Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

NASA Astrophysics Data System (ADS)

Geng, Guannan; Zhang, Qiang; Martin, Randall V.; Lin, Jintai; Huo, Hong; Zheng, Bo; Wang, Siwen; He, Kebin

2017-03-01

Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope = 1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

Modelling the spatial distribution of SO2 and NOx emissions in Ireland.

PubMed

de Kluizenaar, Y; Aherne, J; Farrell, E P

2001-01-01

The spatial distributions of sulphur dioxide (SO2) and nitrogen oxides (NOx) emissions are essential inputs to models of atmospheric transport and deposition. Information of this type is required for international negotiations on emission reduction through the critical load approach. High-resolution emission maps for the Republic of Ireland have been created using emission totals and a geographical information system, supported by surrogate statistics and landcover information. Data have been subsequently allocated to the EMEP 50 x 50-km grid, used in long-range transport models for the investigation of transboundary air pollution. Approximately two-thirds of SO2 emissions in Ireland emanate from two grid-squares. Over 50% of total SO2 emissions originate from one grid-square in the west of Ireland, where the largest point sources of SO2 are located. Approximately 15% of the total SO2 emissions originate from the grid-square containing Dublin. SO2 emission densities for the remaining areas are very low, < 1 t km-2 year-1 for most grid-squares. NOx emissions show a very similar distribution pattern. However, NOx emissions are more evenly spread over the country, as about 40% of total NOx emissions originate from road transport.

The Semantic Retrieval of Spatial Data Service Based on Ontology in SIG

NASA Astrophysics Data System (ADS)

Sun, S.; Liu, D.; Li, G.; Yu, W.

2011-08-01

The research of SIG (Spatial Information Grid) mainly solves the problem of how to connect different computing resources, so that users can use all the resources in the Grid transparently and seamlessly. In SIG, spatial data service is described in some kinds of specifications, which use different meta-information of each kind of services. This kind of standardization cannot resolve the problem of semantic heterogeneity, which may limit user to obtain the required resources. This paper tries to solve two kinds of semantic heterogeneities (name heterogeneity and structure heterogeneity) in spatial data service retrieval based on ontology, and also, based on the hierarchical subsumption relationship among concept in ontology, the query words can be extended and more resource can be matched and found for user. These applications of ontology in spatial data resource retrieval can help to improve the capability of keyword matching, and find more related resources.

A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

USGS Publications Warehouse

Wang, Lizhu; Riseng, Catherine M.; Mason, Lacey; Werhrly, Kevin; Rutherford, Edward; McKenna, James E.; Castiglione, Chris; Johnson, Lucinda B.; Infante, Dana M.; Sowa, Scott P.; Robertson, Mike; Schaeffer, Jeff; Khoury, Mary; Gaiot, John; Hollenhurst, Tom; Brooks, Colin N.; Coscarelli, Mark

2015-01-01

Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

Context-dependent spatially periodic activity in the human entorhinal cortex

PubMed Central

Nguyen, T. Peter; Török, Ágoston; Shen, Jason Y.; Briggs, Deborah E.; Modur, Pradeep N.; Buchanan, Robert J.

2017-01-01

The spatially periodic activity of grid cells in the entorhinal cortex (EC) of the rodent, primate, and human provides a coordinate system that, together with the hippocampus, informs an individual of its location relative to the environment and encodes the memory of that location. Among the most defining features of grid-cell activity are the 60° rotational symmetry of grids and preservation of grid scale across environments. Grid cells, however, do display a limited degree of adaptation to environments. It remains unclear if this level of environment invariance generalizes to human grid-cell analogs, where the relative contribution of visual input to the multimodal sensory input of the EC is significantly larger than in rodents. Patients diagnosed with nontractable epilepsy who were implanted with entorhinal cortical electrodes performing virtual navigation tasks to memorized locations enabled us to investigate associations between grid-like patterns and environment. Here, we report that the activity of human entorhinal cortical neurons exhibits adaptive scaling in grid period, grid orientation, and rotational symmetry in close association with changes in environment size, shape, and visual cues, suggesting scale invariance of the frequency, rather than the wavelength, of spatially periodic activity. Our results demonstrate that neurons in the human EC represent space with an enhanced flexibility relative to neurons in rodents because they are endowed with adaptive scalability and context dependency. PMID:28396399

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Hippocampal Remapping Is Constrained by Sparseness rather than Capacity

PubMed Central

Kammerer, Axel; Leibold, Christian

2014-01-01

Grid cells in the medial entorhinal cortex encode space with firing fields that are arranged on the nodes of spatial hexagonal lattices. Potential candidates to read out the space information of this grid code and to combine it with other sensory cues are hippocampal place cells. In this paper, we investigate a population of grid cells providing feed-forward input to place cells. The capacity of the underlying synaptic transformation is determined by both spatial acuity and the number of different spatial environments that can be represented. The codes for different environments arise from phase shifts of the periodical entorhinal cortex patterns that induce a global remapping of hippocampal place fields, i.e., a new random assignment of place fields for each environment. If only a single environment is encoded, the grid code can be read out at high acuity with only few place cells. A surplus in place cells can be used to store a space code for more environments via remapping. The number of stored environments can be increased even more efficiently by stronger recurrent inhibition and by partitioning the place cell population such that learning affects only a small fraction of them in each environment. We find that the spatial decoding acuity is much more resilient to multiple remappings than the sparseness of the place code. Since the hippocampal place code is sparse, we thus conclude that the projection from grid cells to the place cells is not using its full capacity to transfer space information. Both populations may encode different aspects of space. PMID:25474570

CheckDen, a program to compute quantum molecular properties on spatial grids.

PubMed

Pacios, Luis F; Fernandez, Alberto

2009-09-01

CheckDen, a program to compute quantum molecular properties on a variety of spatial grids is presented. The program reads as unique input wavefunction files written by standard quantum packages and calculates the electron density rho(r), promolecule and density difference function, gradient of rho(r), Laplacian of rho(r), information entropy, electrostatic potential, kinetic energy densities G(r) and K(r), electron localization function (ELF), and localized orbital locator (LOL) function. These properties can be calculated on a wide range of one-, two-, and three-dimensional grids that can be processed by widely used graphics programs to render high-resolution images. CheckDen offers also other options as extracting separate atom contributions to the property computed, converting grid output data into CUBE and OpenDX volumetric data formats, and perform arithmetic combinations with grid files in all the recognized formats.

Grid scale drives the scale and long-term stability of place maps

PubMed Central

Mallory, Caitlin S; Hardcastle, Kiah; Bant, Jason S; Giocomo, Lisa M

2018-01-01

Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally-defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here, we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory. PMID:29335607

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

NASA Astrophysics Data System (ADS)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.

Implementation of data node in spatial information grid based on WS resource framework and WS notification

NASA Astrophysics Data System (ADS)

Zhang, Dengrong; Yu, Le

2006-10-01

Abstract-An approach of constructing a data node in spatial information grid (SIG) based on Web Service Resource Framework (WSRF) and Web Service Notification (WSN) is described in this paper. Attentions are paid to construct and implement SIG's resource layer, which is the most important part. A study on this layer find out, it is impossible to require persistent interaction with the clients of the services in common SIG architecture because of inheriting "stateless" and "not persistent" limitations of Web Service. A WSRF/WSN-based data node is designed to hurdle this short comes. Three different access modes are employed to test the availability of this node. Experimental results demonstrate this service node can successfully respond to standard OGC requests and returns specific spatial data in different network environment, also is stateful, dynamic and persistent.

A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

Grid computing enhances standards-compatible geospatial catalogue service

NASA Astrophysics Data System (ADS)

Chen, Aijun; Di, Liping; Bai, Yuqi; Wei, Yaxing; Liu, Yang

2010-04-01

A catalogue service facilitates sharing, discovery, retrieval, management of, and access to large volumes of distributed geospatial resources, for example data, services, applications, and their replicas on the Internet. Grid computing provides an infrastructure for effective use of computing, storage, and other resources available online. The Open Geospatial Consortium has proposed a catalogue service specification and a series of profiles for promoting the interoperability of geospatial resources. By referring to the profile of the catalogue service for Web, an innovative information model of a catalogue service is proposed to offer Grid-enabled registry, management, retrieval of and access to geospatial resources and their replicas. This information model extends the e-business registry information model by adopting several geospatial data and service metadata standards—the International Organization for Standardization (ISO)'s 19115/19119 standards and the US Federal Geographic Data Committee (FGDC) and US National Aeronautics and Space Administration (NASA) metadata standards for describing and indexing geospatial resources. In order to select the optimal geospatial resources and their replicas managed by the Grid, the Grid data management service and information service from the Globus Toolkits are closely integrated with the extended catalogue information model. Based on this new model, a catalogue service is implemented first as a Web service. Then, the catalogue service is further developed as a Grid service conforming to Grid service specifications. The catalogue service can be deployed in both the Web and Grid environments and accessed by standard Web services or authorized Grid services, respectively. The catalogue service has been implemented at the George Mason University/Center for Spatial Information Science and Systems (GMU/CSISS), managing more than 17 TB of geospatial data and geospatial Grid services. This service makes it easy to share and interoperate geospatial resources by using Grid technology and extends Grid technology into the geoscience communities.

Absence of Visual Input Results in the Disruption of Grid Cell Firing in the Mouse.

PubMed

Chen, Guifen; Manson, Daniel; Cacucci, Francesca; Wills, Thomas Joseph

2016-09-12

Grid cells are spatially modulated neurons within the medial entorhinal cortex whose firing fields are arranged at the vertices of tessellating equilateral triangles [1]. The exquisite periodicity of their firing has led to the suggestion that they represent a path integration signal, tracking the organism's position by integrating speed and direction of movement [2-10]. External sensory inputs are required to reset any errors that the path integrator would inevitably accumulate. Here we probe the nature of the external sensory inputs required to sustain grid firing, by recording grid cells as mice explore familiar environments in complete darkness. The absence of visual cues results in a significant disruption of grid cell firing patterns, even when the quality of the directional information provided by head direction cells is largely preserved. Darkness alters the expression of velocity signaling within the entorhinal cortex, with changes evident in grid cell firing rate and the local field potential theta frequency. Short-term (<1.5 s) spike timing relationships between grid cell pairs are preserved in the dark, indicating that network patterns of excitatory and inhibitory coupling between grid cells exist independently of visual input and of spatially periodic firing. However, we find no evidence of preserved hexagonal symmetry in the spatial firing of single grid cells at comparable short timescales. Taken together, these results demonstrate that visual input is required to sustain grid cell periodicity and stability in mice and suggest that grid cells in mice cannot perform accurate path integration in the absence of reliable visual cues. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

DOE PAGES

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

2016-12-05

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughoutmore » this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2 σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.« less

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

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

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughoutmore » this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2 σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.« less

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

NASA Astrophysics Data System (ADS)

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

2016-12-01

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4-190 %, with an average of 120 % (2σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Smoothing effect for spatially distributed renewable resources and its impact on power grid robustness.

PubMed

Nagata, Motoki; Hirata, Yoshito; Fujiwara, Naoya; Tanaka, Gouhei; Suzuki, Hideyuki; Aihara, Kazuyuki

2017-03-01

In this paper, we show that spatial correlation of renewable energy outputs greatly influences the robustness of the power grids against large fluctuations of the effective power. First, we evaluate the spatial correlation among renewable energy outputs. We find that the spatial correlation of renewable energy outputs depends on the locations, while the influence of the spatial correlation of renewable energy outputs on power grids is not well known. Thus, second, by employing the topology of the power grid in eastern Japan, we analyze the robustness of the power grid with spatial correlation of renewable energy outputs. The analysis is performed by using a realistic differential-algebraic equations model. The results show that the spatial correlation of the energy resources strongly degrades the robustness of the power grid. Our results suggest that we should consider the spatial correlation of the renewable energy outputs when estimating the stability of power grids.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

PubMed Central

Towse, Benjamin W.; Barry, Caswell; Bush, Daniel; Burgess, Neil

2014-01-01

We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues. PMID:24366144

SoilGrids250m: Global gridded soil information based on machine learning

PubMed Central

Mendes de Jesus, Jorge; Heuvelink, Gerard B. M.; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods—random forest and gradient boosting and/or multinomial logistic regression—as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10–fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License. PMID:28207752

SoilGrids250m: Global gridded soil information based on machine learning.

PubMed

Hengl, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B M; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A; Batjes, Niels H; Leenaars, Johan G B; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data.

PubMed

Wu, Jidong; Li, Ying; Li, Ning; Shi, Peijun

2018-01-01

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time. © 2017 Society for Risk Analysis.

Spatial Distribution of Bed Particles in Natural Boulder-Bed Streams

NASA Astrophysics Data System (ADS)

Clancy, K. F.; Prestegaard, K. L.

2001-12-01

The Wolman pebble count is used to obtain the size distribution of bed particles in natural streams. Statistics such as median particle size (D50) are used in resistance calculations. Additional information such as bed particle heterogeneity may also be obtained from the particle distribution, which is used to predict sediment transport rates (Hey, 1979), (Ferguson, Prestegaard, Ashworth, 1989). Boulder-bed streams have an extreme range of particles in the particle size distribution ranging from sand size particles to particles larger than 0.5-m. A study of a natural boulder-bed reach demonstrated that the spatial distribution of the particles is a significant factor in predicting sediment transport and stream bed and bank stability. Further experiments were performed to test the limits of the spatial distribution's effect on sediment transport. Three stream reaches 40-m in length were selected with similar hydrologic characteristics and spatial distributions but varying average size particles. We used a grid 0.5 by 0.5-m and measured four particles within each grid cell. Digital photographs of the streambed were taken in each grid cell. The photographs were examined using image analysis software to obtain particle size and position of the largest particles (D84) within the reach's particle distribution. Cross section, topography and stream depth were surveyed. Velocity and velocity profiles were measured and recorded. With these data and additional surveys of bankfull floods, we tested the significance of the spatial distributions as average particle size decreases. The spatial distribution of streambed particles may provide information about stream valley formation, bank stability, sediment transport, and the growth rate of riparian vegetation.

Biogenic Emission Sources

EPA Pesticide Factsheets

Biogenic emissions sources come from natural sources and need to accounted for in photochemical grid models. They are computed using a model which utilizes spatial information on vegetation and land use.

Intelligent automated surface grid generation

NASA Technical Reports Server (NTRS)

Yao, Ke-Thia; Gelsey, Andrew

1995-01-01

The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.

Research on the architecture and key technologies of SIG

NASA Astrophysics Data System (ADS)

Fu, Zhongliang; Meng, Qingxiang; Huang, Yan; Liu, Shufan

2007-06-01

Along with the development of computer network, Grid has become one of the hottest issues of researches on sharing and cooperation of Internet resources throughout the world. This paper illustrates a new architecture of SIG-a five-hierarchy architecture (including Data Collecting Layer, Grid Layer, Service Layer, Application Layer and Client Layer) of SIG from the traditional three hierarchies (only including resource layer, service layer and client layer). In the paper, the author proposes a new mixed network mode of Spatial Information Grid which integrates CAG (Certificate Authority of Grid) and P2P (Peer to Peer) in the Grid Layer, besides, the author discusses some key technologies of SIG and analysis the functions of these key technologies.

Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.

2018-01-01

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain may improve its representation, particularly for basins whose orientations (e.g., windward-facing) are favored for orographic precipitation enhancement.

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

NASA Astrophysics Data System (ADS)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

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.

SoilInfo App: global soil information on your palm

NASA Astrophysics Data System (ADS)

Hengl, Tomislav; Mendes de Jesus, Jorge

2015-04-01

ISRIC ' World Soil Information has released in 2014 and app for mobile de- vices called 'SoilInfo' (http://soilinfo-app.org) and which aims at providing free access to the global soil data. SoilInfo App (available for Android v.4.0 Ice Cream Sandwhich or higher, and Apple v.6.x and v.7.x iOS) currently serves the Soil- Grids1km data ' a stack of soil property and class maps at six standard depths at a resolution of 1 km (30 arc second) predicted using automated geostatistical mapping and global soil data models. The list of served soil data includes: soil organic carbon (), soil pH, sand, silt and clay fractions (%), bulk density (kg/m3), cation exchange capacity of the fine earth fraction (cmol+/kg), coarse fragments (%), World Reference Base soil groups, and USDA Soil Taxonomy suborders (DOI: 10.1371/journal.pone.0105992). New soil properties and classes will be continuously added to the system. SoilGrids1km are available for download under a Creative Commons non-commercial license via http://soilgrids.org. They are also accessible via a Representational State Transfer API (http://rest.soilgrids.org) service. SoilInfo App mimics common weather apps, but is also largely inspired by the crowdsourcing systems such as the OpenStreetMap, Geo-wiki and similar. Two development aspects of the SoilInfo App and SoilGrids are constantly being worked on: Data quality in terms of accuracy of spatial predictions and derived information, and Data usability in terms of ease of access and ease of use (i.e. flexibility of the cyberinfrastructure / functionalities such as the REST SoilGrids API, SoilInfo App etc). The development focus in 2015 is on improving the thematic and spatial accuracy of SoilGrids predictions, primarily by using finer resolution covariates (250 m) and machine learning algorithms (such as random forests) to improve spatial predictions.

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 2: User's manual and program listing

NASA Technical Reports Server (NTRS)

Bailey, R. T.; Shih, T. I.-P.; Nguyen, H. L.; Roelke, R. J.

1990-01-01

An efficient computer program, called GRID2D/3D, was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. The theory and method used in GRID2D/3D is described.

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 1: Theory and method

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Bailey, R. T.; Nguyen, H. L.; Roelke, R. J.

1990-01-01

An efficient computer program, called GRID2D/3D was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. This technical memorandum describes the theory and method used in GRID2D/3D.

Influence of conversion on the location of points and lines: The change of location entropy and the probability of a vector point inside the converted grid point

NASA Astrophysics Data System (ADS)

Chen, Nan

2018-03-01

Conversion of points or lines from vector to grid format, or vice versa, is the first operation required for most spatial analysis. Conversion, however, usually causes the location of points or lines to change, which influences the reliability of the results of spatial analysis or even results in analysis errors. The purpose of this paper is to evaluate the change of the location of points and lines during conversion using the concepts of probability and entropy. This paper shows that when a vector point is converted to a grid point, the vector point may be outside or inside the grid point. This paper deduces a formula for computing the probability that the vector point is inside the grid point. It was found that the probability increased with the side length of the grid and with the variances of the coordinates of the vector point. In addition, the location entropy of points and lines are defined in this paper. Formulae for computing the change of the location entropy during conversion are deduced. The probability mentioned above and the change of location entropy may be used to evaluate the location reliability of points and lines in Geographic Information Systems and may be used to choose an appropriate range of the side length of grids before conversion. The results of this study may help scientists and users to avoid mistakes caused by the change of location during conversion as well as in spatial decision and analysis.

[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.

On Information Metrics for Spatial Coding.

PubMed

Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

2018-04-01

The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Spiking Neurons in a Hierarchical Self-Organizing Map Model Can Learn to Develop Spatial and Temporal Properties of Entorhinal Grid Cells and Hippocampal Place Cells

PubMed Central

Pilly, Praveen K.; Grossberg, Stephen

2013-01-01

Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous adaptive robots capable of spatial navigation. PMID:23577130

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-02-01

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present.

Exploration into technical procedures for vertical integration. [information systems

NASA Technical Reports Server (NTRS)

Michel, R. J.; Maw, K. D.

1979-01-01

Issues in the design and use of a digital geographic information system incorporating landuse, zoning, hazard, LANDSAT, and other data are discussed. An eleven layer database was generated. Issues in spatial resolution, registration, grid versus polygonal structures, and comparison of photointerpreted landuse to LANDSAT land cover are examined.

Generalized information fusion and visualization using spatial voting and data modeling

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.

2013-05-01

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

Hebbian Plasticity Realigns Grid Cell Activity with External Sensory Cues in Continuous Attractor Models

PubMed Central

Mulas, Marcello; Waniek, Nicolai; Conradt, Jörg

2016-01-01

After the discovery of grid cells, which are an essential component to understand how the mammalian brain encodes spatial information, three main classes of computational models were proposed in order to explain their working principles. Amongst them, the one based on continuous attractor networks (CAN), is promising in terms of biological plausibility and suitable for robotic applications. However, in its current formulation, it is unable to reproduce important electrophysiological findings and cannot be used to perform path integration for long periods of time. In fact, in absence of an appropriate resetting mechanism, the accumulation of errors over time due to the noise intrinsic in velocity estimation and neural computation prevents CAN models to reproduce stable spatial grid patterns. In this paper, we propose an extension of the CAN model using Hebbian plasticity to anchor grid cell activity to environmental landmarks. To validate our approach we used as input to the neural simulations both artificial data and real data recorded from a robotic setup. The additional neural mechanism can not only anchor grid patterns to external sensory cues but also recall grid patterns generated in previously explored environments. These results might be instrumental for next generation bio-inspired robotic navigation algorithms that take advantage of neural computation in order to cope with complex and dynamic environments. PMID:26924979

West Flank Coso, CA FORGE 3D geologic model

DOE Data Explorer

Doug Blankenship

2016-03-01

This is an x,y,z file of the West Flank FORGE 3D geologic model. Model created in Earthvision by Dynamic Graphic Inc. The model was constructed with a grid spacing of 100 m. Geologic surfaces were extrapolated from the input data using a minimum tension gridding algorithm. The data file is tabular data in a text file, with lithology data associated with X,Y,Z grid points. All the relevant information is in the file header (the spatial reference, the projection etc.) In addition all the fields in the data file are identified in the header.

Fallon FORGE 3D Geologic Model

DOE Data Explorer

Doug Blankenship

2016-03-01

An x,y,z scattered data file for the 3D geologic model of the Fallon FORGE site. Model created in Earthvision by Dynamic Graphic Inc. The model was constructed with a grid spacing of 100 m. Geologic surfaces were extrapolated from the input data using a minimum tension gridding algorithm. The data file is tabular data in a text file, with lithology data associated with X,Y,Z grid points. All the relevant information is in the file header (the spatial reference, the projection etc.) In addition all the fields in the data file are identified in the header.

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

Integration and management of massive remote-sensing data based on GeoSOT subdivision model

NASA Astrophysics Data System (ADS)

Li, Shuang; Cheng, Chengqi; Chen, Bo; Meng, Li

2016-07-01

Owing to the rapid development of earth observation technology, the volume of spatial information is growing rapidly; therefore, improving query retrieval speed from large, rich data sources for remote-sensing data management systems is quite urgent. A global subdivision model, geographic coordinate subdivision grid with one-dimension integer coding on 2n-tree, which we propose as a solution, has been used in data management organizations. However, because a spatial object may cover several grids, ample data redundancy will occur when data are stored in relational databases. To solve this redundancy problem, we first combined the subdivision model with the spatial array database containing the inverted index. We proposed an improved approach for integrating and managing massive remote-sensing data. By adding a spatial code column in an array format in a database, spatial information in remote-sensing metadata can be stored and logically subdivided. We implemented our method in a Kingbase Enterprise Server database system and compared the results with the Oracle platform by simulating worldwide image data. Experimental results showed that our approach performed better than Oracle in terms of data integration and time and space efficiency. Our approach also offers an efficient storage management system for existing storage centers and management systems.

The Variable Grid Method, an Approach for the Simultaneous Visualization and Assessment of Spatial Trends and Uncertainty

NASA Astrophysics Data System (ADS)

Rose, K.; Glosser, D.; Bauer, J. R.; Barkhurst, A.

2015-12-01

The products of spatial analyses that leverage the interpolation of sparse, point data to represent continuous phenomena are often presented without clear explanations of the uncertainty associated with the interpolated values. As a result, there is frequently insufficient information provided to effectively support advanced computational analyses and individual research and policy decisions utilizing these results. This highlights the need for a reliable approach capable of quantitatively producing and communicating spatial data analyses and their inherent uncertainties for a broad range of uses. To address this need, we have developed the Variable Grid Method (VGM), and associated Python tool, which is a flexible approach that can be applied to a variety of analyses and use case scenarios where users need a method to effectively study, evaluate, and analyze spatial trends and patterns while communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations, etc. We will present examples of our research utilizing the VGM to quantify key spatial trends and patterns for subsurface data interpolations and their uncertainties and leverage these results to evaluate storage estimates and potential impacts associated with underground injection for CO2 storage and unconventional resource production and development. The insights provided by these examples identify how the VGM can provide critical information about the relationship between uncertainty and spatial data that is necessary to better support their use in advance computation analyses and informing research, management and policy decisions.

High-resolution wavefront reconstruction using the frozen flow hypothesis

NASA Astrophysics Data System (ADS)

Liu, Xuewen; Liang, Yonghui; Liu, Jin; Xu, Jieping

2017-10-01

This paper describes an approach to reconstructing wavefronts on finer grid using the frozen flow hypothesis (FFH), which exploits spatial and temporal correlations between consecutive wavefront sensor (WFS) frames. Under the assumption of FFH, slope data from WFS can be connected to a finer, composite slope grid using translation and down sampling, and elements in transformation matrices are determined by wind information. Frames of slopes are then combined and slopes on finer grid are reconstructed by solving a sparse, large-scale, ill-posed least squares problem. By using reconstructed finer slope data and adopting Fried geometry of WFS, high-resolution wavefronts are then reconstructed. The results show that this method is robust even with detector noise and wind information inaccuracy, and under bad seeing conditions, high-frequency information in wavefronts can be recovered more accurately compared with when correlations in WFS frames are ignored.

Spatial Variability of CCN Sized Aerosol Particles

NASA Astrophysics Data System (ADS)

Asmi, A.; Väänänen, R.

