauer effect for control of spatial distribution of laser emission are discussed.

A Geographic-Information-Systems-Based Approach to Analysis of Characteristics Predicting Student Persistence and Graduation

ERIC Educational Resources Information Center

Ousley, Chris

2010-01-01

This study sought to provide empirical evidence regarding the use of spatial analysis in enrollment management to predict persistence and graduation. The research utilized data from the 2000 U.S. Census and applicant records from The University of Arizona to study the spatial distributions of enrollments. Based on the initial results, stepwise…

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

mocca code for star cluster simulations - VI. Bimodal spatial distribution of blue stragglers

NASA Astrophysics Data System (ADS)

Hypki, Arkadiusz; Giersz, Mirek

2017-11-01

The paper presents an analysis of formation mechanism and properties of spatial distributions of blue stragglers in evolving globular clusters, based on numerical simulations done with the mocca code. First, there are presented N-body and mocca simulations which try to reproduce the simulations presented by Ferraro et al. (2012). Then, we show the agreement between N-body and the mocca code. Finally, we discuss the formation process of the bimodal distribution. We report that we could not reproduce simulations from Ferraro et al. (2012). Moreover, we show that the so-called bimodal spatial distribution of blue stragglers is a very transient feature. It is formed for one snapshot in time and it can easily vanish in the next one. Moreover, we show that the radius of avoidance proposed by Ferraro et al. (2012) goes out of sync with the apparent minimum of the bimodal distribution after about two half-mass relaxation times (without finding out what is the reason for that). This finding creates a real challenge for the dynamical clock, which uses this radius to determine the dynamical age of globular clusters. Additionally, the paper discusses a few important problems concerning the apparent visibilities of the bimodal distributions, which have to be taken into account while studying the spatial distributions of blue stragglers.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

RockFall analyst: A GIS extension for three-dimensional and spatially distributed rockfall hazard modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Derek Martin, C.; Lim, C. H.

2007-02-01

Geographic information system (GIS) modeling is used in combination with three-dimensional (3D) rockfall process modeling to assess rockfall hazards. A GIS extension, RockFall Analyst (RA), which is capable of effectively handling large amounts of geospatial information relative to rockfall behaviors, has been developed in ArcGIS using ArcObjects and C#. The 3D rockfall model considers dynamic processes on a cell plane basis. It uses inputs of distributed parameters in terms of raster and polygon features created in GIS. Two major components are included in RA: particle-based rockfall process modeling and geostatistics-based rockfall raster modeling. Rockfall process simulation results, 3D rockfall trajectories and their velocity features either for point seeders or polyline seeders are stored in 3D shape files. Distributed raster modeling, based on 3D rockfall trajectories and a spatial geostatistical technique, represents the distribution of spatial frequency, the flying and/or bouncing height, and the kinetic energy of falling rocks. A distribution of rockfall hazard can be created by taking these rockfall characteristics into account. A barrier analysis tool is also provided in RA to aid barrier design. An application of these modeling techniques to a case study is provided. The RA has been tested in ArcGIS 8.2, 8.3, 9.0 and 9.1.

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

A Theoretical Approach to Analyze the Parametric Influence on Spatial Patterns of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) Populations.

PubMed

Garcia, A G; Godoy, W A C

2017-06-01

Studies of the influence of biological parameters on the spatial distribution of lepidopteran insects can provide useful information for managing agricultural pests, since the larvae of many species cause serious impacts on crops. Computational models to simulate the spatial dynamics of insect populations are increasingly used, because of their efficiency in representing insect movement. In this study, we used a cellular automata model to explore different patterns of population distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), when the values of two biological parameters that are able to influence the spatial pattern (larval viability and adult longevity) are varied. We mapped the spatial patterns observed as the parameters varied. Additionally, by using population data for S. frugiperda obtained in different hosts under laboratory conditions, we were able to describe the expected spatial patterns occurring in corn, cotton, millet, and soybean crops based on the parameters varied. The results are discussed from the perspective of insect ecology and pest management. We concluded that computational approaches can be important tools to study the relationship between the biological parameters and spatial distributions of lepidopteran insect pests.

Simulations inform design of regional occupancy-based monitoring for a sparsely distributed, territorial species

Treesearch

Quresh S. Latif; Martha M. Ellis; Victoria A. Saab; Kim Mellen-McLean

2017-01-01

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy-based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify...

Difet: Distributed Feature Extraction Tool for High Spatial Resolution Remote Sensing Images

NASA Astrophysics Data System (ADS)

Eken, S.; Aydın, E.; Sayar, A.

2017-11-01

In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

Invasive Species Distribution Modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Treesearch

Tomáš Václavík; Ross K. Meentemeyer

2009-01-01

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges...

Environmental determinants of the spatial distribution of Angiostrongylus vasorum, Crenosoma vulpis and Eucoleus aerophilus in Hungary.

PubMed

Tolnai, Z; Széll, Z; Sréter, T

2015-01-30

Angiostrongylus vasorum, Crenosoma vulpis and Eucoleus aerophilus (syn. Capillaria aerophila) are the most important lungworm species infecting wild and domesticated canids in Europe. To investigate the spatial distribution of these parasites and the factors influencing their circulation in the fox populations, 937 red foxes (Vulpes vulpes) were tested for lungworm infection in Hungary. The prevalence of A. vasorum, C. vulpis and E. aerophilus infection was high (17.9, 24.6 and 61.7%). The distribution pattern of infection in foxes and the relationship of this pattern with landscape and climate was analyzed by geographic information system. Based on the analysis, the annual precipitation was the major determinant of the spatial distribution of A. vasorum and C. vulpis and E. aerophilus. Nevertheless, the mean annual temperature also influenced the distribution of A. vasorum and E. aerophilus. The positive relationship with annual precipitation and the negative relationship with mean annual temperature can be attributed to the sensitivity of larvae, eggs and intermediate hosts (snails and slugs) of lungworms for desiccation. Based on the highly clumped distribution of A. vasorum and C. vulpis, the indirect life cycle (larvae, slugs and snails) of these parasites seems to be particularly sensitive for environmental effects. The distribution of E. aerophilus was considerably less clumped indicating a lower sensitivity of the direct life cycle (eggs) of this parasite for environmental factors. Based on these results, lungworm infections in canids including dogs can be expected mainly in relatively wet and cool areas. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India

NASA Astrophysics Data System (ADS)

Verma, S.; Gupta, R. D.

2014-11-01

In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.

Reduction of spatial distribution of risk factors for transportation of contaminants released by coal mining activities.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-09-15

It is reported that water-energy nexus composes two of the biggest development and human health challenges. In the present study we presented a Risk Potential Index (RPI) model which encapsulates Source, Vector (Transport), and Target risks for forecasting surface water contamination. The main aim of the model is to identify critical surface water risk zones for an open cast mining environment, taking Jharia Coalfield, India as the study area. The model also helps in feasible sampling design. Based on spatial analysis various risk zones were successfully delineated. Monthly RPI distribution revealed that the risk of surface water contamination was highest during the monsoon months. Surface water samples were analysed to validate the model. A GIS based alternative management option was proposed to reduce surface water contamination risk and observed 96% and 86% decrease in the spatial distribution of very high risk areas for the months June and July respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Applications of Model-Based Geostatistics in Helminth Epidemiology and Control

PubMed Central

Magalhães, Ricardo J. Soares; Clements, Archie C.A.; Patil, Anand P.; Gething, Peter W.; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. PMID:21295680

[Spatial structural characteristics of natural Populus davidiana - Betula platyphylla secondary forest].

PubMed

Shao, Fang-Li; Yu, Xin-Xiao; Song, Si-Ming; Zhao, Yang

2011-11-01

This paper analyzed the spatial structural characteristics of natural Populus davidiana - Betula platyphylla secondary forest in a 4 hm2 plot of Mulan Paddock, based on the diameter distribution and the spatial structure parameters mingling degree, neighborhood comparison, and angle index. In the forest, the diameter distribution of the stands presented as an inverse 'J' curve, the average mingling degree was 0.4, with the individuals at weak and zero mingling degree reached 51.6%, and the average mingling degree of P. davidiana and B. platyphylla was 0.25 and 0.39, respectively. The neighborhood comparison based on the diameter at breast height (DBH) and tree height was almost the same, suggesting that the P. davidiana and B. platyphylla were in the transition state from subdominant to middle. The horizontal distribution pattern had a close relation to the minimum measured DBH, being clustered when the DBH was > or = 1 cm and < 6 cm, and random when the DBH was > or = 6 cm.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

PubMed Central

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers. PMID:25206325

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

Spatial height directed microfluidic synthesis of transparent inorganic upconversion nano film

NASA Astrophysics Data System (ADS)

Liu, Xiaoxia; Zhu, Cheng; Liao, Wei; Jin, Junyang; Ni, Yaru; Lu, Chunhua; Xu, Zhongzi

2017-11-01

A microfluidic-based synthesis of an inorganic upconversion nano film has been developed with a large area of dense-distributed NaYF4 crystal grains in a silica glass micro-reactor and the film exhibits high transparence, strong upconversion luminescence and robust adhesion with the substrate. The spatial heights of micro-reactors are tuned between 31 and 227 mm, which can regulate flow regimes. The synergistic effect of spatial height and fluid regime is put forward, which influences diffusion paths and assembly ways of different precursor molecules and consequently directs final distributions and morphologies of crystal grains, as well as optical properties due to diversity of surface and thickness of films. The spatial height of 110 mm is advantageous for high transmittance of upconversion film due to the flat surface and appropriate film thickness of 67 nm. The height of 150 mm is in favor of uniform distribution of upconversion fluorescence and achieving the strongest fluorescence due to minimized optical loss. Such a transparent upconversion film with a large area of uniform distribution is promising to promote the application of upconversion materials and spatial height directed microfluidic regime have a certain significance on many microfluidic synthesis.

Study on temporal variation and spatial distribution for rural poverty in China based on GIS

NASA Astrophysics Data System (ADS)

Feng, Xianfeng; Xu, Xiuli; Wang, Yingjie; Cui, Jing; Mo, Hongyuan; Liu, Ling; Yan, Hong; Zhang, Yan; Han, Jiafu

2009-07-01

Poverty is one of the most serious challenges all over the world, is an obstacle to hinder economics and agriculture in poverty area. Research on poverty alleviation in China is very useful and important. In this paper, we will explore the comprehensive poverty characteristics in China, analyze the current poverty status, spatial distribution and temporal variations about rural poverty in China, and to category the different poverty types and their spatial distribution. First, we achieved the gathering and processing the relevant data. These data contain investigation data, research reports, statistical yearbook, censuses, social-economic data, physical and anthrop geographical data, etc. After deeply analysis of these data, we will get the distribution of poverty areas by spatial-temporal data model according to different poverty given standard in different stages in China to see the poverty variation and the regional difference in County-level. Then, the current poverty status, spatial pattern about poverty area in villages-level will be lucubrated; the relationship among poverty, environment (including physical and anthrop geographical factors) and economic development, etc. will be expanded. We hope our research will enhance the people knowledge of poverty in China and contribute to the poverty alleviation in China.

Distribution of late Pleistocene ice-rich syngenetic permafrost of the Yedoma Suite in east and central Siberia, Russia

USGS Publications Warehouse

Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer

2013-01-01

This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.

Using the Spatial Distribution of Installers to Define Solar Photovoltaic Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Shaughnessy, Eric; Nemet, Gregory F.; Darghouth, Naim

2016-09-01

Solar PV market research to date has largely relied on arbitrary jurisdictional boundaries, such as counties, to study solar PV market dynamics. This paper seeks to improve solar PV market research by developing a methodology to define solar PV markets. The methodology is based on the spatial distribution of solar PV installers. An algorithm is developed and applied to a rich dataset of solar PV installations to study the outcomes of the installer-based market definitions. The installer-based approach exhibits several desirable properties. Specifically, the higher market granularity of the installer-based approach will allow future PV market research to study themore » relationship between market dynamics and pricing with more precision.« less

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution

PubMed Central

Poulin, Robert; Lagrue, Clément

2017-01-01

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance–mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance–mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites. PMID:27994156

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Analysis of spatial configuration of the Palace Museum: an application of the axial-based space syntax

NASA Astrophysics Data System (ADS)

Chen, Jie; Lu, Feng

2006-10-01

Movement in a spatial system is produced and determined by the structure of the complex space itself, rather than special attractors within the whole spatial system. Based on this theory of space syntax, tourists' convergence and dispersal in the Palace Museum should be originated by the distribution of the internal constructions form. This article presents an application of the space syntax approach to the Palace Museum. After analyzing its internal spatial configuration, as a conclusion, the paper provides some rational advices so as to facilitate tourists as well as protect our invaluable cultural heritage.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Optimal sampling design for estimating spatial distribution and abundance of a freshwater mussel population

USGS Publications Warehouse

Pooler, P.S.; Smith, D.R.

2005-01-01

We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.

Spatial heterogeneity distribution of soil total nitrogen and total phosphorus in the Yaoxiang watershed in a hilly area of northern China based on geographic information system and geostatistics.

PubMed

Liu, Yu; Gao, Peng; Zhang, Liyong; Niu, Xiang; Wang, Bing

2016-10-01

Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients ( C v ) of STN and STP in the 0- to 10-cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10- to 30-cm soil layer (28.77% and 11.60%, respectively). Moreover, the C v of STN was higher than that of STP. (2) The maximum C 0 /( C 0  +  C 1 ) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.

3D scene reconstruction based on multi-view distributed video coding in the Zernike domain for mobile applications

NASA Astrophysics Data System (ADS)

Palma, V.; Carli, M.; Neri, A.

2011-02-01

In this paper a Multi-view Distributed Video Coding scheme for mobile applications is presented. Specifically a new fusion technique between temporal and spatial side information in Zernike Moments domain is proposed. Distributed video coding introduces a flexible architecture that enables the design of very low complex video encoders compared to its traditional counterparts. The main goal of our work is to generate at the decoder the side information that optimally blends temporal and interview data. Multi-view distributed coding performance strongly depends on the side information quality built at the decoder. At this aim for improving its quality a spatial view compensation/prediction in Zernike moments domain is applied. Spatial and temporal motion activity have been fused together to obtain the overall side-information. The proposed method has been evaluated by rate-distortion performances for different inter-view and temporal estimation quality conditions.

Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network

PubMed Central

Zhou, Shenglu; Su, Quanlong; Yi, Haomin

2017-01-01

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolation and BP neural network methods to estimate the spatial distribution of arsenic (As) and cadmium (Cd) pollution in the study area. Additionally, we introduced a cross-validation method to measure the errors of the estimation results by the two interpolation methods and discussed the accuracy of the information contained in the estimation results. The conclusions are as follows: data distribution characteristics, spatial variability, and mean square errors (MSE) of the different methods showed large differences. Estimation results from BP neural network models have a higher accuracy, the MSE of As and Cd are 0.0661 and 0.1743, respectively. However, the interpolation results show significant skewed distribution, and spatial autocorrelation is strong. Using Kriging interpolation, the MSE of As and Cd are 0.0804 and 0.2983, respectively. The estimation results have poorer accuracy. Combining the two methods can improve the accuracy of the Kriging interpolation and more comprehensively represent the spatial distribution characteristics of metal(loid)s in regional soil. The study may provide a scientific basis and technical support for the regulation of soil metal(loid) pollution. PMID:29278363

Analysis of the spatial distribution of prostate cancer obtained from histopathological images

NASA Astrophysics Data System (ADS)

Diaz, Kristians; Castaneda, Benjamin; Montero, Maria Luisa; Yao, Jorge; Joseph, Jean; Rubens, Deborah; Parker, Kevin J.

2013-03-01

Understanding the spatial distribution of prostate cancer and how it changes according to prostate specific antigen (PSA) values, Gleason score, and other clinical parameters may help comprehend the disease and increase the overall success rate of biopsies. This work aims to build 3D spatial distributions of prostate cancer and examine the extent and location of cancer as a function of independent clinical parameters. The border of the gland and cancerous regions from wholemount histopathological images are used to reconstruct 3D models showing the localization of tumor. This process utilizes color segmentation and interpolation based on mathematical morphological distance. 58 glands are deformed into one prostate atlas using a combination of rigid, affine, and b-spline deformable registration techniques. Spatial distribution is developed by counting the number of occurrences in a given position in 3D space from each registered prostate cancer. Finally a difference between proportions is used to compare different spatial distributions. Results show that prostate cancer has a significant difference (SD) in the right zone of the prostate between populations with PSA greater and less than 5ng/ml. Age does not have any impact in the spatial distribution of the disease. Positive and negative capsule-penetrated cases show a SD in the right posterior zone. There is SD in almost all the glands between cases with tumors larger and smaller than 10% of the whole prostate. A larger database is needed to improve the statistical validity of the test. Finally, information from whole-mount histopathological images may provide better insight into prostate cancer.

Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

PubMed Central

Hinckley, A; Bachand, A; Nuckols, J; Reif, J

2005-01-01

Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure misclassification in epidemiological studies of DBPs. PMID:15961627

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extens...

GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

NASA Astrophysics Data System (ADS)

Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.

2003-04-01

Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.

Damage identification method for continuous girder bridges based on spatially-distributed long-gauge strain sensing under moving loads

NASA Astrophysics Data System (ADS)

Wu, Bitao; Wu, Gang; Yang, Caiqian; He, Yi

2018-05-01

A novel damage identification method for concrete continuous girder bridges based on spatially-distributed long-gauge strain sensing is presented in this paper. First, the variation regularity of the long-gauge strain influence line of continuous girder bridges which changes with the location of vehicles on the bridge is studied. According to this variation regularity, a calculation method for the distribution regularity of the area of long-gauge strain history is investigated. Second, a numerical simulation of damage identification based on the distribution regularity of the area of long-gauge strain history is conducted, and the results indicate that this method is effective for identifying damage and is not affected by the speed, axle number and weight of vehicles. Finally, a real bridge test on a highway is conducted, and the experimental results also show that this method is very effective for identifying damage in continuous girder bridges, and the local element stiffness distribution regularity can be revealed at the same time. This identified information is useful for maintaining of continuous girder bridges on highways.

Asymmetric competition causes multimodal size distributions in spatially structured populations

PubMed Central

Velázquez, Jorge; Allen, Robert B.; Coomes, David A.; Eichhorn, Markus P.

2016-01-01

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts. PMID:26817778

Spatial distribution of calcium-gated chloride channels in olfactory cilia.

PubMed

French, Donald A; Badamdorj, Dorjsuren; Kleene, Steven J

2010-12-30

In vertebrate olfactory receptor neurons, sensory cilia transduce odor stimuli into changes in neuronal membrane potential. The voltage changes are primarily caused by the sequential openings of two types of channel: a cyclic-nucleotide-gated (CNG) cationic channel and a calcium-gated chloride channel. In frog, the cilia are 25 to 200 µm in length, so the spatial distributions of the channels may be an important determinant of odor sensitivity. To determine the spatial distribution of the chloride channels, we recorded from single cilia as calcium was allowed to diffuse down the length of the cilium and activate the channels. A computational model of this experiment allowed an estimate of the spatial distribution of the chloride channels. On average, the channels were concentrated in a narrow band centered at a distance of 29% of the ciliary length, measured from the base of the cilium. This matches the location of the CNG channels determined previously. This non-uniform distribution of transduction proteins is consistent with similar findings in other cilia. On average, the two types of olfactory transduction channel are concentrated in the same region of the cilium. This may contribute to the efficient detection of weak stimuli.

Ground and satellite based assessment of meteorological droughts: The Coello river basin case study

NASA Astrophysics Data System (ADS)

Cruz-Roa, A. F.; Olaya-Marín, E. J.; Barrios, M. I.

2017-10-01

The spatial distribution of droughts is a key factor for designing water management policies at basin scale in arid and semi-arid regions. Ground hydro-meteorological data in neo-tropical areas are scarce; therefore, the merging of ground and satellite datasets is a promissory approach for improving our understanding of water distribution. This paper compares three monthly rainfall interpolation methods for drought evaluation. The ordinary kriging technique based on ground data, and cokriging with elevation as auxiliary variable were compared against cokriging using the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA). Twenty rain gauge stations and the 3B42V7 version of the TMPA research dataset were considered. Comparisons were made over the Coello river basin (Colombia) at 3″ spatial resolution covering a period of eight years (1998-2005). The best spatial rainfall estimation was found for cokriging using ground data and elevation. The spatial support of TMPA dataset is very coarse for a merged interpolation with ground data, this spatial scales discrepancy highlight the need to consider scaling rules in the interpolation process.

A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring.

PubMed

Takahashi, Kunihiko; Kulldorff, Martin; Tango, Toshiro; Yih, Katherine

2008-04-11

Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. Based on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic. The flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.

Topologically Consistent Models for Efficient Big Geo-Spatio Data Distribution

NASA Astrophysics Data System (ADS)

Jahn, M. W.; Bradley, P. E.; Doori, M. Al; Breunig, M.

2017-10-01

Geo-spatio-temporal topology models are likely to become a key concept to check the consistency of 3D (spatial space) and 4D (spatial + temporal space) models for emerging GIS applications such as subsurface reservoir modelling or the simulation of energy and water supply of mega or smart cities. Furthermore, the data management for complex models consisting of big geo-spatial data is a challenge for GIS and geo-database research. General challenges, concepts, and techniques of big geo-spatial data management are presented. In this paper we introduce a sound mathematical approach for a topologically consistent geo-spatio-temporal model based on the concept of the incidence graph. We redesign DB4GeO, our service-based geo-spatio-temporal database architecture, on the way to the parallel management of massive geo-spatial data. Approaches for a new geo-spatio-temporal and object model of DB4GeO meeting the requirements of big geo-spatial data are discussed in detail. Finally, a conclusion and outlook on our future research are given on the way to support the processing of geo-analytics and -simulations in a parallel and distributed system environment.

Regional-specific Stochastic Simulation of Spatially-distributed Ground-motion Time Histories using Wavelet Packet Analysis

NASA Astrophysics Data System (ADS)

Huang, D.; Wang, G.

2014-12-01

Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.

Surface plasmon enhanced cell microscopy with blocked random spatial activation

NASA Astrophysics Data System (ADS)

Son, Taehwang; Oh, Youngjin; Lee, Wonju; Yang, Heejin; Kim, Donghyun

2016-03-01

We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.

A nonparametric spatial scan statistic for continuous data.

PubMed

Jung, Inkyung; Cho, Ho Jin

2015-10-20

Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

List of U.S. Army Research Institute Research and Technical Publications for Public Release/Unlimited Distribution, Fiscal Year 2008

DTIC Science & Technology

2009-11-01

times were shorter, collisions were fewer, and more targets were photographed. Effects of video game experience and spatial ability were also...Control Spatial ability, video game , user-interface, remote control, robot TR 1230 The Perception and Estimation of Egocentric Distance in Real and...development by RDECOM-STTC, and ARI is using the AW-VTT to research challenges in the use of distributed, game -based simulations for training

In vivo measurements of cutaneous melanin across spatial scales: using multiphoton microscopy and spatial frequency domain spectroscopy

PubMed Central

Saager, Rolf B.; Balu, Mihaela; Crosignani, Viera; Sharif, Ata; Durkin, Anthony J.; Kelly, Kristen M.; Tromberg, Bruce J.

2015-01-01

Abstract. The combined use of nonlinear optical microscopy and broadband reflectance techniques to assess melanin concentration and distribution thickness in vivo over the full range of Fitzpatrick skin types is presented. Twelve patients were measured using multiphoton microscopy (MPM) and spatial frequency domain spectroscopy (SFDS) on both dorsal forearm and volar arm, which are generally sun-exposed and non-sun-exposed areas, respectively. Both MPM and SFDS measured melanin volume fractions between ∼5% (skin type I non-sun-exposed) and 20% (skin type VI sun exposed). MPM measured epidermal (anatomical) thickness values ∼30–65  μm, while SFDS measured melanin distribution thickness based on diffuse optical path length. There was a strong correlation between melanin concentration and melanin distribution (epidermal) thickness measurements obtained using the two techniques. While SFDS does not have the ability to match the spatial resolution of MPM, this study demonstrates that melanin content as quantified using SFDS is linearly correlated with epidermal melanin as measured using MPM (R2=0.8895). SFDS melanin distribution thickness is correlated to MPM values (R2=0.8131). These techniques can be used individually and/or in combination to advance our understanding and guide therapies for pigmentation-related conditions as well as light-based treatments across a full range of skin types. PMID:26065839

High resolution population distribution maps for Southeast Asia in 2010 and 2015.

PubMed

Gaughan, Andrea E; Stevens, Forrest R; Linard, Catherine; Jia, Peng; Tatem, Andrew J

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.

High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015

PubMed Central

Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org. PMID:23418469

Influence of spatiotemporally distributed irradiance data input on temperature evolution in parabolic trough solar field simulations

NASA Astrophysics Data System (ADS)

Bubolz, K.; Schenk, H.; Hirsch, T.

2016-05-01

Concentrating solar field operation is affected by shadowing through cloud movement. For line focusing systems the impact of varying irradiance has been studied before by several authors with simulations of relevant thermodynamics assuming spatially homogeneous irradiance or using artificial test signals. While today's simulation capabilities allow more and more a higher spatiotemporal resolution of plant processes there are only few studies on influence of spatially distributed irradiance due to lack of available data. Based on recent work on generating real irradiance maps with high spatial resolution this paper demonstrates their influence on solar field thermodynamics. For a case study an irradiance time series is chosen. One solar field section with several loops and collecting header is modeled for simulation purpose of parabolic trough collectors and oil as heat transfer medium. Assuming homogeneous mass flow distribution among all loops we observe spatially varying temperature characteristics. They are analysed without and with mass flow control and their impact on solar field control design is discussed. Finally, the potential of distributed irradiance data is outlined.

A dam-reservoir module for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena

2017-04-01

Developing modeling tools that help to assess the spatial distribution of water resources is a key issue to achieve better solutions for the optimal management of water availability among users in a river basin. Streamflow dynamics depends on (i) the spatial variability of rainfall, (ii) the heterogeneity of catchment behavior and response, and (iii) local human regulations (e.g., reservoirs) that store and control surface water. These aspects can be successfully handled by distributed or semi-distributed hydrological models. In this study, we develop a dam-reservoir module within a semi-distributed rainfall-runoff model (de Lavenne et al. 2016). The model runs at the daily time step, and has five parameters for each sub-catchment as well as a streamflow velocity parameter for flow routing. Its structure is based on two stores, one for runoff production and one for routing. The calibration of the model is performed from upstream to downstream sub-catchments, which efficiently uses spatially-distributed streamflow measurements. In a previous study, Payan et al. (2008) described a strategy to implement a dam module within a lumped rainfall-runoff model. Here we propose to adapt this strategy to a semi-distributed hydrological modelling framework. In this way, the specific location of existing reservoirs inside a river basin is explicitly accounted for. Our goal is to develop a tool that can provide answers to the different issues involved in spatial water management in human-influenced contexts and at large modelling scales. The approach is tested for the Seine basin in France. Results are shown for model performance with and without the dam module. Also, a comparison with the lumped GR5J model highlights the improvements obtained in model performance by considering human influences more explicitly, and by facilitating parameter identifiability. This work opens up new perspectives for streamflow naturalization analyses and scenario-based spatial assessment of water resources under global change. References de Lavenne, A.; Thirel, G.; Andréassian, V.; Perrin, C. & Ramos, M.-H. (2016), 'Spatial variability of the parameters of a semi-distributed hydrological model', PIAHS 373, 87-94. Payan, J.-L.; Perrin, C.; Andréassian, V. & Michel, C. (2008), 'How can man-made water reservoirs be accounted for in a lumped rainfall-runoff model?', Water Resour. Res. 44(3), W03420.

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A. H.; Hazenberg, P.; Torfs, P. J. J. F.; Uijlenhoet, R.

2012-09-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

Mapping local and global variability in plant trait distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude - 2016

DOE Data Explorer

Andres, R.J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, G. [Appalachian State University, Boone, NC (United States)

2016-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude - 2015

DOE Data Explorer

Andres, R.J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, J. [Appalachian State University, Boone, NC (United States)

2015-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2011 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2015), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2010) (V.2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2010-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2006) (V.2009)

DOE Data Explorer

Andres, R. J. [.; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Marland, Greg [Appalachian State University, Boone, North Carolina (USA)

2009-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2006.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2011) (1950 - 2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA_; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2011-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, North Caroline (USA)

2012-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2009.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude - 2013

DOE Data Explorer

Andres, R. J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, G. [Appalachain State University, Boone, NC (United States)

1996-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Evaluation of a semi-distributed model through an assessment of the spatial coherence of Intercatchment Groundwater Flows

NASA Astrophysics Data System (ADS)

de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena

2016-04-01

Semi-distributed hydrological models aim to provide useful information to understand and manage the spatial distribution of water resources. However, their evaluation is often limited to independent and single evaluations at each sub-catchment within larger catchments. This enables to qualify model performance at different points, but does not provide a coherent assessment of the overall spatial consistency of the model. To cope with these methodological deficiencies, we propose a two-step strategy. First, we apply a sequential spatial calibration procedure to define spatially consistent model parameters. Secondly, we evaluate the hydrological simulations using variables that involve some dependency between sub-catchments to evaluate the overall coherence of model outputs. In this study, we particularly choose to look at the simulated Intercatchment Groundwater Flows (IGF). The idea is that the water that is lost in one place should be recovered somewhere else within the catchment to guarantee a spatially coherent water balance in time. The model used is a recently developed daily semi-distributed model, which is based on a spatial distribution of the lumped GR5J model. The model has five parameters for each sub-catchments and a streamflow velocity parameter for flow routing between them. It implements two reservoirs, one for production and one for routing, and estimates IGF according to the level of the second in a way that catchment can release water to IGF during high flows and receive water through IGF during low flows. The calibration of the model is performed from upstream to downstream, making an efficient use of spatially distributed streamflow measurements. To take model uncertainty into account, we implemented three variants of the original model structure, each one computing in a different way the IGF in each sub-catchment. The study is applied on over 1000 catchments in France. By exploring a wide area and a variability of hydrometeorological conditions, we aim to detect IGF even between catchments which can be quite distant from one another.

Development of a Heterogenic Distributed Environment for Spatial Data Processing Using Cloud Technologies

NASA Astrophysics Data System (ADS)

Garov, A. S.; Karachevtseva, I. P.; Matveev, E. V.; Zubarev, A. E.; Florinsky, I. V.

2016-06-01

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (http://cartsrv.mexlab.ru/geoportal) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

2016-12-01

Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.

Traveltime-based descriptions of transport and mixing in heterogeneous domains

NASA Astrophysics Data System (ADS)

Luo, Jian; Cirpka, Olaf A.

2008-09-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass transfer coefficients. In most applications, breakthrough curves (BTCs) of conservative and reactive compounds are measured at only a few locations and spatially explicit models are calibrated by matching these BTCs. A common difficulty in such applications is that the individual BTCs differ too strongly to justify the assumption of spatial homogeneity, whereas the number of observation points is too small to identify the spatial distribution of the decisive parameters. The key objective of the current study is to characterize physical transport by the analysis of conservative tracer BTCs and predict the macroscopic BTCs of compounds that react upon mixing from the interpretation of conservative tracer BTCs and reactive parameters determined in the laboratory. We do this in the framework of traveltime-based transport models which do not require spatially explicit, costly aquifer characterization. By considering BTCs of a conservative tracer measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the traveltime-based framework, the BTC of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct traveltime value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of traveltimes, which also determines the weights associated with each stream tube. Key issues in using the traveltime-based framework include the description of mixing mechanisms and the estimation of the traveltime distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the traveltime distribution, given a BTC integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases wherein the true traveltime distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and traveltime distributions to fit conservative BTCs and describe the tailing. A reactive transport case of a dual Michaelis-Menten problem demonstrates that the reactive mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local BTCs.

GIS-BASED HYDROLOGIC MODELING: THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local scale problems toward complex, spatially explicit regional ones. Such problems have to be
addressed with distributed models that can compute runoff and erosion at different spatial a...

Spatial and kinematic distributions of transition populations in intermediate redshift galaxy clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crawford, Steven M.; Wirth, Gregory D.; Bershady, Matthew A., E-mail: crawford@saao.ac.za, E-mail: wirth@keck.hawaii.edu, E-mail: mab@astro.wisc.edu

2014-05-01

We analyze the spatial and velocity distributions of confirmed members in five massive clusters of galaxies at intermediate redshift (0.5 < z < 0.9) to investigate the physical processes driving galaxy evolution. Based on spectral classifications derived from broad- and narrow-band photometry, we define four distinct galaxy populations representing different evolutionary stages: red sequence (RS) galaxies, blue cloud (BC) galaxies, green valley (GV) galaxies, and luminous compact blue galaxies (LCBGs). For each galaxy class, we derive the projected spatial and velocity distribution and characterize the degree of subclustering. We find that RS, BC, and GV galaxies in these clusters havemore » similar velocity distributions, but that BC and GV galaxies tend to avoid the core of the two z ≈ 0.55 clusters. GV galaxies exhibit subclustering properties similar to RS galaxies, but their radial velocity distribution is significantly platykurtic compared to the RS galaxies. The absence of GV galaxies in the cluster cores may explain their somewhat prolonged star-formation history. The LCBGs appear to have recently fallen into the cluster based on their larger velocity dispersion, absence from the cores of the clusters, and different radial velocity distribution than the RS galaxies. Both LCBG and BC galaxies show a high degree of subclustering on the smallest scales, leading us to conclude that star formation is likely triggered by galaxy-galaxy interactions during infall into the cluster.« less

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane

PubMed Central

Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian

2016-01-01

Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

Rupture Propagation for Stochastic Fault Models

NASA Astrophysics Data System (ADS)

Favreau, P.; Lavallee, D.; Archuleta, R.

2003-12-01

The inversion of strong motion data of large earhquakes give the spatial distribution of pre-stress on the ruptured faults and it can be partially reproduced by stochastic models, but a fundamental question remains: how rupture propagates, constrained by the presence of spatial heterogeneity? For this purpose we investigate how the underlying random variables, that control the pre-stress spatial variability, condition the propagation of the rupture. Two stochastic models of prestress distributions are considered, respectively based on Cauchy and Gaussian random variables. The parameters of the two stochastic models have values corresponding to the slip distribution of the 1979 Imperial Valley earthquake. We use a finite difference code to simulate the spontaneous propagation of shear rupture on a flat fault in a 3D continuum elastic body. The friction law is the slip dependent friction law. The simulations show that the propagation of the rupture front is more complex, incoherent or snake-like for a prestress distribution based on Cauchy random variables. This may be related to the presence of a higher number of asperities in this case. These simulations suggest that directivity is stronger in the Cauchy scenario, compared to the smoother rupture of the Gauss scenario.

Unleashing spatially distributed ecohydrology modeling using Big Data tools

NASA Astrophysics Data System (ADS)

Miles, B.; Idaszak, R.

2015-12-01

Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well as point time series of arbitrary variables at arbitrary points in space within a watershed or river basin. By treating ecohydrology modeling as a Big Data problem, we hope to provide a platform for answering transformative science and management questions related to water quantity and quality in a world of non-stationary climate.

[Ecological risk assessment of land use based on exploratory spatial data analysis (ESDA): a case study of Haitan Island, Fujian Province].

PubMed

Wu, Jian; Chen, Peng; Wen, Chao-Xiang; Fu, Shi-Feng; Chen, Qing-Hui

2014-07-01

As a novel environment management tool, ecological risk assessment has provided a new perspective for the quantitative evaluation of ecological effects of land-use change. In this study, Haitan Island in Fujian Province was taken as a case. Based on the Landsat TM obtained in 1990, SPOT5 RS images obtained in 2010, general layout planning map of Pingtan Comprehensive Experimental Zone in 2030, as well as the field investigation data, we established an ecological risk index to measure ecological endpoints. By using spatial autocorrelation and semivariance analysis of Exploratory Spatial Data Analysis (ESDA), the ecological risk of Haitan Island under different land-use situations was assessed, including the past (1990), present (2010) and future (2030), and the potential risk and its changing trend were analyzed. The results revealed that the ecological risk index showed obvious scale effect, with strong positive correlation within 3000 meters. High-high (HH) and low-low (LL) aggregations were predominant types in spatial distribution of ecological risk index. The ecological risk index showed significant isotropic characteristics, and its spatial distribution was consistent with Anselin Local Moran I (LISA) distribution during the same period. Dramatic spatial distribution change of each ecological risk area was found among 1990, 2010 and 2030, and the fluctuation trend and amplitude of different ecological risk areas were diverse. The low ecological risk area showed a rise-to-fall trend while the medium and high ecological risk areas showed a fall-to-rise trend. In the planning period, due to intensive anthropogenic disturbance, the high ecological risk area spread throughout the whole region. To reduce the ecological risk in land-use and maintain the regional ecological security, the following ecological risk control strategies could be adopted, i.e., optimizing the spatial pattern of land resources, protecting the key ecoregions and controlling the scale of construction land use.

The spatial distribution of gender differences in obesity prevalence differs from overall obesity prevalence among US adults

PubMed Central

Gartner, Danielle R.; Taber, Daniel R.; Hirsch, Jana A.; Robinson, Whitney R.

2016-01-01

Purpose While obesity disparities between racial and socioeconomic groups have been well characterized, those based on gender and geography have not been as thoroughly documented. This study describes obesity prevalence by state, gender, and race/ethnicity to (1) characterize obesity gender inequality, (2) determine if the geographic distribution of inequality is spatially clustered and (3) contrast the spatial clustering patterns of obesity gender inequality with overall obesity prevalence. Methods Data from the Centers for Disease Control and Prevention’s 2013 Behavioral Risk Factor Surveillance System (BRFSS) were used to calculate state-specific obesity prevalence and gender inequality measures. Global and Local Moran’s Indices were calculated to determine spatial autocorrelation. Results Age-adjusted, state-specific obesity prevalence difference and ratio measures show spatial autocorrelation (z-score=4.89, p-value <0.001). Local Moran’s Indices indicate the spatial distributions of obesity prevalence and obesity gender inequalities are not the same. High and low values of obesity prevalence and gender inequalities cluster in different areas of the U.S. Conclusion Clustering of gender inequality suggests that spatial processes operating at the state level, such as occupational or physical activity policies or social norms, are involved in the etiology of the inequality and necessitate further attention to the determinates of obesity gender inequality. PMID:27039046

Extended Shared Socioeconomic Pathways for Coastal Impact Assessment: Spatial Coastal Population Scenarios

NASA Astrophysics Data System (ADS)

Merkens, Jan-Ludolf; Reimann, Lena; Hinkel, Jochen; Vafeidis, Athanasios T.

2016-04-01

This work extends the Shared Socioeconomic Pathways (SSPs) by developing spatial projections of global coastal population distribution for the five basic SSPs. Based on a series of coastal migration drivers, which were identified from existing literature, we develop coastal narratives for the five basic SSPs (SSP1-5). These narratives account for differences in coastal versus inland population development in urban and rural areas. To spatially distribute population we use the International Institute for Applied Systems Analysis (IIASA) national population and urbanisation projections and employ country-specific growth rates which differ for coastal and inland as well as for urban and rural regions. These rates are derived from spatial analysis of historical population data. We then adjust these rates for each SSP based on the coastal narratives. The resulting global population grids depict the projected distribution of coastal population for each SSP, until the end of the 21st century, at a spatial resolution of 30 arc seconds. These grids exhibit a three- to four-fold increase in coastal population compared to the basic SSPs. Across all SSPs, except for SSP3, coastal population peaks by the middle of the 21st century and declines afterwards. In SSP3 the coastal population grows continuously until 2100. Compared to the base year 2000 the coastal population increases considerably in all SSPs. The extended SSPs are intended to be utilised in Impact, Adaptation and Vulnerability (IAV) assessments as they allow for improved analysis of exposure to sea-level rise and coastal flooding under different physical and socioeconomic scenarios.

Insights from Modelling the Spatial Dependence Structure of Hydraulic Conductivity at the MADE Site Using Spatial Copulas

NASA Astrophysics Data System (ADS)

Haslauer, Claus; Bohling, Geoff

2013-04-01

Hydraulic conductivity (K) is a fundamental parameter that influences groundwater flow and solute transport. Measurements of K are limited and uncertain. Moreover, the spatial structure of K, which impacts the groundwater velocity field and hence directly influences the advective spreading of a solute migrating in the subsurface, is commonly described by approaches using second order moments. Spatial copulas have in the recent past been applied successfully to model the spatial dependence structure of heterogeneous subsurface datasets. At the MADE site, hydraulic conductivity (K) has been measured in exceptional detail. Two independently collected data-sets were used for this study: (1) ~2000 flowmeter based K measurements, and (2) ~20,000 direct-push based K measurements. These datasets exhibit a very heterogeneous (Var[ln(K)]>2) spatially distributed K field. A copula analysis reveals that the spatial dependence structure of the flowmeter and direct-push datasets are essentially the same. A spatial copula analysis factors out the influence of the marginal distribution of the property under investigation. This independence from the marginal distributions allows the copula analysis to reveal the underlying similarity between the spatial dependence structures of the flowmeter and direct-push datasets despite two complicating factors: 1) an overall offset between the datasets, with direct-push K values being, on average, roughly a factor of five lower than flowmeter K values, due at least in part to opposite biases between the two measurement techniques, and 2) the presence of some anomalously high K values in the direct-push dataset due to a lower limit on accurately measureable pressure responses in high-K zones. In addition, the vertical resolution of the direct-push dataset is ten times finer than that of the flowmeter dataset. Upscaling the direct-push data to compensate for this difference resulted in little change to the spatial structure. The objective of the presented work is to use multidimensional spatial copulas to describe and model the spatial dependence of the spatial structure of K at the heterogeneous MADE site, and evaluate the effects of this multidimensional description on solute transport.

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

NASA Astrophysics Data System (ADS)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

Phase retrieval of singular scalar light fields using a two-dimensional directional wavelet transform and a spatial carrier.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2008-10-01

We evaluate a method based on the two-dimensional directional wavelet transform and the introduction of a spatial carrier to retrieve optical phase distributions in singular scalar light fields. The performance of the proposed phase-retrieval method is compared with an approach based on Fourier transform. The advantages and limitations of the proposed method are discussed.

ESSG-based global spatial reference frame for datasets interrelation

NASA Astrophysics Data System (ADS)

Yu, J. Q.; Wu, L. X.; Jia, Y. J.

2013-10-01

To know well about the highly complex earth system, a large volume of, as well as a large variety of, datasets on the planet Earth are being obtained, distributed, and shared worldwide everyday. However, seldom of existing systems concentrates on the distribution and interrelation of different datasets in a common Global Spatial Reference Frame (GSRF), which holds an invisble obstacle to the data sharing and scientific collaboration. Group on Earth Obeservation (GEO) has recently established a new GSRF, named Earth System Spatial Grid (ESSG), for global datasets distribution, sharing and interrelation in its 2012-2015 WORKING PLAN.The ESSG may bridge the gap among different spatial datasets and hence overcome the obstacles. This paper is to present the implementation of the ESSG-based GSRF. A reference spheroid, a grid subdvision scheme, and a suitable encoding system are required to implement it. The radius of ESSG reference spheroid was set to the double of approximated Earth radius to make datasets from different areas of earth system science being covered. The same paramerters of positioning and orienting as Earth Centred Earth Fixed (ECEF) was adopted for the ESSG reference spheroid to make any other GSRFs being freely transformed into the ESSG-based GSRF. Spheroid degenerated octree grid with radius refiment (SDOG-R) and its encoding method were taken as the grid subdvision and encoding scheme for its good performance in many aspects. A triple (C, T, A) model is introduced to represent and link different datasets based on the ESSG-based GSRF. Finally, the methods of coordinate transformation between the ESSGbased GSRF and other GSRFs were presented to make ESSG-based GSRF operable and propagable.

Spatial relationships of sector-specific fossil fuel CO2 emissions in the United States

NASA Astrophysics Data System (ADS)

Zhou, Yuyu; Gurney, Kevin Robert

2011-09-01

Quantification of the spatial distribution of sector-specific fossil fuel CO2 emissions provides strategic information to public and private decision makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO2 emissions differ substantially and these differences are sector-specific. Area-based sources such as those in the residential and commercial sectors are driven by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO2 emissions confirms that counties with high (low) CO2 emissions tend to be clustered close to other counties with high (low) CO2 emissions and some of the spatial clustering extends to multistate spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multistate perspective. Our findings underscore the potential for geographically focused, sector-specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.

2008-01-01

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

A comparative study of spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) offshore Peru

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Cui, Li; Chen, Xinjun; Liu, Yu

2017-06-01

We examined spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) in the offshore waters of Peru bounded by 78°-86°W and 8°-20°S under 0.5°×0.5° fishing grid. The study is based on the catch-per-unit-effort (CPUE) and fishing effort from Chinese mainland squid jigging fleet in 2003-2004 and 2006-2013. The data for all years as well as the eight years (excluding El Niño events) were studied to examine the effect of climate variation on the spatial distribution of D. gigas. Five spatial clusters reflecting the spatial distribution were computed using K-means and Getis-Ord Gi* for a detailed comparative study. Our results showed that clusters identified by the two methods were quite different in terms of their spatial patterns, and K-means was not as accurate as Getis-Ord Gi*, as inferred from the agreement degree and receiver operating characteristic. There were more areas of hot and cold spots in years without the impact of El Niño, suggesting that such large-scale climate variations could reduce the clustering level of D. gigas. The catches also showed that warm El Niño conditions and high water temperature were less favorable for D. gigas offshore Peru. The results suggested that the use of K-means is preferable if the aim is to discover the spatial distribution of each sub-region (cluster) of the study area, while Getis-Ord Gi* is preferable if the aim is to identify statistically significant hot spots that may indicate the central fishing ground.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

PID temperature controller in pig nursery: spatial characterization of thermal environment

NASA Astrophysics Data System (ADS)

de Souza Granja Barros, Juliana; Rossi, Luiz Antonio; Menezes de Souza, Zigomar

2018-05-01

The use of enhanced technologies of temperature control can improve the thermal conditions in environments of livestock facilities. The objective of this study was to evaluate the spatial distribution of the thermal environment variables in a pig nursery with a heating system with two temperature control technologies based on the geostatistical analysis. The following systems were evaluated: overhead electrical resistance with Proportional, Integral, and Derivative (PID) controller and overhead electrical resistance with a thermostat. We evaluated the climatic variables: dry bulb temperature (Tbs), air relative humidity (RH), temperature and humidity index (THI), and enthalpy in the winter, at 7:00, 12:00, and 18:00 h. The spatial distribution of these variables was mapped by kriging. The results showed that the resistance heating system with PID controllers improved the thermal comfort conditions in the pig nursery in the coldest hours, maintaining the spatial distribution of the air temperature more homogeneous in the pen. During the hottest weather, neither system provided comfort.

An Automatic Instrument to Study the Spatial Scaling Behavior of Emissivity

PubMed Central

Tian, Jing; Zhang, Renhua; Su, Hongbo; Sun, Xiaomin; Chen, Shaohui; Xia, Jun

2008-01-01

In this paper, the design of an automatic instrument for measuring the spatial distribution of land surface emissivity is presented, which makes the direct in situ measurement of the spatial distribution of emissivity possible. The significance of this new instrument lies in two aspects. One is that it helps to investigate the spatial scaling behavior of emissivity and temperature; the other is that, the design of the instrument provides theoretical and practical foundations for the implement of measuring distribution of surface emissivity on airborne or spaceborne. To improve the accuracy of the measurements, the emissivity measurement and its uncertainty are examined in a series of carefully designed experiments. The impact of the variation of target temperature and the environmental irradiance on the measurement of emissivity is analyzed as well. In addition, the ideal temperature difference between hot environment and cool environment is obtained based on numerical simulations. Finally, the scaling behavior of surface emissivity caused by the heterogeneity of target is discussed. PMID:27879735

PID temperature controller in pig nursery: spatial characterization of thermal environment

NASA Astrophysics Data System (ADS)

de Souza Granja Barros, Juliana; Rossi, Luiz Antonio; Menezes de Souza, Zigomar

2017-11-01

The use of enhanced technologies of temperature control can improve the thermal conditions in environments of livestock facilities. The objective of this study was to evaluate the spatial distribution of the thermal environment variables in a pig nursery with a heating system with two temperature control technologies based on the geostatistical analysis. The following systems were evaluated: overhead electrical resistance with Proportional, Integral, and Derivative (PID) controller and overhead electrical resistance with a thermostat. We evaluated the climatic variables: dry bulb temperature (Tbs), air relative humidity (RH), temperature and humidity index (THI), and enthalpy in the winter, at 7:00, 12:00, and 18:00 h. The spatial distribution of these variables was mapped by kriging. The results showed that the resistance heating system with PID controllers improved the thermal comfort conditions in the pig nursery in the coldest hours, maintaining the spatial distribution of the air temperature more homogeneous in the pen. During the hottest weather, neither system provided comfort.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Towards a 3d Spatial Urban Energy Modelling Approach

NASA Astrophysics Data System (ADS)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Variations in spatial patterns of soil-vegetation properties and the emergence of multiple resilience thresholds within different debris flow fan positions

NASA Astrophysics Data System (ADS)

Mohseni, Neda; Hosseinzadeh, Seyed Reza; Sepehr, Adel; Golzarian, Mahmood Reza; Shabani, Farzin

2017-08-01

Debris flow fans are non-equilibrium landforms resulting from the spatial variations of debris flows deposited on them. This geomorphic disturbance involving the asymmetric redistribution of water and sediment may create spatially heterogeneous patterns of soil-vegetation along landforms. In this research, founded on field-based observations, we characterized the spatial patterns of some soil (e.g., particle size distribution including fine and coarse covers, and infiltration capacity) and vegetation (e.g., plant distance, vegetation density, patch size, and average number of patches) properties within different debris flow fan positions (Upper, Middle, and Lower fan) located at the base of the Binaloud Mountain hillslope in northeastern Iran. Thereafter, using a mathematical model of dry land vegetation dynamics, we calculated response trends of the different positions to the same environmental harshness gradient. Field measurements of soil-vegetation properties and infiltration rates showed that the asymmetric redistribution of debris flow depositions can cause statistically significant differences (P < 0.05) in the spatial patterns of soil and eco-hydrological characteristics along different landform positions. The results showed that mean plant distance, mean vegetation density, and the average number of patches decreased as the coarse covers increased toward the Lower fan plots. Conversely, an increase in infiltration rate was observed. The simulation results on the aerial images taken from different positions, illustrated that positions with a heterogeneous distribution of vegetation patterns were not desertified to the same degree of aridity. Thus, the Middle and Lower positions could survive under harsher aridity conditions, due to the emergence of more varied spatial vegetation patterns than at the Upper fan position. The findings, based on a combined field and modeling approach, highlighted that debris flow as a geomorphic process with the asymmetric distribution of depositions on the gentle slope of an alluvial fan, can incur multiple resilience thresholds with different degrees of self-organization under stressful conditions over the spatial heterogeneities of soil-dependent vegetation structures.