2014-12-01

The computational limitations restrict the grid size used in GCM models, and for many cloud types they are too large when compared to the scale of the cloud formation processes. Several parameterizations for e.g. convective cloud formation exist, but information on spatial subgrid variation of the cloud condensation nuclei (CCNs) sized aerosol concentration is not known. We quantify this variation as a function of the spatial scale by using datasets from airborne aerosol measurement campaigns around the world including EUCAARI LONGREX, ATAR, INCA, INDOEX, CLAIRE, PEGASOS and several regional airborne campaigns in Finland. The typical shapes of the distributions are analyzed. When possible, we use information obtained by CCN counters. In some other cases, we use particle size distribution measured by for example SMPS to get approximated CCN concentration. Other instruments used include optical particle counters or condensational particle counters. When using the GCM models, the CCN concentration used for each the grid-box is often considered to be either flat, or as an arithmetic mean of the concentration inside the grid-box. However, the aircraft data shows that the concentration values are often lognormal distributed. This, combined with the subgrid variations in the land use and atmospheric properties, might cause that the aerosol-cloud interactions calculated by using mean values to vary significantly from the true effects both temporary and spatially. This, in turn, can cause non-linear bias into the GCMs. We calculate the CCN aerosol concentration distribution as a function of different spatial scales. The measurements allow us to study the variation of these distributions within from hundreds of meters up to hundreds of kilometers. This is used to quantify the potential error when mean values are used in GCMs.

Shearing-induced asymmetry in entorhinal grid cells.

PubMed

Stensola, Tor; Stensola, Hanne; Moser, May-Britt; Moser, Edvard I

2015-02-12

Grid cells are neurons with periodic spatial receptive fields (grids) that tile two-dimensional space in a hexagonal pattern. To provide useful information about location, grids must be stably anchored to an external reference frame. The mechanisms underlying this anchoring process have remained elusive. Here we show in differently sized familiar square enclosures that the axes of the grids are offset from the walls by an angle that minimizes symmetry with the borders of the environment. This rotational offset is invariably accompanied by an elliptic distortion of the grid pattern. Reversing the ellipticity analytically by a shearing transformation removes the angular offset. This, together with the near-absence of rotation in novel environments, suggests that the rotation emerges through non-coaxial strain as a function of experience. The systematic relationship between rotation and distortion of the grid pattern points to shear forces arising from anchoring to specific geometric reference points as key elements of the mechanism for alignment of grid patterns to the external world.

Mapping the spatial distribution of subsurface saline material in the Darling River valley

NASA Astrophysics Data System (ADS)

Triantafilis, John; Buchanan, Sam Mostyn

2010-02-01

In the Australian landscape larg stores of soluble salt are present naturally. In many cases it is attributable to salts entrapped as marine sediment in earlier geological time. At the district level, the need for information on the presence of saline subsurface material is increasing, particularly for its application to salinity hazard assessment and environmental management. This is the case in irrigated areas, where changes in hydrology can result in secondary salinisation. To reduce the expense, environmental studies use a regression relationship to make use of more readily observed measurements (e.g. electromagnetic (EM) data) which are strongly correlated with the variable of interest. In this investigation a methodology is outlined for mapping the spatial distribution of average subsurface (6-12 m) salinity (EC e — mS m - 1 ) using an environmental correlation with EM34 survey data collected across the Bourke Irrigation District (BID) in the Darling River valley. The EM34 is used in the horizontal dipole mode at coil configurations of 10 (EM34-10), 20 (EM34-20), and 40 (EM34-40). A multiple-linear regression (MLR) relationship is established between average subsurface EC e and the three EM34 signal data using a forward modeling stepwise linear modeling approach. The spatial distribution of average subsurface salinity generally reflects the known surface expression of point-source salinisation and provides information for future environmental monitoring and natural resource management. The generation of EM34 data on various contrived grids (i.e. 1, 1.5, 2. 2.5 and 3 km) indicates that in terms of accuracy, the data available on the 0.5 (RMSE = 188) and 1 km (RMSE = 283) grid are best, with the least biased predictions achieved using 1 (ME = - 1) and 2 km (ME = 12) grids. Viewing the spatial distribution of subsurface saline material showed that the 0.5 km spacing is optimal, particularly in order to account for short-range spatial variation between various physiographic units. The Relative Improvement (RI) shows that increasing EM grids from 1, 1.5, 2, 2.5 to 3 km gave RI of - 53, - 100%, - 107%, - 128% and - 140%, respectively. We conclude that at a minimum a 1 km grid is needed for reconnaissance EM34 surveying.

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/

Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

PubMed

Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2018-04-01

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

Is Fourier analysis performed by the visual system or by the visual investigator.

PubMed

Ochs, A L

1979-01-01

A numerical Fourier transform was made of the pincushion grid illusion and the spectral components orthogonal to the illusory lines were isolated. Their inverse transform creates a picture of the illusion. The spatial-frequency response of cortical, simple receptive field neurons similarly filters the grid. A complete set of these neurons thus approximates a two-dimensional Fourier analyzer. One cannot conclude, however, that the brain actually uses frequency-domain information to interpret visual images.

Multi-grid finite element method used for enhancing the reconstruction accuracy in Cerenkov luminescence tomography

NASA Astrophysics Data System (ADS)

Guo, Hongbo; He, Xiaowei; Liu, Muhan; Zhang, Zeyu; Hu, Zhenhua; Tian, Jie

2017-03-01

Cerenkov luminescence tomography (CLT), as a promising optical molecular imaging modality, can be applied to cancer diagnostic and therapeutic. Most researches about CLT reconstruction are based on the finite element method (FEM) framework. However, the quality of FEM mesh grid is still a vital factor to restrict the accuracy of the CLT reconstruction result. In this paper, we proposed a multi-grid finite element method framework, which was able to improve the accuracy of reconstruction. Meanwhile, the multilevel scheme adaptive algebraic reconstruction technique (MLS-AART) based on a modified iterative algorithm was applied to improve the reconstruction accuracy. In numerical simulation experiments, the feasibility of our proposed method were evaluated. Results showed that the multi-grid strategy could obtain 3D spatial information of Cerenkov source more accurately compared with the traditional single-grid FEM.

Modelling effects on grid cells of sensory input during self‐motion

PubMed Central

Raudies, Florian; Hinman, James R.

2016-01-01

Abstract The neural coding of spatial location for memory function may involve grid cells in the medial entorhinal cortex, but the mechanism of generating the spatial responses of grid cells remains unclear. This review describes some current theories and experimental data concerning the role of sensory input in generating the regular spatial firing patterns of grid cells, and changes in grid cell firing fields with movement of environmental barriers. As described here, the influence of visual features on spatial firing could involve either computations of self‐motion based on optic flow, or computations of absolute position based on the angle and distance of static visual cues. Due to anatomical selectivity of retinotopic processing, the sensory features on the walls of an environment may have a stronger effect on ventral grid cells that have wider spaced firing fields, whereas the sensory features on the ground plane may influence the firing of dorsal grid cells with narrower spacing between firing fields. These sensory influences could contribute to the potential functional role of grid cells in guiding goal‐directed navigation. PMID:27094096

Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex

PubMed Central

Raudies, Florian; Hasselmo, Michael E.

2015-01-01

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules. PMID:26584432

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

NASA Astrophysics Data System (ADS)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Towards a consistent framework to oversample multi-sensors, multi-species satellite data into a common grid

NASA Astrophysics Data System (ADS)

Sun, K.; Zhu, L.; Gonzalez Abad, G.; Nowlan, C. R.; Miller, C. E.; Huang, G.; Liu, X.; Chance, K.; Yang, K.

2017-12-01

It has been well demonstrated that regridding Level 2 products (satellite observations from individual footprints, or pixels) from multiple sensors/species onto regular spatial and temporal grids makes the data more accessible for scientific studies and can even lead to additional discoveries. However, synergizing multiple species retrieved from multiple satellite sensors faces many challenges, including differences in spatial coverage, viewing geometry, and data filtering criteria. These differences will lead to errors and biases if not treated carefully. Operational gridded products are often at 0.25°×0.25° resolution with a global scale, which is too coarse for local heterogeneous emission sources (e.g., urban areas), and at fixed temporal intervals (e.g., daily or monthly). We propose a consistent framework to fully use and properly weight the information of all possible individual satellite observations. A key aspect of this work is an accurate knowledge of the spatial response function (SRF) of the satellite Level 2 pixels. We found that the conventional overlap-area-weighting method (tessellation) is accurate only when the SRF is homogeneous within the parameterized pixel boundary and zero outside the boundary. There will be a tessellation error if the SRF is a smooth distribution, and if this distribution is not properly considered. On the other hand, discretizing the SRF at the destination grid will also induce errors. By balancing these error sources, we found that the SRF should be used in gridding OMI data to 0.2° for fine resolutions. Case studies by merging multiple species and wind data into 0.01° grid will be shown in the presentation.

TRMM .25 deg x .25 deg Gridded Precipitation Text Product

NASA Technical Reports Server (NTRS)

Stocker, Erich; Kelley, Owen

2009-01-01

Since the launch of the Tropical Rainfall Measuring Mission (TRMM), the Precipitation Measurement Missions science team has endeavored to provide TRMM precipitation retrievals in a variety of formats that are more easily usable by the broad science community than the standard Hierarchical Data Format (HDF) in which TRMM data is produced and archived. At the request of users, the Precipitation Processing System (PPS) has developed a .25 x .25 gridded product in an easily used ASCII text format. The entire TRMM mission data has been made available in this format. The paper provides the details of this new precipitation product that is designated with the TRMM designator 3G68.25. The format is packaged into daily files. It provides hourly precipitation information from the TRMM microwave imager (TMI), precipitation radar (PR), and TMI/PR combined rain retrievals. A major advantage of this approach is the inclusion only of rain data, compression when a particular grid has no rain from the PR or combined, and its direct ASCII text format. For those interested only in rain retrievals and whether rain is convection or stratiform, these products provide a huge reduction in the data volume inherent in the standard TRMM products. This paper provides examples of the 3G68 data products and their uses. It also provides information about C tools that can be used to aggregate daily files into larger time samples. In addition, it describes the possibilities inherent in the spatial sampling which allows resampling into coarser spatial sampling. The paper concludes with information about downloading the gridded text data products.

Modelling noise propagation using Grid Resources. Progress within GDI-Grid

NASA Astrophysics Data System (ADS)

Kiehle, Christian; Mayer, Christian; Padberg, Alexander; Stapelfeld, Hartmut

2010-05-01

Modelling noise propagation using Grid Resources. Progress within GDI-Grid. GDI-Grid (english: SDI-Grid) is a research project funded by the German Ministry for Science and Education (BMBF). It aims at bridging the gaps between OGC Web Services (OWS) and Grid infrastructures and identifying the potential of utilizing the superior storage capacities and computational power of grid infrastructures for geospatial applications while keeping the well-known service interfaces specified by the OGC. The project considers all major OGC webservice interfaces for Web Mapping (WMS), Feature access (Web Feature Service), Coverage access (Web Coverage Service) and processing (Web Processing Service). The major challenge within GDI-Grid is the harmonization of diverging standards as defined by standardization bodies for Grid computing and spatial information exchange. The project started in 2007 and will continue until June 2010. The concept for the gridification of OWS developed by lat/lon GmbH and the Department of Geography of the University of Bonn is applied to three real-world scenarios in order to check its practicability: a flood simulation, a scenario for emergency routing and a noise propagation simulation. The latter scenario is addressed by the Stapelfeldt Ingenieurgesellschaft mbH located in Dortmund adapting their LimA software to utilize grid resources. Noise mapping of e.g. traffic noise in urban agglomerates and along major trunk roads is a reoccurring demand of the EU Noise Directive. Input data requires road net and traffic, terrain, buildings and noise protection screens as well as population distribution. Noise impact levels are generally calculated in 10 m grid and along relevant building facades. For each receiver position sources within a typical range of 2000 m are split down into small segments, depending on local geometry. For each of the segments propagation analysis includes diffraction effects caused by all obstacles on the path of sound propagation. This immense intensive calculation needs to be performed for a major part of European landscape. A LINUX version of the commercial LimA software for noise mapping analysis has been implemented on a test cluster within the German D-GRID computer network. Results and performance indicators will be presented. The presentation is an extension to last-years presentation "Spatial Data Infrastructures and Grid Computing: the GDI-Grid project" that described the gridification concept developed in the GDI-Grid project and provided an overview of the conceptual gaps between Grid Computing and Spatial Data Infrastructures. Results from the GDI-Grid project are incorporated in the OGC-OGF (Open Grid Forum) collaboration efforts as well as the OGC WPS 2.0 standards working group developing the next major version of the WPS specification.

Probabilistic Learning by Rodent Grid Cells

PubMed Central

Cheung, Allen

2016-01-01

Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations. PMID:27792723

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.

Gridded Model Information Support System (GMISS) user's guide. Volume 3. Model-concentration data-retrieval subsystem

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

Not Available

The Gridded Model Information Support System (GMISS) is a data base management system for selected Regional Oxidant Model (ROM) input data and species concentrations produced by gridded photochemical air pollution models. The Model Concentration Data Retrieval Subsystem allows State and local air pollution control agencies to retrieve these hourly data for use in support of their regulatory programs. These hourly data may be used to calculate initial and boundary conditions for the Empirical Kinetics Modeling Approach (EKMA). They may be used for other modeling application needs as well as to support evaluation of regional emission controls strategies. Both temporal andmore » spatial subsets of the data may be retrieved. The document describes how to invoke and execute the Model Concentration Data Retrieval Subsystem using the full screen menus.« less

Climate Change Impacts on Freshwater Recreational Fishing in the United States

EPA Science Inventory

Using a geographic information system, a spatially explicit modeling framework was developed consisting grid cells organized into 2,099 eight-digit hydrologic unit code (HUC-8) polygons for the coterminous United States. Projected temperature and precipitation changes associated...

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya.

PubMed

Eisele, Thomas P; Keating, Joseph; Swalm, Chris; Mbogo, Charles M; Githeko, Andrew K; Regens, James L; Githure, John I; Andrews, Linda; Beier, John C

2003-12-10

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population asymptotically equal to 320,000) and Malindi (population asymptotically equal to 81,000), Kenya. Grid cells of 270 meters x 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter x 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level. RESULTS: Multivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51). CONCLUSIONS: NDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters x 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.

Signal to Noise Ratio for Different Gridded Rainfall Products of Indian Monsoon

NASA Astrophysics Data System (ADS)

Nehra, P.; Shastri, H. K.; Ghosh, S.; Mishra, V.; Murtugudde, R. G.

2014-12-01

Gridded rainfall datasets provide useful information of spatial and temporal distribution of precipitation over a region. For India, there are 3 gridded rainfall data products available from India Meteorological Department (IMD), Tropical Rainfall Measurement Mission (TRMM) and Asian Precipitation - Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), these compile precipitation information obtained through satellite based measurement and ground station based data. The gridded rainfall data from IMD is available at spatial resolution of 1°, 0.5° and 0.25° where as TRMM and APHRODITE is available at 0.25°. Here, we employ 7 years (1998-2004) of common time period amongst the 3 data products for the south-west monsoon season, i.e., the months June to September. We examine temporal mean and standard deviation of these 3 products to observe substantial variation amongst them at 1° resolution whereas for 0.25° resolution, all the data types are nearly identical. We determine the Signal to Noise Ratio (SNR) of the 3 products at 1° and 0.25° resolution based on noise separation technique adopting horizontal separation of the power spectrum generated with the Fast Fourier Transformation (FFT). A methodology is developed for threshold based separation of signal and noise from the power spectrum, treating the noise as white. The variance of signal to that of noise is computed to obtain SNR. Determination of SNR for different regions over the country shows the highest SNR with APHRODITE at 0.25° resolution. It is observed that the eastern part of India has the highest SNR in all cases considered whereas the northern and southern most Indian regions have lowest SNR. An incremental linear trend is observed among the SNR values and the spatial variance of corresponding region. Relationship between the computed SNR values and the interpolation method used with the dataset is analyzed. The SNR analysis provides an effective tool to evaluate the gridded precipitation data products. However detailed analysis is needed to determine the processes that lead to these SNR distributions so that the quality of the gridded rainfall data products can be further improved and transferability of the gridding algorithms can be explored to produce a unified high-quality rainfall dataset.

seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

NASA Astrophysics Data System (ADS)

Lussana, Cristian; Saloranta, Tuomo; Skaugen, Thomas; Magnusson, Jan; Tveito, Ole Einar; Andersen, Jess

2018-02-01

The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall-runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2 dataset 1957-2015 is available at https://doi.org/10.5281/zenodo.845733. Daily updates from 2015 onwards are available at http://thredds.met.no/thredds/catalog/metusers/senorge2/seNorge2/provisional_archive/PREC1d/gridded_dataset/catalog.html.

Land Cover Change Detection using Neural Network and Grid Cells Techniques

NASA Astrophysics Data System (ADS)

Bagan, H.; Li, Z.; Tangud, T.; Yamagata, Y.

2017-12-01

In recent years, many advanced neural network methods have been applied in land cover classification, each of which has both strengths and limitations. In which, the self-organizing map (SOM) neural network method have been used to solve remote sensing data classification problems and have shown potential for efficient classification of remote sensing data. In SOM, both the distribution and the topology of features of the input layer are identified by using an unsupervised, competitive, neighborhood learning method. The high-dimensional data are then projected onto a low-dimensional map (competitive layer), usually as a two-dimensional map. The neurons (nodes) in the competitive layer are arranged by topological order in the input space. Spatio-temporal analyses of land cover change based on grid cells have demonstrated that gridded data are useful for obtaining spatial and temporal information about areas that are smaller than municipal scale and are uniform in size. Analysis based on grid cells has many advantages: grid cells all have the same size allowing for easy comparison; grids integrate easily with other scientific data; grids are stable over time and thus facilitate the modelling and analysis of very large multivariate spatial data sets. This study chose time-series MODIS and Landsat images as data sources, applied SOM neural network method to identify the land utilization in Inner Mongolia Autonomous Region of China. Then the results were integrated into grid cell to get the dynamic change maps. Land cover change using MODIS data in Inner Mongolia showed that urban area increased more than fivefold in recent 15 years, along with the growth of mining area. In terms of geographical distribution, the most obvious place of urban expansion is Ordos in southwest Inner Mongolia. The results using Landsat images from 1986 to 2014 in northeastern part of the Inner Mongolia show degradation in grassland from 1986 to 2014. Grid-cell-based spatial correlation analysis also confirmed a strong negative correlation between grassland and barren land, indicating that grassland degradation in this region is due to the urbanization and coal mining activities over the past three decades.

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches.

PubMed

Suzuki, Noriyuki; Murasawa, Kaori; Sakurai, Takeo; Nansai, Keisuke; Matsuhashi, Keisuke; Moriguchi, Yuichi; Tanabe, Kiyoshi; Nakasugi, Osami; Morita, Masatoshi

2004-11-01

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.

Nonuniform grid implicit spatial finite difference method for acoustic wave modeling in tilted transversely isotropic media

NASA Astrophysics Data System (ADS)

Chu, Chunlei; Stoffa, Paul L.

2012-01-01

Discrete earth models are commonly represented by uniform structured grids. In order to ensure accurate numerical description of all wave components propagating through these uniform grids, the grid size must be determined by the slowest velocity of the entire model. Consequently, high velocity areas are always oversampled, which inevitably increases the computational cost. A practical solution to this problem is to use nonuniform grids. We propose a nonuniform grid implicit spatial finite difference method which utilizes nonuniform grids to obtain high efficiency and relies on implicit operators to achieve high accuracy. We present a simple way of deriving implicit finite difference operators of arbitrary stencil widths on general nonuniform grids for the first and second derivatives and, as a demonstration example, apply these operators to the pseudo-acoustic wave equation in tilted transversely isotropic (TTI) media. We propose an efficient gridding algorithm that can be used to convert uniformly sampled models onto vertically nonuniform grids. We use a 2D TTI salt model to demonstrate its effectiveness and show that the nonuniform grid implicit spatial finite difference method can produce highly accurate seismic modeling results with enhanced efficiency, compared to uniform grid explicit finite difference implementations.

Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density.

PubMed

Lęski, Szymon; Kublik, Ewa; Swiejkowski, Daniel A; Wróbel, Andrzej; Wójcik, Daniel K

2010-12-01

Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4 × 5 × 7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

Grid cell spatial tuning reduced following systemic muscarinic receptor blockade

PubMed Central

Newman, Ehren L.; Climer, Jason R.; Hasselmo, Michael E.

2014-01-01

Grid cells of the medial entorhinal cortex exhibit a periodic and stable pattern of spatial tuning that may reflect the output of a path integration system. This grid pattern has been hypothesized to serve as a spatial coordinate system for navigation and memory function. The mechanisms underlying the generation of this characteristic tuning pattern remain poorly understood. Systemic administration of the muscarinic antagonist scopolamine flattens the typically positive correlation between running speed and entorhinal theta frequency in rats. The loss of this neural correlate of velocity, an important signal for the calculation of path integration, raises the question of what influence scopolamine has on the grid cell tuning as a read out of the path integration system. To test this, the spatial tuning properties of grid cells were compared before and after systemic administration of scopolamine as rats completed laps on a circle track for food rewards. The results show that the spatial tuning of the grid cells was reduced following scopolamine administration. The tuning of head direction cells, in contrast, was not reduced by scopolamine. This is the first report to demonstrate a link between cholinergic function and grid cell tuning. This work suggests that the loss of tuning in the grid cell network may underlie the navigational disorientation observed in Alzheimer's patients and elderly individuals with reduced cholinergic tone. PMID:24493379

An Efficient Algorithm for Mapping Imaging Data to 3D Unstructured Grids in Computational Biomechanics

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

Einstein, Daniel R.; Kuprat, Andrew P.; Jiao, Xiangmin

2013-01-01

Geometries for organ scale and multiscale simulations of organ function are now routinely derived from imaging data. However, medical images may also contain spatially heterogeneous information other than geometry that are relevant to such simulations either as initial conditions or in the form of model parameters. In this manuscript, we present an algorithm for the efficient and robust mapping of such data to imaging based unstructured polyhedral grids in parallel. We then illustrate the application of our mapping algorithm to three different mapping problems: 1) the mapping of MRI diffusion tensor data to an unstuctured ventricular grid; 2) the mappingmore » of serial cyro-section histology data to an unstructured mouse brain grid; and 3) the mapping of CT-derived volumetric strain data to an unstructured multiscale lung grid. Execution times and parallel performance are reported for each case.« less

Grid enablement of OpenGeospatial Web Services: the G-OWS Working Group

NASA Astrophysics Data System (ADS)

Mazzetti, Paolo

2010-05-01

In last decades two main paradigms for resource sharing emerged and reached maturity: the Web and the Grid. They both demonstrate suitable for building Distributed Computing Infrastructures (DCIs) supporting the coordinated sharing of resources (i.e. data, information, services, etc) on the Internet. Grid and Web DCIs have much in common as a result of their underlying Internet technology (protocols, models and specifications). However, being based on different requirements and architectural approaches, they show some differences as well. The Web's "major goal was to be a shared information space through which people and machines could communicate" [Berners-Lee 1996]. The success of the Web, and its consequent pervasiveness, made it appealing for building specialized systems like the Spatial Data Infrastructures (SDIs). In this systems the introduction of Web-based geo-information technologies enables specialized services for geospatial data sharing and processing. The Grid was born to achieve "flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources" [Foster 2001]. It specifically focuses on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In the Earth and Space Sciences (ESS) the most part of handled information is geo-referred (geo-information) since spatial and temporal meta-information is of primary importance in many application domains: Earth Sciences, Disasters Management, Environmental Sciences, etc. On the other hand, in several application areas there is the need of running complex models which require the large processing and storage capabilities that the Grids are able to provide. Therefore the integration of geo-information and Grid technologies might be a valuable approach in order to enable advanced ESS applications. Currently both geo-information and Grid technologies have reached a high level of maturity, allowing to build such an integration on existing solutions. More specifically, the Open Geospatial Consortium (OGC) Web Services (OWS) specifications play a fundamental role in geospatial information sharing (e.g. in INSPIRE Implementing Rules, GEOSS architecture, GMES Services, etc.). On the Grid side, the gLite middleware, developed in the European EGEE (Enabling Grids for E-sciencE) Projects, is widely spread in Europe and beyond, proving its high scalability and it is one of the middleware chosen for the future European Grid Infrastructure (EGI) initiative. Therefore the convergence between OWS and gLite technologies would be desirable for a seamless access to the Grid capabilities through OWS-compliant systems. Anyway, to achieve this harmonization there are some obstacles to overcome. Firstly, a semantics mismatch must be addressed: gLite handle low-level (e.g. close to the machine) concepts like "file", "data", "instruments", "job", etc., while geo-information services handle higher-level (closer to the human) concepts like "coverage", "observation", "measurement", "model", etc. Secondly, an architectural mismatch must be addressed: OWS implements a Web Service-Oriented-Architecture which is stateless, synchronous and with no embedded security (which is demanded to other specs), while gLite implements the Grid paradigm in an architecture which is stateful, asynchronous (even not fully event-based) and with strong embedded security (based on the VO paradigm). In recent years many initiatives and projects have worked out possible approaches for implementing Grid-enabled OWSs. Just to mention some: (i) in 2007 the OGC has signed a Memorandum of Understanding with the Open Grid Forum, "a community of users, developers, and vendors leading the global standardization effort for grid computing."; (ii) the OGC identified "WPS Profiles - Conflation; and Grid processing" as one of the tasks in the Geo Processing Workflow theme of the OWS Phase 6 (OWS-6); (iii) several national, European and international projects investigated different aspects of this integration, developing demonstrators and Proof-of-Concepts; In this context, "gLite enablement of OpenGeospatial Web Services" (G-OWS) is an initiative started in 2008 by the European CYCLOPS, GENESI-DR, and DORII Projects Consortia in order to collect/coordinate experiences on the enablement of OWS on top of the gLite middleware [GOWS]. Currently G-OWS counts ten member organizations from Europe and beyond, and four European Projects involved. It broadened its scope to the development of Spatial Data and Information Infrastructures (SDI and SII) based on the Grid/Cloud capacity in order to enable Earth Science applications and tools. Its operational objectives are the following: i) to contribute to the OGC-OGF initiative; ii) to release a reference implementation as standard gLite APIs (under the gLite software license); iii) to release a reference model (including procedures and guidelines) for OWS Grid-ification, as far as gLite is concerned; iv) to foster and promote the formation of consortiums for participation to projects/initiatives aimed at building Grid-enabled SDIs To achieve this objectives G-OWS bases its activities on two main guiding principles: a) the adoption of a service-oriented architecture based on the information modelling approach, and b) standardization as a means of achieving interoperability (i.e. adoption of standards from ISO TC211, OGC OWS, OGF). In the first year of activity G-OWS has designed a general architectural framework stemming from the FP6 CYCLOPS studies and enriched by the outcomes of other projects and initiatives involved (i.e. FP7 GENESI-DR, FP7 DORII, AIST GeoGrid, etc.). Some proof-of-concepts have been developed to demonstrate the flexibility and scalability of such architectural framework. The G-OWS WG developed implementations of gLite-enabled Web Coverage Service (WCS) and Web Processing Service (WPS), and an implementation of a Shibboleth authentication for gLite-enabled OWS in order to evaluate the possible integration of Web and Grid security models. The presentation will aim to communicate the G-OWS organization, activities, future plans and means to involve the ESSI community. References [Berners-Lee 1996] T. Berners-Lee, "WWW: Past, present, and future". IEEE Computer, 29(10), Oct. 1996, pp. 69-77. [Foster 2001] I. Foster, C. Kesselman and S. Tuecke, "The Anatomy of the Grid. The International Journal ofHigh Performance Computing Applications", 15(3):200-222, Fall 2001 [GOWS] G-OWS WG, https://www.g-ows.org/, accessed: 15 January 2010

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.