The role of environmental variables in structuring landscape-scale species distributions in seafloor habitats.

PubMed

Kraan, Casper; Aarts, Geert; Van der Meer, Jaap; Piersma, Theunis

2010-06-01

Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants.

PubMed

Meng, Yu; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2014-10-15

Sulcal pits, the locally deepest points in sulci of the highly convoluted and variable cerebral cortex, are found to be spatially consistent across human adult individuals. It is suggested that sulcal pits are genetically controlled and have close relationships with functional areas. To date, the existing imaging studies of sulcal pits are mainly focused on adult brains, yet little is known about the spatial distribution and temporal development of sulcal pits in the first 2 years of life, which is the most dynamic and critical period of postnatal brain development. Studying sulcal pits during this period would greatly enrich our limited understandings of the origins and developmental trajectories of sulcal pits, and would also provide important insights into many neurodevelopmental disorders associated with abnormal cortical foldings. In this paper, by using surface-based morphometry, for the first time, we systemically investigated the spatial distribution and temporal development of sulcal pits in major cortical sulci from 73 healthy infants, each with three longitudinal 3T MR scans at term birth, 1 year, and 2 years of age. Our results suggest that the spatially consistent distributions of sulcal pits in major sulci across individuals have already existed at term birth and this spatial distribution pattern keeps relatively stable in the first 2 years of life, despite that the cerebral cortex expands dramatically and the sulcal depth increases considerably during this period. Specially, the depth of sulcal pits increases regionally heterogeneously, with more rapid growth in the high-order association cortex, including the prefrontal and temporal cortices, than the sensorimotor cortex in the first 2 years of life. Meanwhile, our results also suggest that there exist hemispheric asymmetries of the spatial distributions of sulcal pits in several cortical regions, such as the central, superior temporal and postcentral sulci, consistently from birth to 2 years of age, which likely has close relationships with the lateralization of brain functions of these regions. This study provides detailed insights into the spatial distribution and temporal development of deep sulcal landmarks in infants. Copyright © 2014 Elsevier Inc. All rights reserved.

Definition of the Spatial Resolution of X-Ray Microanalysis in Thin Foils

NASA Technical Reports Server (NTRS)

Williams, D. B.; Michael, J. R.; Goldstein, J. I.; Romig, A. D., Jr.

1992-01-01

The spatial resolution of X-ray microanalysis in thin foils is defined in terms of the incident electron beam diameter and the average beam broadening. The beam diameter is defined as the full width tenth maximum of a Gaussian intensity distribution. The spatial resolution is calculated by a convolution of the beam diameter and the average beam broadening. This definition of the spatial resolution can be related simply to experimental measurements of composition profiles across interphase interfaces. Monte Carlo calculations using a high-speed parallel supercomputer show good agreement with this definition of the spatial resolution and calculations based on this definition. The agreement is good over a range of specimen thicknesses and atomic number, but is poor when excessive beam tailing distorts the assumed Gaussian electron intensity distributions. Beam tailing occurs in low-Z materials because of fast secondary electrons and in high-Z materials because of plural scattering.

Integrating distributional, spatial prioritization, and individual-based models to evaluate potential critical habitat networks: A case study using the Northern Spotted Owl

EPA Science Inventory

As part of the northern spotted owl recovery planning effort, we evaluated a series of alternative critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individual-based population model (HexSim). With this suite ...

Comparing species distribution models constructed with different subsets of environmental predictors

USGS Publications Warehouse

Bucklin, David N.; Basille, Mathieu; Benscoter, Allison M.; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.; Speroterra, Carolina; Watling, James I.

2014-01-01

Our results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

The design and research of poverty alleviation monitoring and evaluation system: a case study in the Jiangxi province

NASA Astrophysics Data System (ADS)

Mo, Hong-yuan; Wang, Ying-jie; Yu, Zhuo-yuan

2009-07-01

The Poverty Alleviation Monitoring and Evaluation System (PAMES) is introduced in this paper. The authors present environment platform selection, and details of system design and realization. Different with traditional research of poverty alleviation, this paper develops a new analytical geo-visualization approach to study the distribution and causes of poverty phenomena within Geographic Information System (GIS). Based on the most detailed poverty population data, the spatial location and population statistical indicators of poverty village in Jiangxi province, the distribution characteristics of poverty population are detailed. The research results can provide much poverty alleviation decision support from a spatial-temporal view. It should be better if the administrative unit of poverty-stricken area to be changed from county to village according to spatial distribution pattern of poverty.

Boundary control for a flexible manipulator based on infinite dimensional disturbance observer

NASA Astrophysics Data System (ADS)

Jiang, Tingting; Liu, Jinkun; He, Wei

2015-07-01

This paper focuses on disturbance observer and boundary control design for the flexible manipulator in presence of both boundary disturbance and spatially distributed disturbance. Taking the infinite-dimensionality of the flexural dynamics into account, this study proposes a partial differential equation (PDE) model. Since the spatially distributed disturbance is infinite dimensional, it cannot be compensated by the typical disturbance observer, which is designed by finite dimensional approach. To estimate the spatially distributed disturbance, we propose a novel infinite dimensional disturbance observer (IDDO). Applying the IDDO as a feedforward compensator, a boundary control scheme is designed to regulate the joint position and eliminate the elastic vibration simultaneously. Theoretical analysis validates the stability of both the proposed disturbance observer and the boundary controller. The performance of the closed-loop system is demonstrated by numerical simulations.

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Area-based tests for association between spatial patterns

NASA Astrophysics Data System (ADS)

Maruca, Susan L.; Jacquez, Geoffrey M.

Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new ``spatially explicit'' techniques provide information and insights that cannot be obtained from the spectral information alone.

Maxillofacial Injuries as Markers of Interpersonal Violence in Belo Horizonte-Brazil: Analysis of the Socio-Spatial Vulnerability of the Location of Victim’s Residences

PubMed Central

Silva, Carlos José de Paula; Moura, Ana Clara Mourão; Paiva, Paula Cristina Pelli; Ferreira, Raquel Conceição; Silvestrini, Rafaella Almeida; Vargas, Andréa Maria Duarte; de Paula, Liliam Pacheco Pinto; Naves, Marcelo Drummond; Ferreira, Efigênia Ferreira e

2015-01-01

The aim of the present study was to analyze the spatial pattern of cases of maxillofacial injuries caused by interpersonal violence, based on the location of the victim’s residence, and to investigate the existence of conditions of socio-spatial vulnerability in these areas. This is a cross-sectional study, using the data of victims attended in three emergency hospitals in Belo Horizonte-Brazil between January 2008 and December 2010. Based on the process of spatial signature, the socio-spatial condition of the victims was identified according to data from census tracts. The spatial distribution trends of the addresses of victims were analyzed using Kernel maps and Ripley’s K function. Multicriteria analysis was used to analyze the territorial insertion of victims, using a combination of variables to obtain the degree of socio-spatial vulnerability. The residences of the victims were distributed in an aggregated manner in urban areas, with a confidence level of 99%. The highest densities were found in areas of unfavorable socioeconomic conditions and, to a lesser extent, areas with worse residential and neighborhood infrastructure. Spatial clusters of households formed in slums with a significant level of socio-spatial vulnerability. Explanations of the living conditions in segregated urban areas and analysis of the concentration of more vulnerable populations should be a priority in the development of public health and safety policies. PMID:26274320

Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

NASA Astrophysics Data System (ADS)

Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Shichkin, A. V.; Tyagunov, A. G.; Medvedev, A. N.

2017-06-01

Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

Reconstruction of spatial distributions of sound velocity and absorption in soft biological tissues using model ultrasonic tomographic data

NASA Astrophysics Data System (ADS)

Burov, V. A.; Zotov, D. I.; Rumyantseva, O. D.

2014-07-01

A two-step algorithm is used to reconstruct the spatial distributions of the acoustic characteristics of soft biological tissues-the sound velocity and absorption coefficient. Knowing these distributions is urgent for early detection of benign and malignant neoplasms in biological tissues, primarily in the breast. At the first stage, large-scale distributions are estimated; at the second step, they are refined with a high resolution. Results of reconstruction on the base of model initial data are presented. The principal necessity of preliminary reconstruction of large-scale distributions followed by their being taken into account at the second step is illustrated. The use of CUDA technology for processing makes it possible to obtain final images of 1024 × 1024 samples in only a few minutes.

Twenty years of changes in spatial association and community structure among desert perennials.

PubMed

Miriti, Maria N

2007-05-01

I present results from analyses of 20 years of spatiotemporal dynamics in a desert perennial community. Plants were identified and mapped in a 1-ha permanent plot in Joshua Tree National Park (California, USA) in 1984. Plant size, mortality, and new seedlings were censused every five years through 2004. Two species, Ambrosia dumosa and Tetracoccus hallii, were dominant based on their relative abundance and ubiquitous distributions. Spatial analysis for distance indices (SADIE) identified regions of significantly high (patches) or low (gaps) densities. I used SADIE to test for (1) transience in the distribution of patches and gaps within species over time and (2) changes in juvenile-adult associations with conspecific adults and adults of the two dominant species over time. Plant performance was quantified in patches and gaps to determine plant responsiveness to local spatial associations. Species identity was found to influence associations between juveniles and adults. Juveniles of all species showed significant positive spatial associations with the dominant A. dumosa but not with T. hallii. The broad distribution of A. dumosa may increase the spatial extent of non-dominant species that are facilitated by this dominant. The spatial location of patches and gaps was generally consistent over time for adults but not juveniles. Observed variability in the locations of juvenile patches and gaps suggested that suitable locations for establishment were broad relative to occupied regions of the habitat, and that conditions for seed germination were independent of conditions for seedling survival. A dramatic change in spatial distributions and associations within and between species occurred after a major drought that influenced data from the final census. Positive associations between juveniles and adults of all species were found independent of previous associations and most species distributions contracted to areas that were previously characterized by low density. By linking performance to spatial distribution, results from this study offer a spatial context for plant-plant interactions within and among species. Community composition could be influenced both by individual species tolerances of abiotic conditions and by the competitive or facilitative interactions individuals exert over neighbors.

USE OF REVA'S WEB-BASED ENVIRONMENTAL DECISION TOOLKIT (EDT) TO ASSESS VULNERABILITY TO MERCURY ACROSS THE UNITED STATES

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of 1) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

Coupling fine-scale root and canopy structure using ground-based remote sensing

Treesearch

Brady Hardiman; Christopher Gough; John Butnor; Gil Bohrer; Matteo Detto; Peter Curtis

2017-01-01

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in...

Spatial perspectives in state-and-transition models: A missing link to land management?

USDA-ARS?s Scientific Manuscript database

Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Relation between the chord length distribution of an infinitely long cylinder and that of its base

NASA Astrophysics Data System (ADS)

Sukiasian, H. S.; Gille, Wilfried

2007-05-01

Chord length distributions are defined for planar and spatial geometric figures. There exist connections between the planar and the spatial cases: The chord length distribution densities (CLDs) of a cylinder B and its base S (the cylinder's orthogonal cross section) are interrelated by a simple, surveyable integral transformation. From this transformation, it was concluded that the odd moments of the CLD f(x ) of S define the leading asymptotic terms of the CLD Aμ(r) of B. The power series of Aμ(r) at r =0 can be traced back to the derivatives of f(x ) in the origin. As a general conclusion, there exist different geometric bodies B in R3 with the same CLD Aμ(r). An exact recognition of B via its CLD is not possible. CLDs do not characterize spatial sets. This result is of importance in materials science in order to avoid wrong interpretations in structure research. The new CLD integral transformation has been illustrated in connection with the transitions triangle→triangular rod and rectangle→rectangular rod.

The applications of model-based geostatistics in helminth epidemiology and control.

PubMed

Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Vapor cell geometry effect on Rydberg atom-based microwave electric field measurement

NASA Astrophysics Data System (ADS)

Zhang, Linjie; Liu, Jiasheng; Jia, Yue; Zhang, Hao; Song, Zhenfei; Jia, Suotang

2018-03-01

The geometry effect of a vapor cell on the metrology of a microwave electric field is investigated. Based on the splitting of the electromagnetically induced transparency spectra of cesium Rydberg atoms in a vapor cell, high-resolution spatial distribution of the microwave electric field strength is achieved for both a cubic cell and a cylinder cell. The spatial distribution of the microwave field strength in two dimensions is measured with sub-wavelength resolution. The experimental results show that the shape of a vapor cell has a significant influence on the abnormal spatial distribution because of the Fabry–Pérot effect inside a vapor cell. A theoretical simulation is obtained for different vapor cell wall thicknesses and shows that a restricted wall thickness results in a measurement fluctuation smaller than 3% at the center of the vapor cell. Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA03044200 and 2016YFF0200104), the National Natural Science Foundation of China (Grant Nos. 91536110, 61505099, and 61378013), and the Fund for Shanxi “331 Project” Key Subjects Construction, China.

Different modelling approaches to evaluate nitrogen transport and turnover at the watershed scale

NASA Astrophysics Data System (ADS)

Epelde, Ane Miren; Antiguedad, Iñaki; Brito, David; Jauch, Eduardo; Neves, Ramiro; Garneau, Cyril; Sauvage, Sabine; Sánchez-Pérez, José Miguel

2016-08-01

This study presents the simulation of hydrological processes and nutrient transport and turnover processes using two integrated numerical models: Soil and Water Assessment Tool (SWAT) (Arnold et al., 1998), an empirical and semi-distributed numerical model; and Modelo Hidrodinâmico (MOHID) (Neves, 1985), a physics-based and fully distributed numerical model. This work shows that both models reproduce satisfactorily water and nitrate exportation at the watershed scale at annual and daily basis, MOHID providing slightly better results. At the watershed scale, both SWAT and MOHID simulated similarly and satisfactorily the denitrification amount. However, as MOHID numerical model was the only one able to reproduce adequately the spatial variation of the soil hydrological conditions and water table level fluctuation, it proved to be the only model able of reproducing the spatial variation of the nutrient cycling processes that are dependent to the soil hydrological conditions such as the denitrification process. This evidences the strength of the fully distributed and physics-based models to simulate the spatial variability of nutrient cycling processes that are dependent to the hydrological conditions of the soils.

Photon event distribution sampling: an image formation technique for scanning microscopes that permits tracking of sub-diffraction particles with high spatial and temporal resolutions.

PubMed

Larkin, J D; Publicover, N G; Sutko, J L

2011-01-01

In photon event distribution sampling, an image formation technique for scanning microscopes, the maximum likelihood position of origin of each detected photon is acquired as a data set rather than binning photons in pixels. Subsequently, an intensity-related probability density function describing the uncertainty associated with the photon position measurement is applied to each position and individual photon intensity distributions are summed to form an image. Compared to pixel-based images, photon event distribution sampling images exhibit increased signal-to-noise and comparable spatial resolution. Photon event distribution sampling is superior to pixel-based image formation in recognizing the presence of structured (non-random) photon distributions at low photon counts and permits use of non-raster scanning patterns. A photon event distribution sampling based method for localizing single particles derived from a multi-variate normal distribution is more precise than statistical (Gaussian) fitting to pixel-based images. Using the multi-variate normal distribution method, non-raster scanning and a typical confocal microscope, localizations with 8 nm precision were achieved at 10 ms sampling rates with acquisition of ~200 photons per frame. Single nanometre precision was obtained with a greater number of photons per frame. In summary, photon event distribution sampling provides an efficient way to form images when low numbers of photons are involved and permits particle tracking with confocal point-scanning microscopes with nanometre precision deep within specimens. © 2010 The Authors Journal of Microscopy © 2010 The Royal Microscopical Society.

The concept for realization of quantum-cascade lasers emitting at 7.5 μm wavelength

NASA Astrophysics Data System (ADS)

Novikov, I. I.; Babichev, A. V.; Bugrov, V. E.; Gladyshev, A. G.; Karachinsky, L. Ya; Kolodeznyi, E. S.; Kurochkin, A. S.; Savelyev, A. V.; Sokolovskii, G. S.; Egorov, A. Yu

2017-11-01

We consider the advantages and disadvantages of various designs of waveguide for heterostructures of quantum cascade lasers (QCL) in a spectral region of 7.5 μm. Based on a numerical calculation we make a comparison of light wave distribution in QCL waveguides with different designs. We demonstrate the benefits of practical QCL realization with an extended five-layered waveguide formed by introducing extra layers of InGaAs, which allows to modify the spatial distribution of the light wave and get the rectangular shape of the spatial distribution of light wave intensity in the laser active area.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

NASA Astrophysics Data System (ADS)

Manson, F. J.; Loneragan, N. R.; Phinn, S. R.

2003-07-01

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.

Evaluation of Karst Soil Erosion and Nutrient Loss Based on RUSLE Model in Guizhou Province

NASA Astrophysics Data System (ADS)

Zeng, Cheng; Li, Yangbing; Bai, Xiaoyong; Luo, Guangjie

2018-01-01

Based on GIS technology and RUSLE model, the spatial variation characteristics of soil erosion were analyzed in karst areas, and the relationship between soil erosion and soil nutrient loss was discussed. The results showed that the soil differences in spatial variation between nutrient losses. The results illustrate the total soil erosion in is 10316.31 × 104t • a-1, accounting for 84.95% of the total land area in Guizhou Province. The spatial distribution of soil erosion showing the characteristics of the southeast to the northwest strip. The annual average soil erosion modulu is 691.94 t • km-2 • a-1, of which karst is 720.28t • km-2 • a-1 and non-karst is 689.53 t • km-2 • a-1. The total nutrient losses such as soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP) and total potassium (TK) were 596.72 × 104t • a-1 due to soil erosion, and SOC, TN and TP and TK were 38.13, 1.61, 0.41 and 14.70t • km-2 • a-1, respectively. The average amount of loss and total loss are the largest in non-karst, and four kinds of nutrient is the smallest in karst gorge. The spatial variation of soil erosion in the study area is the process of increasing the erosion area with the increase of the erosion rate, and the difference of the spatial distribution of soil erosion determines the spatial distribution of soil nutrient loss.

Estimating the spatial distribution of artificial groundwater recharge using multiple tracers.

PubMed

Moeck, Christian; Radny, Dirk; Auckenthaler, Adrian; Berg, Michael; Hollender, Juliane; Schirmer, Mario

2017-10-01

Stable isotopes of water, organic micropollutants and hydrochemistry data are powerful tools for identifying different water types in areas where knowledge of the spatial distribution of different groundwater is critical for water resource management. An important question is how the assessments change if only one or a subset of these tracers is used. In this study, we estimate spatial artificial infiltration along an infiltration system with stage-discharge relationships and classify different water types based on the mentioned hydrochemistry data for a drinking water production area in Switzerland. Managed aquifer recharge via surface water that feeds into the aquifer creates a hydraulic barrier between contaminated groundwater and drinking water wells. We systematically compare the information from the aforementioned tracers and illustrate differences in distribution and mixing ratios. Despite uncertainties in the mixing ratios, we found that the overall spatial distribution of artificial infiltration is very similar for all the tracers. The highest infiltration occurred in the eastern part of the infiltration system, whereas infiltration in the western part was the lowest. More balanced infiltration within the infiltration system could cause the elevated groundwater mound to be distributed more evenly, preventing the natural inflow of contaminated groundwater. Dedicated to Professor Peter Fritz on the occasion of his 80th birthday.

Landscape genetics and the spatial distribution of chronic wasting disease

USGS Publications Warehouse

Blanchong, Julie A.; Samuel, M.D.; Scribner, K.T.; Weckworth, B.V.; Langenberg, J.A.; Filcek, K.B.

2008-01-01

Predicting the spread of wildlife disease is critical for identifying populations at risk, targeting surveillance and designing proactive management programmes. We used a landscape genetics approach to identify landscape features that influenced gene flow and the distribution of chronic wasting disease (CWD) in Wisconsin white-tailed deer. CWD prevalence was negatively correlated with genetic differentiation of study area deer from deer in the area of disease origin (core-area). Genetic differentiation was greatest, and CWD prevalence lowest, in areas separated from the core-area by the Wisconsin River, indicating that this river reduced deer gene flow and probably disease spread. Features of the landscape that influence host dispersal and spatial patterns of disease can be identified based on host spatial genetic structure. Landscape genetics may be used to predict high-risk populations based on their genetic connection to infected populations and to target disease surveillance, control and preventative activities. ?? 2007 The Royal Society.

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

Computing Pathways for Urban Decarbonization.

NASA Astrophysics Data System (ADS)

Cremades, R.; Sommer, P.

2016-12-01

Urban areas emit roughly three quarters of global carbon emissions. Cities are crucial elements for a decarbonized society. Urban expansion and related transportation needs lead to increased energy use, and to carbon-intensive lock-ins that create barriers for climate change mitigation globally. The authors present the Integrated Urban Complexity (IUC) model, based on self-organizing Cellular Automata (CA), and use it to produce a new kind of spatially explicit Transformation Pathways for Urban Decarbonization (TPUD). IUC is based on statistical evidence relating the energy needed for transportation with the spatial distribution of population, specifically IUC incorporates variables from complexity science related to urban form, like the slope of the rank-size rule or spatial entropy, which brings IUC a step beyond existing models. The CA starts its evolution with real-world urban land use and population distribution data from the Global Human Settlement Layer. Thus, the IUC model runs over existing urban settlements, transforming the spatial distribution of population so the energy consumption for transportation is minimized. The statistical evidence that governs the evolution of the CA departs from the database of the International Association of Public Transport. A selected case is presented using Stuttgart (Germany) as an example. The results show how IUC varies urban density in those places where it improves the performance of crucial parameters related to urban form, producing a TPUD that shows where the spatial distribution of population should be modified with a degree of detail of 250 meters of cell size. The TPUD shows how the urban complex system evolves over time to minimize energy consumption for transportation. The resulting dynamics or urban decarbonization show decreased energy per capita, although total energy increases for increasing population. The results provide innovative insights: by checking current urban planning against a TPUD, urban planners could understand where existing plans contradict the Agenda 2030, primarily the Sustainable Development Goals (SDGs) Climate Action (SDG 13), and Sustainable Cities and Communities (SDG 11). For the first time, evidence-based transformation pathways are produced to decarbonize cities.

Study on light scattering characterization for polishing surface of optical elements

NASA Astrophysics Data System (ADS)

Zhang, Yingge; Tian, Ailing; Wang, Chunhui; Wang, Dasen; Liu, Weiguo

2017-02-01

Based on the principle of bidirectional reflectance distribution function (BRDF), the relationship between the surface roughness and the spatial scattering distribution of the optical elements were studied. First, a series of optical components with different surface roughness was obtained by the traditional polishing processing, and measured by Talysurf CCI 3000. Secondly, the influences of different factors on the scattering characteristics were simulated and analyzed, such as different surface roughness, incident wavelength and incident angle. Finally, the experimental device was built, and the spatial distribution of scattered light was measured with the different conditions, and then the data curve variation was analyzed. It was shown that the experimental method was reliable by comparing the simulation and experimental results. Base on this to know, many studies on light scattering characteristics for optical element polishing surface can try later.

Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes

PubMed Central

Pittman, Simon J.; Brown, Kerry A.

2011-01-01

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management. PMID:21637787

Multi-scale approach for predicting fish species distributions across coral reef seascapes.

PubMed

Pittman, Simon J; Brown, Kerry A

2011-01-01

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management.

Sustainable Forest Management Support Based on the Spatial Distribution of Fuels for Fire Management

Treesearch

José Germán Flores Garnica; Juan de Dios Benavides Solorio; David Arturo Moreno Gonzalez

2006-01-01

Fire behavior simulation is based mainly on the fuel model-concept. However, there are great difficulties to develop the corresponding maps, therefore it is suggested the generation of four fuel maps (1-hour, 10-hours, 100-hours and alive). These maps will allow a better definition of the spatial variation of forest fuels, even within a zone classified as a given fuel...