GIS characterization of spatially distributed lifeline damage

USGS Publications Warehouse

Toprak, Selcuk; O'Rourke, Thomas; Tutuncu, Ilker

1999-01-01

This paper describes the visualization of spatially distributed water pipeline damage following an earthquake using geographical information systems (GIS). Pipeline damage is expressed as a repair rate (RR). Repair rate contours are developed with GIS by dividing the study area into grid cells (n ?? n), determining the number of particular pipeline repairs in each grid cell, and dividing the number of repairs by the length of that pipeline in each cell area. The resulting contour plot is a two-dimensional visualization of point source damage. High damage zones are defined herein as areas with an RR value greater than the mean RR for the entire study area of interest. A hyperbolic relationship between visual display of high pipeline damage zones and grid size, n, was developed. The relationship is expressed in terms of two dimensionless parameters, threshold area coverage (TAC) and dimensionless grid size (DGS). The relationship is valid over a wide range of different map scales spanning approximately 1,200 km2 for the largest portion of the Los Angeles water distribution system to 1 km2 for the Marina in San Francisco. This relationship can aid GIS users to get sufficiently refined, but easily visualized, maps of damage patterns.

Outcomes of Spatially Fractionated Radiotherapy (GRID) for Bulky Soft Tissue Sarcomas in a Large Animal Model

PubMed Central

Gieger, Tracy L.; Karakashian, Alexander A.; Nikolova-Karakashian, Mariana N.; Posner, Lysa P.; Roback, Donald M.; Rivera, Judith N.; Chang, Sha

2017-01-01

GRID directs alternating regions of high- and low-dose radiation at tumors. A large animal model mimicking the geometries of human treatments is needed to complement existing rodent systems (eg, microbeam) and clarify the physical and biological attributes of GRID. A pilot study was undertaken in pet dogs with spontaneous soft tissue sarcomas to characterize responses to GRID. Subjects were treated with either 20 Gy (3 dogs) or 25 Gy (3 dogs), delivered using 6 MV X-rays and a commercial GRID collimator. Acute toxicity and tumor responses were assessed 2, 4, and 6 weeks later. Acute Radiation Therapy Oncology Group grade I skin toxicity was observed in 3 of the 6 dogs; none experienced a measurable response, per Response Evaluation Criteria in Solid Tumors. Serum vascular endothelial growth factor, tumor necrosis factor α, and secretory sphingomyelinase were assayed at baseline, 1, 4, 24, and 48 hours after treatment. There was a trend toward platelet-corrected serum vascular endothelial growth factor concentration being lower 1 and 48 hours after GRID than at baseline. There was a significant decrease in secretory sphingomyelinase activity 48 hours after 25 Gy GRID (P = .03). Serum tumor necrosis factor α was quantified measurable at baseline in 4 of the 6 dogs and decreased in each of those subjects at all post-GRID time points. The new information generated by this study includes the observation that high-dose, single fraction application of GRID does not induce measurable reduction in volume of canine soft tissue sarcomas. In contrast to previously published data, these data suggest that GRID may be associated with at least short-term reduction in serum concentration of vascular endothelial growth factor and serum activity of secretory sphingomyelinase. Because GRID can be applied safely, and these tumors can be subsequently surgically resected as part of routine veterinary care, pet dogs with sarcomas are an appealing model for studying the radiobiologic responses to spatially fractionated radiotherapy. PMID:28168937

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

Increased tree-ring network density reveals more precise estimations of sub-regional hydroclimate variability and climate dynamics in the Midwest, USA

NASA Astrophysics Data System (ADS)

Maxwell, Justin T.; Harley, Grant L.

2017-08-01

Understanding the historic variability in the hydroclimate provides important information on possible extreme dry or wet periods that in turn inform water management plans. Tree rings have long provided historical context of hydroclimate variability of the U.S. However, the tree-ring network used to create these countrywide gridded reconstructions is sparse in certain locations, such as the Midwest. Here, we increase ( n = 20) the spatial resolution of the tree-ring network in southern Indiana and compare a summer (June-August) Palmer Drought Severity Index (PDSI) reconstruction to existing gridded reconstructions of PDSI for this region. We find both droughts and pluvials that were previously unknown that rival the most intense PDSI values during the instrumental period. Additionally, historical drought occurred in Indiana that eclipsed instrumental conditions with regard to severity and duration. During the period 1962-2004 CE, we find that teleconnections of drought conditions through the Atlantic Meridional Overturning Circulation have a strong influence ( r = -0.60, p < 0.01) on secondary tree growth in this region for the late spring-early summer season. These findings highlight the importance of continuing to increase the spatial resolution of the tree-ring network used to infer past climate dynamics to capture the sub-regional spatial variability. Increasing the spatial resolution of the tree-ring network for a given region can better identify sub-regional variability, improve the accuracy of regional tree-ring PDSI reconstructions, and provide better information for climatic teleconnections.

Tau Pathology Induces Excitatory Neuron Loss, Grid Cell Dysfunction and Spatial Memory Deficits Reminiscent of Early Alzheimer's Disease

PubMed Central

Fu, Hongjun; Rodriguez, Gustavo A.; Herman, Mathieu; Emrani, Sheina; Nahmani, Eden; Barrett, Geoffrey; Figueroa, Helen Y.; Goldberg, Eliana

2017-01-01

Summary The earliest stages of Alzheimer's disease (AD) are characterized by the formation of mature tangles in the entorhinal cortex and disorientation and confusion navigating familiar places. The medial entorhinal cortex (MEC) contains specialized neurons called grid cells that form part of the spatial navigation system. Here we show in a transgenic mouse model expressing mutant human tau predominantly in the EC that the formation of mature tangles in old mice was associated with excitatory cell loss and deficits in grid cell function, including destabilized grid fields and reduced firing rates, as well as altered network activity. Overt tau pathology in the aged mice was accompanied by spatial memory deficits. Therefore, tau pathology initiated in the entorhinal cortex could lead to deficits in grid cell firing and underlie the deterioration of spatial cognition seen in human AD. PMID:28111080

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Synthetic perspective optical flow: Influence on pilot control tasks

NASA Technical Reports Server (NTRS)

Bennett, C. Thomas; Johnson, Walter W.; Perrone, John A.; Phatak, Anil V.

1989-01-01

One approach used to better understand the impact of visual flow on control tasks has been to use synthetic perspective flow patterns. Such patterns are the result of apparent motion across a grid or random dot display. Unfortunately, the optical flow so generated is based on a subset of the flow information that exists in the real world. The danger is that the resulting optical motions may not generate the visual flow patterns useful for actual flight control. Researchers conducted a series of studies directed at understanding the characteristics of synthetic perspective flow that support various pilot tasks. In the first of these, they examined the control of altitude over various perspective grid textures (Johnson et al., 1987). Another set of studies was directed at studying the head tracking of targets moving in a 3-D coordinate system. These studies, parametric in nature, utilized both impoverished and complex virtual worlds represented by simple perspective grids at one extreme, and computer-generated terrain at the other. These studies are part of an applied visual research program directed at understanding the design principles required for the development of instruments displaying spatial orientation information. The experiments also highlight the need for modeling the impact of spatial displays on pilot control tasks.

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

PubMed

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Application of spatially gridded temperature and land cover data sets for urban heat island analysis

USGS Publications Warehouse

Gallo, Kevin; Xian, George Z.

2014-01-01

Two gridded data sets that included (1) daily mean temperatures from 2006 through 2011 and (2) satellite-derived impervious surface area, were combined for a spatial analysis of the urban heat-island effect within the Dallas-Ft. Worth Texas region. The primary advantage of using these combined datasets included the capability to designate each 1 × 1 km grid cell of available temperature data as urban or rural based on the level of impervious surface area within the grid cell. Generally, the observed differences in urban and rural temperature increased as the impervious surface area thresholds used to define an urban grid cell were increased. This result, however, was also dependent on the size of the sample area included in the analysis. As the spatial extent of the sample area increased and included a greater number of rural defined grid cells, the observed urban and rural differences in temperature also increased. A cursory comparison of the spatially gridded temperature observations with observations from climate stations suggest that the number and location of stations included in an urban heat island analysis requires consideration to assure representative samples of each (urban and rural) environment are included in the analysis.

Need for speed: An optimized gridding approach for spatially explicit disease simulations.

PubMed

Sellman, Stefan; Tsao, Kimberly; Tildesley, Michael J; Brommesson, Peter; Webb, Colleen T; Wennergren, Uno; Keeling, Matt J; Lindström, Tom

2018-04-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power.

Need for speed: An optimized gridding approach for spatially explicit disease simulations

PubMed Central

Tildesley, Michael J.; Brommesson, Peter; Webb, Colleen T.; Wennergren, Uno; Lindström, Tom

2018-01-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power. PMID:29624574

Tensor-guided fitting of subduction slab depths

USGS Publications Warehouse

Bazargani, Farhad; Hayes, Gavin P.

2013-01-01

Geophysical measurements are often acquired at scattered locations in space. Therefore, interpolating or fitting the sparsely sampled data as a uniform function of space (a procedure commonly known as gridding) is a ubiquitous problem in geophysics. Most gridding methods require a model of spatial correlation for data. This spatial correlation model can often be inferred from some sort of secondary information, which may also be sparsely sampled in space. In this paper, we present a new method to model the geometry of a subducting slab in which we use a data‐fitting approach to address the problem. Earthquakes and active‐source seismic surveys provide estimates of depths of subducting slabs but only at scattered locations. In addition to estimates of depths from earthquake locations, focal mechanisms of subduction zone earthquakes also provide estimates of the strikes of the subducting slab on which they occur. We use these spatially sparse strike samples and the Earth’s curved surface geometry to infer a model for spatial correlation that guides a blended neighbor interpolation of slab depths. We then modify the interpolation method to account for the uncertainties associated with the depth estimates.

Mapping Atmospheric Moisture Climatologies across the Conterminous United States

PubMed Central

Daly, Christopher; Smith, Joseph I.; Olson, Keith V.

2015-01-01

Spatial climate datasets of 1981–2010 long-term mean monthly average dew point and minimum and maximum vapor pressure deficit were developed for the conterminous United States at 30-arcsec (~800m) resolution. Interpolation of long-term averages (twelve monthly values per variable) was performed using PRISM (Parameter-elevation Relationships on Independent Slopes Model). Surface stations available for analysis numbered only 4,000 for dew point and 3,500 for vapor pressure deficit, compared to 16,000 for previously-developed grids of 1981–2010 long-term mean monthly minimum and maximum temperature. Therefore, a form of Climatologically-Aided Interpolation (CAI) was used, in which the 1981–2010 temperature grids were used as predictor grids. For each grid cell, PRISM calculated a local regression function between the interpolated climate variable and the predictor grid. Nearby stations entering the regression were assigned weights based on the physiographic similarity of the station to the grid cell that included the effects of distance, elevation, coastal proximity, vertical atmospheric layer, and topographic position. Interpolation uncertainties were estimated using cross-validation exercises. Given that CAI interpolation was used, a new method was developed to allow uncertainties in predictor grids to be accounted for in estimating the total interpolation error. Local land use/land cover properties had noticeable effects on the spatial patterns of atmospheric moisture content and deficit. An example of this was relatively high dew points and low vapor pressure deficits at stations located in or near irrigated fields. The new grids, in combination with existing temperature grids, enable the user to derive a full suite of atmospheric moisture variables, such as minimum and maximum relative humidity, vapor pressure, and dew point depression, with accompanying assumptions. All of these grids are available online at http://prism.oregonstate.edu, and include 800-m and 4-km resolution data, images, metadata, pedigree information, and station inventory files. PMID:26485026

Conceptual Design of the Everglades Depth Estimation Network (EDEN) Grid

USGS Publications Warehouse

Jones, John W.; Price, Susan D.

2007-01-01

INTRODUCTION The Everglades Depth Estimation Network (EDEN) offers a consistent and documented dataset that can be used to guide large-scale field operations, to integrate hydrologic and ecological responses, and to support biological and ecological assessments that measure ecosystem responses to the Comprehensive Everglades Restoration Plan (Telis, 2006). Ground elevation data for the greater Everglades and the digital ground elevation models derived from them form the foundation for all EDEN water depth and associated ecologic/hydrologic modeling (Jones, 2004, Jones and Price, 2007). To use EDEN water depth and duration information most effectively, it is important to be able to view and manipulate information on elevation data quality and other land cover and habitat characteristics across the Everglades region. These requirements led to the development of the geographic data layer described in this techniques and methods report. Relying on extensive experience in GIS data development, distribution, and analysis, a great deal of forethought went into the design of the geographic data layer used to index elevation and other surface characteristics for the Greater Everglades region. To allow for simplicity of design and use, the EDEN area was broken into a large number of equal-sized rectangles ('Cells') that in total are referred to here as the 'grid'. Some characteristics of this grid, such as the size of its cells, its origin, the area of Florida it is designed to represent, and individual grid cell identifiers, could not be changed once the grid database was developed. Therefore, these characteristics were selected to design as robust a grid as possible and to ensure the grid's long-term utility. It is desirable to include all pertinent information known about elevation and elevation data collection as grid attributes. Also, it is very important to allow for efficient grid post-processing, sub-setting, analysis, and distribution. This document details the conceptual design of the EDEN grid spatial parameters and cell attribute-table content.

Geospatial characterization of deforestation, fragmentation and forest fires in Telangana state, India: conservation perspective.

PubMed

Sudhakar Reddy, C; Vazeed Pasha, S; Jha, C S; Dadhwal, V K

2015-07-01

Conservation of biodiversity has been put to the highest priority throughout the world. The process of identifying threatened ecosystems will search for different drivers related to biodiversity loss. The present study aimed to generate spatial information on deforestation and ecological degradation indicators of fragmentation and forest fires using systematic conceptual approach in Telangana state, India. Identification of ecosystems facing increasing vulnerability can help to safeguard the extinctions of species and useful for conservation planning. The technological advancement of satellite remote sensing and Geographical Information System has increased greatly in assessment and monitoring of ecosystem-level changes. The areas of threat were identified by creating grid cells (5 × 5 km) in Geographical Information System (GIS). Deforestation was assessed using multi-source data of 1930, 1960, 1975, 1985, 1995, 2005 and 2013. The forest cover of 40,746 km(2), 29,299 km(2), 18,652 km(2), 18,368 km(2), 18,006 km(2), 17,556 km(2) and 17,520 km(2) was estimated during 1930, 1960, 1975, 1985, 1995, 2005 and 2013, respectively. Historical evaluation of deforestation revealed that major changes had occurred in forests of Telangana and identified 1095 extinct, 397 critically endangered, 523 endangered and 311 vulnerable ecosystem grid cells. The fragmentation analysis has identified 307 ecosystem grid cells under critically endangered status. Forest burnt area information was extracted using AWiFS data of 2005 to 2014. Spatial analysis indicates total fire-affected forest in Telangana as 58.9% in a decadal period. Conservation status has been recorded depending upon values of threat for each grid, which forms the basis for conservation priority hotspots. Of existing forest, 2.1% grids had severe ecosystem collapse and had been included under the category of conservation priority hotspot-I, followed by 27.2% in conservation priority hotspot-II and 51.5% in conservation priority hotspot-III. This analysis complements assessment of ecosystems undergoing multiple threats. An integrated approach involving the deforestation and degradation indicators is useful in formulating the strategies to take appropriate conservation measures.

GIS Methodic and New Database for Magmatic Rocks. Application for Atlantic Oceanic Magmatism.

NASA Astrophysics Data System (ADS)

Asavin, A. M.

2001-12-01

There are several geochemical Databases in INTERNET available now. There one of the main peculiarities of stored geochemical information is geographical coordinates of each samples in those Databases. As rule the software of this Database use spatial information only for users interface search procedures. In the other side, GIS-software (Geographical Information System software),for example ARC/INFO software which using for creation and analyzing special geological, geochemical and geophysical e-map, have been deeply involved with geographical coordinates for of samples. We join peculiarities GIS systems and relational geochemical Database from special software. Our geochemical information system created in Vernadsky Geological State Museum and institute of Geochemistry and Analytical Chemistry from Moscow. Now we tested system with data of geochemistry oceanic rock from Atlantic and Pacific oceans, about 10000 chemical analysis. GIS information content consist from e-map covers Wold Globes. Parts of these maps are Atlantic ocean covers gravica map (with grid 2''), oceanic bottom hot stream, altimeteric maps, seismic activity, tectonic map and geological map. Combination of this information content makes possible created new geochemical maps and combination of spatial analysis and numerical geochemical modeling of volcanic process in ocean segment. Now we tested information system on thick client technology. Interface between GIS system Arc/View and Database resides in special multiply SQL-queries sequence. The result of the above gueries were simple DBF-file with geographical coordinates. This file act at the instant of creation geochemical and other special e-map from oceanic region. We used more complex method for geophysical data. From ARC\\View we created grid cover for polygon spatial geophysical information.

Factorial inferential grid grouping and representativeness analysis for a systematic selection of representative grids

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Yao, Yao

2017-08-01

A factorial inferential grid grouping and representativeness analysis (FIGGRA) approach is developed to achieve a systematic selection of representative grids in large-scale climate change impact assessment and adaptation (LSCCIAA) studies and other fields of Earth and space sciences. FIGGRA is applied to representative-grid selection for temperature (Tas) and precipitation (Pr) over the Loess Plateau (LP) to verify methodological effectiveness. FIGGRA is effective at and outperforms existing grid-selection approaches (e.g., self-organizing maps) in multiple aspects such as clustering similar grids, differentiating dissimilar grids, and identifying representative grids for both Tas and Pr over LP. In comparison with Pr, the lower spatial heterogeneity and higher spatial discontinuity of Tas over LP lead to higher within-group similarity, lower between-group dissimilarity, lower grid grouping effectiveness, and higher grid representativeness; the lower interannual variability of the spatial distributions of Tas results in lower impacts of the interannual variability on the effectiveness of FIGGRA. For LP, the spatial climatic heterogeneity is the highest in January for Pr and in October for Tas; it decreases from spring, autumn, summer to winter for Tas and from summer, spring, autumn to winter for Pr. Two parameters, i.e., the statistical significance level (α) and the minimum number of grids in every climate zone (Nmin), and their joint effects are significant for the effectiveness of FIGGRA; normalization of a nonnormal climate-variable distribution is helpful for the effectiveness only for Pr. For FIGGRA-based LSCCIAA studies, a low value of Nmin is recommended for both Pr and Tas, and a high and medium value of α for Pr and Tas, respectively.

The study of combining Latin Hypercube Sampling method and LU decomposition method (LULHS method) for constructing spatial random field

NASA Astrophysics Data System (ADS)

WANG, P. T.

2015-12-01

Groundwater modeling requires to assign hydrogeological properties to every numerical grid. Due to the lack of detailed information and the inherent spatial heterogeneity, geological properties can be treated as random variables. Hydrogeological property is assumed to be a multivariate distribution with spatial correlations. By sampling random numbers from a given statistical distribution and assigning a value to each grid, a random field for modeling can be completed. Therefore, statistics sampling plays an important role in the efficiency of modeling procedure. Latin Hypercube Sampling (LHS) is a stratified random sampling procedure that provides an efficient way to sample variables from their multivariate distributions. This study combines the the stratified random procedure from LHS and the simulation by using LU decomposition to form LULHS. Both conditional and unconditional simulations of LULHS were develpoed. The simulation efficiency and spatial correlation of LULHS are compared to the other three different simulation methods. The results show that for the conditional simulation and unconditional simulation, LULHS method is more efficient in terms of computational effort. Less realizations are required to achieve the required statistical accuracy and spatial correlation.

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Shih, T. I-P.; Roelke, R. J.

1991-01-01

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

A Quadtree-gridding LBM with Immersed Boundary for Two-dimension Viscous Flows

NASA Astrophysics Data System (ADS)

Yao, Jieke; Feng, Wenliang; Chen, Bin; Zhou, Wei; Cao, Shikun

2017-07-01

An un-uniform quadtree grids lattice Boltzmann method (LBM) with immersed boundary is presented in this paper. In overlapping for different level grids, temporal and spatial interpolation are necessary to ensure the continuity of physical quantity. In order to take advantage of the equation for temporal and spatial step in the same level grids, equal interval interpolation, which is simple to apply to any refined boundary grids in the LBM, is adopted in temporal and spatial aspects to obtain second-order accuracy. The velocity correction, which can guarantee more preferably no-slip boundary condition than the direct forcing method and the momentum exchange method in the traditional immersed-boundary LBM, is used for solid boundary to make the best of Cartesian grid. In present quadtree-gridding immersed-boundary LBM, large eddy simulation (LES) is adopted to simulate the flows over obstacle in higher Reynolds number (Re). The incompressible viscous flows over circular cylinder are carried out, and a great agreement is obtained.

Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

NASA Astrophysics Data System (ADS)

Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

2017-10-01

A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3.9 and 6.5 °C for 2050s and 2080s relative to 1990s in Ontario, respectively; Cooling degree days and hot days will significantly increase over southern Ontario and heating degree days and cold days will significantly decrease in northern Ontario. Annual total precipitation will increase over Ontario and heavy precipitation events will increase as well. These results are consistent with conclusions in many other studies in the literature.

Research on Ultrasonic Flaw Detection of Steel Weld in Spatial Grid Structure

NASA Astrophysics Data System (ADS)

Du, Tao; Sun, Jiandong; Fu, Shengguang; Zhang, Changquan; Gao, Qing

2017-06-01

The welding quality of spatial grid member is an important link in quality control of steel structure. The paper analyzed the reasons that the welding seam of small-bore pipe with thin wall grid structure is difficult to be detected by ultrasonic wave from the theoretical and practical aspects. A series of feasible detection methods was also proposed by improving probe and operation approaches in this paper, and the detection methods were verified by project cases. Over the years, the spatial grid structure is widely used the engineering by virtue of its several outstanding characteristics such as reasonable structure type, standard member, excellent space integrity and quick installation. The wide application of spatial grid structure brings higher requirements on nondestructive test of grid structure. The implementation of new Code for Construction Quality Acceptance of Steel Structure Work GB50205-2001 strengthens the site inspection of steel structure, especially the site inspection of ultrasonic flaw detection in steel weld. The detection for spatial grid member structured by small-bore and thin-walled pipes is difficult due to the irregular influence of sound pressure in near-field region of sound field, sound beam diffusion generated by small bore pipe and reduction of sensitivity. Therefore, it is quite significant to select correct detecting conditions. The spatial grid structure of welding ball and bolt ball is statically determinate structure with high-order axial force which is connected by member bars and joints. It is welded by shrouding or conehead of member bars and of member bar and bolt-node sphere. It is obvious that to ensure the quality of these welding positions is critical to the quality of overall grid structure. However, the complexity of weld structure and limitation of ultrasonic detection method cause many difficulties in detection. No satisfactory results will be obtained by the conventional detection technology, so some special approaches must be used.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Gujarat

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Tamil Nadu

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Tamil Nadu is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Rajasthan

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Andhra Pradesh

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Karnataka

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Maharashtra

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

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Improved Forecasting of Next Day Ozone Concentrations in the Eastern U.S.

EPA Science Inventory

There is an urgent need to provide accurate air quality information and forecasts to the general public. A hierarchical space-time model is used to forecast next day spatial patterns of daily maximum 8-hr ozone concentrations. The model combines ozone monitoring data and gridded...

: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”

EPA Science Inventory

Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

The influence of uncertainty and location-specific conditions on the environmental prioritisation of human pharmaceuticals in Europe.

PubMed

Oldenkamp, Rik; Huijbregts, Mark A J; Ragas, Ad M J

2016-05-01

The selection of priority APIs (Active Pharmaceutical Ingredients) can benefit from a spatially explicit approach, since an API might exceed the threshold of environmental concern in one location, while staying below that same threshold in another. However, such a spatially explicit approach is relatively data intensive and subject to parameter uncertainty due to limited data. This raises the question to what extent a spatially explicit approach for the environmental prioritisation of APIs remains worthwhile when accounting for uncertainty in parameter settings. We show here that the inclusion of spatially explicit information enables a more efficient environmental prioritisation of APIs in Europe, compared with a non-spatial EU-wide approach, also under uncertain conditions. In a case study with nine antibiotics, uncertainty distributions of the PAF (Potentially Affected Fraction) of aquatic species were calculated in 100∗100km(2) environmental grid cells throughout Europe, and used for the selection of priority APIs. Two APIs have median PAF values that exceed a threshold PAF of 1% in at least one environmental grid cell in Europe, i.e., oxytetracycline and erythromycin. At a tenfold lower threshold PAF (i.e., 0.1%), two additional APIs would be selected, i.e., cefuroxime and ciprofloxacin. However, in 94% of the environmental grid cells in Europe, no APIs exceed either of the thresholds. This illustrates the advantage of following a location-specific approach in the prioritisation of APIs. This added value remains when accounting for uncertainty in parameter settings, i.e., if the 95th percentile of the PAF instead of its median value is compared with the threshold. In 96% of the environmental grid cells, the location-specific approach still enables a reduction of the selection of priority APIs of at least 50%, compared with a EU-wide prioritisation. Copyright © 2016 Elsevier Ltd. All rights reserved.