Distribution of ULF energy (f is less than 80 mHz) in the inner magnetosphere - A statistical analysis of AMPTE CCE magnetic field data

NASA Technical Reports Server (NTRS)

Takahashi, Kazue; Anderson, Brian J.

1992-01-01

Magnetic field measurements made with the AMPTE CCE spacecraft are used to investigate the distribution of ULF energy in the inner magnetosphere. The data base is employed to examine the spatial distribution of ULF energy. The spatial distribution of wave power and spectral structures are used to identify several pulsation types, including multiharmonic toroidal oscillations; equatorial compressional Pc 3 oscillations; second harmonic poloidal oscillations; and nightside compressional oscillations. The frequencies of the toroidal oscillations are applied to determine the statistical radial profile of the plasma mass density and Alfven velocity. A clear signature of the plasma pause in the profiles of these average parameters is found.

Laser interferometry for the determination of thickness distributions of low absorbing films and their spatial and thickness resolutions.

PubMed

Mishima, T; Kao, K C

1982-03-15

New laser interferometry has been developed, based on the principle that a 2-D fringe pattern can be produced by interference of spatially coherent light beams. To avoid the effect of reflection from the back surface of the substrate, the Brewster angle of incidence is adopted; to suppress the effect of diffraction, a lens or a lens system is used. This laser interferometry is an efficient nondestructive technique for the determination of thickness distributions or uniformities of low absorbing films on transparent substrates over a large area without involving laborious computations. The limitation of spatial resolution, thickness resolution, and visibility of fringes is fully analyzed.

Use of Anecdotal Occurrence Data in Species Distribution Models: An Example Based on the White-Nosed Coati (Nasua narica) in the American Southwest

PubMed Central

Frey, Jennifer K.; Lewis, Jeremy C.; Guy, Rachel K.; Stuart, James N.

2013-01-01

Simple Summary We evaluated the influence of occurrence records with different reliability on predicted distribution of a unique, rare mammal in the American Southwest, the white-nosed coati (Nasua narica). We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data. Abstract Species distributions are usually inferred from occurrence records. However, these records are prone to errors in spatial precision and reliability. Although influence of spatial errors has been fairly well studied, there is little information on impacts of poor reliability. Reliability of an occurrence record can be influenced by characteristics of the species, conditions during the observation, and observer’s knowledge. Some studies have advocated use of anecdotal data, while others have advocated more stringent evidentiary standards such as only accepting records verified by physical evidence, at least for rare or elusive species. Our goal was to evaluate the influence of occurrence records with different reliability on species distribution models (SDMs) of a unique mammal, the white-nosed coati (Nasua narica) in the American Southwest. We compared SDMs developed using maximum entropy analysis of combined bioclimatic and biophysical variables and based on seven subsets of occurrence records that varied in reliability and spatial precision. We found that the predicted distribution of the coati based on datasets that included anecdotal occurrence records were similar to those based on datasets that only included physical evidence. Coati distribution in the American Southwest was predicted to occur in southwestern New Mexico and southeastern Arizona and was defined primarily by evenness of climate and Madrean woodland and chaparral land-cover types. Coati distribution patterns in this region suggest a good model for understanding the biogeographic structure of range margins. We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data. PMID:26487405

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-01

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230fs, which is caused by the spatial--temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged.

Facilitating political decisions using species distribution models to assess restoration measures in heavily modified estuaries.

PubMed

Heuner, Maike; Weber, Arnd; Schröder, Uwe; Kleinschmit, Birgit; Schröder, Boris

2016-09-15

The European Water Framework Directive requires a good ecological potential for heavily modified water bodies. This standard has not been reached for most large estuaries by 2015. Management plans for estuaries fall short in linking implementations between restoration measures and underlying spatial analyses. The distribution of emergent macrophytes - as an indicator of habitat quality - is here used to assess the ecological potential. Emergent macrophytes are capable of settling on gentle tidal flats where hydrodynamic stress is comparatively low. Analyzing their habitats based on spatial data, we set up species distribution models with 'elevation relative to mean high water', 'mean bank slope', and 'length of bottom friction' from shallow water up to the vegetation belt as key predictors representing hydrodynamic stress. Effects of restoration scenarios on habitats were assessed applying these models. Our findings endorse species distribution models as crucial spatial planning tools for implementing restoration measures in modified estuaries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study

PubMed Central

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; DeFelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-01-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm3 from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented. PMID:23365213

Three-dimensional spatial distribution of synapses in the neocortex: a dual-beam electron microscopy study.

PubMed

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; Defelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-06-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm(3) from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented.

Analysis of spatial distribution and transmission characters for highly pathogenic avian influenza in Chinese mainland in 2004

NASA Astrophysics Data System (ADS)

Liu, Y. L.; Wei, C. J.; Yan, L.; Chi, T. H.; Wu, X. B.; Xiao, C. S.

2006-03-01

After the outbreak of highly pathogenic Avian Influenza (HPAI) in South Korea in the end of year 2003, estimates of the impact of HPAI in affected countries vary greatly, the total direct losses are about 3 billion US dollars, and it caused 15 million birds and poultry flocks death. It is significant to understand the spatial distribution and transmission characters of HPAI for its prevention and control. According to 50 outbreak cases for HPAI in Chinese mainland during 2004, this paper introduces the approach of spatial distribution and transmission characters for HPAI and its results. Its approach is based on remote sensing and GIS techniques. Its supporting data set involves normalized difference vegetation index (NDVI) and land surface temperature (Ts) derived from a time-series of remote sensing data of 1 kilometer-resolution NOAA/AVHRR, birds' migration routes, topology geographic map, lake and wetland maps, and meteorological observation data. In order to analyze synthetically using these data, a supporting platform for analysis Avian Influenza epidemic situation (SPAS/AI) was developed. Supporting by SPAS/AI, the integrated information from multi-sources can be easily used to the analysis of the spatial distribution and transmission character of HPAI. The results show that the range of spatial distribution and transmission of HPAI in China during 2004 connected to environment factors NDVI, Ts and the distributions of lake and wetland, and especially to bird migration routes. To some extent, the results provide some suggestions for the macro-decision making for the prevention and control of HPAI in the areas of potential risk and reoccurrence.

The relationship between extreme precipitation events and landslides distributions in 2009 in Lower Austria

NASA Astrophysics Data System (ADS)

Katzensteiner, H.; Bell, R.; Petschko, H.; Glade, T.

2012-04-01

The prediction and forecast of widespread landsliding for a given triggering event is an open research question. Numerous studies tried to link spatial rainfall and landslide distributions. This study focuses on analysing the relationship between intensive precipitation and rainfall-triggered shallow landslides in the year 2009 in Lower Austria. Landslide distributions were gained from the building ground register, which is maintained by the Geological Survey of Lower Austria. It contains detailed information of landslides, which were registered due to damage reports. Spatially distributed rainfall estimates were extracted from INCA (Integrated Nowcasting through Comprehensive Analysis) precipitation analysis, which is a combination of station data interpolation and radar data in a spatial resolution of 1km developed by the Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria. The importance of the data source is shown by comparing rainfall data based on reference gauges, spatial interpolation and INCA-analysis for a certain storm period. INCA precipitation data can detect precipitating cells that do not hit a station but might trigger a landslide, which is an advantage over the application of reference stations for the definition of rainfall thresholds. Empirical thresholds at regional scale were determined based on rainfall-intensity and duration in the year 2009 and landslide information. These thresholds are dependent on the criteria which separate the landslide triggering and non-triggering precipitation events from each other. Different approaches for defining thresholds alter the shape of the threshold as well. A temporarily threshold I=8,8263*D^(-0.672) for extreme rainfall events in summer in Lower Austria was defined. A verification of the threshold with similar events of other years as well as following analyses based on a larger landslide database are in progress.

Synchrotron-based X-ray fluorescence microscopy enables multiscale spatial visualization of ions involved in fungal lignocellulose deconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirker, Grant; Zelinka, Sam; Gleber, Sophie -Charlotte

Ions play an important role in the growth and development of filamentous fungi, particularly in the fungal decay process of lignocellulose materials. The role of ions in wood degradation, and more broadly fungal metabolism, have implications for diverse research disciplines ranging from plant pathology and forest ecology, to wood protection. Despite the importance of ions in both enzymatic and non-enzymatic fungal decay mechanisms, the spatial distribution of ions in wood and fungal hyphae during decay is not known. Here we employ synchrotron based X-ray fluorescence microscopy (XFM) to map physiologically relevant ions, such as K, Ca, Mn, Fe, and Zn,more » in wood being decayed by the model brown rot fungus Serpula lacrymans. Two-dimensional XFM maps were obtained to study the ion spatial distributions from mm to submicron length scales in wood and hyphae. Three-dimensional ion volume reconstructions with submicron spatial resolution were also acquired of wood cell walls and fungal hyphae, and an estimation of oxalate concentration at the microscale was made. Results show that the fungus actively transports some ions, such as Fe, into the wood and controls the distribution of ions at both the bulk wood and cellular length scales. Within the fungal hyphae, ion volume reconstructions show inhomogeneous ion distributions at the micron length scale and this localization may be indicative of both physiological status and requirements or in some cases, potentially sites associated with the initiation of metal-catalyzed wood degradation. Finally, these measurements illustrate how synchrotron based XFM is uniquely qualified for probing the role of ions in the growth and metabolic processes of filamentous fungi.« less

Synchrotron-based X-ray fluorescence microscopy enables multiscale spatial visualization of ions involved in fungal lignocellulose deconstruction

DOE PAGES

Kirker, Grant; Zelinka, Sam; Gleber, Sophie -Charlotte; ...

2017-01-31

Ions play an important role in the growth and development of filamentous fungi, particularly in the fungal decay process of lignocellulose materials. The role of ions in wood degradation, and more broadly fungal metabolism, have implications for diverse research disciplines ranging from plant pathology and forest ecology, to wood protection. Despite the importance of ions in both enzymatic and non-enzymatic fungal decay mechanisms, the spatial distribution of ions in wood and fungal hyphae during decay is not known. Here we employ synchrotron based X-ray fluorescence microscopy (XFM) to map physiologically relevant ions, such as K, Ca, Mn, Fe, and Zn,more » in wood being decayed by the model brown rot fungus Serpula lacrymans. Two-dimensional XFM maps were obtained to study the ion spatial distributions from mm to submicron length scales in wood and hyphae. Three-dimensional ion volume reconstructions with submicron spatial resolution were also acquired of wood cell walls and fungal hyphae, and an estimation of oxalate concentration at the microscale was made. Results show that the fungus actively transports some ions, such as Fe, into the wood and controls the distribution of ions at both the bulk wood and cellular length scales. Within the fungal hyphae, ion volume reconstructions show inhomogeneous ion distributions at the micron length scale and this localization may be indicative of both physiological status and requirements or in some cases, potentially sites associated with the initiation of metal-catalyzed wood degradation. Finally, these measurements illustrate how synchrotron based XFM is uniquely qualified for probing the role of ions in the growth and metabolic processes of filamentous fungi.« less

Judging The Effectiveness Of Wool Combing By The Entropy Of The Images Of Wool Slivers

NASA Astrophysics Data System (ADS)

Rodrigues, F. Carvalho; Carvalho, Fernando D.; Peixoto, J. Pinto; Silva, M. Santos

1989-04-01

In general it can be said that the textile industry endeavours to render a bunch of fibers chaotically distributed in space into an ordered spatial distribution. This fact is independent of the nature the fibers, i.e., the aim of getting into higher order states in the spatial distribution of the fibers dictates different industrial processes depending on whether the fibers are wool, cotton or man made but the all effect is centred on obtaining at every step of any of the processes a more ordered state regarding the spatial distribution of the fibers. Thinking about the textile processes as a method of getting order out of chaos, the concept of entropy appears as the most appropriate judging parameter on the effectiveness of a step in the chain of an industrial process to produce a regular textile. In fact, entropy is the hidden parameter not only for the textile industry but also for the non woven and paper industrial processes. It happens that in these industries the state of order is linked with the spatial distribution of fibers and to obtain an image of a spatial distribution is an easy matter. To compute the image entropy from the grey level distribution requires only the use of the Shannon formula. In this paper to illustrate the usefulness of employing the entropy of an image concept to textiles the evolution of the entropy of wool slivers along the combing process is matched against the state of parallelization of the fibbers along the seven steps as measured by the existing method. The advantages of the entropy method over the previous method based on diffraction is also demonstrated.

Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

NASA Astrophysics Data System (ADS)

Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.

2011-12-01

A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

PubMed Central

Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J

2009-01-01

Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme.

PubMed

Espinosa, Manuel O; Polop, Francisco; Rotela, Camilo H; Abril, Marcelo; Scavuzzo, Carlos M

2016-11-21

The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Analysis of the spatial and temporal distribution of malaria in an area of Northern Guatemala with seasonal malaria transmission.

PubMed

Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J

2018-06-23

The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.

Spatial and temporal disaggregation of the on-road vehicle emission inventory in a medium-sized Andean city. Comparison of GIS-based top-down methodologies

NASA Astrophysics Data System (ADS)

Gómez, C. D.; González, C. M.; Osses, M.; Aristizábal, B. H.

2018-04-01

Emission data is an essential tool for understanding environmental problems associated with sources and dynamics of air pollutants in urban environments, especially those emitted from vehicular sources. There is a lack of knowledge about the estimation of air pollutant emissions and particularly its spatial and temporal distribution in South America, mainly in medium-sized cities with population less than one million inhabitants. This work performed the spatial and temporal disaggregation of the on-road vehicle emission inventory (EI) in the medium-sized Andean city of Manizales, Colombia, with a spatial resolution of 1 km × 1 km and a temporal resolution of 1 h. A reported top-down methodology, based on the analysis of traffic flow levels and road network distribution, was applied. Results obtained allowed the identification of several hotspots of emission at the downtown zone and the residential and commercial area of Manizales. Downtown exhibited the highest percentage contribution of emissions normalized by its total area, with values equal to 6% and 5% of total CO and PM10 emissions per km2 respectively. These indexes were higher than those obtained in residential-commercial area with values of 2%/km2 for both pollutants. Temporal distribution showed strong relationship with driving patterns at rush hours, as well as an important influence of passenger cars and motorcycles in emissions of CO both at downtown and residential-commercial areas, and the impact of public transport in PM10 emissions in the residential-commercial zone. Considering that detailed information about traffic counts and road network distribution is not always available in medium-sized cities, this work compares other simplified top-down methods for spatially assessing the on-road vehicle EI. Results suggested that simplified methods could underestimate the spatial allocation of downtown emissions, a zone dominated by high traffic of vehicles. The comparison between simplified methods based on total traffic counts and road density distribution suggested that the use of total traffic counts in a simplified form could enhance higher uncertainties in the spatial disaggregation of emissions. Results obtained could add new information that help to improve the air pollution management system in the city and contribute to local public policy decisions. Additionally, this work provides appropriate resolution emission fluxes for ongoing research in atmospheric modeling in the city, with the aim to improve the understanding of transport, transformation and impacts of pollutant emissions in urban air quality.

Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

NASA Astrophysics Data System (ADS)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional validation on spatial results was done for the groundwater head values at observation wells. To ensure that the lumped model can produce results as accurate as the spatially distributed models or close regardless to the number of parameters and implemented physical processes, it was checked whether the structure of the lumped models had to be adjusted. The concept has been implemented in a PCRaster - Python platform and tested for two Belgian case studies (catchments of the rivers Dijle and Grote Nete). So far, use is made of existing model structures (NAM, PDM, VHM and HBV). Acknowledgement: These results were obtained within the scope of research activities for the Flemish Environment Agency (VMM) - division Operational Water Management on "Next Generation hydrological modeling", in cooperation with IMDC consultants, and for Flanders Hydraulics Research (Waterbouwkundig Laboratorium) on "Effect of climate change on the hydrological regime of navigable watercourses in Belgium".

Spatial mode discriminator based on leaky waveguides

NASA Astrophysics Data System (ADS)

Xu, Jing; Liu, Jialing; Shi, Hongkang; Chen, Yuntian

2018-06-01

We propose a conceptually simple and experimentally compatible configuration to discriminate the spatial mode based on leaky waveguides, which are inserted in-between the transmission link. The essence of such a spatial mode discriminator is to introduce the leakage of the power flux on purpose for detection. Importantly, the leaky angle of each individual spatial mode with respect to the propagation direction are different for non-degenerated modes, while the radiation patterns of the degenerated spatial modes in the plane perpendicular to the propagation direction are also distinguishable. Based on these two facts, we illustrate the operation principle of the spatial mode discriminators via two concrete examples; a w-type slab leaky waveguide without degeneracy, and a cylindrical leaky waveguide with degeneracy. The correlation between the leakage angle and the spatial mode distribution for a slab leaky waveguide, as well as differences between the in-plane radiation patterns of degenerated modes in a cylindrical leaky waveguide, are verified numerically and analytically. Such findings can be readily useful in discriminating the spatial modes for optical communication or optical sensing.

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.

2014-10-07

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Spatial distribution of cutaneous leishmaniasis in the state of Paraná, Brazil.

PubMed

Melo, Helen Aline; Rossoni, Diogo Francisco; Teodoro, Ueslei

2017-01-01

The geographic distribution of cutaneous leishmaniasis (CL) makes it a disease of major clinical importance in Brazil, where it is endemic in the state of Paraná. The objective of this study was to analyze the spatial distribution of CL in Paraná between 2001 and 2015, based on data from the Sistema de Informação de Agravos de Notificação (Information System for Notifiable Diseases) regarding autochthonous CL cases. Spatial autocorrelation was performed using Moran's Global Index and the Local Indicator of Spatial Association (LISA). The construction of maps was based on categories of association (high-high, low-low, high-low, and low-high). A total of 4,557 autochthonous cases of CL were registered in the state of Paraná, with an annual average of 303.8 (± 135.2) and a detection coefficient of 2.91. No correlation was found between global indices and their respective significance in 2001 (I = -0.456, p = 0.676), but evidence of spatial autocorrelation was found in other years (p< 0.05). In the construction and analysis of the cluster maps, areas with a high-high positive association were found in the Ivaí-Pirapó, Tibagi, Cinzas-Laranjinha, and Ribeira areas. The state of Paraná should keep a constant surveillance over CL due to the prominent presence of socioeconomic and environmental factors such as the favorable circumstances for the vectors present in peri-urban and agriculture áreas.

Spatial distribution of cutaneous leishmaniasis in the state of Paraná, Brazil

PubMed Central

2017-01-01

The geographic distribution of cutaneous leishmaniasis (CL) makes it a disease of major clinical importance in Brazil, where it is endemic in the state of Paraná. The objective of this study was to analyze the spatial distribution of CL in Paraná between 2001 and 2015, based on data from the Sistema de Informação de Agravos de Notificação (Information System for Notifiable Diseases) regarding autochthonous CL cases. Spatial autocorrelation was performed using Moran’s Global Index and the Local Indicator of Spatial Association (LISA). The construction of maps was based on categories of association (high-high, low-low, high-low, and low-high). A total of 4,557 autochthonous cases of CL were registered in the state of Paraná, with an annual average of 303.8 (± 135.2) and a detection coefficient of 2.91. No correlation was found between global indices and their respective significance in 2001 (I = -0.456, p = 0.676), but evidence of spatial autocorrelation was found in other years (p< 0.05). In the construction and analysis of the cluster maps, areas with a high-high positive association were found in the Ivaí-Pirapó, Tibagi, Cinzas-Laranjinha, and Ribeira areas. The state of Paraná should keep a constant surveillance over CL due to the prominent presence of socioeconomic and environmental factors such as the favorable circumstances for the vectors present in peri-urban and agriculture áreas. PMID:28938013

GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation.

PubMed

Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie

2012-01-17

We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.

Development of a distributed air pollutant dry deposition modeling framework

Treesearch

Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

2012-01-01

A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

PubMed

Dankers, Frank; Wijsman, Robin; Troost, Esther G C; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L

2017-05-07

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy

NASA Astrophysics Data System (ADS)

Dankers, Frank; Wijsman, Robin; Troost, Esther G. C.; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L.

2017-05-01

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Adaptive proxy map server for efficient vector spatial data rendering

NASA Astrophysics Data System (ADS)

Sayar, Ahmet

2013-01-01

The rapid transmission of vector map data over the Internet is becoming a bottleneck of spatial data delivery and visualization in web-based environment because of increasing data amount and limited network bandwidth. In order to improve both the transmission and rendering performances of vector spatial data over the Internet, we propose a proxy map server enabling parallel vector data fetching as well as caching to improve the performance of web-based map servers in a dynamic environment. Proxy map server is placed seamlessly anywhere between the client and the final services, intercepting users' requests. It employs an efficient parallelization technique based on spatial proximity and data density in case distributed replica exists for the same spatial data. The effectiveness of the proposed technique is proved at the end of the article by the application of creating map images enriched with earthquake seismic data records.

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

Mapping snow depth distribution in forested terrain using unmanned aerial vehicles and structure-from-motion

NASA Astrophysics Data System (ADS)

Webster, C.; Bühler, Y.; Schirmer, M.; Stoffel, A.; Giulia, M.; Jonas, T.

2017-12-01

Snow depth distribution in forests exhibits strong spatial heterogeneity compared to adjacent open sites. Measurement of snow depths in forests is currently limited to a) manual point measurements, which are sparse and time-intensive, b) ground-penetrating radar surveys, which have limited spatial coverage, or c) airborne LiDAR acquisition, which are expensive and may deteriorate in denser forests. We present the application of unmanned aerial vehicles in combination with structure-from-motion (SfM) methods to photogrammetrically map snow depth distribution in forested terrain. Two separate flights were carried out 10 days apart across a heterogeneous forested area of 900 x 500 m. Corresponding snow depth maps were derived using both, LiDAR-based and SfM-based DTM data, obtained during snow-off conditions. Manual measurements collected following each flight were used to validate the snow depth maps. Snow depths were resolved at 5cm resolution and forest snow depth distribution structures such as tree wells and other areas of preferential melt were represented well. Differential snow depth maps showed maximum ablation in the exposed south sides of trees and smaller differences in the centre of gaps and on the north side of trees. This new application of SfM to map snow depth distribution in forests demonstrates a straightforward method for obtaining information that was previously only available through manual spatially limited ground-based measurements. These methods could therefore be extended to more frequent observation of snow depths in forests as well as estimating snow accumulation and depletion rates.

The spatial distribution of gender differences in obesity prevalence differs from overall obesity prevalence among US adults.

PubMed

Gartner, Danielle R; Taber, Daniel R; Hirsch, Jana A; Robinson, Whitney R

2016-04-01

Although obesity disparities between racial and socioeconomic groups have been well characterized, those based on gender and geography have not been as thoroughly documented. This study describes obesity prevalence by state, gender, and race and/or ethnicity to (1) characterize obesity gender inequality, (2) determine if the geographic distribution of inequality is spatially clustered, and (3) contrast the spatial clustering patterns of obesity gender inequality with overall obesity prevalence. Data from the Centers for Disease Control and Prevention's 2013 Behavioral Risk Factor Surveillance System were used to calculate state-specific obesity prevalence and gender inequality measures. Global and local Moran's indices were calculated to determine spatial autocorrelation. Age-adjusted, state-specific obesity prevalence difference and ratio measures show spatial autocorrelation (z-score = 4.89, P-value < .001). Local Moran's indices indicate the spatial distributions of obesity prevalence and obesity gender inequalities are not the same. High and low values of obesity prevalence and gender inequalities cluster in different areas of the United States. Clustering of gender inequality suggests that spatial processes operating at the state level, such as occupational or physical activity policies or social norms, are involved in the etiology of the inequality and necessitate further attention to the determinates of obesity gender inequality. Copyright © 2016 Elsevier Inc. All rights reserved.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.

The Not So Simple Globular Cluster ω Cen. I. Spatial Distribution of the Multiple Stellar Populations

NASA Astrophysics Data System (ADS)

Calamida, A.; Strampelli, G.; Rest, A.; Bono, G.; Ferraro, I.; Saha, A.; Iannicola, G.; Scolnic, D.; James, D.; Smith, C.; Zenteno, A.

2017-04-01

We present a multi-band photometric catalog of ≈1.7 million cluster members for a field of view of ≈2° × 2° across ω Cen. Photometry is based on images collected with the Dark Energy Camera on the 4 m Blanco telescope and the Advanced Camera for Surveys on the Hubble Space Telescope. The unprecedented photometric accuracy and field coverage allowed us, for the first time, to investigate the spatial distribution of ω Cen multiple populations from the core to the tidal radius, confirming its very complex structure. We found that the frequency of blue main-sequence stars is increasing compared to red main-sequence stars starting from a distance of ≈25‧ from the cluster center. Blue main-sequence stars also show a clumpy spatial distribution, with an excess in the northeast quadrant of the cluster pointing toward the direction of the Galactic center. Stars belonging to the reddest and faintest red-giant branch also show a more extended spatial distribution in the outskirts of ω Cen, a region never explored before. Both these stellar sub-populations, according to spectroscopic measurements, are more metal-rich compared to the cluster main stellar population. These findings, once confirmed, make ω Cen the only stellar system currently known where metal-rich stars have a more extended spatial distribution compared to metal-poor stars. Kinematic and chemical abundance measurements are now needed for stars in the external regions of ω Cen to better characterize the properties of these sub-populations. Based on observations made with the Dark Energy Camera (DECam) on the 4 m Blanco telescope (NOAO) under programs 2014A-0327, 2015A-0151, 2016A-0189, PIs: A. Calamida, A. Rest, and on observations made with the NASA/ESA Hubble Space Telescope, obtained by the Space Telescope Science Institute. STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires

PubMed Central

Russo, Lucia; Russo, Paola; Siettos, Constantinos I.

2016-01-01

Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire. PMID:27780249

A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

PubMed

Russo, Lucia; Russo, Paola; Siettos, Constantinos I

2016-01-01

Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.

Research on mixed network architecture collaborative application model

NASA Astrophysics Data System (ADS)

Jing, Changfeng; Zhao, Xi'an; Liang, Song

2009-10-01

When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.

Seasonal Differences in Spatial Scales of Chlorophyll-A Concentration in Lake TAIHU，CHINA

NASA Astrophysics Data System (ADS)

Bao, Y.; Tian, Q.; Sun, S.; Wei, H.; Tian, J.

2012-08-01

Spatial distribution of chlorophyll-a (chla) concentration in Lake Taihu is non-uniform and seasonal variability. Chla concentration retrieval algorithms were separately established using measured data and remote sensing images (HJ-1 CCD and MODIS data) in October 2010, March 2011, and September 2011. Then parameters of semi- variance were calculated on the scale of 30m, 250m and 500m for analyzing spatial heterogeneity in different seasons. Finally, based on the definitions of Lumped chla (chlaL) and Distributed chla (chlaD), seasonal model of chla concentration scale error was built. The results indicated that: spatial distribution of chla concentration in spring was more uniform. In summer and autumn, chla concentration in the north of the lake such as Meiliang Bay and Zhushan Bay was higher than that in the south of Lake Taihu. Chla concentration on different scales showed the similar structure in the same season, while it had different structure in different seasons. And inversion chla concentration from MODIS 500m had a greater scale error. The spatial scale error changed with seasons. It was higher in summer and autumn than that in spring. The maximum relative error can achieve 23%.

Spatial Distribution and Secular Variation of Geomagnetic Filed in China Described by the CHAOS-6 Model and its Error Analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Gu, Z.; Chen, B.; Yuan, J.; Wang, C.

2016-12-01

The CHAOS-6 geomagnetic field model, presented in 2016 by the Denmark's national space institute (DTU Space), is a model of the near-Earth magnetic field. According the CHAOS-6 model, seven component data of geomagnetic filed at 30 observatories in China in 2015 and at 3 observatories in China spanning the time interval 2008.0-2016.5 were calculated. Also seven component data of geomagnetic filed from the geomagnetic data of practical observations in China was obtained. Based on the model calculated data and the practical data, we have compared and analyzed the spatial distribution and the secular variation of the geomagnetic field in China. There is obvious difference between the two type data. The CHAOS-6 model cannot describe the spatial distribution and the secular variation of the geomagnetic field in China with comparative precision because of the regional and local magnetic anomalies in China.

Spatially resolved, in situ potential measurements through porous electrodes as applied to fuel cells.

PubMed

Hess, Katherine C; Epting, William K; Litster, Shawn

2011-12-15

We report the development and use of a microstructured electrode scaffold (MES) to make spatially resolved, in situ, electrolyte potential measurements through the thickness of a polymer electrolyte fuel cell (PEFC) electrode. This new approach uses a microfabricated apparatus to analyze the coupled transport and electrochemical phenomena in porous electrodes at the microscale. In this study, the MES allows the fuel cell to run under near-standard operating conditions, while providing electrolyte potential measurements at discrete distances through the electrode's thickness. Here we use spatial distributions of electrolyte potential to evaluate the effects of Ohmic and mass transport resistances on the through-plane reaction distribution for various operating conditions. Additionally, we use the potential distributions to estimate the ionic conductivity of the electrode. Our results indicate the in situ conductivity is higher than typically estimated for PEFC electrodes based on bulk polymer electrolyte membrane (PEM) conductivity.

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Assessment of Regional Explosion Discriminants Using Data Sets of Unparalleled Spatial Sampling

DTIC Science & Technology

2012-10-31

Air Force Research Laboratory AFRL ...Final Report APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED. AIR FORCE RESEARCH LABORATORY Space Vehicles...Directorate 3550 Aberdeen Ave SE AIR FORCE MATERIEL COMMAND KIRTLAND AIR FORCE BASE, NM 87117-5776 Approved for public release; distribution

Spatial Relationships of Sector-Specific Fossil-fuel CO2 Emissions in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yuyu; Gurney, Kevin R.

2011-07-01

Quantification of the spatial distribution of sector-specific fossil fuel CO2 emissions provides strategic information to public and private decision-makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO2 emissions differ substantially and these differences are sector-specific. Area-based sources such as those in the residential and commercial sectors are drivenmore » by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO2 emissions confirms that counties with high (low) CO2 emissions tend to be clustered close to other counties with high (low) CO2 emissions and some of the spatial clustering extends to multi-state spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multi-state perspective. Our findings underscore the potential for geographically focused, sector-specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements. Keywords: Fossil-fuel; Carbon dioxide emissions; Sectoral; Spatial cluster; Emissions mitigation policy« less

Modeling pluvial flooding damage in urban environments: spatial relationships between citizens' complaints and overland catchment areas

NASA Astrophysics Data System (ADS)

Gaitan, Santiago; ten Veldhuis, Marie-Claire; van de Giesen, Nick

2013-04-01

Extreme weather events such as floods and storms are expected to cause severe economic losses in The Netherlands. Cumulative damage due to pluvial flooding can be considerable, especially in lowland areas where this type of floods occurs relatively frequently. Currently, in The Netherlands, water-related damages to property and contents are covered through private insurance. As pluvial flooding is becoming heavier and more likely to occur, sound modelling of damages is required to ensure that insurance systems are able to stand as an adaptation measure. Current damage models based on rainfall intensity, registries of insurance claims, and classifications of building types are unable to fully explain damage variability. Further developments assessing additional explanatory factors and reducing uncertainties, are required in order to significantly explain damage. In this study, urban topography is used as an explanatory factor for modelling of urban pluvial flooding. Flood damage is evaluated based on complaints data, a valuable resource for assessing vulnerability to urban pluvial flooding. Though previous research has shown coincidences between the localization of high complaint counts and large size catchments areas in Rotterdam, additional research is needed to establish the precise spatial relationship of those two variables. This additional task is the focus of the presented work. To that end a data base of complaints, that was made available by the Municipality Administration of the City, will be analysed. It comprises close to 36800 complaints from 2004 to 2011. The geographical position of the registries is aggregated into 4 to 6-digit Postal Code zones, which represents entire streets or relative positions along a street, respectively. The Municipality also provided the DEM, characterized by a spatial resolution of 0.5 m × 0.5 m, a vertical precision of 5 cm, and an accuracy better than two standard deviations of 15 cm. First the localization of complaints will be tested for spatial randomness: the distribution of Global Moran's I will be used as a measure of spatial aggregation of complaints. We expect high values of spatial aggregation, that would confirm the existence of a spatial structure in the distribution of complaints. Then we will probe how much does the extent of catchment areas influence such distribution of complaints. That will be done through both an ordinary least squares regression and a geographically weighted regression. By contrasting the results from these two regressions, the relationship between complaints and size of catchment area across the urban environment will be evaluated. The results will confirm whether complaints have a spatial distribution pattern. Furthermore, the results will provide insight into the importance of the size of catchment areas as a significant factor for complaints distribution, and for the assessment of urban vulnerability to pluvial flooding in the City of Rotterdam.

EVALUATION OF IN SITU COSOLVENT FLUSHING DYNAMICS USING A NETWORK OF SPATIALLY DISTRIBUTED MULTILEVEL SAMPLERS

EPA Science Inventory

A network of multilevel samplers was used to evaluate the spatial patterns in containment extraction during an in situ cosolvent flushing field test. The study was conducted in an isolation test cell installed in a fuel contaminated site at Hill Air Force Base, Utah. Partitioni...

Geostatistical Evaluation of Natural Tree Regeneration of a Disturbed Forest

Treesearch

José Germán Flores Garnica; David Arturo Moreno Gonzalez; Juan de Dios Benavides Solorio

2006-01-01

The implementation of silvicultural strategies in a forest management has to guaranty forest sustainability, which is supported by an adequate regeneration. Therefore, quality and intensity of silvicultural practices is based on an accurate knowledge of the current spatial distribution of regeneration. At the same time, this regeneration is determined by the spatial...

[Spatial distribution characteristics of China cotton fiber quality and climatic factors based on GIS].

PubMed

Xiong, Zong-Wei; Gu, Sheng-Hao; Mao, Li-Li; Wang, Xue-Jiao; Zhang, Li-Zhen; Zhou, Zhi-Guo

2012-12-01

By using geographical information system (GIS), the cotton fiber quality data from 2005 to 2011 and the daily meteorological data from 1981 to 2010 at 82 sites (counties and cities) in China major cotton production regions were collected and treated with spatial interpolation. The spatial information system of cotton fiber quality in China major cotton production regions was established based on GIS, and the spatial distribution characteristics of the cotton fiber quality and their relationships with the local climatic factors were analyzed. In the northwest region (especially Xinjiang) of China, due to the abundant sunlight, low precipitation, and low relative humidity, the cotton fiber length, micronaire, and grade ranked the first. In the Yangtze River region and Yellow River region, the specific strength of cotton fiber was higher, and in the Yangtze River region, the cotton fiber length and specific strength were higher, while the micronaire and grade were lower than those in the Yellow River region. The cotton fiber quality was closely related to the climate factors such as temperature, sunlight, rainfall, and humidity.

Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems

PubMed Central

Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas

2015-01-01

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892

Synchrotron-based X-ray fluorescence microscopy enables multiscale spatial visualization of ions involved in fungal lignocellulose deconstruction

NASA Astrophysics Data System (ADS)

Kirker, Grant; Zelinka, Sam; Gleber, Sophie-Charlotte; Vine, David; Finney, Lydia; Chen, Si; Hong, Young Pyo; Uyarte, Omar; Vogt, Stefan; Jellison, Jody; Goodell, Barry; Jakes, Joseph E.

2017-01-01

The role of ions in the fungal decay process of lignocellulose biomaterials, and more broadly fungal metabolism, has implications for diverse research disciplines ranging from plant pathology and forest ecology, to carbon sequestration. Despite the importance of ions in fungal decay mechanisms, the spatial distribution and quantification of ions in lignocellulosic cell walls and fungal hyphae during decay is not known. Here we employ synchrotron-based X-ray fluorescence microscopy (XFM) to map and quantify physiologically relevant ions, such as K, Ca, Mn, Fe, and Zn, in wood being decayed by the model brown rot fungus Serpula lacrymans. Two-dimensional XFM maps were obtained to study the ion spatial distributions from mm to submicron length scales in wood, fungal hyphae with the dried extracellular matrix (ECM) from the fungus, and Ca oxalate crystals. Three-dimensional ion volume reconstructions were also acquired of wood cell walls and hyphae with ECM. Results show that the fungus actively transports some ions, such as Fe, into the wood and controls the distribution of ions at both the bulk wood and cell wall length scales. These measurements provide new insights into the movement of ions during decay and illustrate how synchrotron-based XFM is uniquely suited study these ions.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Distributed fiber optic vibration sensor with enhanced response bandwidth and high signal-to-noise ratio

NASA Astrophysics Data System (ADS)

Chen, Dian; Liu, Qingwen; Fan, Xinyu; He, Zuyuan

2017-04-01

A novel distributed fiber-optic vibration sensor (DVS) is proposed based on multi-pulse time-gated digital optical frequency domain reflectometry (TGD-OFDR), which can solve both the trade-off between the maximum measurable distance and the spatial resolution, and the one between the measurement distance and the vibration response bandwidth. A 21-kHz vibration is detected experimentally over 10-kilometer-long fiber, with a signal-to-noise ratio approaching 25 dB and a spatial resolution of 10 m.

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

NASA Astrophysics Data System (ADS)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi-precision information assimilation method of other geotechnical parameters.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751 - 2008) (V. 2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Boden, T. A. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Marland, G. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.

2012-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2008.html) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751 - 2009) (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marlad, Greg [Appalachian State University, Boone, NC (USA)

2012-01-01

The annual, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1751-2009 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2012) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2015-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2011.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Relative impacts of the fragmentation and spatial structure of habitats on freshwater fish distributions: application on French watersheds (Invited)

NASA Astrophysics Data System (ADS)

Le Pichon, C.; Belliard, J.; Talès, E.; Gorges, G.; Clément, F.

2009-12-01

Most of the rivers of the Ile de France region, intimately linked with the megalopolis of Paris, are severely altered and freshwater fishes are exposed to habitat alteration, reduced connectivity and pollution. Several species thus present fragmented distributions and decreasing densities. In this context, the European Water Framework Directive (2000) has goals of hydrosystems rehabilitation and no further damage. In particular, the preservation and restoration of ecological connectivity of river networks is a key element for fish populations. These goals require the identification of natural and anthropological factors which influence the spatial distribution of species. We have proposed a riverscape approach, based on landscape ecology concepts, combined with a set of spatial analysis methods to assess the multiscale relationships between the spatial pattern of fish habitats and processes depending on fish movements. In particular, we used this approach to test the relative roles of spatial arrangement of fish habitats and the presence of physical barriers in explaining fish spatial distributions in a small rural watershed (106 km2). We performed a spatially continuous analysis of fish-habitat relationships. Fish habitats and physical barriers were mapped along the river network (33 km) with a GPS and imported into a GIS. In parallel, a longitudinal electrofishing survey of the distribution and abundance of fishes was made using a point abundance sampling scheme. Longitudinal arrangement of fish habitats were evaluated using spatial analysis methods: patch/distance metrics and moving window analysis. Explanatory models were developed to test the relative contribution of local environmental variables and spatial context in explaining fish presence. We have recorded about 100 physical barriers, on average one every 330 meters; most artificial barriers were road pipe culverts, falls associated with ponds and sluice gates. Contrasted fish communities and densities were observed in the different areas of the watershed, related to various land use (riparian forest or agriculture). The first results of fish-habitat association analysis on a 5 km stream are that longitudinal distribution of fish species was mainly impacted by falls associated with ponds. The impact was both due to the barrier effect and to the modification of aquatic habitats. Abundance distribution of Salmo trutta and Cottus gobio was particularly affected. Spatially continuous analysis of fish-habitat relationships allowed us to identify the relative impacts of habitat alteration and presence of physical barriers to fish movements. These techniques could help prioritize preservation and restoration policies in human-impacted watersheds, in particular, identifying the key physical barriers to remove.

Spatial Distribution and Relationship of T1ρ and T2 Relaxation Times in Knee Cartilage With Osteoarthritis

PubMed Central

Li, Xiaojuan; Pai, Alex; Blumenkrantz, Gabrielle; Carballido-Gamio, Julio; Link, Thomas; Ma, Benjamin; Ries, Michael; Majumdar, Sharmila

2009-01-01

T1ρ and T2 relaxation time constants have been proposed to probe biochemical changes in osteoarthritic cartilage. This study aimed to evaluate the spatial correlation and distribution of T1ρ and T2 values in osteoarthritic cartilage. Ten patients with osteoarthritis (OA) and 10 controls were studied at 3T. The spatial correlation of T1ρ and T2 values was investigated using Z-scores. The spatial variation of T1ρ and T2 values in patellar cartilage was studied in different cartilage layers. The distribution of these relaxation time constants was measured using texture analysis parameters based on gray-level co-occurrence matrices (GLCM). The mean Z-scores for T1ρ and T2 values were significantly higher in OA patients vs. controls (P < 0.05). Regional correlation coefficients of T1ρ and T2 Z-scores showed a large range in both controls and OA patients (0.2– 0.7). OA patients had significantly greater GLCM contrast and entropy of T1ρ values than controls (P < 0.05). In summary, T1ρ and T2 values are not only increased but are also more heterogeneous in osteoarthritic cartilage. T1ρ and T2 values show different spatial distributions and may provide complementary information regarding cartilage degeneration in OA. PMID:19319904

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

PubMed Central

Yin, Wenwu; Yu, Hongjie; Si, Yali; Li, Jianhui; Zhou, Yuanchun; Zhou, Xiaoyan; Magalhães, Ricardo J. Soares.

2013-01-01

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program. PMID:23991098

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data.

PubMed

Wijetunge, Chalini D; Saeed, Isaam; Boughton, Berin A; Spraggins, Jeffrey M; Caprioli, Richard M; Bacic, Antony; Roessner, Ute; Halgamuge, Saman K

2015-10-01

Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in 'omics' data acquisition generates detailed information about the spatial distribution of molecules in a given biological sample. Various data processing methods have been developed for exploring the resultant high volume data. However, most of these methods process data in the spectral domain and do not make the most of the important spatial information available through this technology. Therefore, we propose a novel streamlined data analysis pipeline specifically developed for MALDI-IMS data utilizing significant spatial information for identifying hidden significant molecular distribution patterns in these complex datasets. The proposed unsupervised algorithm uses Sliding Window Normalization (SWN) and a new spatial distribution based peak picking method developed based on Gray level Co-Occurrence (GCO) matrices followed by clustering of biomolecules. We also use gist descriptors and an improved version of GCO matrices to extract features from molecular images and minimum medoid distance to automatically estimate the number of possible groups. We evaluated our algorithm using a new MALDI-IMS metabolomics dataset of a plant (Eucalypt) leaf. The algorithm revealed hidden significant molecular distribution patterns in the dataset, which the current Component Analysis and Segmentation Map based approaches failed to extract. We further demonstrate the performance of our peak picking method over other traditional approaches by using a publicly available MALDI-IMS proteomics dataset of a rat brain. Although SWN did not show any significant improvement as compared with using no normalization, the visual assessment showed an improvement as compared to using the median normalization. The source code and sample data are freely available at http://exims.sourceforge.net/. awgcdw@student.unimelb.edu.au or chalini_w@live.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2016-12-01

Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content

Microscale soil structure development after glacial retreat - using machine-learning based segmentation of elemental distributions obtained by NanoSIMS

NASA Astrophysics Data System (ADS)

Schweizer, Steffen; Schlueter, Steffen; Hoeschen, Carmen; Koegel-Knabner, Ingrid; Mueller, Carsten W.

2017-04-01

Soil organic matter (SOM) is distributed on mineral surfaces depending on physicochemical soil properties that vary at the submicron scale. Nanoscale secondary ion mass spectrometry (NanoSIMS) can be used to visualize the spatial distribution of up to seven elements simultaneously at a lateral resolution of approximately 100 nm from which patterns of SOM coatings can be derived. Existing computational methods are mostly confined to visualization and lack spatial quantification measures of coverage and connectivity of organic matter coatings. This study proposes a methodology for the spatial analysis of SOM coatings based on supervised pixel classification and automatic image analysis of the 12C, 12C14N (indicative for SOM) and 16O (indicative for mineral surfaces) secondary ion distributions. The image segmentation of the secondary ion distributions into mineral particle surface and organic coating was done with a machine learning algorithm, which accounts for multiple features like size, color, intensity, edge and texture in all three ion distributions simultaneously. Our workflow allowed the spatial analysis of differences in the SOM coverage during soil development in the Damma glacier forefield (Switzerland) based on NanoSIMS measurements (n=121; containing ca. 4000 particles). The Damma chronosequence comprises several stages of soil development with increasing ice-free period (from ca. 15 to >700 years). To investigate mineral-associated SOM in the developing soil we obtained clay fractions (<2 μm) from two density fractions: light mineral (1.6 to 2.2 g cm3) and heavy mineral (>2.2 g cm3). We found increased coverage and a simultaneous development from patchy-distributed organic coatings to more connected coatings with increasing time after glacial retreat. The normalized N:C ratio (12C14N: (12C14N + 12C)) on the organic matter coatings was higher in the medium-aged soils than in the young and mature ones in both heavy and light mineral fraction. This reflects the sequential accumulation of proteinaceous SOM in the medium-aged soils and C-rich compounds in the mature soils. The results of our microscale image analysis correlated well with the SOM concentration of the fractions measured by elemental analyzer. Image analysis in combination with secondary ion distributions provides a powerful tool at the required microscale and enhances our mechanistic understanding of SOM stabilization in soil.

Spatial analyses for nonoverlapping objects with size variations and their application to coral communities.

PubMed

Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko

2014-07-01

Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

On validating remote sensing simulations using coincident real data

NASA Astrophysics Data System (ADS)

Wang, Mingming; Yao, Wei; Brown, Scott; Goodenough, Adam; van Aardt, Jan

2016-05-01

The remote sensing community often requires data simulation, either via spectral/spatial downsampling or through virtual, physics-based models, to assess systems and algorithms. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is one such first-principles, physics-based model for simulating imagery for a range of modalities. Complex simulation of vegetation environments subsequently has become possible, as scene rendering technology and software advanced. This in turn has created questions related to the validity of such complex models, with potential multiple scattering, bidirectional distribution function (BRDF), etc. phenomena that could impact results in the case of complex vegetation scenes. We selected three sites, located in the Pacific Southwest domain (Fresno, CA) of the National Ecological Observatory Network (NEON). These sites represent oak savanna, hardwood forests, and conifer-manzanita-mixed forests. We constructed corresponding virtual scenes, using airborne LiDAR and imaging spectroscopy data from NEON, ground-based LiDAR data, and field-collected spectra to characterize the scenes. Imaging spectroscopy data for these virtual sites then were generated using the DIRSIG simulation environment. This simulated imagery was compared to real AVIRIS imagery (15m spatial resolution; 12 pixels/scene) and NEON Airborne Observation Platform (AOP) data (1m spatial resolution; 180 pixels/scene). These tests were performed using a distribution-comparison approach for select spectral statistics, e.g., established the spectra's shape, for each simulated versus real distribution pair. The initial comparison results of the spectral distributions indicated that the shapes of spectra between the virtual and real sites were closely matched.

Analysis and modeling of optical crosstalk in InP-based Geiger-mode avalanche photodiode FPAs

NASA Astrophysics Data System (ADS)

Chau, Quan; Jiang, Xudong; Itzler, Mark A.; Entwistle, Mark; Piccione, Brian; Owens, Mark; Slomkowski, Krystyna

2015-05-01

Optical crosstalk is a major factor limiting the performance of Geiger-mode avalanche photodiode (GmAPD) focal plane arrays (FPAs). This is especially true for arrays with increased pixel density and broader spectral operation. We have performed extensive experimental and theoretical investigations on the crosstalk effects in InP-based GmAPD FPAs for both 1.06-μm and 1.55-μm applications. Mechanisms responsible for intrinsic dark counts are Poisson processes, and their inter-arrival time distribution is an exponential function. In FPAs, intrinsic dark counts and cross talk events coexist, and the inter-arrival time distribution deviates from purely exponential behavior. From both experimental data and computer simulations, we show the dependence of this deviation on the crosstalk probability. The spatial characteristics of crosstalk are also demonstrated. From the temporal and spatial distribution of crosstalk, an efficient algorithm to identify and quantify crosstalk is introduced.

[Evaluation on environmental quality of heavy metals in soils and vegetables based on geostatistics and GIS].

PubMed

Xie, Zheng-miao; Li, Jing; Wang, Bi-ling; Chen, Jian-jun

2006-10-01

Contents of heavy metals (Pb, Zn, Cd, Cu) in soils and vegetables from Dongguan town in Shangyu city, China were studied using geostatistical analysis and GIS technique to evaluate environmental quality. Based on the evaluation criteria, the distribution of the spatial variability of heavy metals in soil-vegetable system was mapped and analyzed. The results showed that the distribution of soil heavy metals in a large number of soil samples in Dongguan town was asymmetric. The contents of Zn and Cu were lower than those of Cd and Pb. The concentrations distribution of Pb, Zn, Cd and Cu in soils and vegetables were different in spatial variability. There was a close relationship between total and available contents of heavy metals in soil. The contents of Pb and Cd in green vegetables were higher than those of Zn and Cu and exceeded the national sanitation standards for vegetables.

Phase sensitive distributed vibration sensing based on ultraweak fiber Bragg grating array using double-pulse

NASA Astrophysics Data System (ADS)

Liu, Tao; Wang, Feng; Zhang, Xuping; Zhang, Lin; Yuan, Quan; Liu, Yu; Yan, Zhijun

2017-08-01

A distributed vibration sensing technique using double-optical-pulse based on phase-sensitive optical time-domain reflectometry (ϕ-OTDR) and an ultraweak fiber Bragg grating (UWFBG) array is proposed for the first time. The single-mode sensing fiber is integrated with the UWFBG array that has uniform spatial interval and ultraweak reflectivity. The relatively high reflectivity of the UWFBG, compared with the Rayleigh scattering, gains a high signal-to-noise ratio for the signal, which can make the system achieve the maximum detectable frequency limited by the round-trip time of the probe pulse in fiber. A corresponding experimental ϕ-OTDR system with a 4.5 km sensing fiber integrated with the UWFBG array was setup for the evaluation of the system performance. Distributed vibration sensing is successfully realized with spatial resolution of 50 m. The sensing range of the vibration frequency can cover from 3 Hz to 9 kHz.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Real-space measurement of potential distribution in PECVD ONO electrets by Kelvin probe force microscopy.