True-3D Accentuating of Grids and Streets in Urban Topographic Maps Enhances Human Object Location Memory

PubMed Central

Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

2015-01-01

Cognitive representations of learned map information are subject to systematic distortion errors. Map elements that divide a map surface into regions, such as content-related linear symbols (e.g. streets, rivers, railway systems) or additional artificial layers (coordinate grids), provide an orientation pattern that can help users to reduce distortions in their mental representations. In recent years, the television industry has started to establish True-3D (autostereoscopic) displays as mass media. These modern displays make it possible to watch dynamic and static images including depth illusions without additional devices, such as 3D glasses. In these images, visual details can be distributed over different positions along the depth axis. Some empirical studies of vision research provided first evidence that 3D stereoscopic content attracts higher attention and is processed faster. So far, the impact of True-3D accentuating has not yet been explored concerning spatial memory tasks and cartography. This paper reports the results of two empirical studies that focus on investigations whether True-3D accentuating of artificial, regular overlaying line features (i.e. grids) and content-related, irregular line features (i.e. highways and main streets) in official urban topographic maps (scale 1/10,000) further improves human object location memory performance. The memory performance is measured as both the percentage of correctly recalled object locations (hit rate) and the mean distances of correctly recalled objects (spatial accuracy). It is shown that the True-3D accentuating of grids (depth offset: 5 cm) significantly enhances the spatial accuracy of recalled map object locations, whereas the True-3D emphasis of streets significantly improves the hit rate of recalled map object locations. These results show the potential of True-3D displays for an improvement of the cognitive representation of learned cartographic information. PMID:25679208

The Aging Navigational System.

PubMed

Lester, Adam W; Moffat, Scott D; Wiener, Jan M; Barnes, Carol A; Wolbers, Thomas

2017-08-30

The discovery of neuronal systems dedicated to computing spatial information, composed of functionally distinct cell types such as place and grid cells, combined with an extensive body of human-based behavioral and neuroimaging research has provided us with a detailed understanding of the brain's navigation circuit. In this review, we discuss emerging evidence from rodents, non-human primates, and humans that demonstrates how cognitive aging affects the navigational computations supported by these systems. Critically, we show 1) that navigational deficits cannot solely be explained by general deficits in learning and memory, 2) that there is no uniform decline across different navigational computations, and 3) that navigational deficits might be sensitive markers for impending pathological decline. Following an introduction to the mechanisms underlying spatial navigation and how they relate to general processes of learning and memory, the review discusses how aging affects the perception and integration of spatial information, the creation and storage of memory traces for spatial information, and the use of spatial information during navigational behavior. The closing section highlights the clinical potential of behavioral and neural markers of spatial navigation, with a particular emphasis on neurodegenerative disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Voxel inversion of airborne electromagnetic data for improved model integration

NASA Astrophysics Data System (ADS)

Fiandaca, Gianluca; Auken, Esben; Kirkegaard, Casper; Vest Christiansen, Anders

2014-05-01

Inversion of electromagnetic data has migrated from single site interpretations to inversions including entire surveys using spatial constraints to obtain geologically reasonable results. Though, the model space is usually linked to the actual observation points. For airborne electromagnetic (AEM) surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space, and the geophysical information has to be relocated for integration in (hydro)geological models. We have developed a new geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the soil properties is computed everywhere by means of an interpolation function (e.g. inverse distance or kriging). Given this definition of the voxel model space, the 1D forward responses of the AEM data are computed as follows: 1) a 1D model subdivision, in terms of model thicknesses, is defined for each 1D data set, creating "virtual" layers. 2) the "virtual" 1D models at the sounding positions are finalized by interpolating the soil properties (the resistivity) in the center of the "virtual" layers. 3) the forward response is computed in 1D for each "virtual" model. We tested the new inversion scheme on an AEM survey carried out with the SkyTEM system close to Odder, in Denmark. The survey comprises 106054 dual mode AEM soundings, and covers an area of approximately 13 km X 16 km. The voxel inversion was carried out on a structured grid of 260 X 325 X 29 xyz nodes (50 m xy spacing), for a total of 2450500 inversion parameters. A classical spatially constrained inversion (SCI) was carried out on the same data set, using 106054 spatially constrained 1D models with 29 layers. For comparison, the SCI inversion models have been gridded on the same grid of the voxel inversion. The new voxel inversion and the classic SCI give similar data fit and inversion models. The voxel inversion decouples the geophysical model from the position of acquired data, and at the same time fits the data as well as the classic SCI inversion. Compared to the classic approach, the voxel inversion is better suited for informing directly (hydro)geological models and for sequential/Joint/Coupled (hydro)geological inversion. We believe that this new approach will facilitate the integration of geophysics, geology and hydrology for improved groundwater and environmental management.

Environmental boundaries as a mechanism for correcting and anchoring spatial maps

PubMed Central

2016-01-01

Abstract Ubiquitous throughout the animal kingdom, path integration‐based navigation allows an animal to take a circuitous route out from a home base and using only self‐motion cues, calculate a direct vector back. Despite variation in an animal's running speed and direction, medial entorhinal grid cells fire in repeating place‐specific locations, pointing to the medial entorhinal circuit as a potential neural substrate for path integration‐based spatial navigation. Supporting this idea, grid cells appear to provide an environment‐independent metric representation of the animal's location in space and preserve their periodic firing structure even in complete darkness. However, a series of recent experiments indicate that spatially responsive medial entorhinal neurons depend on environmental cues in a more complex manner than previously proposed. While multiple types of landmarks may influence entorhinal spatial codes, environmental boundaries have emerged as salient landmarks that both correct error in entorhinal grid cells and bind internal spatial representations to the geometry of the external spatial world. The influence of boundaries on error correction and grid symmetry points to medial entorhinal border cells, which fire at a high rate only near environmental boundaries, as a potential neural substrate for landmark‐driven control of spatial codes. The influence of border cells on other entorhinal cell populations, such as grid cells, could depend on plasticity, raising the possibility that experience plays a critical role in determining how external cues influence internal spatial representations. PMID:26563618

Global gridded crop specific agricultural areas from 1961-2014

NASA Astrophysics Data System (ADS)

Konar, M.; Jackson, N. D.

2017-12-01

Current global cropland datasets are limited in crop specificity and temporal resolution. Time series maps of crop specific agricultural areas would enable us to better understand the global agricultural geography of the 20th century. To this end, we develop a global gridded dataset of crop specific agricultural areas from 1961-2014. To do this, we downscale national cropland information using a probabilistic approach. Our method relies upon gridded Global Agro-Ecological Zones (GAEZ) maps, the History Database of the Global Environment (HYDE), and crop calendars from Sacks et al. (2010). We estimate crop-specific agricultural areas for a 0.25 degree spatial grid and annual time scale for all major crops. We validate our global estimates for the year 2000 with Monfreda et al. (2008) and our time series estimates within the United States using government data. This database will contribute to our understanding of global agricultural change of the past century.

GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids

USGS Publications Warehouse

Lien, Jyh-Ming; Liu, Gaisheng; Langevin, Christian D.

2015-01-01

GRIDGEN is a computer program for creating layered quadtree grids for use with numerical models, such as the MODFLOW–USG program for simulation of groundwater flow. The program begins by reading a three-dimensional base grid, which can have variable row and column widths and spatially variable cell top and bottom elevations. From this base grid, GRIDGEN will continuously divide into four any cell intersecting user-provided refinement features (points, lines, and polygons) until the desired level of refinement is reached. GRIDGEN will then smooth, or balance, the grid so that no two adjacent cells, including overlying and underlying cells, differ by more than a user-specified level tolerance. Once these gridding processes are completed, GRIDGEN saves a tree structure file so that the layered quadtree grid can be quickly reconstructed as needed. Once a tree structure file has been created, GRIDGEN can then be used to (1) export the layered quadtree grid as a shapefile, (2) export grid connectivity and cell information as ASCII text files for use with MODFLOW–USG or other numerical models, and (3) intersect the grid with shapefiles of points, lines, or polygons, and save intersection output as ASCII text files and shapefiles. The GRIDGEN program is demonstrated by creating a layered quadtree grid for the Biscayne aquifer in Miami-Dade County, Florida, using hydrologic features to control where refinement is added.

A Tutorial on Creating a Grid Cell Land Cover Data File from Remote Sensing Data.

DTIC Science & Technology

1985-06-01

Creating a Grid Cell Land Cover Data File from Remote Sensing Data Gary E. Ford, Doreen L Meyer, and V. Ralph Algazi Signal and Image Processing Laboratory... L 1. INTRODUCTION Spatial data management systems, also known as geographic information systems, pro- vide powerful, practical tools for the...erosion [8]. Other -... ..... .. . . .. . . -5- 60 Z 0"C. 0 0. , ...- 9L> c 0 o o ( L - 0- 0.0a c 0 4- b. 0 ~ CL*~ C 0 .CL x 0 I" .- -J oo : -. 0 a a Z 0Z I1

An open source software for fast grid-based data-mining in spatial epidemiology (FGBASE).

PubMed

Baker, David M; Valleron, Alain-Jacques

2014-10-30

Examining whether disease cases are clustered in space is an important part of epidemiological research. Another important part of spatial epidemiology is testing whether patients suffering from a disease are more, or less, exposed to environmental factors of interest than adequately defined controls. Both approaches involve determining the number of cases and controls (or population at risk) in specific zones. For cluster searches, this often must be done for millions of different zones. Doing this by calculating distances can lead to very lengthy computations. In this work we discuss the computational advantages of geographical grid-based methods, and introduce an open source software (FGBASE) which we have created for this purpose. Geographical grids based on the Lambert Azimuthal Equal Area projection are well suited for spatial epidemiology because they preserve area: each cell of the grid has the same area. We describe how data is projected onto such a grid, as well as grid-based algorithms for spatial epidemiological data-mining. The software program (FGBASE), that we have developed, implements these grid-based methods. The grid based algorithms perform extremely fast. This is particularly the case for cluster searches. When applied to a cohort of French Type 1 Diabetes (T1D) patients, as an example, the grid based algorithms detected potential clusters in a few seconds on a modern laptop. This compares very favorably to an equivalent cluster search using distance calculations instead of a grid, which took over 4 hours on the same computer. In the case study we discovered 4 potential clusters of T1D cases near the cities of Le Havre, Dunkerque, Toulouse and Nantes. One example of environmental analysis with our software was to study whether a significant association could be found between distance to vineyards with heavy pesticide. None was found. In both examples, the software facilitates the rapid testing of hypotheses. Grid-based algorithms for mining spatial epidemiological data provide advantages in terms of computational complexity thus improving the speed of computations. We believe that these methods and this software tool (FGBASE) will lower the computational barriers to entry for those performing epidemiological research.

Three-Dimensional City Determinants of the Urban Heat Island: A Statistical Approach

NASA Astrophysics Data System (ADS)

Chun, Bum Seok

There is no doubt that the Urban Heat Island (UHI) is a mounting problem in built-up environments, due to the energy retention by the surface materials of dense buildings, leading to increased temperatures, air pollution, and energy consumption. Much of the earlier research on the UHI has used two-dimensional (2-D) information, such as land uses and the distribution of vegetation. In the case of homogeneous land uses, it is possible to predict surface temperatures with reasonable accuracy with 2-D information. However, three-dimensional (3-D) information is necessary to analyze more complex sites, including dense building clusters. Recent research on the UHI has started to consider multi-dimensional models. The purpose of this research is to explore the urban determinants of the UHI, using 2-D/3-D urban information with statistical modeling. The research includes the following stages: (a) estimating urban temperature, using satellite images, (b) developing a 3-D city model by LiDAR data, (c) generating geometric parameters with regard to 2-/3-D geospatial information, and (d) conducting different statistical analyses: OLS and spatial regressions. The research area is part of the City of Columbus, Ohio. To effectively and systematically analyze the UHI, hierarchical grid scales (480m, 240m, 120m, 60m, and 30m) are proposed, together with linear and the log-linear regression models. The non-linear OLS models with Log(AST) as dependent variable have the highest R2 among all the OLS-estimated models. However, both SAR and GSM models are estimated for the 480m, 240m, 120m, and 60m grids to reduce their spatial dependency. Most GSM models have R2s higher than 0.9, except for the 240m grid. Overall, the urban characteristics having high impacts in all grids are embodied in solar radiation, 3-D open space, greenery, and water streams. These results demonstrate that it is possible to mitigate the UHI, providing guidelines for policies aiming to reduce the UHI.

GeoPAT: A toolbox for pattern-based information retrieval from large geospatial databases

NASA Astrophysics Data System (ADS)

Jasiewicz, Jarosław; Netzel, Paweł; Stepinski, Tomasz

2015-07-01

Geospatial Pattern Analysis Toolbox (GeoPAT) is a collection of GRASS GIS modules for carrying out pattern-based geospatial analysis of images and other spatial datasets. The need for pattern-based analysis arises when images/rasters contain rich spatial information either because of their very high resolution or their very large spatial extent. Elementary units of pattern-based analysis are scenes - patches of surface consisting of a complex arrangement of individual pixels (patterns). GeoPAT modules implement popular GIS algorithms, such as query, overlay, and segmentation, to operate on the grid of scenes. To achieve these capabilities GeoPAT includes a library of scene signatures - compact numerical descriptors of patterns, and a library of distance functions - providing numerical means of assessing dissimilarity between scenes. Ancillary GeoPAT modules use these functions to construct a grid of scenes or to assign signatures to individual scenes having regular or irregular geometries. Thus GeoPAT combines knowledge retrieval from patterns with mapping tasks within a single integrated GIS environment. GeoPAT is designed to identify and analyze complex, highly generalized classes in spatial datasets. Examples include distinguishing between different styles of urban settlements using VHR images, delineating different landscape types in land cover maps, and mapping physiographic units from DEM. The concept of pattern-based spatial analysis is explained and the roles of all modules and functions are described. A case study example pertaining to delineation of landscape types in a subregion of NLCD is given. Performance evaluation is included to highlight GeoPAT's applicability to very large datasets. The GeoPAT toolbox is available for download from

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

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

Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized inmore » the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.« less

Seismic wavefield simulation in 2D elastic and viscoelastic tilted transversely isotropic media: comparisons between four different kinds of finite-difference grid schemes

NASA Astrophysics Data System (ADS)

Li, Zhong-sheng; Bai, Chao-ying; Sun, Yao-chong

2013-08-01

In this paper, we use the staggered grid, the auxiliary grid, the rotated staggered grid and the non-staggered grid finite-difference methods to simulate the wavefield propagation in 2D elastic tilted transversely isotropic (TTI) and viscoelastic TTI media, respectively. Under the stability conditions, we choose different spatial and temporal intervals to get wavefront snapshots and synthetic seismograms to compare the four algorithms in terms of computational accuracy, CPU time, phase shift, frequency dispersion and amplitude preservation. The numerical results show that: (1) the rotated staggered grid scheme has the least memory cost and the fastest running speed; (2) the non-staggered grid scheme has the highest computational accuracy and least phase shift; (3) the staggered grid has less frequency dispersion even when the spatial interval becomes larger.

In-time source tracking of watershed loads of Taihu Lake Basin, China based on spatial relationship modeling.

PubMed

Wang, Ce; Bi, Jun; Zhang, Xu-Xiang; Fang, Qiang; Qi, Yi

2018-05-25

Influent river carrying cumulative watershed load plays a significant role in promoting nuisance algal bloom in river-fed lake. It is most relevant to discern in-stream water quality exceedance and evaluate the spatial relationship between risk location and potential pollution sources. However, no comprehensive studies of source tracking in watershed based on management grid have been conducted for refined water quality management, particularly for plain terrain with complex river network. In this study, field investigations were implemented during 2014 in Taige Canal watershed of Taihu Lake Basin. A Geographical Information System (GIS)-based spatial relationship model was established to characterize the spatial relationships of "point (point-source location and monitoring site)-line (river segment)-plane (catchment)." As a practical exemplification, in-time source tracking was triggered on April 15, 2015 at Huangnianqiao station, where TN and TP concentration violated the water quality standard (TN 4.0 mg/L, TP 0.15 mg/L). Of the target grid cells, 53 and 46 were identified as crucial areas having high pollution intensity for TN and TP pollution, respectively. The estimated non-point source load in each grid cell could be apportioned into different source types based on spatial pollution-related entity objects. We found that the non-point source load derived from rural sewage and livestock and poultry breeding accounted for more than 80% of total TN or TP load than another source type of crop farming. The approach in this study would be of great benefit to local authorities for identifying the serious polluted regions and efficiently making environmental policies to reduce watershed load.

WPS mediation: An approach to process geospatial data on different computing backends

NASA Astrophysics Data System (ADS)

Giuliani, Gregory; Nativi, Stefano; Lehmann, Anthony; Ray, Nicolas

2012-10-01

The OGC Web Processing Service (WPS) specification allows generating information by processing distributed geospatial data made available through Spatial Data Infrastructures (SDIs). However, current SDIs have limited analytical capacities and various problems emerge when trying to use them in data and computing-intensive domains such as environmental sciences. These problems are usually not or only partially solvable using single computing resources. Therefore, the Geographic Information (GI) community is trying to benefit from the superior storage and computing capabilities offered by distributed computing (e.g., Grids, Clouds) related methods and technologies. Currently, there is no commonly agreed approach to grid-enable WPS. No implementation allows one to seamlessly execute a geoprocessing calculation following user requirements on different computing backends, ranging from a stand-alone GIS server up to computer clusters and large Grid infrastructures. Considering this issue, this paper presents a proof of concept by mediating different geospatial and Grid software packages, and by proposing an extension of WPS specification through two optional parameters. The applicability of this approach will be demonstrated using a Normalized Difference Vegetation Index (NDVI) mediated WPS process, highlighting benefits, and issues that need to be further investigated to improve performances.

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

Zhang, H; Kong, V; Jin, J

Purpose: A synchronized moving grid (SMOG) has been proposed to reduce scatter and lag artifacts in cone beam computed tomography (CBCT). However, information is missing in each projection because certain areas are blocked by the grid. A previous solution to this issue is acquiring 2 complimentary projections at each position, which increases scanning time. This study reports our first Result using an inter-projection sensor fusion (IPSF) method to estimate missing projection in our prototype SMOG-based CBCT system. Methods: An in-house SMOG assembling with a 1:1 grid of 3 mm gap has been installed in a CBCT benchtop. The grid movesmore » back and forth in a 3-mm amplitude and up-to 20-Hz frequency. A control program in LabView synchronizes the grid motion with the platform rotation and x-ray firing so that the grid patterns for any two neighboring projections are complimentary. A Catphan was scanned with 360 projections. After scatter correction, the IPSF algorithm was applied to estimate missing signal for each projection using the information from the 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct CBCT images. The CBCTs were compared to those reconstructed using normal projections without applying the SMOG system. Results: The SMOG-IPSF method may reduce image dose by half due to the blocked radiation by the grid. The method almost completely removed scatter related artifacts, such as the cupping artifacts. The evaluation of line pair patterns in the CatPhan suggested that the spatial resolution degradation was minimal. Conclusion: The SMOG-IPSF is promising in reducing scatter artifacts and improving image quality while reducing radiation dose.« less

Integration Of 3D Geographic Information System (GIS) For Effective Waste Management Practice

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

Rood, G.J.; Hecox, G.R.

2006-07-01

Soil remediation in response to the presence of residual radioactivity resulting from past MED/AEC activities is currently in progress under the Formerly Utilized Sites Remedial Action Program near the St. Louis, MO airport. During GY05, approximately 92,000 cubic meters (120,000 cubic yards) of radioactive soil was excavated, packaged and transported via rail for disposal at U.S. Ecology or Envirocare of Utah, LLC. To facilitate the management of excavation/transportation/disposal activities, a 3D GIS was developed for the site that was used to estimate the in-situ radionuclide activities, activities in excavation block areas, and shipping activities using a sum-of ratio (SOR) methodmore » for combining various radionuclide compounds into applicable transportation and disposal SOR values. The 3D GIS was developed starting with the SOR values for the approximately 900 samples from 90 borings. These values were processed into a three-dimensional (3D) point grid using kriging with nominal grid spacing of 1.5 by 1.5 meter horizontal by 0.3 meter vertical. The final grid, clipped to the area and soil interval above the planned base of excavation, consisted of 210,000 individual points. Standard GIS volumetric and spatial join procedures were used to calculate the volume of soil represented by each grid point, the base of excavation, depth below ground surface, elevation, surface elevation and SOR values for each point in the final grid. To create the maps needed for management, the point grid results were spatially joined to each excavation area in 0.9 meter (3 foot) depth intervals and the average SOR and total volumes were calculations. The final maps were color-coded for easy identification of areas above the specific transportation or disposal criteria. (authors)« less

EXAMINATION OF MODEL PREDICTIONS AT DIFFERENT HORIZONTAL GRID RESOLUTIONS

EPA Science Inventory

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs ...

Cartograms Facilitate Communication of Climate Change Risks and Responsibilities

NASA Astrophysics Data System (ADS)

Döll, Petra

2017-12-01

Communication of climate change (CC) risks is challenging, in particular if global-scale spatially resolved quantitative information is to be conveyed. Typically, visualization of CC risks, which arise from the combination of hazard, exposure and vulnerability, is confined to showing only the hazards in the form of global thematic maps. This paper explores the potential of contiguous value-by-area cartograms, that is, distorted density-equalizing maps, for improving communication of CC risks and the countries' differentiated responsibilities for CC. Two global-scale cartogram sets visualize, as an example, groundwater-related CC risks in 0.5° grid cells, another one the correlation of (cumulative) fossil-fuel carbon dioxide emissions with the countries' population and gross domestic product. Viewers of the latter set visually recognize the lack of global equity and that the countries' wealth has been built on harmful emissions. I recommend that CC risks are communicated by bivariate gridded cartograms showing the hazard in color and population, or a combination of population and a vulnerability indicator, by distortion of grid cells. Gridded cartograms are also appropriate for visualizing the availability of natural resources to humans. For communicating complex information, sets of cartograms should be carefully designed instead of presenting single cartograms. Inclusion of a conventionally distorted map enhances the viewers' capability to take up the information represented by distortion. Empirical studies about the capability of global cartograms to convey complex information and to trigger moral emotions should be conducted, with a special focus on risk communication.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.

City rats: insight from rat spatial behavior into human cognition in urban environments.

PubMed

Yaski, Osnat; Portugali, Juval; Eilam, David

2011-09-01

The structure and shape of the urban environment influence our ability to find our way about in the city. Understanding how the physical properties of the environment affect spatial behavior and cognition is therefore a necessity. However, there are inherent difficulties in empirically studying complex and large-scale urban environments. These include the need to isolate the impact of specific urban features and to acquire data on the physical activity of individuals. In the present study, we attempted to overcome the above obstacles and examine the relation between urban environments and spatial cognition by testing the spatial behavior of rats. This idea originated from the resemblance in the operative brain functions and in the mechanisms and strategies employed by humans and other animals when acquiring spatial information and establishing an internal representation, as revealed in past studies. Accordingly, we tested rats in arenas that simulated a grid urban layout (e.g. Manhattan streets) and an irregular urban layout (e.g. Jerusalem streets). We found that in the grid layout, rat movement was more structured and extended over a greater area compared with their restricted movement in the irregular layout. These movement patterns recall those of humans in respective urban environments, illustrating that the structure and shape of the environment affect spatial behavior similarly in humans and rats. Overall, testing rats in environments that simulate facets of urban environments can provide new insights into human spatial cognition in urban environments.

Place Cells, Grid Cells, and Memory

PubMed Central

Moser, May-Britt; Rowland, David C.; Moser, Edvard I.

2015-01-01

The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal–entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal–hippocampal circuit may be at the heart of the mechanism for declarative memory formation. PMID:25646382

GOW2.0: A global wave hindcast of high resolution

NASA Astrophysics Data System (ADS)

Menendez, Melisa; Perez, Jorge; Losada, Inigo

2016-04-01

The information provided by reconstructions of historical wind generated waves is of paramount importance for a variety of coastal and offshore purposes (e.g. risk assessment, design of costal structures and coastal management). Here, a new global wave hindcast (GOW2.0) is presented. This hindcast is an update of GOW1.0 (Reguero et al. 2012) motivated by the emergence of new settings and atmospheric information from reanalysis during recent years. GOW2.0 is based on version 4.18 of WaveWatch III numerical model (Tolman, 2014). Main features of the model set-up are the analysis and selection of recent source terms concerning wave generation and dissipation (Ardhuin et al. 2010, Zieger et al., 2015) and the implementation of obstruction grids to improve the modeling of wave shadowing effects in line with the approach described in Chawla and Tolman (2007). This has been complemented by a multigrid system and the use of the hourly wind and ice coverage from the Climate Forecast System Reanalysis, CFSR (30km spatial resolution approximately). The multigrid scheme consists of a series of "two-way" nested domains covering the whole ocean basins at a 0.5° spatial resolution and continental shelfs worldwide at a 0.25° spatial resolution. In addition, a technique to reconstruct wave 3D spectra for any grid-point is implemented from spectral partitioning information. A validation analysis of GOW2.0 outcomes has been undertaken considering wave spectral information from surface buoy stations and multi-mission satellite data for a spatial validation. GOW2.0 shows a substantial improvement over its predecessor for all the analyzed variables. In summary, GOW2.0 reconstructs historical wave spectral data and climate information from 1979 to present at hourly resolution providing higher spatial resolution over regions where local generated wind seas, bimodal-spectral behaviour and relevant swell transformations across the continental shelf are important. Ardhuin F, Rogers E, Babanin AV, et al (2010). Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation. J Phys Oceanogr. 2010;40(9):1917-1941. doi:10.1175/2010JPO4324.1. Chawla A, Tolman HL. Obstruction grids for spectral wave models. Ocean Model. 2008;22(1-2):12-25. doi:10.1016/j.ocemod.2008.01.003. Reguero BG, Menendez M, Mendez FJ, Minguez R, Losada IJ (2012). A Global Ocean Wave (GOW) calibrated reanalysis from 1948 onwards. Coastal Engineering, 65, 38-55. Tolman HL (2014). User manual and system documentation of WAVEWATCH III version 4.18. NOAA / NWS / NCEP / MMAB Tech Note. Zieger S, Babanin AV, Rogers WE, Young IR (2015). Observation-based source terms in the third-generation wave model WAVEWATCH. Ocean Modelling, 96, 2-25.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

Documentation of a digital spatial data base for hydrologic investigations, Broward County, Florida

USGS Publications Warehouse

Sonenshein, R.S.