PubMed

Emmerich, F; Thielemann, C

2016-05-20

Multilayers of silicon oxide/silicon nitride/silicon oxide (ONO) are known for their good electret properties due to deep energy traps near the material interfaces, facilitating charge storage. However, measurement of the space charge distribution in such multilayers is a challenge for conventional methods if layer thickness dimensions shrink below 1 μm. In this paper, we propose an atomic force microscope based method to determine charge distributions in ONO layers with spatial resolution below 100 nm. By applying Kelvin probe force microscopy (KPFM) on freshly cleaved, corona-charged multilayers, the surface potential is measured directly along the z-axis and across the interfaces. This new method gives insights into charge distribution and charge movement in inorganic electrets with a high spatial resolution.

Investigation of the electric field distribution in the human brain based on MRI and EEG data

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Borisov, A. V.; Knyazkova, A. I.; Shapovalova, A. V.; Ilyasova, E. E.; Sandykova, E. A.

2018-04-01

This work is devoted to the development of the approach to restoration of the spatial-temporal distribution of electric field in the human brain. This field was estimated from the model derived from the Maxwell's equations with boundary conditions corresponding to electric potentials at the EEG electrodes, which are located on the surface of the head according to the standard "10-20" scheme. The MRI data were used for calculation of the spatial distribution of the electrical conductivity of biotissues in the human brain. The study of the electric field distribution using our approach was carried out for the healthy child and the child with autism. The research was carried out using the equipment of the Tomsk Regional Common Use Center of Tomsk State University.

The roles of competition and habitat in the dynamics of populations and species distributions Ecology

Treesearch

Charles B. Yackulic; Janice Reid; James D. Nichols; James E. Hines; Raymond Davis; Eric Forsman

2014-01-01

The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition’s importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl,...

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

2012-12-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of temporal correlation structure, Hydrol. Earth Syst. Sci. Discuss., 9, 3087-3127, doi:10.5194/hessd-9-3087-2012, 2012b.

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2015-03-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2014-11-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

Origin of Pareto-like spatial distributions in ecosystems.

PubMed

Manor, Alon; Shnerb, Nadav M

2008-12-31

Recent studies of cluster distribution in various ecosystems revealed Pareto statistics for the size of spatial colonies. These results were supported by cellular automata simulations that yield robust criticality for endogenous pattern formation based on positive feedback. We show that this patch statistics is a manifestation of the law of proportionate effect. Mapping the stochastic model to a Markov birth-death process, the transition rates are shown to scale linearly with cluster size. This mapping provides a connection between patch statistics and the dynamics of the ecosystem; the "first passage time" for different colonies emerges as a powerful tool that discriminates between endogenous and exogenous clustering mechanisms. Imminent catastrophic shifts (such as desertification) manifest themselves in a drastic change of the stability properties of spatial colonies.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Evaluation of ET-based drought index derived from geostationary satellite data

USDA-ARS?s Scientific Manuscript database

The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle,...

A Rapid Monitoring and Evaluation Method of Schistosomiasis Based on Spatial Information Technology.

PubMed

Wang, Yong; Zhuang, Dafang

2015-12-12

Thanks to Spatial Information Technologies (SITs) such as Remote Sensing (RS) and Geographical Information System (GIS) that are being quickly developed and updated, SITs are being used more widely in the public health field. The use of SITs to study the characteristics of the temporal and spatial distribution of Schistosoma japonicum and to assess the risk of infection provides methods for the control and prevention of schistosomiasis japonica has gradually become a hot topic in the field. The purpose of the present paper was to use RS and GIS technology to develop an efficient method of prediction and assessment of the risk of schistosomiasis japonica. We choose the Yueyang region, close to the east DongTing Lake (Hunan Province, China), as the study area, where a recent serious outbreak of schistosomiasis japonica took place. We monitored and evaluated the transmission risk of schistosomiasis japonica in the region using SITs. Water distribution data were extracted from RS images. The ground temperature, ground humidity and vegetation index were calculated based on RS images. Additionally, the density of oncomelania snails, which are the Schistosoma japonicum intermediate host, was calculated on the base of RS data and field measurements. The spatial distribution of oncomelania snails was explored using SITs in order to estimate the area surrounding the residents with transmission risk of schistosomiasis japonica. Our research result demonstrated: (1) the risk factors for the transmission of schistosomiasis japonica were closely related to the living environment of oncomelania snails. Key factors such as water distribution, ground temperature, ground humidity and vegetation index can be quickly obtained and calculated from RS images; (2) using GIS technology and a RS deduction technique along with statistical regression models, the density distribution model of oncomelania snails could be quickly built; (3) using SITs and analysis with overlaying population distribution data, the range of transmission risk of schistosomiasis japonica of the study area can be quickly monitored and evaluated. This method will help support the decision making for the control and prevention of schistosomiasis and form a valuable application using SITs for the schistosomiasis research.

Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

NASA Astrophysics Data System (ADS)

Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

2014-10-01

Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary information compared to Co-OK, and BME outperforms RK by integrating the auxiliary data in a probability form.

High performance and highly reliable Raman-based distributed temperature sensors based on correlation-coded OTDR and multimode graded-index fibers

NASA Astrophysics Data System (ADS)

Soto, M. A.; Sahu, P. K.; Faralli, S.; Sacchi, G.; Bolognini, G.; Di Pasquale, F.; Nebendahl, B.; Rueck, C.

2007-07-01

The performance of distributed temperature sensor systems based on spontaneous Raman scattering and coded OTDR are investigated. The evaluated DTS system, which is based on correlation coding, uses graded-index multimode fibers, operates over short-to-medium distances (up to 8 km) with high spatial and temperature resolutions (better than 1 m and 0.3 K at 4 km distance with 10 min measuring time) and high repeatability even throughout a wide temperature range.

Long-term impact of the World Bank Loan Project for schistosomiasis control: a comparison of the spatial distribution of schistosomiasis risk in China.

PubMed

Zhang, Zhijie; Zhu, Rong; Ward, Michael P; Xu, Wanghong; Zhang, Lijuan; Guo, Jiagang; Zhao, Fei; Jiang, Qingwu

2012-01-01

The World Bank Loan Project (WBLP) for controlling schistosomiasis in China was implemented during 1992-2001. Its short-term impact has been assessed from non-spatial perspective, but its long-term impact remains unclear and a spatial evaluation has not previously been conducted. Here we compared the spatial distribution of schistosomiasis risk using national datasets in the lake and marshland regions from 1999-2001 and 2007-2008 to evaluate the long-term impact of WBLP strategy on China's schistosomiasis burden. A hierarchical Poisson regression model was developed in a Bayesian framework with spatially correlated and uncorrelated heterogeneities at the county-level, modeled using a conditional autoregressive prior structure and a spatially unstructured Gaussian distribution, respectively. There were two important findings from this study. The WBLP strategy was found to have a good short-term impact on schistosomiasis control, but its long-term impact was not ideal. It has successfully reduced the morbidity of schistosomiasis to a low level, but can not contribute further to China's schistosomiasis control because of the current low endemic level. A second finding is that the WBLP strategy could not effectively compress the spatial distribution of schistosomiasis risk. To achieve further reductions in schistosomiasis-affected areas, and for sustainable control, focusing on the intermediate host snail should become the next step to interrupt schistosomiasis transmission within the two most affected regions surrounding the Dongting and Poyang Lakes. Furthermore, in the lower reaches of the Yangtze River, the WBLP's morbidity control strategy may need to continue for some time until snails in the upriver provinces have been well controlled. It is difficult to further reduce morbidity due to schistosomiasis using a chemotherapy-based control strategy in the lake and marshland regions of China because of the current low endemic levels of infection. The future control strategy for schistosomiasis should instead focus on a snail-based integrated control strategy to maintain the program achievements and sustainably reduce the burden of schistosomiasis in China.

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

NASA Astrophysics Data System (ADS)

Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

2014-10-01

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

2017-09-01

Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Modular and hierarchical structure of social contact networks

NASA Astrophysics Data System (ADS)

Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2013-10-01

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-06-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-03-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Do morphometric parameters and geological conditions determine chemistry of glacier surface ice? Spatial distribution of contaminants present in the surface ice of Spitsbergen glaciers (European Arctic).

PubMed

Lehmann, Sara; Gajek, Grzegorz; Chmiel, Stanisław; Polkowska, Żaneta

2016-12-01

The chemism of the glaciers is strongly determined by long-distance transport of chemical substances and their wet and dry deposition on the glacier surface. This paper concerns spatial distribution of metals, ions, and dissolved organic carbon, as well as the differentiation of physicochemical parameters (pH, electrical conductivity) determined in ice surface samples collected from four Arctic glaciers during the summer season in 2012. The studied glaciers represent three different morphological types: ground based (Blomlibreen and Scottbreen), tidewater which evolved to ground based (Renardbreen), and typical tidewater glacier (Recherchebreen). All of the glaciers are functioning as a glacial system and hence are subject to the same physical processes (melting, freezing) and the process of ice flowing resulting from the cross-impact force of gravity and topographic conditions. According to this hypothesis, the article discusses the correlation between morphometric parameters, changes in mass balance, geological characteristics of the glaciers and the spatial distribution of analytes on the surface of ice. A strong correlation (r = 0.63) is recorded between the aspect of glaciers and values of pH and ions, whereas dissolved organic carbon (DOC) depends on the minimum elevation of glaciers (r = 0.55) and most probably also on the development of the accumulation area. The obtained results suggest that although certain morphometric parameters largely determine the spatial distribution of analytes, also the geology of the bed of glaciers strongly affects the chemism of the surface ice of glaciers in the phase of strong recession.

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

Uncovering urban human mobility from large scale taxi GPS data

NASA Astrophysics Data System (ADS)

Tang, Jinjun; Liu, Fang; Wang, Yinhai; Wang, Hua

2015-11-01

Taxi GPS trajectories data contain massive spatial and temporal information of urban human activity and mobility. Taking taxi as mobile sensors, the information derived from taxi trips benefits the city and transportation planning. The original data used in study are collected from more than 1100 taxi drivers in Harbin city. We firstly divide the city area into 400 different transportation districts and analyze the origin and destination distribution in urban area on weekday and weekend. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to cluster pick-up and drop-off locations. Furthermore, four spatial interaction models are calibrated and compared based on trajectories in shopping center of Harbin city to study the pick-up location searching behavior. By extracting taxi trips from GPS data, travel distance, time and average speed in occupied and non-occupied status are then used to investigate human mobility. Finally, we use observed OD matrix of center area in Harbin city to model the traffic distribution patterns based on entropy-maximizing method, and the estimation performance verify its effectiveness in case study.

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Ecological and management implications of climate-driven changes in spatial and temporal distributions of marine species

NASA Astrophysics Data System (ADS)

Mills, K.; Pershing, A. J.; Nye, J. A.; Henderson, M. E.; Thomas, A. C.; Hernandez, C.; Alexander, M. A.; Schuetz, J.; Allyn, A.

2016-02-01

Ocean temperatures in the Gulf of Maine have warmed rapidly over the past decade, and the seasonal cycle of temperatures has shifted towards earlier warming in the spring and later cooling in the fall. Warming temperatures have been associated with northward shifts in spatial distributions of many marine fish and invertebrate species in the region. In addition, changing phenology—particularly of migratory species—is also being observed. The rates at which species distributions change in space and time vary by species, and these differential rates have important implications for trophic interactions and fisheries. In this presentation, we will identify groups of species on the Northeast Shelf based on whether their distribution responses to warming temperatures lead, lag, or track temperature signals. Life history and population characteristics provide a basis for understanding how species cluster in these groups. Differential rates of changes in spatial and temporal distributions affect trophic interactions. American lobster provides one example of a prey species that may be affected by changes in the spatial distribution and migration phenology of its predators. Changes in natural mortality on important commercial species may affect fisheries by altering stock dynamics and allowable catch levels, but fisheries will also be affected by the need to change their fishing locations, times, or target species. Some of these fishery responses are already being observed in the Northeast, but many are constrained by the management system. Our presentation will conclude by identifying some ways in which fisheries management adjustments might help address issues of stock sustainability and fishery access for species that are experiencing climate-related distribution shifts.

SimAlba: A Spatial Microsimulation Approach to the Analysis of Health Inequalities

PubMed Central

Campbell, Malcolm; Ballas, Dimitris

2016-01-01

This paper presents applied geographical research based on a spatial microsimulation model, SimAlba, aimed at estimating geographically sensitive health variables in Scotland. SimAlba has been developed in order to answer a variety of “what-if” policy questions pertaining to health policy in Scotland. Using the SimAlba model, it is possible to simulate the distributions of previously unknown variables at the small area level such as smoking, alcohol consumption, mental well-being, and obesity. The SimAlba microdataset has been created by combining Scottish Health Survey and Census data using a deterministic reweighting spatial microsimulation algorithm developed for this purpose. The paper presents SimAlba outputs for Scotland’s largest city, Glasgow, and examines the spatial distribution of the simulated variables for small geographical areas in Glasgow as well as the effects on individuals of different policy scenario outcomes. In simulating previously unknown spatial data, a wealth of new perspectives can be examined and explored. This paper explores a small set of those potential avenues of research and shows the power of spatial microsimulation modeling in an urban context. PMID:27818989

Microclimate predicts within-season distribution dynamics of montane forest birds

Treesearch

Sarah J.K. Frey; Adam S. Hadley; Matthew G. Betts; Mark Robertson

2016-01-01

Aim: Climate changes are anticipated to have pervasive negative effects on biodiversity and are expected to necessitate widespread range shifts or contractions. Such projections are based upon the assumptions that (1) species respond primarily to broad-scale climatic regimes, or (2) that variation in climate at fine spatial scales is less relevant at coarse spatial...

Spatial heterogeneity and air pollution removal by an urban forest

Treesearch

Francisco J. Escobedo; David J. Nowak

2009-01-01

Estimates of air pollution removal by the urban forest have mostly been based on mean values of forest structure variables for an entire city. However, the urban forest is not uniformly distributed across a city because of biophysical and social factors. Consequently, air pollution removal function by urban vegetation should vary because of this spatial heterogeneity....

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

The Not So Simple Globular Cluster ω Cen. I. Spatial Distribution of the Multiple Stellar Populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calamida, A.; Saha, A.; Strampelli, G.

2017-04-01

We present a multi-band photometric catalog of ≈1.7 million cluster members for a field of view of ≈2° × 2° across ω Cen. Photometry is based on images collected with the Dark Energy Camera on the 4 m Blanco telescope and the Advanced Camera for Surveys on the Hubble Space Telescope . The unprecedented photometric accuracy and field coverage allowed us, for the first time, to investigate the spatial distribution of ω Cen multiple populations from the core to the tidal radius, confirming its very complex structure. We found that the frequency of blue main-sequence stars is increasing compared to red main-sequencemore » stars starting from a distance of ≈25′ from the cluster center. Blue main-sequence stars also show a clumpy spatial distribution, with an excess in the northeast quadrant of the cluster pointing toward the direction of the Galactic center. Stars belonging to the reddest and faintest red-giant branch also show a more extended spatial distribution in the outskirts of ω Cen, a region never explored before. Both these stellar sub-populations, according to spectroscopic measurements, are more metal-rich compared to the cluster main stellar population. These findings, once confirmed, make ω Cen the only stellar system currently known where metal-rich stars have a more extended spatial distribution compared to metal-poor stars. Kinematic and chemical abundance measurements are now needed for stars in the external regions of ω Cen to better characterize the properties of these sub-populations.« less

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE PAGES

Shi, Yuning; Eissenstat, David M.; He, Yuting; ...

2018-05-12

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Auditory spectral versus spatial temporal order judgment: Threshold distribution analysis.

PubMed

Fostick, Leah; Babkoff, Harvey

2017-05-01

Some researchers suggested that one central mechanism is responsible for temporal order judgments (TOJ), within and across sensory channels. This suggestion is supported by findings of similar TOJ thresholds in same modality and cross-modality TOJ tasks. In the present study, we challenge this idea by analyzing and comparing the threshold distributions of the spectral and spatial TOJ tasks. In spectral TOJ, the tones differ in their frequency ("high" and "low") and are delivered either binaurally or monaurally. In spatial (or dichotic) TOJ, the two tones are identical but are presented asynchronously to the two ears and thus differ with respect to which ear received the first tone and which ear received the second tone ("left"/"left"). Although both tasks are regarded as measures of auditory temporal processing, a review of data published in the literature suggests that they trigger different patterns of response. The aim of the current study was to systematically examine spectral and spatial TOJ threshold distributions across a large number of studies. Data are based on 388 participants in 13 spectral TOJ experiments, and 222 participants in 9 spatial TOJ experiments. None of the spatial TOJ distributions deviated significantly from the Gaussian; while all of the spectral TOJ threshold distributions were skewed to the right, with more than half of the participants accurately judging temporal order at very short interstimulus intervals (ISI). The data do not support the hypothesis that 1 central mechanism is responsible for all temporal order judgments. We suggest that different perceptual strategies are employed when performing spectral TOJ than when performing spatial TOJ. We posit that the spectral TOJ paradigm may provide the opportunity for two-tone masking or temporal integration, which is sensitive to the order of the tones and thus provides perceptual cues that may be used to judge temporal order. This possibility should be considered when interpreting spectral TOJ data, especially in the context of comparing different populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Yuning; Eissenstat, David M.; He, Yuting

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

Spatial Distributions of Guest Molecule and Hydration Level in Dendrimer-Based Guest–Host Complex

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chih-Ying; Chen, Hsin-Lung; Do, Changwoo

2016-08-09

Using the electrostatic complex of G4 poly(amidoamine) (PAMAM) dendrimer with an amphiphilic surfactant as a model system, contrast variation small angle neutron scattering (SANS) is implemented to resolve the key structural characteristics of dendrimer-based guest–host system. Quantifications of the radial distributions of the scattering length density and the hydration level within the complex molecule reveal that the surfactant is embedded in the peripheral region of dendrimer and the steric crowding in this region increases the backfolding of the dendritic segments, thereby reducing the hydration level throughout the complex molecule. Here, the insights into the spatial location of the guest moleculesmore » as well as the perturbations of dendrimer conformation and hydration level deduced here are crucial for the delicate design of dendrimer-based guest–host system for biomedical applications.« less

Monthly AOD maps combining strengths of remote sensing products

NASA Astrophysics Data System (ADS)

Kinne, Stefan

2010-05-01

The mid-visible aerosol optical depth (AOD) is the most prominent property to quantify aerosol amount the atmospheric column. Almost all aerosol retrievals of satellite sensors provide estimates for this property, however, often with limited success. As sensors differ in capabilities individual retrievals have local and regional strengths and weaknesses. Focusing on individual retrieval strengths a satellite based AOD composite has been constructed. Hereby, every retrieval performance has been assessed in statistical comparisons to ground-based sun-photometry, which provide highly accurate references though only at few globally distributed monitoring sites. Based on these comparisons, which consider bias as well as spatial patterns and seasonality, the regionally best performing satellite AOD products are combined. The resulting remote sensing AOD composite provide a general reference for the spatial and temporal AOD distribution on an (almost) global basis - solely tied to sensor data.

Runoff simulation sensitivity to remotely sensed initial soil water content

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Schmugge, T. J.; Jackson, T. J.; Unkrich, C. L.; Keefer, T. O.; Parry, R.; Bach, L. B.; Amer, S. A.

1994-05-01

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

Fast-ion D(alpha) measurements and simulations in DIII-D

NASA Astrophysics Data System (ADS)

Luo, Yadong

The fast-ion Dalpha diagnostic measures the Doppler-shifted Dalpha light emitted by neutralized fast ions. For a favorable viewing geometry, the bright interferences from beam neutrals, halo neutrals, and edge neutrals span over a small wavelength range around the Dalpha rest wavelength and are blocked by a vertical bar at the exit focal plane of the spectrometer. Background subtraction and fitting techniques eliminate various contaminants in the spectrum. Fast-ion data are acquired with a time evolution of ˜1 ms, spatial resolution of ˜5 cm, and energy resolution of ˜10 keV. A weighted Monte Carlo simulation code models the fast-ion Dalpha spectra based on the fast-ion distribution function from other sources. In quiet plasmas, the spectral shape is in excellent agreement and absolute magnitude also has reasonable agreement. The fast-ion D alpha signal has the expected dependencies on plasma and neutral beam parameters. The neutral particle diagnostic and neutron diagnostic corroborate the fast-ion Dalpha measurements. The relative spatial profile is in agreement with the simulated profile based on the fast-ion distribution function from the TRANSP analysis code. During ion cyclotron heating, fast ions with high perpendicular energy are accelerated, while those with low perpendicular energy are barely affected. The spatial profile is compared with the simulated profiles based on the fast-ion distribution functions from the CQL Fokker-Planck code. In discharges with Alfven instabilities, both the spatial profile and spectral shape suggests that fast ions are redistributed. The flattened fast-ion Dalpha profile is in agreement with the fast-ion pressure profile.

Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia.

PubMed

Chammartin, Frédérique; Scholte, Ronaldo G C; Malone, John B; Bavia, Mara E; Nieto, Prixia; Utzinger, Jürg; Vounatsou, Penelope

2013-05-25

The prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented. We analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission. Results show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia. We provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control.

Spatial Distribution of Io's Neutral Oxygen Cloud Observed by Hisaki

NASA Astrophysics Data System (ADS)

Koga, Ryoichi; Tsuchiya, Fuminori; Kagitani, Masato; Sakanoi, Takeshi; Yoneda, Mizuki; Yoshioka, Kazuo; Yoshikawa, Ichiro; Kimura, Tomoki; Murakami, Go; Yamazaki, Atsushi; Smith, H. Todd; Bagenal, Fran

2018-05-01

We report on the spatial distribution of a neutral oxygen cloud surrounding Jupiter's moon Io and along Io's orbit observed by the Hisaki satellite. Atomic oxygen and sulfur in Io's atmosphere escape from the exosphere mainly through atmospheric sputtering. Some of the neutral atoms escape from Io's gravitational sphere and form neutral clouds around Jupiter. The extreme ultraviolet spectrograph called EXCEED (Extreme Ultraviolet Spectroscope for Exospheric Dynamics) installed on the Japan Aerospace Exploration Agency's Hisaki satellite observed the Io plasma torus continuously in 2014-2015, and we derived the spatial distribution of atomic oxygen emissions at 130.4 nm. The results show that Io's oxygen cloud is composed of two regions, namely, a dense region near Io and a diffuse region with a longitudinally homogeneous distribution along Io's orbit. The dense region mainly extends on the leading side of Io and inside of Io's orbit. The emissions spread out to 7.6 Jupiter radii (RJ). Based on Hisaki observations, we estimated the radial distribution of the atomic oxygen number density and oxygen ion source rate. The peak atomic oxygen number density is 80 cm-3, which is spread 1.2 RJ in the north-south direction. We found more oxygen atoms inside Io's orbit than a previous study. We estimated the total oxygen ion source rate to be 410 kg/s, which is consistent with the value derived from a previous study that used a physical chemistry model based on Hisaki observations of ultraviolet emission ions in the Io plasma torus.

A satellite-based drought index describing anomalies in evapotranspiration for global crop monitoring

USDA-ARS?s Scientific Manuscript database

The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle, ...

New spatial upscaling methods for multi-point measurements: From normal to p-normal

NASA Astrophysics Data System (ADS)

Liu, Feng; Li, Xin

2017-12-01

Careful attention must be given to determining whether the geophysical variables of interest are normally distributed, since the assumption of a normal distribution may not accurately reflect the probability distribution of some variables. As a generalization of the normal distribution, the p-normal distribution and its corresponding maximum likelihood estimation (the least power estimation, LPE) were introduced in upscaling methods for multi-point measurements. Six methods, including three normal-based methods, i.e., arithmetic average, least square estimation, block kriging, and three p-normal-based methods, i.e., LPE, geostatistics LPE and inverse distance weighted LPE are compared in two types of experiments: a synthetic experiment to evaluate the performance of the upscaling methods in terms of accuracy, stability and robustness, and a real-world experiment to produce real-world upscaling estimates using soil moisture data obtained from multi-scale observations. The results show that the p-normal-based methods produced lower mean absolute errors and outperformed the other techniques due to their universality and robustness. We conclude that introducing appropriate statistical parameters into an upscaling strategy can substantially improve the estimation, especially if the raw measurements are disorganized; however, further investigation is required to determine which parameter is the most effective among variance, spatial correlation information and parameter p.