1992-01-01

Geographic information systems have become an important tool in planning for the protection and development of natural resources, including ground water and surface water. A digital spatial data base consisting of 18 data layers that can be accessed by a geographic information system was developed for Broward County, Florida. Five computer programs, including one that can be used to create documentation files for each data layer and four that can be used to create data layers from data files not already in geographic information system format, were also developed. Four types of data layers have been developed. Data layers for manmade features include major roads, municipal boundaries, the public land-survey section grid, land use, and underground storage tank facilities. The data layer for topographic features consists of surveyed point land-surface elevations. Data layers for hydrologic features include surface-water and rainfall data-collection stations, surface-water bodies, water-control district boundaries, and water-management basins. Data layers for hydrogeologic features include soil associations, transmissivity polygons, hydrogeologic unit depths, and a finite-difference model grid for south-central Broward County. Each data layer is documented as to the extent of the features, number of features, scale, data sources, and a description of the attribute tables where applicable.

Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions

PubMed Central

Shipston‐Sharman, Oliver; Solanka, Lukas

2016-01-01

Abstract Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing. PMID:27870120

On the uncertainties associated with using gridded rainfall data as a proxy for observed

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Verdon-Kidd, D. C.

2011-09-01

Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods)? This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets - the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia (SA) initially using gridded data as the source of rainfall input and then gauged rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged or point data. Rather the intention is to quantify differences between various gridded data sources and how they compare with gauged data so that these differences can be considered and accounted for in studies that utilise these gridded datasets. Ultimately, if key decisions are going to be based on the outputs of models that use gridded data, an estimate (or at least an understanding) of the uncertainties relating to the assumptions made in the development of gridded data and how that gridded data compares with reality should be made.

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

Space-time modeling using environmental constraints in a mobile robot system

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1990-01-01

Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.

A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS

EPA Science Inventory

A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...

Science Enabling Applications of Gridded Radiances and Products

NASA Astrophysics Data System (ADS)

Goldberg, M.; Wolf, W.; Zhou, L.

2005-12-01

New generations of hyperspectral sounders and imagers are not only providing vastly improved information to monitor, assess and predict the Earth's environment, they also provide tremendous volumes of data to manage. Key management challenges must include data processing, distribution, archive and utilization. At the NOAA/NESDIS Office of Research and Applications, we have started to address the challenge of utilizing high volume satellite by thinning observations and developing gridded datasets from the observations made from the NASA AIRS, AMSU and MODIS instrument. We have developed techniques for intelligent thinning of AIRS data for numerical weather prediction, by selecting the clearest AIRS 14 km field of view within a 3 x 3 array. The selection uses high spatial resolution 1 km MODIS data which are spatially convolved to the AIRS field of view. The MODIS cloud masks and AIRS cloud tests are used to select the clearest. During the real-time processing the data are thinned and gridded to support monitoring, validation and scientific studies. Products from AIRS, which includes profiles of temperature, water vapor and ozone and cloud-corrected infrared radiances for more than 2000 channels, are derived from a single AIRS/AMSU field of regard, which is a 3 x 3 array of AIRS footprints (each with a 14 km spatial resolution) collocated with a single AMSU footprint (42 km). One of our key gridded dataset is a daily 3 x 3 latitude/longitude projection which contains the nearest AIRS/AMSU field of regard with respect to the center of the 3 x 3 lat/lon grid. This particular gridded dataset is 1/40 the size of the full resolution data. This gridded dataset is the type of product request that can be used to support algorithm validation and improvements. It also provides for a very economical approach for reprocessing, testing and improving algorithms for climate studies without having to reprocess the full resolution data stored at the DAAC. For example, on a single CPU workstation, all the AIRS derived products can be derived from a single year of gridded data in 5 days. This relatively short turnaround time, which can be reduced considerably to 3 hours by using a cluster of 40 pc G5processors, allows for repeated reprocessing at the PIs home institution before substantial investments are made to reprocess the full resolution data sets archived at the DAAC. In other words, do not reprocess the full resolution data until the science community have tested and selected the optimal algorithm on the gridded data. Development and applications of gridded radiances and products will be discussed. The applications can be provided as part of a web-based service.

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

2017-12-01

SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be demonstrated by results obtained while developing the methodology for assessing collective significance of trends in multi-site weather series. The performance of the proposed test statistics is assessed based on large number of realisations of synthetic series produced by WG assuming a given statistical structure and trend of the weather series.

Filling the gap: Using fishers' knowledge to map the extent and intensity of fishing activity.

PubMed

Szostek, Claire L; Murray, Lee G; Bell, Ewen; Kaiser, Michel J

2017-08-01

Knowledge of the extent and intensity of fishing activities is critical to inform management in relation to fishing impacts on marine conservation features. Such information can also provide insight into the potential socio-economic impacts of closures (or other restrictions) of fishing grounds that could occur through the future designation of Marine Conservation Zones (MCZs). We assessed the accuracy and validity of fishing effort data (spatial extent and relative effort) obtained from Fishers' Local Knowledge (LK) data compared to that derived from Vessel Monitoring System (VMS) data for a high-value shellfish fishery, the king scallop (Pecten maximus L.) dredge fishery in the English Channel. The spatial distribution of fishing effort from LK significantly correlated with VMS data and the correlation increased with increasing grid cell resolution. Using a larger grid cell size for data aggregation increases the estimation of the total area of seabed impacted by the fishery. In the absence of historical VMS data for vessels ≤15 m LOA (Length Overall), LK data for the inshore fleet provided important insights into the relative effort of the inshore (<6 NM from land) king scallop fishing fleet in the English Channel. The LK data provided a good representation of the spatial extent of inshore fishing activity, whereas representation of the offshore fishery was more precautionary in terms of defining total impact. Significantly, the data highlighted frequently fished areas of particular importance to the inshore fleet. In the absence of independent sources of geospatial information, the use of LK can inform the development of marine planning in relation to both sustainable fishing and conservation objectives, and has application in both developed and developing countries where VMS technology is not utilised in fisheries management. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

USGS Publications Warehouse

Phillips, D.L.; Marks, D.G.

1996-01-01

In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

An ergonomic study on the navigation structure and information units of websites with multimedia content. A case study of the Xbox 360 promotional website.

PubMed

Ariel, Eduardo; de Moraes, Anamaria

2012-01-01

This paper presents an ergonomic study on the navigation structures and information units of entertainment sites with multimedia content. This research is a case study on the XBOX 360 promotional website. It analyzes the presentation of the content on a grid that simulates the spatial displacement of the screen's elements and evaluates the interaction that the page allows for, from the users' point of view.

Entorhinal cortex receptive fields are modulated by spatial attention, even without movement

PubMed Central

König, Peter; König, Seth; Buffalo, Elizabeth A

2018-01-01

Grid cells in the entorhinal cortex allow for the precise decoding of position in space. Along with potentially playing an important role in navigation, grid cells have recently been hypothesized to make a general contribution to mental operations. A prerequisite for this hypothesis is that grid cell activity does not critically depend on physical movement. Here, we show that movement of covert attention, without any physical movement, also elicits spatial receptive fields with a triangular tiling of space. In monkeys trained to maintain central fixation while covertly attending to a stimulus moving in the periphery we identified a significant population (20/141, 14% neurons at a FDR <5%) of entorhinal cells with spatially structured receptive fields. This contrasts with recordings obtained in the hippocampus, where grid-like representations were not observed. Our results provide evidence that neurons in macaque entorhinal cortex do not rely on physical movement. PMID:29537964

High dose bystander effects in spatially fractionated radiation therapy

PubMed Central

Asur, Rajalakshmi; Butterworth, Karl T.; Penagaricano, Jose A.; Prise, Kevin M.; Griffin, Robert J.

2014-01-01

Traditional radiotherapy of bulky tumors has certain limitations. Spatially fractionated radiation therapy (GRID) and intensity modulated radiotherapy (IMRT) are examples of advanced modulated beam therapies that help in significant reductions in normal tissue damage. GRID refers to the delivery of a single high dose of radiation to a large treatment area that is divided into several smaller fields, while IMRT allows improved dose conformity to the tumor target compared to conventional three-dimensional conformal radiotherapy. In this review, we consider spatially fractionated radiotherapy approaches focusing on GRID and IMRT, and present complementary evidence from different studies which support the role of radiation induced signaling effects in the overall radiobiological rationale for these treatments. PMID:24246848

[Spatial distribution pattern and fractal analysis of Larix chinensis populations in Qinling Mountain].

PubMed

Guo, Hua; Wang, Xiaoan; Xiao, Yaping

2005-02-01

In this paper, the fractal characters of Larix chinensis populations in Qinling Mountain were studied by contiguous grid quadrate sampling method and by boxing-counting dimension and information dimension. The results showed that the high boxing-counting dimension (1.8087) and information dimension (1.7931) reflected a higher spatial occupational degree of L. chinensis populations. Judged by the dispersal index and Morisita's pattern index, L. chinensis populations clumped at three different age stages (0-25, 25-50 and over 50 years). From Greig-Smiths' mean variance analysis, the figure of pattern scale showed that L. chinensis populations clumped in 128 m2 and 512 m2, and the different age groups clumped in different scales. The pattern intensities decreased with increasing age, and tended to reduce with increasing area when detected by Kershaw's PI index. The spatial pattern characters of L. chinensis populations may be their responses to environmental factors.

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station data and the gridded product opens up the possibility of merging real-time satellite and intermittent gauge observations to produce more accurate real-time hydrological predictions.

Andreev reflection, a tool to investigate vortex dynamics and quantum turbulence in 3He-B.

PubMed

Fisher, Shaun Neil; Jackson, Martin James; Sergeev, Yuri A; Tsepelin, Viktor

2014-03-25

Andreev reflection of quasiparticle excitations provides a sensitive and passive probe of flow in superfluid (3)He-B. It is particularly useful for studying complex flows generated by vortex rings and vortex tangles (quantum turbulence). We describe the reflection process and discuss the results of numerical simulations of Andreev reflection from vortex rings and from quantum turbulence. We present measurements of vortices generated by a vibrating grid resonator at very low temperatures. The Andreev reflection is measured using an array of vibrating wire sensors. At low grid velocities, ballistic vortex rings are produced. At higher grid velocities, the rings collide and reconnect to produce quantum turbulence. We discuss spatial correlations of the fluctuating vortex signals measured by the different sensor wires. These reveal detailed information about the formation of quantum turbulence and about the underlying vortex dynamics.

Andreev reflection, a tool to investigate vortex dynamics and quantum turbulence in 3He-B

PubMed Central

Fisher, Shaun Neil; Jackson, Martin James; Sergeev, Yuri A.; Tsepelin, Viktor

2014-01-01

Andreev reflection of quasiparticle excitations provides a sensitive and passive probe of flow in superfluid 3He-B. It is particularly useful for studying complex flows generated by vortex rings and vortex tangles (quantum turbulence). We describe the reflection process and discuss the results of numerical simulations of Andreev reflection from vortex rings and from quantum turbulence. We present measurements of vortices generated by a vibrating grid resonator at very low temperatures. The Andreev reflection is measured using an array of vibrating wire sensors. At low grid velocities, ballistic vortex rings are produced. At higher grid velocities, the rings collide and reconnect to produce quantum turbulence. We discuss spatial correlations of the fluctuating vortex signals measured by the different sensor wires. These reveal detailed information about the formation of quantum turbulence and about the underlying vortex dynamics. PMID:24704872

A physically based analytical spatial air temperature and humidity model

NASA Astrophysics Data System (ADS)

Yang, Yang; Endreny, Theodore A.; Nowak, David J.

2013-09-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

NASA Technical Reports Server (NTRS)

Sellers, Piers

2012-01-01

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

The Art of Grid Fields: Geometry of Neuronal Time

PubMed Central

Shilnikov, Andrey L.; Maurer, Andrew Porter

2016-01-01

The discovery of grid cells in the entorhinal cortex has both elucidated our understanding of spatial representations in the brain, and germinated a large number of theoretical models regarding the mechanisms of these cells’ striking spatial firing characteristics. These models cross multiple neurobiological levels that include intrinsic membrane resonance, dendritic integration, after hyperpolarization characteristics and attractor dynamics. Despite the breadth of the models, to our knowledge, parallels can be drawn between grid fields and other temporal dynamics observed in nature, much of which was described by Art Winfree and colleagues long before the initial description of grid fields. Using theoretical and mathematical investigations of oscillators, in a wide array of mediums far from the neurobiology of grid cells, Art Winfree has provided a substantial amount of research with significant and profound similarities. These theories provide specific inferences into the biological mechanisms and extraordinary resemblances across phenomenon. Therefore, this manuscript provides a novel interpretation on the phenomenon of grid fields, from the perspective of coupled oscillators, postulating that grid fields are the spatial representation of phase resetting curves in the brain. In contrast to prior models of gird cells, the current manuscript provides a sketch by which a small network of neurons, each with oscillatory components can operate to form grid cells, perhaps providing a unique hybrid between the competing attractor neural network and oscillatory interference models. The intention of this new interpretation of the data is to encourage novel testable hypotheses. PMID:27013981

A Hybrid 3D Indoor Space Model

NASA Astrophysics Data System (ADS)

Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel

2016-10-01

GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

Comparison of two spatially-resolved fossil fuel CO2 emissions inventories at the urban scale in four US cities

NASA Astrophysics Data System (ADS)

Liang, J.; Gurney, K. R.; O'Keeffe, D.; Patarasuk, R.; Hutchins, M.; Rao, P.

2017-12-01

Spatially-resolved fossil fuel CO2 (FFCO2) emissions are used not only in complex atmospheric modeling systems as prior scenarios to simulate concentrations of CO2 in the atmosphere, but to improve understanding of relationships with socioeconomic factors in support of sustainability policymaking. We present a comparison of ODIAC, a top-down global gridded FFCO2 emissions dataset, and Hesita, a bottom-up FFCO2 emissions dataset, in four US cities, including Los Angles, Indianapolis, Salt Lake City and Baltimore City. ODIAC was developed by downscaling national total emissions to 1km-by-1km grid cells using satellite nightlight imagery as proxy. Hesita was built from the ground up by allocating sector-specific county-level emissions to urban-level spatial surrogates including facility locations, road maps, building footprints/parcels, railroad maps and shipping lanes. The differences in methodology and data sources could lead to large discrepancies in FFCO2 estimates at the urban scale, and these discrepancies need to be taken into account in conducting atmospheric modeling or socioeconomic analysis. This comparison work is aimed at quantifying the statistical and spatial difference between the two FFCO2 inventories. An analysis of the difference in total emissions, spatial distribution and statistical distribution resulted in the following findings: (1) ODIAC agrees well with Hestia in total FFCO2 emissions estimates across the four cities with a difference from 3%-20%; (2) Small-scale areal and linear spatial features such as roads and buildings are either entirely missing or not very well represented in ODIAC, since nightlight imagery might not be able to capture these information. This might further lead to underestimated on-road FFCO2 emissions in ODIAC; (3) The statistical distribution of ODIAC is more concentrated around the mean with much less samples in the lower range. These phenomena could result from the nightlight halo and saturation effects; (4) The grid-cell cumulative emissions of ODIAC appear in good agreement with that of Hestia, implying the two inventories have similar overall spatial structures at the city scale.

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

NASA Astrophysics Data System (ADS)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)

Scalability study of parallel spatial direct numerical simulation code on IBM SP1 parallel supercomputer

NASA Technical Reports Server (NTRS)

Hanebutte, Ulf R.; Joslin, Ronald D.; Zubair, Mohammad

1994-01-01

The implementation and the performance of a parallel spatial direct numerical simulation (PSDNS) code are reported for the IBM SP1 supercomputer. The spatially evolving disturbances that are associated with laminar-to-turbulent in three-dimensional boundary-layer flows are computed with the PS-DNS code. By remapping the distributed data structure during the course of the calculation, optimized serial library routines can be utilized that substantially increase the computational performance. Although the remapping incurs a high communication penalty, the parallel efficiency of the code remains above 40% for all performed calculations. By using appropriate compile options and optimized library routines, the serial code achieves 52-56 Mflops on a single node of the SP1 (45% of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a 'real world' simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP for the same simulation. The scalability information provides estimated computational costs that match the actual costs relative to changes in the number of grid points.

Documenting Uncertainty and Error in Gridded Growing Degree Day and Spring Onset Maps Generated by the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Switzer, J.; Rosemartin, A.; Marsh, L.; Gerst, K.; Crimmins, M.; Weltzin, J. F.

2016-12-01

Since 2016 the USA National Phenology Network (USA-NPN; www.usanpn.org) has produced and delivered daily maps and short-term forecasts of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States. Because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening, and migration, these data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. We will be expanding the suite of gridded map products offered by the USA-NPN to include predictive species-specific maps of phenological transitions in plants and animals at fine spatial and temporal resolution in the future. Data products, such as the gridded maps currently produced by the USA-NPN, inherently contain uncertainty and error arising from multiple sources, including error propagated forward from underlying climate data and from the models implemented. As providing high-quality, vetted data in a transparent way is central to the USA-NPN, we aim to identify and report the sources and magnitude of uncertainty and error in gridded maps and forecast products. At present, we compare our real-time gridded products to independent, trustworthy data sources, such as the Climate Reference Network, on a daily basis and report Mean Absolute Error and bias through an interactive online dashboard.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Optimal Interpolation scheme to generate reference crop evapotranspiration

NASA Astrophysics Data System (ADS)

Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco

2018-05-01

We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.

On the uncertainties associated with using gridded rainfall data as a proxy for observed

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Verdon-Kidd, D. C.

2012-05-01

Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods). This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets - the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids - particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is to quantify differences between various gridded data sources and how they compare with gauged data so that these differences can be considered and accounted for in studies that utilise these gridded datasets. Ultimately, if key decisions are going to be based on the outputs of models that use gridded data, an estimate (or at least an understanding) of the uncertainties relating to the assumptions made in the development of gridded data and how that gridded data compares with reality should be made.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

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

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, 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. 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. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the 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 soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

Assessing and correcting spatial representativeness of tower eddy-covariance flux measurements

NASA Astrophysics Data System (ADS)

Metzger, S.; Xu, K.; Desai, A. R.; Taylor, J. R.; Kljun, N.; Blanken, P.; Burns, S. P.; Scott, R. L.

2014-12-01

Estimating the landscape-scale exchange of ecologically relevant trace gas and energy fluxes from tower eddy-covariance (EC) measurements is often complicated by surface heterogeneity. For example, a tower EC measurement may represent less than 1% of a grid cell resolved by mechanistic models (order 100-1000 km2). In particular for data assimilation or comparison with large-scale observations, it is hence critical to assess and correct the spatial representativeness of tower EC measurements. We present a procedure that determines from a single EC tower the spatio-temporally explicit flux field of its surrounding. The underlying principle is to extract the relationship between biophysical drivers and ecological responses from measurements under varying environmental conditions. For this purpose, high-frequency EC flux processing and source area calculations (≈60 h-1) are combined with remote sensing retrievals of land surface properties and subsequent machine learning. Methodological details are provided in our companion presentation "Towards the spatial rectification of tower-based eddy-covariance flux observations". We apply the procedure to one year of data from each of four AmeriFlux sites under different climate and ecological environments: Lost Creek shrub fen wetland, Niwot Ridge subalpine conifer, Park Falls mixed forest, and Santa Rita mesquite savanna. We find that heat fluxes from the Park Falls 122-m-high EC measurement and from a surrounding 100 km2 target area differ up to 100 W m-2, or 65%. Moreover, 85% and 24% of the EC flux observations are adequate surrogates of the mean surface-atmosphere exchange and its spatial variability across a 900 km2 target area, respectively, at 5% significance and 80% representativeness levels. Alternatively, the resulting flux grids can be summarized as probability density functions, and used to inform mechanistic models directly with the mean flux value and its spatial variability across a model grid cell. Lastly, for each site we evaluate the applicability of the procedure based on a full bottom-up uncertainty budget.

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

Brown, S

A database was generated of estimates of geographically referenced carbon densities of forest vegetation in tropical Southeast Asia for 1980. A geographic information system (GIS) was used to incorporate spatial databases of climatic, edaphic, and geomorphological indices and vegetation to estimate potential (i.e., in the absence of human intervention and natural disturbance) carbon densities of forests. The resulting map was then modified to estimate actual 1980 carbon density as a function of population density and climatic zone. The database covers the following 13 countries: Bangladesh, Brunei, Cambodia (Campuchea), India, Indonesia, Laos, Malaysia, Myanmar (Burma), Nepal, the Philippines, Sri Lanka, Thailand,more » and Vietnam. The data sets within this database are provided in three file formats: ARC/INFOTM exported integer grids, ASCII (American Standard Code for Information Interchange) files formatted for raster-based GIS software packages, and generic ASCII files with x, y coordinates for use with non-GIS software packages. This database includes ten ARC/INFO exported integer grid files (five with the pixel size 3.75 km x 3.75 km and five with the pixel size 0.25 degree longitude x 0.25 degree latitude) and 27 ASCII files. The first ASCII file contains the documentation associated with this database. Twenty-four of the ASCII files were generated by means of the ARC/INFO GRIDASCII command and can be used by most raster-based GIS software packages. The 24 files can be subdivided into two groups of 12 files each. These files contain real data values representing actual carbon and potential carbon density in Mg C/ha (1 megagram = 10{sup 6} grams) and integer-coded values for country name, Weck's Climatic Index, ecofloristic zone, elevation, forest or non-forest designation, population density, mean annual precipitation, slope, soil texture, and vegetation classification. One set of 12 files contains these data at a spatial resolution of 3.75 km, whereas the other set of 12 files has a spatial resolution of 0.25 degree. The remaining two ASCII data files combine all of the data from the 24 ASCII data files into 2 single generic data files. The first file has a spatial resolution of 3.75 km, and the second has a resolution of 0.25 degree. Both files also provide a grid-cell identification number and the longitude and latitude of the center-point of each grid cell. The 3.75-km data in this numeric data package yield an actual total carbon estimate of 42.1 Pg (1 petagram = 10{sup 15} grams) and a potential carbon estimate of 73.6 Pg; whereas the 0.25-degree data produced an actual total carbon estimate of 41.8 Pg and a total potential carbon estimate of 73.9 Pg. Fortran and SAS{trademark} access codes are provided to read the ASCII data files, and ARC/INFO and ARCVIEW command syntax are provided to import the ARC/INFO exported integer grid files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).« less

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

Brown, S.

A database was generated of estimates of geographically referenced carbon densities of forest vegetation in tropical Southeast Asia for 1980. A geographic information system (GIS) was used to incorporate spatial databases of climatic, edaphic, and geomorphological indices and vegetation to estimate potential (i.e., in the absence of human intervention and natural disturbance) carbon densities of forests. The resulting map was then modified to estimate actual 1980 carbon density as a function of population density and climatic zone. The database covers the following 13 countries: Bangladesh, Brunei, Cambodia (Campuchea), India, Indonesia, Laos, Malaysia, Myanmar (Burma), Nepal, the Philippines, Sri Lanka, Thailand,more » and Vietnam. The data sets within this database are provided in three file formats: ARC/INFO{trademark} exported integer grids, ASCII (American Standard Code for Information Interchange) files formatted for raster-based GIS software packages, and generic ASCII files with x, y coordinates for use with non-GIS software packages. This database includes ten ARC/INFO exported integer grid files (five with the pixel size 3.75 km x 3.75 km and five with the pixel size 0.25 degree longitude x 0.25 degree latitude) and 27 ASCII files. The first ASCII file contains the documentation associated with this database. Twenty-four of the ASCII files were generated by means of the ARC/INFO GRIDASCII command and can be used by most raster-based GIS software packages. The 24 files can be subdivided into two groups of 12 files each. These files contain real data values representing actual carbon and potential carbon density in Mg C/ha (1 megagram = 10{sup 6} grams) and integer- coded values for country name, Weck's Climatic Index, ecofloristic zone, elevation, forest or non-forest designation, population density, mean annual precipitation, slope, soil texture, and vegetation classification. One set of 12 files contains these data at a spatial resolution of 3.75 km, whereas the other set of 12 files has a spatial resolution of 0.25 degree. The remaining two ASCII data files combine all of the data from the 24 ASCII data files into 2 single generic data files. The first file has a spatial resolution of 3.75 km, and the second has a resolution of 0.25 degree. Both files also provide a grid-cell identification number and the longitude and latitude of the centerpoint of each grid cell. The 3.75-km data in this numeric data package yield an actual total carbon estimate of 42.1 Pg (1 petagram = 10{sup 15} grams) and a potential carbon estimate of 73.6 Pg; whereas the 0.25-degree data produced an actual total carbon estimate of 41.8 Pg and a total potential carbon estimate of 73.9 Pg. Fortran and SASTM access codes are provided to read the ASCII data files, and ARC/INFO and ARCVIEW command syntax are provided to import the ARC/INFO exported integer grid files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).« less

The Statistical Differences Between the Gridded Temperature Datasets, and its Implications for Stochastic Modelling

NASA Astrophysics Data System (ADS)

Fredriksen, H. B.; Løvsletten, O.; Rypdal, M.; Rypdal, K.

2014-12-01

Several research groups around the world collect instrumental temperature data and combine them in different ways to obtain global gridded temperature fields. The three most well known datasets are HadCRUT4 produced by the Climatic Research Unit and the Met Office Hadley Centre in UK, one produced by NASA GISS, and one produced by NOAA. Recently Berkeley Earth has also developed a gridded dataset. All these four will be compared in our analysis. The statistical properties we will focus on are the standard deviation and the Hurst exponent. These two parameters are sufficient to describe the temperatures as long-range memory stochastic processes; the standard deviation describes the general fluctuation level, while the Hurst exponent relates the strength of the long-term variability to the strength of the short-term variability. A higher Hurst exponent means that the slow variations are stronger compared to the fast, and that the autocovariance function will have a stronger tail. Hence the Hurst exponent gives us information about the persistence or memory of the process. We make use of these data to show that data averaged over a larger area exhibit higher Hurst exponents and lower variance than data averaged over a smaller area, which provides information about the relationship between temporal and spatial correlations of the temperature fluctuations. Interpolation in space has some similarities with averaging over space, although interpolation is more weighted towards the measurement locations. We demonstrate that the degree of spatial interpolation used can explain some differences observed between the variances and memory exponents computed from the various datasets.