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

PubMed

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Geostatistical and GIS analysis of the spatial variability of alluvial gold content in Ngoura-Colomines area, Eastern Cameroon: Implications for the exploration of primary gold deposit

NASA Astrophysics Data System (ADS)

Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul

2018-06-01

Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.

A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma

NASA Astrophysics Data System (ADS)

Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel

2017-03-01

Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

PubMed

Freeman, Mary Pyott; Stow, Douglas A; An, Li

2017-10-01

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Mean mortality remained static from 1997 to 2002 (4, 2.2, and 4.2 trees/ha for Palomar, Volcan, and Laguna) and then increased by 2005 to 10.3, 9.7, and 5.2 trees/ha, respectively. The increase in mortality between 2002 and 2005 represents the temporal pattern of a discrete disturbance event, attributable to the 2002-2003 drought. Dead trees are significantly clustered for all dates, based on spatial cluster analysis, indicating that they form distinct groups, as opposed to spatially random single dead trees. Other tests indicate no directional shift or spread of mortality over time, but rather an increase in density. While general temporal and spatial mortality processes are uniform across all study areas, the plot-based species and quantity distribution of mortality, and diameter distributions of dead vs. living trees, vary by study area. The results of this study improve our understanding of stand- to landscape-level forest structure and dynamics, particularly by examining them from the multiple perspectives of field and remotely sensed data. © 2017 by the Ecological Society of America.

Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response

NASA Astrophysics Data System (ADS)

Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.

2016-06-01

Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.

Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

PubMed

Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin

2017-07-31

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Location of Road Emergency Stations in Fars Province, Using Spatial Multi-Criteria Decision Making.

PubMed

Goli, Ali; Ansarizade, Najmeh; Barati, Omid; Kavosi, Zahra

2015-01-01

To locate the road emergency stations in Fars province based on using spatial multi-criteria decision making (Delphi method). In this study, the criteria affecting the location of road emergency stations have been identified through Delphi method and their importance was determined using Analytical Hierarchical Process (AHP). With regard to the importance of the criteria and by using Geographical Information System (GIS), the appropriateness of the existing stations with the criteria and the way of their distribution has been explored, and the appropriate arenas for creating new emergency stations were determined. In order to investigate the spatial distribution pattern of the stations, Moran's Index was used. The accidents (0.318), placement position (0.235), time (0.198), roads (0.160), and population (0.079) were introduced as the main criteria in location road emergency stations. The findings showed that the distribution of the existing stations was clustering (Moran's I=0.3). Three priorities were introduced for establishing new stations. Some arenas including Abade, north of Eghlid and Khoram bid, and small parts of Shiraz, Farashband, Bavanat, and Kazeroon were suggested as the first priority. GIS is a useful and applicable tool in investigating spatial distribution and geographical accessibility to the setting that provide health care, including emergency stations.

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

Distribution and spatial variation of hydrothermal faunal assemblages at Lucky Strike (Mid-Atlantic Ridge) revealed by high-resolution video image analysis

NASA Astrophysics Data System (ADS)

Cuvelier, Daphne; Sarrazin, Jozée; Colaço, Ana; Copley, Jon; Desbruyères, Daniel; Glover, Adrian G.; Tyler, Paul; Serrão Santos, Ricardo

2009-11-01

Whilst the fauna inhabiting hydrothermal vent structures in the Atlantic Ocean is reasonably well known, less is understood about the spatial distributions of the fauna in relation to abiotic and biotic factors. In this study, a major active hydrothermal edifice (Eiffel Tower, at 1690 m depth) on the Lucky Strike vent field (Mid-Atlantic Ridge (MAR)) was investigated. Video transects were carried out by ROV Victor 6000 and complete image coverage was acquired. Four distinct assemblages, ranging from dense larger-sized Bathymodiolus mussel beds to smaller-sized mussel clumps and alvinocaridid shrimps, and two types of substrata were defined based on high definition photographs and video imagery. To evaluate spatial variation, faunal distribution was mapped in three dimensions. A high degree of patchiness characterizes this 11 m high sulfide structure. The differences observed in assemblage and substratum distribution were related to habitat characteristics (fluid exits, depth and structure orientation). Gradients in community structure were observed, which coincided with an increasing distance from the fluid exits. A biological zonation model for the Eiffel Tower edifice was created in which faunal composition and distribution can be visually explained by the presence/absence of fluid exits.

Two dimensional distribution measurement of electric current generated in a polymer electrolyte fuel cell using 49 NMR surface coils.

PubMed

Ogawa, Kuniyasu; Sasaki, Tatsuyoshi; Yoneda, Shigeki; Tsujinaka, Kumiko; Asai, Ritsuko

2018-05-17

In order to increase the current density generated in a PEFC (polymer electrolyte fuel cell), a method for measuring the spatial distribution of both the current and the water content of the MEA (membrane electrode assembly) is necessary. Based on the frequency shifts of NMR (nuclear magnetic resonance) signals acquired from the water contained in the MEA using 49 NMR coils in a 7 × 7 arrangement inserted in the PEFC, a method for measuring the two-dimensional spatial distribution of electric current generated in a unit cell with a power generation area of 140 mm × 160 mm was devised. We also developed an inverse analysis method to determine the two-dimensional electric current distribution that can be applied to actual PEFC connections. Two analytical techniques, namely coarse graining of segments and stepwise search, were used to shorten the calculation time required for inverse analysis of the electric current map. Using this method and techniques, spatial distributions of electric current and water content in the MEA were obtained when the PEFC generated electric power at 100 A. Copyright © 2018 Elsevier Inc. All rights reserved.

Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic - Size-based ecosystem model

NASA Astrophysics Data System (ADS)

Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.

2015-11-01

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

A simple optode based method for imaging O2 distribution and dynamics in tap water biofilms.

PubMed

Staal, M; Prest, E I; Vrouwenvelder, J S; Rickelt, L F; Kühl, M

2011-10-15

A ratiometric luminescence intensity imaging approach is presented, which enables spatial O2 measurements in biofilm reactors with transparent planar O2 optodes. Optodes consist of an O2 sensitive luminescent dye immobilized in a 1-10 μm thick polymeric layer on a transparent carrier, e.g. a glass window. The method is based on sequential imaging of the O2 dependent luminescence intensity, which are subsequently normalized with luminescent intensity images recorded under anoxic conditions. We present 2-dimensional O2 distribution images at the base of a tap water biofilm measured with the new ratiometric method and compare the results with O2 distribution images obtained in the same biofilm reactor with luminescence lifetime imaging. Using conventional digital cameras, such simple normalized luminescence intensity imaging can yield images of 2-dimensional O2 distributions with a high signal-to-noise ratio and spatial resolution comparable or even surpassing those obtained with expensive and complex luminescence lifetime imaging systems. The method can be applied to biofilm growth incubators allowing intermittent experimental shifts to anoxic conditions or in systems, in which the O2 concentration is depleted during incubation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator.

PubMed

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-20

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200 mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230 fs, which is caused by the spatial-temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged. © 2011 Optical Society of America

Nonuniformity correction of infrared cameras by reading radiance temperatures with a spatially nonhomogeneous radiation source

NASA Astrophysics Data System (ADS)

Gutschwager, Berndt; Hollandt, Jörg

2017-01-01

We present a novel method of nonuniformity correction (NUC) of infrared cameras and focal plane arrays (FPA) in a wide optical spectral range by reading radiance temperatures and by applying a radiation source with an unknown and spatially nonhomogeneous radiance temperature distribution. The benefit of this novel method is that it works with the display and the calculation of radiance temperatures, it can be applied to radiation sources of arbitrary spatial radiance temperature distribution, and it only requires sufficient temporal stability of this distribution during the measurement process. In contrast to this method, an initially presented method described the calculation of NUC correction with the reading of monitored radiance values. Both methods are based on the recording of several (at least three) images of a radiation source and a purposeful row- and line-shift of these sequent images in relation to the first primary image. The mathematical procedure is explained in detail. Its numerical verification with a source of a predefined nonhomogeneous radiance temperature distribution and a thermal imager of a predefined nonuniform FPA responsivity is presented.

The effect of the electric wind on the spatial distribution of chemical species in the positive corona discharge

NASA Astrophysics Data System (ADS)

Yanallah, K.; Pontiga, F.; Bouazza, M. R.; Chen, J. H.

2017-08-01

The electrohydrodynamic air flow generated by a positive corona discharge, and its effect on the spatial distribution of chemical species within a wire-plate corona reactor, have been numerically simulated. The computational model is based on the solutions of the Navier-Stokes equation and the continuity equation of each chemical species generated by the electrical discharge. A simplified analytical expression of the electric force density, which only requires the current density as the input parameter, has been used in the Navier-Stokes equation to obtain the velocity field. For the solution of the continuity equations, a plasma chemistry model that includes the most important reactions between electrons, atoms and molecules in air has been used. Similar to the electric force, the electron density distribution has been approximated by using a semi-analytical expression appropriate for the electrode geometry. The results of the study show that the spatial distribution of chemical species can be very different, and depends on the interplay between the electrohydrodynamic flow, the chemical kinetics of the species and its characteristic lifetime.

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

USGS Publications Warehouse

Guo, J.; Tsang, L.; Josberger, E.G.; Wood, A.W.; Hwang, J.-N.; Lettenmaier, D.P.

2003-01-01

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Segre, Daniel

2014-08-14

The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Spatial analysis to identify hotspots of prevalence of schizophrenia.

PubMed

Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis

2008-10-01

The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.

3D shape representation with spatial probabilistic distribution of intrinsic shape keypoints

NASA Astrophysics Data System (ADS)

Ghorpade, Vijaya K.; Checchin, Paul; Malaterre, Laurent; Trassoudaine, Laurent

2017-12-01

The accelerated advancement in modeling, digitizing, and visualizing techniques for 3D shapes has led to an increasing amount of 3D models creation and usage, thanks to the 3D sensors which are readily available and easy to utilize. As a result, determining the similarity between 3D shapes has become consequential and is a fundamental task in shape-based recognition, retrieval, clustering, and classification. Several decades of research in Content-Based Information Retrieval (CBIR) has resulted in diverse techniques for 2D and 3D shape or object classification/retrieval and many benchmark data sets. In this article, a novel technique for 3D shape representation and object classification has been proposed based on analyses of spatial, geometric distributions of 3D keypoints. These distributions capture the intrinsic geometric structure of 3D objects. The result of the approach is a probability distribution function (PDF) produced from spatial disposition of 3D keypoints, keypoints which are stable on object surface and invariant to pose changes. Each class/instance of an object can be uniquely represented by a PDF. This shape representation is robust yet with a simple idea, easy to implement but fast enough to compute. Both Euclidean and topological space on object's surface are considered to build the PDFs. Topology-based geodesic distances between keypoints exploit the non-planar surface properties of the object. The performance of the novel shape signature is tested with object classification accuracy. The classification efficacy of the new shape analysis method is evaluated on a new dataset acquired with a Time-of-Flight camera, and also, a comparative evaluation on a standard benchmark dataset with state-of-the-art methods is performed. Experimental results demonstrate superior classification performance of the new approach on RGB-D dataset and depth data.

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

NASA Technical Reports Server (NTRS)

Hussain, A. K. M. F.

1980-01-01

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

Extracting information on the spatial variability in erosion rate stored in detrital cooling age distributions in river sands

NASA Astrophysics Data System (ADS)

Braun, Jean; Gemignani, Lorenzo; van der Beek, Peter

2018-03-01

One of the main purposes of detrital thermochronology is to provide constraints on the regional-scale exhumation rate and its spatial variability in actively eroding mountain ranges. Procedures that use cooling age distributions coupled with hypsometry and thermal models have been developed in order to extract quantitative estimates of erosion rate and its spatial distribution, assuming steady state between tectonic uplift and erosion. This hypothesis precludes the use of these procedures to assess the likely transient response of mountain belts to changes in tectonic or climatic forcing. Other methods are based on an a priori knowledge of the in situ distribution of ages to interpret the detrital age distributions. In this paper, we describe a simple method that, using the observed detrital mineral age distributions collected along a river, allows us to extract information about the relative distribution of erosion rates in an eroding catchment without relying on a steady-state assumption, the value of thermal parameters or an a priori knowledge of in situ age distributions. The model is based on a relatively low number of parameters describing lithological variability among the various sub-catchments and their sizes and only uses the raw ages. The method we propose is tested against synthetic age distributions to demonstrate its accuracy and the optimum conditions for it use. In order to illustrate the method, we invert age distributions collected along the main trunk of the Tsangpo-Siang-Brahmaputra river system in the eastern Himalaya. From the inversion of the cooling age distributions we predict present-day erosion rates of the catchments along the Tsangpo-Siang-Brahmaputra river system, as well as some of its tributaries. We show that detrital age distributions contain dual information about present-day erosion rate, i.e., from the predicted distribution of surface ages within each catchment and from the relative contribution of any given catchment to the river distribution. The method additionally allows comparing modern erosion rates to long-term exhumation rates. We provide a simple implementation of the method in Python code within a Jupyter Notebook that includes the data used in this paper for illustration purposes.

Characterization and spatial distribution of mangrove forest types based on ALOS-PALSAR mosaic 25m-resolution in Southeast Asia

NASA Astrophysics Data System (ADS)

Darmawan, S.; Takeuchi, W.; Nakazono, E.; Parwati, E.; Dien, V. T.; Oo, K. S.; Wikantika, K.; Sari, D. K.

2016-06-01

The objective of this research is to investigate characteristics of mangrove forest types and to identify spatial distribution of mangrove forest based on ALOS PALSAR mosaic 25m- resolution in Southeast Asia. Methodology consists of collecting of ALOS PALSAR image for overall Southeast Asia region, preprocessing include converting DN to NRCS and filtering, collecting regions of interest of mangrove forest in Southeast Asia, plotting, characterization and classification. Result on this research we found characteristics of mangrove forest on HH values around -10.88 dB to -6.65 dB and on HV value around -16.49 dB to -13.26 dB. On polarization of HH which the highest backscattering value is mangrove forest in Preak Piphot River Cambodia, Thái Thủy Thai Binh Vietnam, and Vạn Ninh tp. Móng Cái Quảng Ninh Vietnam whereas the lowest backscattering value is mangrove forest in Thailand area. On polarization of HV which the highest backscattering value is mangrove forest in Preak Piphot River Cambodia, Sorong and Teluk Bintuni Indonesia whereas the lowest backscattering value is mangrove forest in Subang Indonesia, Giao Thiện Giao Thuỷ Nam Định, Vietnam and Puyu Mueng Satun Thailand. Based on characterization, we create a rule criteria for classification of mangrove areas and non mangrove area. Finally we found spatial distribution of mangrove forest based on ALOS PALSAR 25m-resolution in Southeast Asia.

Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference

USGS Publications Warehouse

Olea, R.A.; Pardo-Iguzquiza, E.

2011-01-01

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.

Floral abundance, richness, and spatial distribution drive urban garden bee communities.

PubMed

Plascencia, M; Philpott, S M

2017-10-01

In urban landscapes, gardens provide refuges for bee diversity, but conservation potential may depend on local and landscape features. Foraging and population persistence of bee species, as well as overall pollinator community structure, may be supported by the abundance, richness, and spatial distribution of floral resources. Floral resources strongly differ in urban gardens. Using hand netting and pan traps to survey bees, we examined whether abundance, richness, and spatial distribution of floral resources, as well as ground cover and garden landscape surroundings influence bee abundance, species richness, and diversity on the central coast of California. Differences in floral abundance and spatial distribution, as well as urban cover in the landscape, predicted different bee community variables. Abundance of all bees and of honeybees (Apis mellifera) was lower in sites with more urban land cover surrounding the gardens. Honeybee abundance was higher in sites with patchy floral resources, whereas bee species richness and bee diversity was higher in sites with more clustered floral resources. Surprisingly, bee species richness and bee diversity was lower in sites with very high floral abundance, possibly due to interactions with honeybees. Other studies have documented the importance of floral abundance and landscape surroundings for bees in urban gardens, but this study is the first to document that the spatial arrangement of flowers strongly predicts bee abundance and richness. Based on these findings, it is likely that garden managers may promote bee conservation by managing for floral connectivity and abundance within these ubiquitous urban habitats.

Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

NASA Technical Reports Server (NTRS)

Lin, D. S.; Wood, E. F.; Famiglietti, J. S.; Mancini, M.

1994-01-01

Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Demonstration of Lasercom and Spatial Tracking with a Silicon Geiger-Mode APD Array

DTIC Science & Technology

2016-02-26

standardized pixel mask as described in the previous paragraph disabling 167 of the 1024 detectors in the array , this gives an absolute maximum rate...number of elements in an array based detector .5 In this paper, we present the results of photon-counting communication tests based on an arrayed ...semiconductor photon-counting detector .6 The array also has the ability to sense the spatial distribution of the received light giving it the potential to act

Spatial redistribution of radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zakgeim, A. L.; Il’inskaya, N. D.; Karandashev, S. A.

2017-02-15

The spatial distribution of equilibrium and nonequilibrium (including luminescent) IR (infrared) radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures (λ{sub max} = 3.4 μm) is measured and analyzed; the structural features of the photodiodes, including the reflective properties of the ohmic contacts, are taken into account. Optical area enhancement due to multiple internal reflection in photodiodes with different geometric characteristics is estimated.

Predictability of depression severity based on posterior alpha oscillations.

PubMed

Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

2016-04-01

We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

COST-EFFECTIVE SAMPLING FOR SPATIALLY DISTRIBUTED PHENOMENA

EPA Science Inventory

Various measures of sampling plan cost and loss are developed and analyzed as they relate to a variety of multidisciplinary sampling techniques. The sampling choices examined include methods from design-based sampling, model-based sampling, and geostatistics. Graphs and tables ar...

Spatial interpolation techniques using R

EPA Science Inventory

Interpolation techniques are used to predict the cell values of a raster based on sample data points. For example, interpolation can be used to predict the distribution of sediment particle size throughout an estuary based on discrete sediment samples. We demonstrate some inter...

The AgESGUI geospatial simulation system for environmental model application and evaluation

USDA-ARS?s Scientific Manuscript database

Practical decision making in spatially-distributed environmental assessment and management is increasingly being based on environmental process-based models linked to geographical information systems (GIS). Furthermore, powerful computers and Internet-accessible assessment tools are providing much g...

Sidelobe apodization in optical pulse compression reflectometry for fiber optic distributed acoustic sensing.

PubMed

Mompó, Juan José; Martín-López, Sonia; González-Herráez, Miguel; Loayssa, Alayn

2018-04-01

We demonstrate a technique to reduce the sidelobes in optical pulse compression reflectometry for distributed acoustic sensing. The technique is based on using a Gaussian probe pulse with linear frequency modulation. This is shown to improve the sidelobe suppression by 13 dB compared to the use of square pulses without any significant penalty in terms of spatial resolution. In addition, a 2.25 dB enhancement in signal-to-noise ratio is calculated compared to the use of receiver-side windowing. The method is tested by measuring 700 Hz vibrations with a 140  nε amplitude at the end of a 50 km fiber sensing link with 34 cm spatial resolution, giving a record 147,058 spatially resolved points.

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

Synchrotron-based X-ray fluorescence microscopy enables multiscale spatial visualization of ions involved in fungal lignocellulose deconstruction

Treesearch

Grant T. Kirker; Samuel Zelinka; Sophie-Charlotte Gleber; David Vine; Lydia Finney; Si Chen; Young Pyo Hong; Omar Uyarte; Stefan Vogt; Jody Jellison; Barry Goodell; Joseph E. Jakes

2017-01-01

The role of ions in the fungal decay process of lignocellulose biomaterials, and more broadly fungal metabolism, has implications for diverse research disciplines ranging from plant pathology and forest ecology, to carbon sequestration. Despite the importance of ions in fungal decay mechanisms, the spatial distribution and quantification of ions in lignocellulosic cell...

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

Assessment and mapping of water pollution indices in zone-III of municipal corporation of hyderabad using remote sensing and geographic information system.

PubMed

Asadi, S S; Vuppala, Padmaja; Reddy, M Anji

2005-01-01

A preliminary survey of area under Zone-III of MCH was undertaken to assess the ground water quality, demonstrate its spatial distribution and correlate with the land use patterns using advance techniques of remote sensing and geographical information system (GIS). Twenty-seven ground water samples were collected and their chemical analysis was done to form the attribute database. Water quality index was calculated from the measured parameters, based on which the study area was classified into five groups with respect to suitability of water for drinking purpose. Thematic maps viz., base map, road network, drainage and land use/land cover were prepared from IRS ID PAN + LISS III merged satellite imagery forming the spatial database. Attribute database was integrated with spatial sampling locations map in Arc/Info and maps showing spatial distribution of water quality parameters were prepared in Arc View. Results indicated that high concentrations of total dissolved solids (TDS), nitrates, fluorides and total hardness were observed in few industrial and densely populated areas indicating deteriorated water quality while the other areas exhibited moderate to good water quality.

Spatial study of mortality in motorcycle accidents in the State of Pernambuco, Northeastern Brazil.

PubMed

Silva, Paul Hindenburg Nobre de Vasconcelos; Lima, Maria Luiza Carvalho de; Moreira, Rafael da Silveira; Souza, Wayner Vieira de; Cabral, Amanda Priscila de Santana

2011-04-01

To analyze the spatial distribution of mortality due to motorcycle accidents in the state of Pernambuco, Northeastern Brazil. A population-based ecological study using data on mortality in motorcycle accidents from 01/01/2000 to 31/12/2005. The analysis units were the municipalities. For the spatial distribution analysis, an average mortality rate was calculated, using deaths from motorcycle accidents recorded in the Mortality Information System as the numerator, and as the denominator the population of the mid-period. Spatial analysis techniques, mortality smoothing coefficient estimate by the local empirical Bayesian method and Moran scatterplot, applied to the digital cartographic base of Pernambuco were used. The average mortality rate for motorcycle accidents in Pernambuco was 3.47 per 100 thousand inhabitants. Of the 185 municipalities, 16 were part of five clusters identified with average mortality rates ranging from 5.66 to 11.66 per 100 thousand inhabitants, and were considered critical areas. Three clusters are located in the area known as sertão and two in the agreste of the state. The risk of dying from a motorcycle accident is greater in conglomerate areas outside the metropolitan axis, and intervention measures should consider the economic, social and cultural contexts.

Interpretation of heavy rainfall spatial distribution in mountain watersheds by copula functions

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Balistrocchi, Matteo

2016-04-01

The spatial distribution of heavy rainfalls can strongly influence flood dynamics in mountain watersheds, depending on their geomorphologic features, namely orography, slope, land covers and soil types. Unfortunately, the direct observation of rainfall fields by meteorological radar is very difficult in this situation, so that interpolation of rain gauge observations or downscaling of meteorological predictions must be adopted to derive spatial rainfall distributions. To do so, various stochastic and physically based approaches are already available, even though the first one is the most familiar in hydrology. Indeed, Kriging interpolation procedures represent very popular techniques to face this problem by means of a stochastic approach. A certain number of restrictive assumptions and parameter uncertainties however affects Kriging. Many alternative formulations and additional procedures were therefore developed during the last decades. More recently, copula functions (Joe, 1997; Nelsen, 2006; Salvadori et al. 2007) were suggested to provide a more straightforward solution to carry out spatial interpolations of hydrologic variables (Bardossy & Pegram; 2009). Main advantages lie in the possibility of i) assessing the dependence structure relating to rainfall variables independently of marginal distributions, ii) expressing the association degree through rank correlation coefficients, iii) implementing marginal distributions and copula functions belonging to different models to develop complex joint distribution functions, iv) verifying the model reliability by effective statistical tests (Genest et al., 2009). A suitable case study to verify these potentialities is provided by the Taro River, a right-bank tributary of the Po River (northern Italy), whose contributing area amounts to about 2˙000 km2. The mountain catchment area is divided into two similar watersheds, so that spatial distribution is crucial in extreme flood event generation. A quite well diffused hydro-meteorological network, consisting of about 30 rain gauges and 10 hydrometers, monitors this medium-size watershed. A decade of rainfall-runoff event observations are available. Severe rainfall events were identified with reference to a main raingauge station, by using an interevent time definition and a depth threshold. Rainfall depths were thus derived and the spatial variability of their association degree was represented by using the Kendall coefficient. A unique copula model based on Gumbel copula function was finally found to be suitable to represent the dependence structure relating to rainfall depths observed in distinct raingauges. Bardossy A., Pegram G. (2009), Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299-2314. Genest C., Rémilland B., Beaudoin D. (2009), Goodness-of-fit tests for copulas: a review and a power study, Insur. Math. Econ., 44(2), 199-213. Joe H. (1997), Multivariate models and dependence concepts, Chapman and Hall, London. Nelsen R. B. (2006), An introduction to copulas, second ed., Springer, New York. Salvadori G., De Michele C., Kottegoda N. T., Rosso R. (2007), Extremes in nature: an approach using copulas, Springer, Dordrecht, The Nederlands.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton–proton collisions at $$\\sqrt s =$$ 8 TeV

DOE PAGES

Khachatryan, Vardan

2015-04-24

Our search is presented for quark contact interactions and extra spatial dimensions in proton–proton collisions at √s=8TeVusing dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7fb -1collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7)TeV formore » destructive (constructive) interference at 95% confidence level. Finally, lower limits between 5.9 and 8.4TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed–Dimopoulos–Dvali model of extra spatial dimensions.« less

The coalescent process in models with selection and recombination.