Evaluation of the National Solar Radiation Database (NSRDB) Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Xie, Y.; Sengupta, M.; Habte, A.; Lopez, A.

2017-12-01

Solar resource is essential for a wide spectrum of applications including renewable energy, climate studies, and solar forecasting. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. While measurements provide data for the development and validation of solar resource models and other applications modeled data expands the ability to address the needs for increased accuracy and spatial and temporal resolution. The National Renewable Energy Laboratory (NREL) has developed and regular updates modeled solar resource through the National Solar Radiation Database (NSRDB). The recent NSRDB dataset was developed using the physics-based Physical Solar Model (PSM) and provides gridded solar irradiance (global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance) at a 4-km by 4-km spatial and half-hourly temporal resolution covering 18 years from 1998-2015. A comprehensive validation of the performance of the NSRDB (1998-2015) was conducted to quantify the accuracy of the spatial and temporal variability of the solar radiation data. Further, the study assessed the ability of NSRDB (1998-2015) to accurately capture inter-annual variability, which is essential information for solar energy conversion projects and grid integration studies. Comparisons of the NSRDB (1998-2015) with nine selected ground-measured data were conducted under both clear- and cloudy-sky conditions. These locations provide a high quality data covering a variety of geographical locations and climates. The comparison of the NSRDB to the ground-based data demonstrated that biases were within +/- 5% for GHI and +/-10% for DNI. A comprehensive uncertainty estimation methodology was established to analyze the performance of the gridded NSRDB and includes all sources of uncertainty at various time-averaged periods, a method that is not often used in model evaluation. Further, the study analyzed the inter-annual and mean-anomaly of the 18 years of solar radiation data. This presentation will outline the validation methodology and provide detailed results of the comparison.

Consolidating Data of Global Urban Populations: a Comparative Approach

NASA Astrophysics Data System (ADS)

Blankespoor, B.; Khan, A.; Selod, H.

2017-12-01

Global data on city populations are essential for the study of urbanization, city growth and the spatial distribution of human settlements. Such data are either gathered by combining official estimates of urban populations from across countries or extracted from gridded population models that combine these estimates with geospatial data. These data sources provide varying estimates of urban populations and each approach has its advantages and limitations. In particular, official figures suffer from a lack of consistency in defining urban units (across both space and time) and often provide data for jurisdictions rather than the functionally meaningful urban area. On the other hand, gridded population models require a user-imposed definition to identify urban areas and are constrained by the modelling techniques and input data employed. To address these drawbacks, we combine these approaches by consolidating information from three established sources: (i) the Citypopulation.de (Brinkhoff, 2016); (ii) the World Urban Prospects data (United Nations, 2014); and (iii) the Global Human Settlements population grid (GHS-POP) (EC - JRC, 2015). We create urban footprints with GHS-POP and spatially merge georeferenced city points from both UN WUP and Citypopulation.de with these urban footprints to identify city points that belong to a single agglomeration. We create a consolidated dataset by combining population data from the UN WUP and Citypopulation.de. The flexible framework outlined can incorporate information from alternative inputs to identify urban clusters e.g. by using night-time lights, built-up area or alternative gridded population models (e.g WorldPop or Landscan) and the parameters employed (e.g. density thresholds for urban footprints) may also be adjusted, e.g., as a function of city-specific characteristics. Our consolidated dataset provides a wider and more accurate coverage of city populations to support studies of urbanization. We apply the data to re-examine Zipf's Law. Brinkhoff, Thomas. 2016. City Population.EC - JRC; Columbia University, CIESIN. 2015. GHS population grid, derived from GPW4, multi-temporal (1975, 1990, 2000, 2015).United Nations, Department of Economic and Social Affairs, Population Division. 2014. World Urbanization Prospects: 2014 Revision.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells

PubMed Central

Si, Bailu; Romani, Sandro; Tsodyks, Misha

2014-01-01

The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations. PMID:24743341

Annual Fossil-Fuel CO2 Emissions: Uncertainty of Emissions Gridded by On Degree Latitude by One Degree Longitude (1950-2013) (V. 2016)

DOE Data Explorer

Andres, R. J. [CDIAC; Boden, T. A. [CDIAC

2016-01-01

The annual, gridded fossil-fuel CO2 emissions uncertainty 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). Andres et al. (2016) describes the basic methodology in estimating the uncertainty in the (gridded fossil fuel data product ). This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty.

Monthly Fossil-Fuel CO2 Emissions: Uncertainty of Emissions Gridded by On Degree Latitude by One Degree Longitude (Uncertainties, V.2016)

DOE Data Explorer

Andres, J.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2016-01-01

The monthly, gridded fossil-fuel CO2 emissions uncertainty 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). Andres et al. (2016) describes the basic methodology in estimating the uncertainty in the (gridded fossil fuel data product ). This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty.

Research on the comparison of extension mechanism of cellular automaton based on hexagon grid and rectangular grid

NASA Astrophysics Data System (ADS)

Zhai, Xiaofang; Zhu, Xinyan; Xiao, Zhifeng; Weng, Jie

2009-10-01

Historically, cellular automata (CA) is a discrete dynamical mathematical structure defined on spatial grid. Research on cellular automata system (CAS) has focused on rule sets and initial condition and has not discussed its adjacency. Thus, the main focus of our study is the effect of adjacency on CA behavior. This paper is to compare rectangular grids with hexagonal grids on their characteristics, strengths and weaknesses. They have great influence on modeling effects and other applications including the role of nearest neighborhood in experimental design. Our researches present that rectangular and hexagonal grids have different characteristics. They are adapted to distinct aspects, and the regular rectangular or square grid is used more often than the hexagonal grid. But their relative merits have not been widely discussed. The rectangular grid is generally preferred because of its symmetry, especially in orthogonal co-ordinate system and the frequent use of raster from Geographic Information System (GIS). However, in terms of complex terrain, uncertain and multidirectional region, we have preferred hexagonal grids and methods to facilitate and simplify the problem. Hexagonal grids can overcome directional warp and have some unique characteristics. For example, hexagonal grids have a simpler and more symmetric nearest neighborhood, which avoids the ambiguities of the rectangular grids. Movement paths or connectivity, the most compact arrangement of pixels, make hexagonal appear great dominance in the process of modeling and analysis. The selection of an appropriate grid should be based on the requirements and objectives of the application. We use rectangular and hexagonal grids respectively for developing city model. At the same time we make use of remote sensing images and acquire 2002 and 2005 land state of Wuhan. On the base of city land state in 2002, we make use of CA to simulate reasonable form of city in 2005. Hereby, these results provide a proof of concept for hexagonal which has great dominance.

WebGIS based on semantic grid model and web services

NASA Astrophysics Data System (ADS)

Zhang, WangFei; Yue, CaiRong; Gao, JianGuo

2009-10-01

As the combination point of the network technology and GIS technology, WebGIS has got the fast development in recent years. With the restriction of Web and the characteristics of GIS, traditional WebGIS has some prominent problems existing in development. For example, it can't accomplish the interoperability of heterogeneous spatial databases; it can't accomplish the data access of cross-platform. With the appearance of Web Service and Grid technology, there appeared great change in field of WebGIS. Web Service provided an interface which can give information of different site the ability of data sharing and inter communication. The goal of Grid technology was to make the internet to a large and super computer, with this computer we can efficiently implement the overall sharing of computing resources, storage resource, data resource, information resource, knowledge resources and experts resources. But to WebGIS, we only implement the physically connection of data and information and these is far from the enough. Because of the different understanding of the world, following different professional regulations, different policies and different habits, the experts in different field will get different end when they observed the same geographic phenomenon and the semantic heterogeneity produced. Since these there are large differences to the same concept in different field. If we use the WebGIS without considering of the semantic heterogeneity, we will answer the questions users proposed wrongly or we can't answer the questions users proposed. To solve this problem, this paper put forward and experienced an effective method of combing semantic grid and Web Services technology to develop WebGIS. In this paper, we studied the method to construct ontology and the method to combine Grid technology and Web Services and with the detailed analysis of computing characteristics and application model in the distribution of data, we designed the WebGIS query system driven by ontology based on Grid technology and Web Services.

Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

NASA Astrophysics Data System (ADS)

Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

2017-06-01

The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.

Results from Evaluations of Gridded CrIS/ATMS Visualization for Operational Forecasting

NASA Astrophysics Data System (ADS)

Stevens, E.; Zavodsky, B.; Dostalek, J.; Berndt, E.; Hoese, D.; White, K.; Bowlan, M.; Gambacorta, A.; Wheeler, A.; Haisley, C.; Smith, N.

2017-12-01

For forecast challenges which require diagnosis of the three-dimensional atmosphere, current observations, such as radiosondes, may not offer enough information. Satellite data can help fill the spatial and temporal gaps between soundings. In particular, temperature and moisture retrievals from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), which combines infrared soundings from the Cross-track Infrared Sounder (CrIS) with the Advanced Technology Microwave Sounder (ATMS) to retrieve profiles of temperature and moisture. NUCAPS retrievals are available in a wide swath with approximately 45-km spatial resolution at nadir and a local Equator crossing time of 1:30 A.M./P.M. enabling three-dimensional observations at asynoptic times. This abstract focuses on evaluation of a new visualization for NUCAPS within the operational National Weather Service Advanced Weather Interactive Processing System (AWIPS) decision support system that allows these data to be viewed in gridded horizontal maps or vertical cross sections. Two testbed evaluations have occurred in 2017: a Cold Air Aloft (CAA) evaluation at the Alaska Center Weather Service Unit and a Convective Potential evaluation at the NOAA Hazardous Weather Testbed. For CAA, at high latitudes during the winter months, the air at altitudes used by passenger and cargo aircraft can reach temperatures cold enough (-65°C) to begin to freeze jet fuel, and Gridded NUCAPS visualization was shown to help fill in the spatial and temporal gaps in data-sparse areas across the Alaskan airspace by identifying the 3D spatial extent of cold air features. For convective potential, understanding the vertical distribution of temperature and moisture is also very important for forecasting the potential for convection related to severe weather such as lightning, large hail, and tornadoes. The Gridded NUCAPS visualization was shown to aid forecasters in understanding temperature and moisture characteristics at critical levels for determining cap strength and instability. In both cases, when the products are used in conjunction with numerical output to reinforce confidence in model products or provide an alternative observation if forecasters are not sure the model is properly representing the atmosphere.

Representation of Non-Spatial and Spatial Information in the Lateral Entorhinal Cortex

PubMed Central

Deshmukh, Sachin S.; Knierim, James J.

2011-01-01

Some theories of memory propose that the hippocampus integrates the individual items and events of experience within a contextual or spatial framework. The hippocampus receives cortical input from two major pathways: the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). During exploration in an open field, the firing fields of MEC grid cells form a periodically repeating, triangular array. In contrast, LEC neurons show little spatial selectivity, and it has been proposed that the LEC may provide non-spatial input to the hippocampus. Here, we recorded MEC and LEC neurons while rats explored an open field that contained discrete objects. LEC cells fired selectively at locations relative to the objects, whereas MEC cells were weakly influenced by the objects. These results provide the first direct demonstration of a double dissociation between LEC and MEC inputs to the hippocampus under conditions of exploration typically used to study hippocampal place cells. PMID:22065409

Methodological Caveats in the Detection of Coordinated Replay between Place Cells and Grid Cells.

PubMed

Trimper, John B; Trettel, Sean G; Hwaun, Ernie; Colgin, Laura Lee

2017-01-01

At rest, hippocampal "place cells," neurons with receptive fields corresponding to specific spatial locations, reactivate in a manner that reflects recently traveled trajectories. These "replay" events have been proposed as a mechanism underlying memory consolidation, or the transfer of a memory representation from the hippocampus to neocortical regions associated with the original sensory experience. Accordingly, it has been hypothesized that hippocampal replay of a particular experience should be accompanied by simultaneous reactivation of corresponding representations in the neocortex and in the entorhinal cortex, the primary interface between the hippocampus and the neocortex. Recent studies have reported that coordinated replay may occur between hippocampal place cells and medial entorhinal cortex grid cells, cells with multiple spatial receptive fields. Assessing replay in grid cells is problematic, however, as the cells exhibit regularly spaced spatial receptive fields in all environments and, therefore, coordinated replay between place cells and grid cells may be detected by chance. In the present report, we adapted analytical approaches utilized in recent studies of grid cell and place cell replay to determine the extent to which coordinated replay is spuriously detected between grid cells and place cells recorded from separate rats. For a subset of the employed analytical methods, coordinated replay was detected spuriously in a significant proportion of cases in which place cell replay events were randomly matched with grid cell firing epochs of equal duration. More rigorous replay evaluation procedures and minimum spike count requirements greatly reduced the amount of spurious findings. These results provide insights into aspects of place cell and grid cell activity during rest that contribute to false detection of coordinated replay. The results further emphasize the need for careful controls and rigorous methods when testing the hypothesis that place cells and grid cells exhibit coordinated replay.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Spatial cell firing during virtual navigation of open arenas by head-restrained mice.

PubMed

Chen, Guifen; King, John Andrew; Lu, Yi; Cacucci, Francesca; Burgess, Neil

2018-06-18

We present a mouse virtual reality (VR) system which restrains head-movements to horizontal rotations, compatible with multi-photon imaging. This system allows expression of the spatial navigation and neuronal firing patterns characteristic of real open arenas (R). Comparing VR to R: place and grid, but not head-direction, cell firing had broader spatial tuning; place, but not grid, cell firing was more directional; theta frequency increased less with running speed; whereas increases in firing rates with running speed and place and grid cells' theta phase precession were similar. These results suggest that the omni-directional place cell firing in R may require local-cues unavailable in VR, and that the scale of grid and place cell firing patterns, and theta frequency, reflect translational motion inferred from both virtual (visual and proprioceptive) and real (vestibular translation and extra-maze) cues. By contrast, firing rates and theta phase precession appear to reflect visual and proprioceptive cues alone. © 2018, Chen et al.

[Spatial analysis of Oncomelania snail information based on grid data-driven].

PubMed

Liu, Gang; Huang, Qiong-Yao; Liu, Yun-Ziang; Wang, Jiang-Tao; Peng, Fei; Liu, Nian-Meng

2011-06-01

To explore the relationship between the Oncomelania snail situation and the distance to the water source, soil humidity, vegetation and water level in flood seasons in the islets of Changsha Section of the Xiang River. Combined with the NDVI and soil humidity of islets, the GIS spatial analysis based on grid data-driven was used to analyze the snail situation in Changsha Section of the Xiang River from 2005 to 2009. The relationship between the snail density and the water level in blood seasons was analyzed. In 2005, the snails in Zengpi Islet were mainly distributed at the range of 40-240 m far away from the nearest water source, and the number at the spots with a distance of 60 m was the largest. There was an obvious positive correlation between the snail density and water level in flood seasons. The ranges of the Normalized Difference Vegetation Index and soil humidity of Zengpi Islet in 2005 were 0-0.982 and 0-0.298, respectively and the main vegetation in Changsha Section of the Xiang River were weed and sedge. The map of snail situation by year was drawn according to the standard water level, which reflected the snail situation intuitionistically. By using spatial analysis based on grid data-driven, the situation of vegetation, soil humidity and snail accurately can be reflected, which can help us to understand the endemic situation timely. Even under the circumstance of human intervention, the water level in flood seasons is still an important factor influencing the change of snail situation.

Examining the occupancy–density relationship for a low-density carnivore

USGS Publications Warehouse

Linden, Daniel W.; Fuller, Angela K.; Royle, J. Andrew; Hare, Matthew P.

2017-01-01

The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools.For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive laboratory processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions.Here, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70 096-km2 region of western New York, USA. We fit occupancy and Royle–Nichols models to species detection–non-detection data collected by cameras, and spatial capture–recapture (SCR) models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km2 grid cells was modelled as a function of landscape attributes known to influence fisher distribution.We found a close relationship between grid cell estimates of fisher state variables from the models using detection–non-detection data and those from the SCR model, likely due to informative spatial covariates across a large landscape extent and a grid cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data.Synthesis and applications. Our work provides empirical evidence that models using detection–non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Possible role of acetylcholine in regulating spatial novelty effects on theta rhythm and grid cells

PubMed Central

Barry, Caswell; Heys, James G.; Hasselmo, Michael E.

2012-01-01

Existing pharmacological and lesion data indicate that acetylcholine plays an important role in memory formation. For example, increased levels of acetylcholine in the hippocampal formation are known to be associated with successful encoding while disruption of the cholinergic system leads to impairments on a range of mnemonic tasks. However, cholinergic signaling from the medial septum also plays a central role in generating and pacing theta-band oscillations throughout the hippocampal formation. Recent experimental results suggest a potential link between these distinct phenomena. Environmental novelty, a condition associated with strong cholinergic drive, has been shown to induce an expansion in the firing pattern of entorhinal grid cells and a reduction in the frequency of theta measured from the LFP. Computational modeling suggests the spatial activity of grid cells is produced by interference between neuronal oscillators; scale being determined by theta-band oscillations impinging on entorhinal stellate cells, the frequency of which is modulated by acetylcholine. Here we propose that increased cholinergic signaling in response to environmental novelty triggers grid expansion by reducing the frequency of the oscillations. Furthermore, we argue that cholinergic induced grid expansion may enhance, or even induce, encoding by producing a mismatch between expanded grid cells and other spatial inputs to the hippocampus, such as boundary vector cells. Indeed, a further source of mismatch is likely to occur between grid cells of different native scales which may expand by different relative amounts. PMID:22363266

An Overview of the GIS Weasel

USGS Publications Warehouse

Viger, Roland J.

2008-01-01

This fact sheet provides a high-level description of the GIS Weasel, a software system designed to aid users in preparing spatial information as input to lumped and distributed parameter environmental simulation models (ESMs). The GIS Weasel provides geographic information system (GIS) tools to help create maps of geographic features relevant to the application of a user?s ESM and to generate parameters from those maps. The operation of the GIS Weasel does not require a user to be a GIS expert, only that a user has an understanding of the spatial information requirements of the model. The GIS Weasel software system provides a GIS-based graphical user interface (GUI), C programming language executables, and general utility scripts. The software will run on any computing platform where ArcInfo Workstation (version 8.1 or later) and the GRID extension are accessible. The user controls the GIS Weasel by interacting with menus, maps, and tables.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

2001-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Histamine Enhances Theta-Coupled Spiking and Gamma Oscillations in the Medial Entorhinal Cortex Consistent With Successful Spatial Recognition.

PubMed

Chen, Quanhui; Luo, Fenlan; Yue, Faguo; Xia, Jianxia; Xiao, Qin; Liao, Xiang; Jiang, Jun; Zhang, Jun; Hu, Bo; Gao, Dong; He, Chao; Hu, Zhian

2017-06-07

Encoding of spatial information in the superficial layers of the medial entorhinal cortex (sMEC) involves theta-modulated spiking and gamma oscillations, as well as spatially tuned grid cells and border cells. Little is known about the role of the arousal-promoting histaminergic system in the modification of information encoded in the sMEC in vivo, and how such histamine-regulated information correlates with behavioral functions. Here, we show that histamine upregulates the neural excitability of a significant proportion of neurons (16.32%, 39.18%, and 52.94% at 30 μM, 300 μM, and 3 mM, respectively) and increases local theta (4-12 Hz) and gamma power (low: 25-48 Hz; high: 60-120 Hz) in the sMEC, through activation of histamine receptor types 1 and 3. During spatial exploration, the strength of theta-modulated firing of putative principal neurons and high gamma oscillations is enhanced about 2-fold by histamine. The histamine-mediated increase of theta phase-locking of spikes and high gamma power is consistent with successful spatial recognition. These results, for the first time, reveal possible mechanisms involving the arousal-promoting histaminergic system in the modulation of spatial cognition. Published by Oxford University Press 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Fibonacci Grids

NASA Technical Reports Server (NTRS)

Swinbank, Richard; Purser, James

2006-01-01

Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude-longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges). One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as "Fibonacci grids". They can be thought of as mathematically ideal generalizations of the patterns occurring naturally in the spiral arrangements of seeds and fruit found in sunflower heads and pineapples (to give two of the many botanical examples). These grids possess virtually uniform and highly isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of these grids in shallow water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional semi-implicit and semi-Lagrangian weather prediction or climate models.

Grid cells form a global representation of connected environments.

PubMed

Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell

2015-05-04

The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5-8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9-11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Grid Cells Form a Global Representation of Connected Environments

PubMed Central

Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell

2015-01-01

Summary The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5–8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9–11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. PMID:25913404

Modeling emissions for three-dimensional atmospheric chemistry transport models.

PubMed

Matthias, Volker; Arndt, Jan A; Aulinger, Armin; Bieser, Johannes; Denier Van Der Gon, Hugo; Kranenburg, Richard; Kuenen, Jeroen; Neumann, Daniel; Pouliot, George; Quante, Markus

2018-01-24

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scale and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed and new methods to improve the spatio-temporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions like national totals on appropriate grids. The wide area of natural emissions is also summarized and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. Emission data is probably the most important input for chemistry transport model (CTM) systems. It needs to be provided in high temporal and spatial resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g. for ammonia emissions, provide grid cell dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

Interpolation methods and the accuracy of lattice-Boltzmann mesh refinement

DOE PAGES

Guzik, Stephen M.; Weisgraber, Todd H.; Colella, Phillip; ...

2013-12-10

A lattice-Boltzmann model to solve the equivalent of the Navier-Stokes equations on adap- tively refined grids is presented. A method for transferring information across interfaces between different grid resolutions was developed following established techniques for finite- volume representations. This new approach relies on a space-time interpolation and solving constrained least-squares problems to ensure conservation. The effectiveness of this method at maintaining the second order accuracy of lattice-Boltzmann is demonstrated through a series of benchmark simulations and detailed mesh refinement studies. These results exhibit smaller solution errors and improved convergence when compared with similar approaches relying only on spatial interpolation. Examplesmore » highlighting the mesh adaptivity of this method are also provided.« less

An adaptive grid to improve the efficiency and accuracy of modelling underwater noise from shipping

NASA Astrophysics Data System (ADS)

Trigg, Leah; Chen, Feng; Shapiro, Georgy; Ingram, Simon; Embling, Clare

2017-04-01

Underwater noise from shipping is becoming a significant concern and has been listed as a pollutant under Descriptor 11 of the Marine Strategy Framework Directive. Underwater noise models are an essential tool to assess and predict noise levels for regulatory procedures such as environmental impact assessments and ship noise monitoring. There are generally two approaches to noise modelling. The first is based on simplified energy flux models, assuming either spherical or cylindrical propagation of sound energy. These models are very quick but they ignore important water column and seabed properties, and produce significant errors in the areas subject to temperature stratification (Shapiro et al., 2014). The second type of model (e.g. ray-tracing and parabolic equation) is based on an advanced physical representation of sound propagation. However, these acoustic propagation models are computationally expensive to execute. Shipping noise modelling requires spatial discretization in order to group noise sources together using a grid. A uniform grid size is often selected to achieve either the greatest efficiency (i.e. speed of computations) or the greatest accuracy. In contrast, this work aims to produce efficient and accurate noise level predictions by presenting an adaptive grid where cell size varies with distance from the receiver. The spatial range over which a certain cell size is suitable was determined by calculating the distance from the receiver at which propagation loss becomes uniform across a grid cell. The computational efficiency and accuracy of the resulting adaptive grid was tested by comparing it to uniform 1 km and 5 km grids. These represent an accurate and computationally efficient grid respectively. For a case study of the Celtic Sea, an application of the adaptive grid over an area of 160×160 km reduced the number of model executions required from 25600 for a 1 km grid to 5356 in December and to between 5056 and 13132 in August, which represents a 2 to 5-fold increase in efficiency. The 5 km grid reduces the number of model executions further to 1024. However, over the first 25 km the 5 km grid produces errors of up to 13.8 dB when compared to the highly accurate but inefficient 1 km grid. The newly developed adaptive grid generates much smaller errors of less than 0.5 dB while demonstrating high computational efficiency. Our results show that the adaptive grid provides the ability to retain the accuracy of noise level predictions and improve the efficiency of the modelling process. This can help safeguard sensitive marine ecosystems from noise pollution by improving the underwater noise predictions that inform management activities. References Shapiro, G., Chen, F., Thain, R., 2014. The Effect of Ocean Fronts on Acoustic Wave Propagation in a Shallow Sea, Journal of Marine System, 139: 217 - 226. http://dx.doi.org/10.1016/j.jmarsys.2014.06.007.

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

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

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.« less

Evaluation of a commercially‐available block for spatially fractionated radiation therapy

PubMed Central

Buckey, Courtney; Cashon, Ken; Gutierrez, Alonso; Esquivel, Carlos; Shi, Chengyu; Papanikolaou, Nikos

2010-01-01

In this paper, we present the dosimetric characteristics of a commercially‐produced universal GRID block for spatially fractioned radiation therapy. The dosimetric properties of the GRID block were evaluated. Ionization chamber and film measurements using both Kodak EDR2 and Gafchromic EBT film were performed in a solid water phantom to determine the relative output of the GRID block as well as its spatial dosimetric characteristics. The surface dose under the block and at the openings was measured using ultra thin TLDs. After introducing the GRID block into the treatment planning system, a treatment plan was created using the GRID block and also by creating a GRID pattern using the multi‐leaf collimator. The percent depth doses measured with film showed that there is a shift of the dmax towards shallower depths for both energies (6 MV and 18 MV) under investigation. It was observed that the skin dose at the GRID openings was higher than the corresponding open field by a factor as high as 50% for both photon energies. The profiles showed the transmission under the block was in the order of 15–20% for 6 MV and 30% for 18 MV. The MUs calculated for a real patient using the block were about 80% less than the corresponding MUs for the same plan using the multileaf collimator to define the GRID. Based on this investigation, this brass GRID compensator is a viable alternative to other solid compensators or MLC‐based fields currently in use. Its ease of creation and use give it decided advantages. Its ability to be created once and used for multiple patients (by varying the collimation of the linear accelerator jaws) makes it attractive from a cost perspective. We believe this compensator can be put to clinical use, and will allow more centers to offer GRID therapy to their patients. PACS number: 87.53.Mr

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

The development of an hourly gridded rainfall product for hydrological applications in England and Wales

NASA Astrophysics Data System (ADS)

Liguori, Sara; O'Loughlin, Fiachra; Souvignet, Maxime; Coxon, Gemma; Freer, Jim; Woods, Ross

2014-05-01

This research presents a newly developed observed sub-daily gridded precipitation product for England and Wales. Importantly our analysis specifically allows a quantification of rainfall errors from grid to the catchment scale, useful for hydrological model simulation and the evaluation of prediction uncertainties. Our methodology involves the disaggregation of the current one kilometre daily gridded precipitation records available for the United Kingdom[1]. The hourly product is created using information from: 1) 2000 tipping-bucket rain gauges; and 2) the United Kingdom Met-Office weather radar network. These two independent datasets provide rainfall estimates at temporal resolutions much smaller than the current daily gridded rainfall product; thus allowing the disaggregation of the daily rainfall records to an hourly timestep. Our analysis is conducted for the period 2004 to 2008, limited by the current availability of the datasets. We analyse the uncertainty components affecting the accuracy of this product. Specifically we explore how these uncertainties vary spatially, temporally and with climatic regimes. Preliminary results indicate scope for improvement of hydrological model performance by the utilisation of this new hourly gridded rainfall product. Such product will improve our ability to diagnose and identify structural errors in hydrological modelling by including the quantification of input errors. References [1] Keller V, Young AR, Morris D, Davies H (2006) Continuous Estimation of River Flows. Technical Report: Estimation of Precipitation Inputs. in Agency E (ed.). Environmental Agency.

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

Grid systems for Earth radiation budget experiment applications

NASA Technical Reports Server (NTRS)

Brooks, D. R.

1981-01-01

Spatial coordinate transformations are developed for several global grid systems of interest to the Earth Radiation Budget Experiment. The grid boxes are defined in terms of a regional identifier and longitude-latitude indexes. The transformations associate longitude with a particular grid box. The reverse transformations identify the center location of a given grid box. Transformations are given to relate the rotating (Earth-based) grid systems to solar position expressed in an inertial (nonrotating) coordinate system. The FORTRAN implementations of the transformations are given, along with sample input and output.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

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.

A stand-alone tidal prediction application for mobile devices

NASA Astrophysics Data System (ADS)

Tsai, Cheng-Han; Fan, Ren-Ye; Yang, Yi-Chung

2017-04-01

It is essential for people conducting fishing, leisure, or research activities at the coasts to have timely and handy tidal information. Although tidal information can be found easily on the internet or using mobile device applications, this information is all applicable for only certain specific locations, not anywhere on the coast, and they need an internet connection. We have developed an application for Android devices, which allows the user to obtain hourly tidal height anywhere on the coast for the next 24 hours without having to have any internet connection. All the necessary information needed for the tidal height calculation is stored in the application. To develop this application, we first simulate tides in the Taiwan Sea using the hydrodynamic model (MIKE21 HD) developed by the DHI. The simulation domain covers the whole coast of Taiwan and the surrounding seas with a grid size of 1 km by 1 km. This grid size allows us to calculate tides with high spatial resolution. The boundary conditions for the simulation domain were obtained from the Tidal Model Driver of the Oregon State University, using its tidal constants of eight constituents: M2, S2, N2, K2, K1, O1, P1, and Q1. The simulation calculates tides for 183 days so that the tidal constants for the above eight constituents of each water grid can be extracted by harmonic analysis. Using the calculated tidal constants, we can predict the tides in each grid of our simulation domain, which is useful when one needs the tidal information for any location in the Taiwan Sea. However, for the mobile application, we only store the eight tidal constants for the water grids on the coast. Once the user activates the application, it reads the longitude and latitude from the GPS sensor in the mobile device and finds the nearest coastal grid which has our tidal constants. Then, the application calculates tidal height variation based on the harmonic analysis. The application also allows the user to input location and time to obtain tides for any historic or future dates for the input location. The predicted tides have been verified with the historic tidal records of certain tidal stations. The verification shows that the tides predicted by the application match the measured record well.

HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution

NASA Astrophysics Data System (ADS)

Janssens-Maenhout, G.; Crippa, M.; Guizzardi, D.; Dentener, F.; Muntean, M.; Pouliot, G.; Keating, T.; Zhang, Q.; Kurokawa, J.; Wankmüller, R.; Denier van der Gon, H.; Kuenen, J. J. P.; Klimont, Z.; Frost, G.; Darras, S.; Koffi, B.; Li, M.

2015-10-01

The mandate of the Task Force Hemispheric Transport of Air Pollution (TF HTAP) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP) is to improve the scientific understanding of the intercontinental air pollution transport, to quantify impacts on human health, vegetation and climate, to identify emission mitigation options across the regions of the Northern Hemisphere, and to guide future policies on these aspects. The harmonization and improvement of regional emission inventories is imperative to obtain consolidated estimates on the formation of global-scale air pollution. An emissions data set has been constructed using regional emission grid maps (annual and monthly) for SO2, NOx, CO, NMVOC, NH3, PM10, PM2.5, BC and OC for the years 2008 and 2010, with the purpose of providing consistent information to global and regional scale modelling efforts. This compilation of different regional gridded inventories - including that of the Environmental Protection Agency (EPA) for USA, the EPA and Environment Canada (for Canada), the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study for Asia (MICS-Asia III) for China, India and other Asian countries - was gap-filled with the emission grid maps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South America, Africa, Russia and Oceania). Emissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1° × 0.1° longitude-latitude, to yield monthly, global, sector-specific grid maps for each substance and year. The HTAP_v2.2 air pollutant grid maps are considered to combine latest available regional information within a complete global data set. The disaggregation by sectors, high spatial and temporal resolution and detailed information on the data sources and references used will provide the user the required transparency. Because HTAP_v2.2 contains primarily official and/or widely used regional emission grid maps, it can be recommended as a global baseline emission inventory, which is regionally accepted as a reference and from which different scenarios assessing emission reduction policies at a global scale could start. An analysis of country-specific implied emission factors shows a large difference between industrialised countries and developing countries for acidifying gaseous air pollutant emissions (SO2 and NOx) from the energy and industry sectors. This is not observed for the particulate matter emissions (PM10, PM2.5), which show large differences between countries in the residential sector instead. The per capita emissions of all world countries, classified from low to high income, reveal an increase in level and in variation for gaseous acidifying pollutants, but not for aerosols. For aerosols, an opposite trend is apparent with higher per capita emissions of particulate matter for low income countries.

An Off-Grid Turbo Channel Estimation Algorithm for Millimeter Wave Communications.

PubMed

Han, Lingyi; Peng, Yuexing; Wang, Peng; Li, Yonghui

2016-09-22

The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave) frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide large array gains via directional beamforming. To achieve such array gains, channel estimation (CE) with high resolution and low latency is of great importance for mmWave communications. However, classic super-resolution subspace CE methods such as multiple signal classification (MUSIC) and estimation of signal parameters via rotation invariant technique (ESPRIT) cannot be applied here due to RF chain constraints. In this paper, an enhanced CE algorithm is developed for the off-grid problem when quantizing the angles of mmWave channel in the spatial domain where off-grid problem refers to the scenario that angles do not lie on the quantization grids with high probability, and it results in power leakage and severe reduction of the CE performance. A new model is first proposed to formulate the off-grid problem. The new model divides the continuously-distributed angle into a quantized discrete grid part, referred to as the integral grid angle, and an offset part, termed fractional off-grid angle. Accordingly, an iterative off-grid turbo CE (IOTCE) algorithm is proposed to renew and upgrade the CE between the integral grid part and the fractional off-grid part under the Turbo principle. By fully exploiting the sparse structure of mmWave channels, the integral grid part is estimated by a soft-decoding based compressed sensing (CS) method called improved turbo compressed channel sensing (ITCCS). It iteratively updates the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner. Monte Carlo simulations are presented to evaluate the performance of the proposed method, and the results show that it enhances the angle detection resolution greatly.

Using High-Resolution Forward Model Simulations of Ideal Atmospheric Tracers to Assess the Spatial Information Content of Inverse CO2 Flux Estimates

NASA Technical Reports Server (NTRS)

Pawson, Steven; Nielsen, J. Eric

2011-01-01

Attribution of observed atmospheric carbon concentrations to emissions on the country, state or city level is often inferred using "inversion" techniques. Such computations are often performed using advanced mathematical techniques, such as synthesis inversion or four-dimensional variational analysis, that invoke tracing observed atmospheric concentrations backwards through a transport model to a source region. It is, to date, not well understood how well such techniques can represent fine spatial (and temporal) structure in the inverted flux fields. This question is addressed using forward-model computations with idealized tracers emitted at the surface in a large number of grid boxes over selected regions and examining how distinctly these emitted tracers can be detected downstream. Initial results show that tracers emitted in half-degree grid boxes over a large region of the Eastern USA cannot be distinguished from each other, even at short distances over the Atlantic Ocean, when they are emitted in grid boxes separated by less than five degrees of latitude - especially when only total-column observations are available. A large number of forward model simulations, with varying meteorological conditions, are used to assess how distinctly three types observations (total column, upper tropospheric column, and surface mixing ratio) can separate emissions from different sources. Inferences inverse modeling and source attribution will be drawn.

FLUXCOM - Overview and First Synthesis

NASA Astrophysics Data System (ADS)

Jung, M.; Ichii, K.; Tramontana, G.; Camps-Valls, G.; Schwalm, C. R.; Papale, D.; Reichstein, M.; Gans, F.; Weber, U.

2015-12-01

We present a community effort aiming at generating an ensemble of global gridded flux products by upscaling FLUXNET data using an array of different machine learning methods including regression/model tree ensembles, neural networks, and kernel machines. We produced products for gross primary production, terrestrial ecosystem respiration, net ecosystem exchange, latent heat, sensible heat, and net radiation for two experimental protocols: 1) at a high spatial and 8-daily temporal resolution (5 arc-minute) using only remote sensing based inputs for the MODIS era; 2) 30 year records of daily, 0.5 degree spatial resolution by incorporating meteorological driver data. Within each set-up, all machine learning methods were trained with the same input data for carbon and energy fluxes respectively. Sets of input driver variables were derived using an extensive formal variable selection exercise. The performance of the extrapolation capacities of the approaches is assessed with a fully internally consistent cross-validation. We perform cross-consistency checks of the gridded flux products with independent data streams from atmospheric inversions (NEE), sun-induced fluorescence (GPP), catchment water balances (LE, H), satellite products (Rn), and process-models. We analyze the uncertainties of the gridded flux products and for example provide a breakdown of the uncertainty of mean annual GPP originating from different machine learning methods, different climate input data sets, and different flux partitioning methods. The FLUXCOM archive will provide an unprecedented source of information for water, energy, and carbon cycle studies.

Distinct speed dependence of entorhinal island and ocean cells, including respective grid cells

PubMed Central

Sun, Chen; Kitamura, Takashi; Yamamoto, Jun; Martin, Jared; Pignatelli, Michele; Kitch, Lacey J.; Schnitzer, Mark J.; Tonegawa, Susumu

2015-01-01

Entorhinal–hippocampal circuits in the mammalian brain are crucial for an animal’s spatial and episodic experience, but the neural basis for different spatial computations remain unknown. Medial entorhinal cortex layer II contains pyramidal island and stellate ocean cells. Here, we performed cell type-specific Ca2+ imaging in freely exploring mice using cellular markers and a miniature head-mounted fluorescence microscope. We found that both oceans and islands contain grid cells in similar proportions, but island cell activity, including activity in a proportion of grid cells, is significantly more speed modulated than ocean cell activity. We speculate that this differential property reflects island cells’ and ocean cells’ contribution to different downstream functions: island cells may contribute more to spatial path integration, whereas ocean cells may facilitate contextual representation in downstream circuits. PMID:26170279

Building capacity for in-situ phenological observation data to support integrated biodiversity information at local to national scales

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2016-12-01

Earth observations from a variety of platforms and across a range of scales are required to support research, natural resource management, and policy- and decision-making in a changing world. Integrated earth observation data provides multi-faceted information critical to decision support, vulnerability and change detection, risk assessments, early warning and modeling, simulation and forecasting in the natural resource societal benefit area. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on phenology - the study of seasonal life-cycle events such as leafing, flowering, reproduction, and migration - as a tool to understand the response of biodiversity to environmental variation and change. USA-NPN provides a hierarchical, national monitoring framework that enables other organizations to leverage the capacity of the Network for their own applications - minimizing investment and duplication of effort - while promoting interoperability and sustainability. Over the last decade, the network has focused on the development of a centralized database for in-situ (ground based) observations of plants and animals, now with 8 M records for the period 1954-present. More recently, we have developed a workflow for the production and validation of spatially gridded phenology products based on models that couple the organismal data with climatological and meteorological data at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km). These gridded data are now ripe for integration with other modeled or earth observation gridded data, e.g., indices of drought impact or land surface reflectance. This greatly broadens capacity to scale organismal observational data to landscapes and regions, and enables novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations. Sustainability emerges from identification of stakeholder needs, segmentation of target audiences (e.g., data contributors, data consumers), documentation of all aspects of the data production and delivery process, development of collaborative partnerships, enterprise approaches to information management, and excellent customer service.

Maintaining a Cognitive Map in Darkness: The Need to Fuse Boundary Knowledge with Path Integration

PubMed Central

Cheung, Allen; Ball, David; Milford, Michael; Wyeth, Gordon; Wiles, Janet

2012-01-01

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's “cognitive map”, or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and – we conjecture – necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments. PMID:22916006

Lighting up the World The first global application of the open source, spatial electrification toolkit (ONSSET)

NASA Astrophysics Data System (ADS)

Mentis, Dimitrios; Howells, Mark; Rogner, Holger; Korkovelos, Alexandros; Siyal, Shahid; Broad, Oliver; Zepeda, Eduardo; Bazilian, Morgan

2016-04-01

In September 2015, the international community has adopted a new set of targets, following and expanding on the millennium development goals (MDGs), the Sustainable Development Goals (SDGs). Ensuring access to affordable, reliable, sustainable and modern energy for all is one of the 17 set goals that each country should work towards realizing. According to the latest Global Tracking Framework, 15% of the global population live without access to electricity. The majority of those (87%) reside in rural areas. Countries can reach universal access through various electrification options, depending on different levels of energy intensity and local characteristics of the studied areas, such as renewable resources availability, spatially differentiated costs of diesel-fuelled electricity generation, distance from power network and major cities, population density and others, data which are usually inadequate in national databases. This general paucity of reliable energy-related information in developing countries calls for the utilization of geospatial data. This paper presents a Geographic Information Systems (GIS) based electrification analysis for all countries that have not yet reached full access to electricity (Sub-Saharan Africa, Developing Asia, Latin America and Middle East). The cost optimal mix of electrification options ranges from grid extensions to mini-grid and stand-alone applications and is identified for all relevant countries. It is illustrated how this mix is influenced by scrolling through various electrification levels and different oil prices. Such an analysis helps direct donors and investors and inform multinational actions with regards to investments related to energy access.

Methods for Combination of GRACE Gravimetry and ICESat Altimetry over Antarctica on Monthly Timescales

NASA Astrophysics Data System (ADS)

Hardy, R. A.; Nerem, R. S.; Wiese, D. N.

2017-12-01

Gravity and surface elevation change data altimetry provide different perspectives on mass variability in Antarctica. In anticipation of the concurrent operation of the successors of GRACE and ICESat, GRACE Follow-On and ICESat-2, we approach the problem of combining these data for enhanced spatial resolution and disaggregation of Antarctica's major mass transport processes. Using elevation changes gathered from over 500 million overlapping ICESat laser shot pairs between 2003 and 2009, we construct gridded models of Antarctic elevation change for each ICESat operational period. Comparing these elevation grids with temporally registered JPL RL05M mascon solutions, we exploit the relationship between surface mass flux and elevation change to inform estimates of effective surface density. These density estimates enable solutions for glacial isostatic adjustment and monthly estimates of surface mass change. These are used alongside spatial statistics from both the data and models of surface mass balance to produce enhanced estimates of Antarctic mass balance. We validate our solutions by modeling the effects of elastic loading and GIA from these solutions on the vertical motion of Antarctica's GNSS sites.

Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling

NASA Astrophysics Data System (ADS)

Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.

2017-12-01

For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce uncertainties in agro-ecosystem modeling. Through the combination of the multi annual land use fractions, the resulting datasets additionally inform about land use changes and trends within the coarser grid cells. We see this as a major advantage, because we are able to maintain much more precise land use information when a coarser cell size is used.

Verification of Weather Running Estimate-Nowcast (WRE-N) Forecasts Using a Spatial-Categorical Method

DTIC Science & Technology

2017-07-01

forecasts and observations on a common grid, which enables the application a number of different spatial verification methods that reveal various...forecasts of continuous meteorological variables using categorical and object-based methods . White Sands Missile Range (NM): Army Research Laboratory (US... Research version of the Weather Research and Forecasting Model adapted for generating short-range nowcasts and gridded observations produced by the

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

Balancing Conflicting Requirements for Grid and Particle Decomposition in Continuum-Lagrangian Solvers

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

Sitaraman, Hariswaran; Grout, Ray

2015-10-30

The load balancing strategies for hybrid solvers that involve grid based partial differential equation solution coupled with particle tracking are presented in this paper. A typical Message Passing Interface (MPI) based parallelization of grid based solves are done using a spatial domain decomposition while particle tracking is primarily done using either of the two techniques. One of the techniques is to distribute the particles to MPI ranks to whose grid they belong to while the other is to share the particles equally among all ranks, irrespective of their spatial location. The former technique provides spatial locality for field interpolation butmore » cannot assure load balance in terms of number of particles, which is achieved by the latter. The two techniques are compared for a case of particle tracking in a homogeneous isotropic turbulence box as well as a turbulent jet case. We performed a strong scaling study for more than 32,000 cores, which results in particle densities representative of anticipated exascale machines. The use of alternative implementations of MPI collectives and efficient load equalization strategies are studied to reduce data communication overheads.« less

Bayesian Non-Stationary Index Gauge Modeling of Gridded Precipitation Extremes

NASA Astrophysics Data System (ADS)

Verdin, A.; Bracken, C.; Caldwell, J.; Balaji, R.; Funk, C. C.

2017-12-01

We propose a Bayesian non-stationary model to generate watershed scale gridded estimates of extreme precipitation return levels. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset is used to obtain gridded seasonal precipitation extremes over the Taylor Park watershed in Colorado for the period 1981-2016. For each year, grid cells within the Taylor Park watershed are aggregated to a representative "index gauge," which is input to the model. Precipitation-frequency curves for the index gauge are estimated for each year, using climate variables with significant teleconnections as proxies. Such proxies enable short-term forecasting of extremes for the upcoming season. Disaggregation ratios of the index gauge to the grid cells within the watershed are computed for each year and preserved to translate the index gauge precipitation-frequency curve to gridded precipitation-frequency maps for select return periods. Gridded precipitation-frequency maps are of the same spatial resolution as CHIRPS (0.05° x 0.05°). We verify that the disaggregation method preserves spatial coherency of extremes in the Taylor Park watershed. Validation of the index gauge extreme precipitation-frequency method consists of ensuring extreme value statistics are preserved on a grid cell basis. To this end, a non-stationary extreme precipitation-frequency analysis is performed on each grid cell individually, and the resulting frequency curves are compared to those produced by the index gauge disaggregation method.

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

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

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

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds

PubMed Central

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie

2018-01-01

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content. PMID:29652811

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds.

PubMed

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie; Huang, Xianfei

2018-04-13

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km², 4.50 km², and 1.87 km², respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content.

Changes In The Heating Degree-days In Norway Due Toglobal Warming

NASA Astrophysics Data System (ADS)

Skaugen, T. E.; Tveito, O. E.; Hanssen-Bauer, I.

A continuous spatial representation of temperature improves the possibility topro- duce maps of temperature-dependent variables. A temperature scenario for the period 2021-2050 is obtained for Norway from the Max-Planck-Institute? AOGCM, GSDIO ECHAM4/OPEC 3. This is done by an ?empirical downscaling method? which in- volves the use of empirical links between large-scale fields and local variables to de- duce estimates of the local variables. The analysis is obtained at forty-six sites in Norway. Spatial representation of the anomalies of temperature in the scenario period compared to the normal period (1961-1990) is obtained with the use of spatial interpo- lation in a GIS. The temperature scenario indicates that we will have a warmer climate in Norway in the future, especially during the winter season. The heating degree-days (HDD) is defined as the accumulated Celsius degrees be- tween the daily mean temperature and a threshold temperature. For Scandinavian countries, this threshold temperature is 17 Celsius degrees. The HDD is found to be a good estimate of accumulated cold. It is therefore a useful index for heating energy consumption within the heating season, and thus to power production planning. As a consequence of the increasing temperatures, the length of the heating season and the HDD within this season will decrease in Norway in the future. The calculations of the heating season and the HDD is estimated at grid level with the use of a GIS. The spatial representation of the heating season and the HDD can then easily be plotted. Local information of the variables being analysed can be withdrawn from the spatial grid in a GIS. The variable is prepared for further spatial analysis. It may also be used as an input to decision making systems.

[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.

Testing a high resolution CO2 and CO emission inventory against atmospheric observations in Salt Lake City, Utah for policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Mallia, D. V.; Fasoli, B.; Bares, R.; Catharine, D.; O'Keeffe, D.; Song, Y.; Huang, J.; Horel, J.; Crosman, E.; Hoch, S.; Ehleringer, J. R.

2016-12-01

We address the need for robust highly-resolved emissions and trace gas concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are the result of proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria air pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present a contemporary (2010-2015) emissions inventory and modeled CO2 and carbon monoxide (CO) concentrations for Salt Lake County, Utah. We compare emissions transported by a dispersion model against stationary measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at hourly, building and road-link resolutions, as well as on an hourly gridded scale. The emissions were scaled using annual Energy Information Administration (EIA) fuel consumption data. We derived a CO emissions inventory using methods similar to Hestia, downscaling total county emissions from the 2011 Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The gridded CO emissions were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The Stochastic Time-Inverted Lagrangian Trasport (STILT) dispersion model was used to transport emissions and estimate pollutant concentrations at an hourly resolution. Modeled results were compared against stationary measurements in the Salt Lake County area. This comparison highlights spatial locations and hours of high variability and uncertainty. Sensitivity to biological fluxes as well as to specific economic sectors was tested by varying their contributions to modeled concentrations and calibrating their emissions.

Methodological Caveats in the Detection of Coordinated Replay between Place Cells and Grid Cells

PubMed Central

Trimper, John B.; Trettel, Sean G.; Hwaun, Ernie; Colgin, Laura Lee

2017-01-01

At rest, hippocampal “place cells,” neurons with receptive fields corresponding to specific spatial locations, reactivate in a manner that reflects recently traveled trajectories. These “replay” events have been proposed as a mechanism underlying memory consolidation, or the transfer of a memory representation from the hippocampus to neocortical regions associated with the original sensory experience. Accordingly, it has been hypothesized that hippocampal replay of a particular experience should be accompanied by simultaneous reactivation of corresponding representations in the neocortex and in the entorhinal cortex, the primary interface between the hippocampus and the neocortex. Recent studies have reported that coordinated replay may occur between hippocampal place cells and medial entorhinal cortex grid cells, cells with multiple spatial receptive fields. Assessing replay in grid cells is problematic, however, as the cells exhibit regularly spaced spatial receptive fields in all environments and, therefore, coordinated replay between place cells and grid cells may be detected by chance. In the present report, we adapted analytical approaches utilized in recent studies of grid cell and place cell replay to determine the extent to which coordinated replay is spuriously detected between grid cells and place cells recorded from separate rats. For a subset of the employed analytical methods, coordinated replay was detected spuriously in a significant proportion of cases in which place cell replay events were randomly matched with grid cell firing epochs of equal duration. More rigorous replay evaluation procedures and minimum spike count requirements greatly reduced the amount of spurious findings. These results provide insights into aspects of place cell and grid cell activity during rest that contribute to false detection of coordinated replay. The results further emphasize the need for careful controls and rigorous methods when testing the hypothesis that place cells and grid cells exhibit coordinated replay. PMID:28824388

Mining and Integration of Environmental Data

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.; Habala, O.; Ciglan, M.

2009-04-01

The project ADMIRE (Advanced Data Mining and Integration Research for Europe) is a 7th FP EU ICT project aims to deliver a consistent and easy-to-use technology for extracting information and knowledge. The project is motivated by the difficulty of extracting meaningful information by data mining combinations of data from multiple heterogeneous and distributed resources. It will also provide an abstract view of data mining and integration, which will give users and developers the power to cope with complexity and heterogeneity of services, data and processes. The data sets describing phenomena from domains like business, society, and environment often contain spatial and temporal dimensions. Integration of spatio-temporal data from different sources is a challenging task due to those dimensions. Different spatio-temporal data sets contain data at different resolutions (e.g. size of the spatial grid) and frequencies. This heterogeneity is the principal challenge of geo-spatial and temporal data sets integration - the integrated data set should hold homogeneous data of the same resolution and frequency. Thus, to integrate heterogeneous spatio-temporal data from distinct source, transformation of one or more data sets is necessary. Following transformation operation are required: • transformation to common spatial and temporal representation - (e.g. transformation to common coordinate system), • spatial and/or temporal aggregation - data from detailed data source are aggregated to match the resolution of other resources involved in the integration process, • spatial and/or temporal record decomposition - records from source with lower resolution data are decomposed to match the granularity of the other data source. This operation decreases data quality (e.g. transformation of data from 50km grid to 10 km grid) - data from lower resolution data set in the integrated schema are imprecise, but it allows us to preserve higher resolution data. We can decompose the spatio-temporal data integration to following phases: • pre-integration data processing - different data set can be physically stored in different formats (e.g. relational databases, text files); it might be necessary to pre-process the data sets to be integrated, • identification of transformation operations necessary to integrate data in spatio-temporal dimensions, • identification of transformation operations to be performed on non-spatio-temporal attributes and • output data schema and set generation - given prepared data and the set of transformation, operations, the final integrated schema is produces. Spatio-temporal dimension brings its specifics also to the problem of mining spatio-temporal data sets. Spatio-temporal relationships exist among records in (s-t) data sets and those relationships should be considered in mining operation. This means that when analyzing a record in spatio-temporal data set, the records in its spatial and/or temporal proximity should be taken into account. In addition, the relationships discovered in spatio-temporal data can be different when mining the same data on different scales (e.g. mining the same data sets on 50 km grid with daily data vs. 10 km grid with hourly data). To be able to do effective data mining, we first needed to gather a sufficient amount of environmental data covering similar area and time span. For this purpose we have engaged in cooperation with several organizations working in the environmental domain in Slovakia, some of which are also our partners from previous research efforts. The organizations which volunteered some of their data are the Slovak Hydro-meteorological Institute (SHMU), the Slovak Water Enterprise (SVP), the Soil Science and Conservation Institute (VUPOP), and the Institute of Hydrology of the Slovak Academy of Sciences (UHSAV). We have prepared scenarios from general meteorology, as well as specialized in hydrology and soil protection.