PubMed

Hudson, R R; Kaplan, N L

1988-11-01

The statistical properties of the process describing the genealogical history of a random sample of genes at a selectively neutral locus which is linked to a locus at which natural selection operates are investigated. It is found that the equations describing this process are simple modifications of the equations describing the process assuming that the two loci are completely linked. Thus, the statistical properties of the genealogical process for a random sample at a neutral locus linked to a locus with selection follow from the results obtained for the selected locus. Sequence data from the alcohol dehydrogenase (Adh) region of Drosophila melanogaster are examined and compared to predictions based on the theory. It is found that the spatial distribution of nucleotide differences between Fast and Slow alleles of Adh is very similar to the spatial distribution predicted if balancing selection operates to maintain the allozyme variation at the Adh locus. The spatial distribution of nucleotide differences between different Slow alleles of Adh do not match the predictions of this simple model very well.

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

A review on the sources and spatial-temporal distributions of Pb in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhang, Jie; Wang, Ming; Zhu, Sixi; Wu, Yunjie

2017-12-01

This paper provided a review on the source, spatial-distribution, temporal variations of Pb in Jiaozhou Bay based on investigation of Pb in surface and waters in different seasons during 1979-1983. The source strengths of Pb sources in Jiaozhou Bay were showing increasing trends, and the pollution level of Pb in this bay was slight or moderate in the early stage of reform and opening-up. Pb contents in the marine bay were mainly determined by the strength and frequency of Pb inputs from human activities, and Pb could be moving from high content areas to low content areas in the ocean interior. Surface waters in the ocean was polluted by human activities, and bottom waters was polluted by means of vertical water’s effect. The process of spatial distribution of Pb in waters was including three steps, i.e., 1), Pb was transferring to surface waters in the bay, 2) Pb was transferring to surface waters, and 3) Pb was transferring to and accumulating in bottom waters.

Forecasting the impact of transport improvements on commuting and residential choice

NASA Astrophysics Data System (ADS)

Elhorst, J. Paul; Oosterhaven, Jan

2006-03-01

This paper develops a probabilistic, competing-destinations, assignment model that predicts changes in the spatial pattern of the working population as a result of transport improvements. The choice of residence is explained by a new non-parametric model, which represents an alternative to the popular multinominal logit model. Travel times between zones are approximated by a normal distribution function with different mean and variance for each pair of zones, whereas previous models only use average travel times. The model’s forecast error of the spatial distribution of the Dutch working population is 7% when tested on 1998 base-year data. To incorporate endogenous changes in its causal variables, an almost ideal demand system is estimated to explain the choice of transport mode, and a new economic geography inter-industry model (RAEM) is estimated to explain the spatial distribution of employment. In the application, the model is used to forecast the impact of six mutually exclusive Dutch core-periphery railway proposals in the projection year 2020.

Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton-proton collisions at √{ s} = 8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Heister, A.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Raupach, F.; Sammet, J.; Schael, S.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Horton, D.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Md Ali, M. A. B.; Casimiro Linares, E.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Khurshid, T.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Karjavin, V.; Konoplyanikov, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Petrushanko, S.; Savrin, V.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Kao, K. Y.; Lei, Y. J.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.

2015-06-01

A search is presented for quark contact interactions and extra spatial dimensions in proton-proton collisions at √{ s} = 8 TeV using dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7 fb-1 collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7) TeV for destructive (constructive) interference at 95% confidence level. Lower limits between 5.9 and 8.4 TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed-Dimopoulos-Dvali model of extra spatial dimensions.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

PubMed

Torres, Leigh G; Read, Andrew J; Halpin, Patrick

2008-10-01

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Strategies for satellite-based monitoring of CO2 from distributed area and point sources

NASA Astrophysics Data System (ADS)

Schwandner, Florian M.; Miller, Charles E.; Duren, Riley M.; Natraj, Vijay; Eldering, Annmarie; Gunson, Michael R.; Crisp, David

2014-05-01

Atmospheric CO2 budgets are controlled by the strengths, as well as the spatial and temporal variabilities of CO2 sources and sinks. Natural CO2 sources and sinks are dominated by the vast areas of the oceans and the terrestrial biosphere. In contrast, anthropogenic and geogenic CO2 sources are dominated by distributed area and point sources, which may constitute as much as 70% of anthropogenic (e.g., Duren & Miller, 2012), and over 80% of geogenic emissions (Burton et al., 2013). Comprehensive assessments of CO2 budgets necessitate robust and highly accurate satellite remote sensing strategies that address the competing and often conflicting requirements for sampling over disparate space and time scales. Spatial variability: The spatial distribution of anthropogenic sources is dominated by patterns of production, storage, transport and use. In contrast, geogenic variability is almost entirely controlled by endogenic geological processes, except where surface gas permeability is modulated by soil moisture. Satellite remote sensing solutions will thus have to vary greatly in spatial coverage and resolution to address distributed area sources and point sources alike. Temporal variability: While biogenic sources are dominated by diurnal and seasonal patterns, anthropogenic sources fluctuate over a greater variety of time scales from diurnal, weekly and seasonal cycles, driven by both economic and climatic factors. Geogenic sources typically vary in time scales of days to months (geogenic sources sensu stricto are not fossil fuels but volcanoes, hydrothermal and metamorphic sources). Current ground-based monitoring networks for anthropogenic and geogenic sources record data on minute- to weekly temporal scales. Satellite remote sensing solutions would have to capture temporal variability through revisit frequency or point-and-stare strategies. Space-based remote sensing offers the potential of global coverage by a single sensor. However, no single combination of orbit and sensor provides the full range of temporal sampling needed to characterize distributed area and point source emissions. For instance, point source emission patterns will vary with source strength, wind speed and direction. Because wind speed, direction and other environmental factors change rapidly, short term variabilities should be sampled. For detailed target selection and pointing verification, important lessons have already been learned and strategies devised during JAXA's GOSAT mission (Schwandner et al, 2013). The fact that competing spatial and temporal requirements drive satellite remote sensing sampling strategies dictates a systematic, multi-factor consideration of potential solutions. Factors to consider include vista, revisit frequency, integration times, spatial resolution, and spatial coverage. No single satellite-based remote sensing solution can address this problem for all scales. It is therefore of paramount importance for the international community to develop and maintain a constellation of atmospheric CO2 monitoring satellites that complement each other in their temporal and spatial observation capabilities: Polar sun-synchronous orbits (fixed local solar time, no diurnal information) with agile pointing allow global sampling of known distributed area and point sources like megacities, power plants and volcanoes with daily to weekly temporal revisits and moderate to high spatial resolution. Extensive targeting of distributed area and point sources comes at the expense of reduced mapping or spatial coverage, and the important contextual information that comes with large-scale contiguous spatial sampling. Polar sun-synchronous orbits with push-broom swath-mapping but limited pointing agility may allow mapping of individual source plumes and their spatial variability, but will depend on fortuitous environmental conditions during the observing period. These solutions typically have longer times between revisits, limiting their ability to resolve temporal variations. Geostationary and non-sun-synchronous low-Earth-orbits (precessing local solar time, diurnal information possible) with agile pointing have the potential to provide, comprehensive mapping of distributed area sources such as megacities with longer stare times and multiple revisits per day, at the expense of global access and spatial coverage. An ad hoc CO2 remote sensing constellation is emerging. NASA's OCO-2 satellite (launch July 2014) joins JAXA's GOSAT satellite in orbit. These will be followed by GOSAT-2 and NASA's OCO-3 on the International Space Station as early as 2017. Additional polar orbiting satellites (e.g., CarbonSat, under consideration at ESA) and geostationary platforms may also become available. However, the individual assets have been designed with independent science goals and requirements, and limited consideration of coordinated observing strategies. Every effort must be made to maximize the science return from this constellation. We discuss the opportunities to exploit the complementary spatial and temporal coverage provided by these assets as well as the crucial gaps in the capabilities of this constellation. References Burton, M.R., Sawyer, G.M., and Granieri, D. (2013). Deep carbon emissions from volcanoes. Rev. Mineral. Geochem. 75: 323-354. Duren, R.M., Miller, C.E. (2012). Measuring the carbon emissions of megacities. Nature Climate Change 2, 560-562. Schwandner, F.M., Oda, T., Duren, R., Carn, S.A., Maksyutov, S., Crisp, D., Miller, C.E. (2013). Scientific Opportunities from Target-Mode Capabilities of GOSAT-2. NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA, White Paper, 6p., March 2013.

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

Correlation between local hemodynamics and lesion distribution in a novel aortic regurgitation murine model of atherosclerosis.

PubMed

Hoi, Yiemeng; Zhou, Yu-Qing; Zhang, Xiaoli; Henkelman, R Mark; Steinman, David A

2011-05-01

Following surgical induction of aortic valve regurgitation (AR), extensive atherosclerotic plaque development along the descending thoracic and abdominal aorta of Ldlr⁻/⁻ mice has been reported, with distinct spatial distributions suggestive of a strong local hemodynamic influence. The objective of this study was to test, using image-based computational fluid dynamics (CFD), whether this is indeed the case. The lumen geometry was reconstructed from micro-CT scanning of a control Ldlr⁻/⁻ mouse, and CFD simulations were carried out for both AR and control flow conditions derived from Doppler ultrasound measurements and literature data. Maps of time-averaged wall shear stress magnitude (TAWSS), oscillatory shear index (OSI) and relative residence time (RRT) were compared against the spatial distributions of plaque stained with oil red O, previously acquired in a group of AR and control mice. Maps of OSI and RRT were found to be consistent with plaque distributions in the AR mice and the absence of plaque in the control mice. TAWSS was uniformly lower under control vs. AR flow conditions, suggesting that levels (> 100 dyn/cm²) exceeded those required to alone induce a pro-atherogenic response. Simulations of a straightened CFD model confirmed the importance of anatomical curvature for explaining the spatial distribution of lesions in the AR mice. In summary, oscillatory and retrograde flow induced in the AR mice, without concomitant low shear, may exacerbate or accelerate lesion formation, but the distinct anatomical curvature of the mouse aorta is responsible for the spatial distribution of lesions.

Sex differences in the spatial distribution of bone in relation to incident hip fracture: Findings from the AGES-Reykjavik study.

PubMed

Marques, Elisa A; Carballido-Gamio, Julio; Gudnason, Vilmundur; Sigurdsson, Gunnar; Sigurdsson, Sigurdur; Aspelund, Thor; Siggeirsdottir, Kristin; Launer, Lenore; Eiriksdottir, Gudny; Lang, Thomas; Harris, Tamara B

2018-05-16

In this case-cohort study, we used data-driven computational anatomy approaches to assess within and between sex spatial differences in proximal femoral bone characteristics in relation to incident hip fracture. One hundred male and 234 female incident hip fracture cases, and 1047 randomly selected noncase subcohort participants (562 female) were chosen from the population-based AGES-Reykjavik study (mean age of 77 years). The baseline -i.e. before hip fracture- hip quantitative computed tomography scans of these subjects were analyzed using voxel-based morphometry, tensor-based morphometry, and surface-based statistical parametric mapping to assess the spatial distribution of volumetric bone mineral density (vBMD), internal structure, and cortical bone properties (thickness, vBMD and trabecular vBMD adjacent to the endosteal surface) of the proximal femur, respectively, in relation to incident hip fracture. Results showed that in both men and women: 1) the superior aspect of the femoral neck and the trochanteric region (except for cortical bone thickness) were consistently identified as being associated with incident hip fracture, and 2) differences in bone properties between noncases and incident hip fracture cases followed similar trends, were located at compatible regions, and manifested heterogeneity in the spatial distribution of their magnitude with focal regions showing larger differences. With respect to sex differences, most of the regions with a significant interaction between fracture group and sex showed: 1) differences of greater magnitude in men between noncases and incident hip fracture cases with different spatial distributions for all bone properties with the exception of cortical bone thickness, and 2) that while most of these regions showed better bone quality in male cases than in female cases, female cases showed higher vBMD in the principal compressive group and higher endotrabecular vBMD at several regions including the anterior, posterior, and lateral aspects of the proximal femur. These findings indicate the value of these image analysis techniques by providing unique information about the specific patterns of bone deterioration associated with incident hip fracture and their sex differences, highlighting the importance of looking to men and women separately in the assessment of hip fracture risk. Copyright © 2017. Published by Elsevier Inc.

Geophysical mapping of palsa peatland permafrost

NASA Astrophysics Data System (ADS)

Sjöberg, Y.; Marklund, P.; Pettersson, R.; Lyon, S. W.

2014-10-01

Permafrost peatlands are hydrological and biogeochemical hotspots in the discontinuous permafrost zone. Non-intrusive geophysical methods offer possibility to map current permafrost spatial distributions in these environments. In this study, we estimate the depths to the permafrost table surface and base across a peatland in northern Sweden, using ground penetrating radar and electrical resistivity tomography. Seasonal thaw frost tables (at ~0.5 m depth), taliks (2.1-6.7 m deep), and the permafrost base (at ~16 m depth) could be detected. Higher occurrences of taliks were discovered at locations with a lower relative height of permafrost landforms indicative of lower ground ice content at these locations. These results highlight the added value of combining geophysical techniques for assessing spatial distribution of permafrost within the rapidly changing sporadic permafrost zone. For example, based on a simple thought experiment for the site considered here, we estimated that the thickest permafrost could thaw out completely within the next two centuries. There is a clear need, thus, to benchmark current permafrost distributions and characteristics particularly in under studied regions of the pan-arctic.

Geophysical mapping of palsa peatland permafrost

NASA Astrophysics Data System (ADS)

Sjöberg, Y.; Marklund, P.; Pettersson, R.; Lyon, S. W.

2015-03-01

Permafrost peatlands are hydrological and biogeochemical hotspots in the discontinuous permafrost zone. Non-intrusive geophysical methods offer a possibility to map current permafrost spatial distributions in these environments. In this study, we estimate the depths to the permafrost table and base across a peatland in northern Sweden, using ground penetrating radar and electrical resistivity tomography. Seasonal thaw frost tables (at ~0.5 m depth), taliks (2.1-6.7 m deep), and the permafrost base (at ~16 m depth) could be detected. Higher occurrences of taliks were discovered at locations with a lower relative height of permafrost landforms, which is indicative of lower ground ice content at these locations. These results highlight the added value of combining geophysical techniques for assessing spatial distributions of permafrost within the rapidly changing sporadic permafrost zone. For example, based on a back-of-the-envelope calculation for the site considered here, we estimated that the permafrost could thaw completely within the next 3 centuries. Thus there is a clear need to benchmark current permafrost distributions and characteristics, particularly in under studied regions of the pan-Arctic.

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950-2008) (V. 2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2011-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2015)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA)

2015-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2010) (V. 2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2013-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2009) (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2012-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree latitude by One Degree Longitude (V. 2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA).

2013-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Water quality modeling in the dead end sections of drinking water distribution networks.

PubMed

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Teuling, Adriaan J.; Torfs, Paul J. J. F.; Uijlenhoet, Remko; Mizukami, Naoki; Clark, Martyn P.

2016-03-01

A meta-analysis on 192 peer-reviewed articles reporting on applications of the variable infiltration capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, L. A.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.; Mizukami, N.; Clark, M. P.

2015-12-01

A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

Maximum Regional Emission Reduction Potential in Residential Sector Based on Spatial Distribution of Population and Resources

NASA Astrophysics Data System (ADS)

Winijkul, E.; Bond, T. C.

2011-12-01

In the residential sector, major activities that generate emissions are cooking and heating, and fuels ranging from traditional (wood) to modern (natural gas, or electricity) are used. Direct air pollutant emissions from this sector are low when natural gas or electricity are the dominant energy sources, as is the case in developed countries. However, in developing countries, people may rely on solid fuels and this sector can contribute a large fraction of emissions. The magnitude of the health loss associated with exposure to indoor smoke as well as its concentration among rural population in developing countries have recently put preventive measures high on the agenda of international development and public health organizations. This study focuses on these developing regions: Central America, Africa, and Asia. Current and future emissions from the residential sector depend on both fuel and cooking device (stove) type. Availability of fuels, stoves, and interventions depends strongly on spatial distribution. However, regional emission calculations do not consider this spatial dependence. Fuel consumption data is presented at country level, without information about where different types of fuel are used. Moreover, information about stove types that are currently used and can be used in the future is not available. In this study, we first spatially allocate current emissions within residential sector. We use Geographic Information System maps of temperature, electricity availability, forest area, and population to determine the distribution of fuel types and availability of stoves. Within each country, consumption of different fuel types, such as fuelwood, coal, and LPG is distributed among different area types (urban, peri-urban, and rural area). Then, the cleanest stove technologies which could be used in the area are selected based on the constraints of each area, i.e. availability of resources. Using this map, the maximum emission reduction compared with current emission in residential sector can be estimated, based on the cleanest plausible fuels and stove availability.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

NASA Astrophysics Data System (ADS)

Felix, Simon; Bolzern, Roman; Battaglia, Marina

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation ofmore » quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.« less

Exploration of Urban Spatial Planning Evaluation Based on Humanland Harmony

NASA Astrophysics Data System (ADS)

Hu, X. S.; Ma, Q. R.; Liang, W. Q.; Wang, C. X.; Xiong, X. Q.; Han, X. H.

2017-09-01

This study puts forward a new concept, "population urbanization level forecast - driving factor analysis - urban spatial planning analysis" for achieving efficient and intensive development of urbanization considering human-land harmony. We analyzed big data for national economic and social development, studied the development trends of population urbanization and its influencing factors using the grey system model in Chengmai county of Hainan province, China. In turn, we calculated the population of Chengmai coming years based on the forecasting urbanization rate and the corresponding amount of urban construction land, and evaluated the urban spatial planning with GIS spatial analysis method in the study area. The result shows that the proposed concept is feasible for evaluation of urban spatial planning, and is meaningful for guiding the rational distribution of urban space, controlling the scale of development, improving the quality of urbanization and thus promoting highly-efficient and intensive use of limited land resource.

Daylight operation of a free space, entanglement-based quantum key distribution system

NASA Astrophysics Data System (ADS)

Peloso, Matthew P.; Gerhardt, Ilja; Ho, Caleb; Lamas-Linares, Antía; Kurtsiefer, Christian

2009-04-01

Many quantum key distribution (QKD) implementations using a free space transmission path are restricted to operation at night time in order to distinguish the signal photons used for a secure key establishment from the background light. Here, we present a lean entanglement-based QKD system overcoming that limitation. By implementing spectral, spatial and temporal filtering techniques, we establish a secure key continuously over several days under varying light and weather conditions.

Spatial analysis of lipid metabolites and expressed genes reveals tissue-specific heterogeneity of lipid metabolism in high- and low-oil Brassica napus L. seeds.

PubMed

Lu, Shaoping; Sturtevant, Drew; Aziz, Mina; Jin, Cheng; Li, Qing; Chapman, Kent D; Guo, Liang

2018-06-01

Despite the importance of oilseeds to worldwide human nutrition, and more recently to the production of bio-based diesel fuels, the detailed mechanisms regulating seed oil biosynthesis remain only partly understood, especially from a tissue-specific perspective. Here, we investigated the spatial distributions of lipid metabolites and transcripts involved in oil biosynthesis from seeds of two low-erucic acid genotypes of Brassica napus with high and low seed-oil content. Integrated results from matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of lipids in situ, lipidome profiling of extracts from seed tissues, and tissue-specific transcriptome analysis revealed complex spatial distribution patterns of lipids and transcripts. In general, it appeared that many triacylglycerol and phosphatidylcholine species distributed heterogeneously throughout the embryos. Tissue-specific transcriptome analysis identified key genes involved in de novo fatty acid biosynthesis in plastid, triacylglycerols assembly and lipid droplet packaging in the endoplasmic reticulum (ER) that may contribute to the high or low oil phenotype and heterogeneity of lipid distribution. Our results imply that transcriptional regulation represents an important means of impacting lipid compartmentalization in oil seeds. While much information remains to be learned about the intricacies of seed oil accumulation and distribution, these studies highlight the advances that come from evaluating lipid metabolism within a spatial context and with multiple omics level datasets. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Revised spatially distributed global livestock emissions

NASA Astrophysics Data System (ADS)

Asrar, G.; Wolf, J.; West, T. O.

2015-12-01

Livestock play an important role in agricultural carbon cycling through consumption of biomass and emissions of methane. Quantification and spatial distribution of methane and carbon dioxide produced by livestock is needed to develop bottom-up estimates for carbon monitoring. These estimates serve as stand-alone international emissions estimates, as input to global emissions modeling, and as comparisons or constraints to flux estimates from atmospheric inversion models. Recent results for the US suggest that the 2006 IPCC default coefficients may underestimate livestock methane emissions. In this project, revised coefficients were calculated for cattle and swine in all global regions, based on reported changes in body mass, quality and quantity of feed, milk production, and management of living animals and manure for these regions. New estimates of livestock methane and carbon dioxide emissions were calculated using the revised coefficients and global livestock population data. Spatial distribution of population data and associated fluxes was conducted using the MODIS Land Cover Type 5, version 5.1 (i.e. MCD12Q1 data product), and a previously published downscaling algorithm for reconciling inventory and satellite-based land cover data at 0.05 degree resolution. Preliminary results for 2013 indicate greater emissions than those calculated using the IPCC 2006 coefficients. Global total enteric fermentation methane increased by 6%, while manure management methane increased by 38%, with variation among species and regions resulting in improved spatial distributions of livestock emissions. These new estimates of total livestock methane are comparable to other recently reported studies for the entire US and the State of California. These new regional/global estimates will improve the ability to reconcile top-down and bottom-up estimates of methane production as well as provide updated global estimates for use in development and evaluation of Earth system models.

Spatial distribution of solute leaching with snowmelt and irrigation: measurements and simulations

NASA Astrophysics Data System (ADS)

Schotanus, D.; van der Ploeg, M. J.; van der Zee, S. E. A. T. M.

2013-04-01

Transport of a tracer and a degradable solute in a heterogeneous soil was measured in the field, and simulated with several transient and steady state infiltration rates. Leaching surfaces were used to investigate the solute leaching in space and time simultaneously. In the simulations, a random field for the scaling factor in the retention curve was used for the heterogeneous soil, which was based on the spatial distribution of drainage in an experiment with a multi-compartment sampler. As a criterion to compare the results from simulations and observations, the sorted and cumulative total drainage in a cell was used. The effect of the ratio of the infiltration rate over the degradation rate on leaching of degradable solutes was investigated. Furthermore, the spatial distribution of the leaching of degradable and non-degradable solutes was compared. The infiltration rate determines the amount of leaching of the degradable solute. This can be partly explained by a decreasing travel time with an increasing infiltration rate. The spatial distribution of the leaching also depends on the infiltration rate. When the infiltration rate is high compared to the degradation rate, the leaching of the degradable solute is similar as for the tracer. The fraction of the pore space of the soil that contributes to solute leaching increases with an increasing infiltration rate. This fraction is similar for a tracer and a degradable solute. With increasing depth, the leaching becomes more homogeneous, as a result of dispersion. The spatial distribution of the solute leaching is different under different transient infiltration rates, therefore, also the amount of leaching is different. With independent stream tube approaches, this effect would be ignored.

Spatial distribution of solute leaching with snowmelt and irrigation: measurements and simulations

NASA Astrophysics Data System (ADS)

Schotanus, D.; van der Ploeg, M. J.; van der Zee, S. E. A. T. M.

2012-12-01

Transport of a tracer and a degradable solute in a heterogeneous soil was measured in the field, and simulated with several transient and steady state infiltration rates. Leaching surfaces were used to investigate the solute leaching in space and time simultaneously. In the simulations, a random field for the scaling factor in the retention curve was used for the heterogeneous soil, which was based on the spatial distribution of drainage in an experiment with a multi-compartment sampler. As a criterion to compare the results from simulations and observations, the sorted and cumulative total drainage in a cell was used. The effect of the ratio of the infiltration rate over the degradation rate on leaching of degradable solutes was investigated. Furthermore, the spatial distribution of the leaching of degradable and non-degradable solutes was compared. The infiltration rate determines the amount of leaching of the degradable solute. This can be partly explained by a decreasing travel time with an increasing infiltration rate. The spatial distribution of the leaching also depends on the infiltration rate. When the infiltration rate is high compared to the degradation rate, the leaching of the degradable solute is similar as for the tracer. The fraction of the soil that contributes to solute leaching increases with an increasing infiltration rate. This fraction is similar for a tracer and a degradable solute. With increasing depth, the leaching becomes more homogeneous, as a result of dispersion. The spatial distribution of the solute leaching is different under different transient infiltration rates, therefore also the amount of leaching is different. With independent stream tube approaches, this effect would be ignored.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.