SU-C-209-03: Anti-Scatter Grid-Line Artifact Minimization for Removing the Grid Lines for Three Different Grids Used with a High Resolution CMOS Detector

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

Rana, R; Bednarek, D; Rudin, S

Purpose: Demonstrate the effectiveness of an anti-scatter grid artifact minimization method by removing the grid-line artifacts for three different grids when used with a high resolution CMOS detector. Method: Three different stationary x-ray grids were used with a high resolution CMOS x-ray detector (Dexela 1207, 75 µm pixels, sensitivity area 11.5cm × 6.5cm) to image a simulated artery block phantom (Nuclear Associates, Stenosis/Aneurysm Artery Block 76–705) combined with a frontal head phantom used as the scattering source. The x-ray parameters were 98kVp, 200mA, and 16ms for all grids. With all the three grids, two images were acquired: the first formore » a scatter-less flat field including the grid and the second of the object with the grid which may still have some scatter transmission. Because scatter has a low spatial frequency distribution, it was represented by an estimated constant value as an initial approximation and subtracted from the image of the object with grid before dividing by an average frame of the grid flat-field with no scatter. The constant value was iteratively changed to minimize residual grid-line artifact. This artifact minimization process was used for all the three grids. Results: Anti-scatter grid lines artifacts were successfully eliminated in all the three final images taken with the three different grids. The image contrast and CNR were also compared before and after the correction, and also compared with those from the image of the object when no grid was used. The corrected images showed an increase in CNR of approximately 28%, 33% and 25% for the three grids, as compared to the images when no grid at all was used. Conclusion: Anti-scatter grid-artifact minimization works effectively irrespective of the specifications of the grid when it is used with a high spatial resolution detector. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

Temperature grid sensor for the measurement of spatial temperature distributions at object surfaces.

PubMed

Schäfer, Thomas; Schubert, Markus; Hampel, Uwe

2013-01-25

This paper presents results of the development and application of a new temperature grid sensor based on the wire-mesh sensor principle. The grid sensor consists of a matrix of 256 Pt1000 platinum chip resistors and an associated electronics that measures the grid resistances with a multiplexing scheme at high speed. The individual sensor elements can be spatially distributed on an object surface and measure transient temperature distributions in real time. The advantage compared with other temperature field measurement approaches such as infrared cameras is that the object under investigation can be thermally insulated and the radiation properties of the surface do not affect the measurement accuracy. The sensor principle is therefore suited for various industrial monitoring applications. Its applicability for surface temperature monitoring has been demonstrated through heating and mixing experiments in a vessel.

Virtual reality and the unfolding of higher dimensions

NASA Astrophysics Data System (ADS)

Aguilera, Julieta C.

2006-02-01

As virtual/augmented reality evolves, the need for spaces that are responsive to structures independent from three dimensional spatial constraints, become apparent. The visual medium of computer graphics may also challenge these self imposed constraints. If one can get used to how projections affect 3D objects in two dimensions, it may also be possible to compose a situation in which to get used to the variations that occur while moving through higher dimensions. The presented application is an enveloping landscape of concave and convex forms, which are determined by the orientation and displacement of the user in relation to a grid made of tesseracts (cubes in four dimensions). The interface accepts input from tridimensional and four-dimensional transformations, and smoothly displays such interactions in real-time. The motion of the user becomes the graphic element whereas the higher dimensional grid references to his/her position relative to it. The user learns how motion inputs affect the grid, recognizing a correlation between the input and the transformations. Mapping information to complex grids in virtual reality is valuable for engineers, artists and users in general because navigation can be internalized like a dance pattern, and further engage us to maneuver space in order to know and experience.

Quantification of the spatial strain distribution of scoliosis using a thin-plate spline method.

PubMed

Kiriyama, Yoshimori; Watanabe, Kota; Matsumoto, Morio; Toyama, Yoshiaki; Nagura, Takeo

2014-01-03

The objective of this study was to quantify the three-dimensional spatial strain distribution of a scoliotic spine by nonhomogeneous transformation without using a statistically averaged reference spine. The shape of the scoliotic spine was determined from computed tomography images from a female patient with adolescent idiopathic scoliosis. The shape of the scoliotic spine was enclosed in a rectangular grid, and symmetrized using a thin-plate spline method according to the node positions of the grid. The node positions of the grid were determined by numerical optimization to satisfy symmetry. The obtained symmetric spinal shape was enclosed within a new rectangular grid and distorted back to the original scoliotic shape using a thin-plate spline method. The distorted grid was compared to the rectangular grid that surrounded the symmetrical spine. Cobb's angle was reduced from 35° in the scoliotic spine to 7° in the symmetrized spine, and the scoliotic shape was almost fully symmetrized. The scoliotic spine showed a complex Green-Lagrange strain distribution in three dimensions. The vertical and transverse compressive/tensile strains in the frontal plane were consistent with the major scoliotic deformation. The compressive, tensile and shear strains on the convex side of the apical vertebra were opposite to those on the concave side. These results indicate that the proposed method can be used to quantify the three-dimensional spatial strain distribution of a scoliotic spine, and may be useful in quantifying the deformity of scoliosis. © 2013 Elsevier Ltd. All rights reserved.

Automated Approach to Very High-Order Aeroacoustic Computations. Revision

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2001-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. For smooth problems, this is best accomplished with very high-order in space and time methods on small stencils. However, the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewski recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that am located near wall boundaries. These procedures are used to develop automatically and to implement very high-order methods (> 15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

An Automated Approach to Very High Order Aeroacoustic Computations in Complex Geometries

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2000-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. And for smooth problems, this is best accomplished with very high order in space and time methods on small stencils. But the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewslci recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that are located near wall boundaries. These procedures are used to automatically develop and implement very high order methods (>15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

Improving the modeling of geomagnetically induced currents in Spain

NASA Astrophysics Data System (ADS)

Torta, J. M.; Marcuello, A.; Campanyà, J.; Marsal, S.; Queralt, P.; Ledo, J.

2017-05-01

Vulnerability assessments of the risk posed by geomagnetically induced currents (GICs) to power transmission grids benefit from accurate knowledge of the geomagnetic field variations at each node of the grid, the Earth's geoelectrical structures beneath them, and the topology and relative resistances of the grid elements in the precise instant of a storm. The results of previous analyses on the threat posed by GICs to the Spanish 400 kV grid are improved in this study by resorting to different strategies to progress in the three aspects identified above. First, although at midlatitude regions the source fields are rather uniform, we have investigated the effect of their spatial changes by interpolating the field from the records of several close observatories with different techniques. Second, we have performed a magnetotelluric (MT) sounding in the vicinity of one of the transformers where GICs are measured to determine the geoelectrical structure of the Earth, and we have identified the importance of estimating the MT impedance tensor when predicting GIC, especially where the effect of lateral heterogeneities is important. Finally, a sensitivity analysis to network changes has allowed us to assess the reliability of both the information about the network topology and resistances, and the assumptions made when all the details or the network status are not available. In our case, the most essential issue to improve the coincidence between model predictions and actual observations came from the use of realistic geoelectric information involving local MT measurements.

Sealife: a semantic grid browser for the life sciences applied to the study of infectious diseases.

PubMed

Schroeder, Michael; Burger, Albert; Kostkova, Patty; Stevens, Robert; Habermann, Bianca; Dieng-Kuntz, Rose

2006-01-01

The objective of Sealife is the conception and realisation of a semantic Grid browser for the life sciences, which will link the existing Web to the currently emerging eScience infrastructure. The SeaLife Browser will allow users to automatically link a host of Web servers and Web/Grid services to the Web content he/she is visiting. This will be accomplished using eScience's growing number of Web/Grid Services and its XML-based standards and ontologies. The browser will identify terms in the pages being browsed through the background knowledge held in ontologies. Through the use of Semantic Hyperlinks, which link identified ontology terms to servers and services, the SeaLife Browser will offer a new dimension of context-based information integration. In this paper, we give an overview over the different components of the browser and their interplay. This SeaLife Browser will be demonstrated within three application scenarios in evidence-based medicine, literature & patent mining, and molecular biology, all relating to the study of infectious diseases. The three applications vertically integrate the molecule/cell, the tissue/organ and the patient/population level by covering the analysis of high-throughput screening data for endocytosis (the molecular entry pathway into the cell), the expression of proteins in the spatial context of tissue and organs, and a high-level library on infectious diseases designed for clinicians and their patients. For more information see http://www.biote.ctu-dresden.de/sealife.

Fossil-Fuel C02 Emissions Database and Exploration System

NASA Astrophysics Data System (ADS)

Krassovski, M.; Boden, T.; Andres, R. J.; Blasing, T. J.

2012-12-01

The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL) quantifies the release of carbon from fossil-fuel use and cement production at global, regional, and national spatial scales. The CDIAC emission time series estimates are based largely on annual energy statistics published at the national level by the United Nations (UN). CDIAC has developed a relational database to house collected data and information and a web-based interface to help users worldwide identify, explore and download desired emission data. The available information is divided in two major group: time series and gridded data. The time series data is offered for global, regional and national scales. Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). The gridded data presents annual and monthly estimates. Annual data presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2008. The monthly, fossil-fuel CO2 emissions estimates from 1950-2008 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2011), 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). This presentation introduces newly build database and web interface, reflects the present state and functionality of the Fossil-Fuel CO2 Emissions Database and Exploration System as well as future plans for expansion.

Research on the key technology of update of land survey spatial data based on embedded GIS and GPS

NASA Astrophysics Data System (ADS)

Chen, Dan; Liu, Yanfang; Yu, Hai; Xia, Yin

2009-10-01

According to the actual needs of the second land-use survey and the PDA's characteristics of small volume and small memory, it can be analyzed that the key technology of the data collection system of field survey based on GPS-PDA is the read speed of the data. In order to enhance the speed and efficiency of the analysis of the spatial data on mobile devices, we classify the layers of spatial data; get the Layer-Grid Index by getting the different levels and blocks of the layer of spatial data; then get the R-TREE index of the spatial data objects. Different scale levels of space are used in different levels management. The grid method is used to do the block management.

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

Habte, A.; Lopez, A.; Sengupta, M.

Typical Meteorological Year (TMY) data sets provide industry standard resource information for building designers and are commonly used by the solar industry to estimate photovoltaic and concentrating solar power system performance. Historically, TMY data sets were only available for certain station locations, but current TMY data sets are available on the same grid as the National Solar Radiation Database data and are referred to as the gridded TMY. In this report, a comparison of TMY, typical direct (normal irradiance) year (TDY), and typical global (horizontal irradiance) year (TGY) data sets were performed to better understand the impact of ancillary weathermore » variables upon them. These analyses identified geographical areas of high and low temporal and spatial variability, thereby providing insight into the representativeness of a particular TMY data set for use in renewable energy as well as other applications.« less

The Internet of things and Smart Grid

NASA Astrophysics Data System (ADS)

Li, Biao; Lv, Sen; Pan, Qing

2018-02-01

The Internet of things and smart grid are the frontier of information and Industry. The combination of Internet of things and smart grid will greatly enhance the ability of smart grid information and communication support. The key technologies of the Internet of things will be applied to the smart grid, and the grid operation and management information perception service centre will be built to support the commanding heights of the world’s smart grid.

Improving a spatial rainfall product using a data-mining approach and its effect on the hydrological response of a meso-scale catchment.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.; Demirel, C.

2017-12-01

The spatial representation of rainfall is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the daily grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. The research is focused on the Skjern catchment (1,050 km2 western Jutland), where we can dispose of the complete rain-gauge database from the Danish Hydrological Observatory and compute the distributed hydrological response at the 1-km scale.To give a better estimation of the gridded rainfall input, we start from ground measurements by simulating the missing data with a stochastic data-mining approach, then we compute again the grid interpolation. To maximize the predictive power of the technique, combinations of station time-series that are the most informative to each other are selected on the basis of their correlation and available historical data. Then, the missing data inside these time-series are simulated together using the direct sampling technique (DS) [1, 2]. DS simulates a datum by sampling the historical record of the same stations where a similar data pattern occurs, preserving their complex statistical relation. The simulated data are reinjected in the whole dataset and used as well as conditioning data to progressively fill up the gaps in other stations.The results show that the proposed methodology, tested on the period 1995-2012, can increase the realism of the grid rainfall product by regenerating the missing ground measurements. The hydrological response is analyzed considering the observations at 5 hydrological stations. The presented methodology can be used in many regions to regenerate the missing data using the information contained in the historical record and propagate the uncertainty of the prediction to the hydrological response. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014.

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP [Investigating the scale dependence of SCM simulated precipitation and cloud by using gridded forcing data at SGP

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-05

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

A map of abstract relational knowledge in the human hippocampal-entorhinal cortex.

PubMed

Garvert, Mona M; Dolan, Raymond J; Behrens, Timothy Ej

2017-04-27

The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.

Spatial networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

The Marine Geoscience Data System and the Global Multi-Resolution Topography Synthesis: Online Resources for Exploring Ocean Mapping Data

NASA Astrophysics Data System (ADS)

Ferrini, V. L.; Morton, J. J.; Carbotte, S. M.

2016-02-01

The Marine Geoscience Data System (MGDS: www.marine-geo.org) provides a suite of tools and services for free public access to data acquired throughout the global oceans including maps, grids, near-bottom photos, and geologic interpretations that are essential for habitat characterization and marine spatial planning. Users can explore, discover, and download data through a combination of APIs and front-end interfaces that include dynamic service-driven maps, a geospatially enabled search engine, and an easy to navigate user interface for browsing and discovering related data. MGDS offers domain-specific data curation with a team of scientists and data specialists who utilize a suite of back-end tools for introspection of data files and metadata assembly to verify data quality and ensure that data are well-documented for long-term preservation and re-use. Funded by the NSF as part of the multi-disciplinary IEDA Data Facility, MGDS also offers Data DOI registration and links between data and scientific publications. MGDS produces and curates the Global Multi-Resolution Topography Synthesis (GMRT: gmrt.marine-geo.org), a continuously updated Digital Elevation Model that seamlessly integrates multi-resolutional elevation data from a variety of sources including the GEBCO 2014 ( 1 km resolution) and International Bathymetric Chart of the Southern Ocean ( 500 m) compilations. A significant component of GMRT includes ship-based multibeam sonar data, publicly available through NOAA's National Centers for Environmental Information, that are cleaned and quality controlled by the MGDS Team and gridded at their full spatial resolution (typically 100 m resolution in the deep sea). Additional components include gridded bathymetry products contributed by individual scientists (up to meter scale resolution in places), publicly accessible regional bathymetry, and high-resolution terrestrial elevation data. New data are added to GMRT on an ongoing basis, with two scheduled releases per year. GMRT is available as both gridded data and images that can be viewed and downloaded directly through the Java application GeoMapApp (www.geomapapp.org) and the web-based GMRT MapTool. In addition, the GMRT GridServer API provides programmatic access to grids, imagery, profiles, and single point elevation values.

Filling in the GAPS: evaluating completeness and coverage of open-access biodiversity databases in the United States

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

Troia, Matthew J.; McManamay, Ryan A.

Primary biodiversity data constitute observations of particular species at given points in time and space. Open-access electronic databases provide unprecedented access to these data, but their usefulness in characterizing species distributions and patterns in biodiversity depend on how complete species inventories are at a given survey location and how uniformly distributed survey locations are along dimensions of time, space, and environment. Our aim was to compare completeness and coverage among three open-access databases representing ten taxonomic groups (amphibians, birds, freshwater bivalves, crayfish, freshwater fish, fungi, insects, mammals, plants, and reptiles) in the contiguous United States. We compiled occurrence records frommore » the Global Biodiversity Information Facility (GBIF), the North American Breeding Bird Survey (BBS), and federally administered fish surveys (FFS). In this study, we aggregated occurrence records by 0.1° × 0.1° grid cells and computed three completeness metrics to classify each grid cell as well-surveyed or not. Next, we compared frequency distributions of surveyed grid cells to background environmental conditions in a GIS and performed Kolmogorov–Smirnov tests to quantify coverage through time, along two spatial gradients, and along eight environmental gradients. The three databases contributed >13.6 million reliable occurrence records distributed among >190,000 grid cells. The percent of well-surveyed grid cells was substantially lower for GBIF (5.2%) than for systematic surveys (BBS and FFS; 82.5%). Still, the large number of GBIF occurrence records produced at least 250 well-surveyed grid cells for six of nine taxonomic groups. Coverages of systematic surveys were less biased across spatial and environmental dimensions but were more biased in temporal coverage compared to GBIF data. GBIF coverages also varied among taxonomic groups, consistent with commonly recognized geographic, environmental, and institutional sampling biases. Lastly, this comprehensive assessment of biodiversity data across the contiguous United States provides a prioritization scheme to fill in the gaps by contributing existing occurrence records to the public domain and planning future surveys.« less

Filling in the GAPS: evaluating completeness and coverage of open-access biodiversity databases in the United States

DOE PAGES

Troia, Matthew J.; McManamay, Ryan A.

2016-06-12

Primary biodiversity data constitute observations of particular species at given points in time and space. Open-access electronic databases provide unprecedented access to these data, but their usefulness in characterizing species distributions and patterns in biodiversity depend on how complete species inventories are at a given survey location and how uniformly distributed survey locations are along dimensions of time, space, and environment. Our aim was to compare completeness and coverage among three open-access databases representing ten taxonomic groups (amphibians, birds, freshwater bivalves, crayfish, freshwater fish, fungi, insects, mammals, plants, and reptiles) in the contiguous United States. We compiled occurrence records frommore » the Global Biodiversity Information Facility (GBIF), the North American Breeding Bird Survey (BBS), and federally administered fish surveys (FFS). In this study, we aggregated occurrence records by 0.1° × 0.1° grid cells and computed three completeness metrics to classify each grid cell as well-surveyed or not. Next, we compared frequency distributions of surveyed grid cells to background environmental conditions in a GIS and performed Kolmogorov–Smirnov tests to quantify coverage through time, along two spatial gradients, and along eight environmental gradients. The three databases contributed >13.6 million reliable occurrence records distributed among >190,000 grid cells. The percent of well-surveyed grid cells was substantially lower for GBIF (5.2%) than for systematic surveys (BBS and FFS; 82.5%). Still, the large number of GBIF occurrence records produced at least 250 well-surveyed grid cells for six of nine taxonomic groups. Coverages of systematic surveys were less biased across spatial and environmental dimensions but were more biased in temporal coverage compared to GBIF data. GBIF coverages also varied among taxonomic groups, consistent with commonly recognized geographic, environmental, and institutional sampling biases. Lastly, this comprehensive assessment of biodiversity data across the contiguous United States provides a prioritization scheme to fill in the gaps by contributing existing occurrence records to the public domain and planning future surveys.« less

Spatial distribution of precipitation extremes in Norway

NASA Astrophysics Data System (ADS)

Verpe Dyrrdal, Anita; Skaugen, Thomas; Lenkoski, Alex; Thorarinsdottir, Thordis; Stordal, Frode; Førland, Eirik J.

2015-04-01

Estimates of extreme precipitation, in terms of return levels, are crucial in planning and design of important infrastructure. Through two separate studies, we have examined the levels and spatial distribution of daily extreme precipitation over catchments in Norway, and hourly extreme precipitation in a point. The analyses were carried out through the development of two new methods for estimating extreme precipitation in Norway. For daily precipitation we fit the Generalized Extreme Value (GEV) distribution to areal time series from a gridded dataset, consisting of daily precipitation during the period 1957-today with a resolution of 1x1 km². This grid-based method is more objective and less manual and time-consuming compared to the existing method at MET Norway. In addition, estimates in ungauged catchments are easier to obtain, and the GEV approach includes a measure of uncertainty, which is a requirement in climate studies today. Further, we go into depth on the debated GEV shape parameter, which plays an important role for longer return periods. We show that it varies according to dominating precipitation types, having positive values in the southeast and negative values in the southwest. We also find indications that the degree of orographic enhancement might affect the shape parameter. For hourly precipitation, we estimate return levels on a 1x1 km² grid, by linking GEV distributions with latent Gaussian fields in a Bayesian hierarchical model (BHM). Generalized linear models on the GEV parameters, estimated from observations, are able to incorporate location-specific geographic and meteorological information and thereby accommodate these effects on extreme precipitation. Gaussian fields capture additional unexplained spatial heterogeneity and overcome the sparse grid on which observations are collected, while a Bayesian model averaging component directly assesses model uncertainty. We find that mean summer precipitation, mean summer temperature, latitude, longitude, mean annual precipitation and elevation are good covariate candidates for hourly precipitation in our model. Summer indices succeed because hourly precipitation extremes often occur during the convective season. The spatial distribution of hourly and daily precipitation differs in Norway. Daily precipitation extremes are larger along the southwestern coast, where large-scale frontal systems dominate during fall season and the mountain ridge generates strong orographic enhancement. The largest hourly precipitation extremes are mostly produced by intense convective showers during summer, and are thus found along the entire southern coast, including the Oslo-region.

SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine

NASA Astrophysics Data System (ADS)

Henshaw, J. D.; Longmore, S. N.; Kruijssen, J. M. D.; Davies, B.; Bally, J.; Barnes, A.; Battersby, C.; Burton, M.; Cunningham, M. R.; Dale, J. E.; Ginsburg, A.; Immer, K.; Jones, P. A.; Kendrew, S.; Mills, E. A. C.; Molinari, S.; Moore, T. J. T.; Ott, J.; Pillai, T.; Rathborne, J.; Schilke, P.; Schmiedeke, A.; Testi, L.; Walker, D.; Walsh, A.; Zhang, Q.

2016-01-01

The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.

Introducing Perception and Modelling of Spatial Randomness in Classroom

ERIC Educational Resources Information Center

De Nóbrega, José Renato

2017-01-01

A strategy to facilitate understanding of spatial randomness is described, using student activities developed in sequence: looking at spatial patterns, simulating approximate spatial randomness using a grid of equally-likely squares, using binomial probabilities for approximations and predictions and then comparing with given Poisson…

geoknife: Reproducible web-processing of large gridded datasets

USGS Publications Warehouse

Read, Jordan S.; Walker, Jordan I.; Appling, Alison P.; Blodgett, David L.; Read, Emily K.; Winslow, Luke A.

2016-01-01

Geoprocessing of large gridded data according to overlap with irregular landscape features is common to many large-scale ecological analyses. The geoknife R package was created to facilitate reproducible analyses of gridded datasets found on the U.S. Geological Survey Geo Data Portal web application or elsewhere, using a web-enabled workflow that eliminates the need to download and store large datasets that are reliably hosted on the Internet. The package provides access to several data subset and summarization algorithms that are available on remote web processing servers. Outputs from geoknife include spatial and temporal data subsets, spatially-averaged time series values filtered by user-specified areas of interest, and categorical coverage fractions for various land-use types.

Coarse-grained hydrodynamics from correlation functions

NASA Astrophysics Data System (ADS)

Palmer, Bruce

2018-02-01

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.

Grid therapy using high definition multileaf collimators: realizing benefits of the bystander effect.

PubMed

Peng, Valery; Suchowerska, Natalka; Rogers, Linda; Claridge Mackonis, Elizabeth; Oakes, Samantha; McKenzie, David R

2017-08-01

In microbeam radiotherapy (MRT), parallel arrays of high-intensity synchrotron x-ray beams achieve normal tissue sparing without compromising tumor control. Grid-therapy using clinical linacs has spatial modulation on a larger scale and achieves promising results for palliative treatments of bulky tumors. The availability of high definition multileaf collimators (HDMLCs) with 2.5 mm leaves provides an opportunity for grid-therapy to more closely approach MRT. However, challenges to the wider implementation of grid-therapy remain because spatial modulation of the target volume runs counter to current radiotherapy practice and mechanisms for the beneficial effects of MRT are not fully understood. Without more knowledge of cell dose responses, a quantitative basis for planning treatments is difficult. The aim of this study is to determine if therapeutic benefits of MRT can be achieved using a linac with HDMLCs and if so, to develop a predictive model to support treatment planning. HD120-MLCs of a Varian Novalis TX TM were used to generate grid patterns of 2.5 and 5.0 mm spacing, which were characterized dosimetrically using Gafchromic TM EBT3 film. Clonogenic survival of normal (HUVEC) and cancer (NCI-H460, HCC-1954) cell lines following irradiation under the grid and open fields using a 6 MV photon beam were compared in-vitro for the same average dose. Relative to an open field, survival of normal cells in a 2.5 mm striped field was the same, while the survival of both cancer cell lines was significantly lower. A mathematical model was developed to incorporate dose gradients of the spatial modulation into the standard linear quadratic model. Our new bystander extended LQ model assumes spatial gradients drive the diffusion of soluble factors that influence survival through bystander effects, successfully predicting the experimental results that show an increased therapeutic ratio. Our results challenge conventional radiotherapy practice and propose that additional gain can be realized by prescribing spatially modulated treatments to harness the bystander effect.

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

A Review of High-Order and Optimized Finite-Difference Methods for Simulating Linear Wave Phenomena

NASA Technical Reports Server (NTRS)

Zingg, David W.

1996-01-01

This paper presents a review of high-order and optimized finite-difference methods for numerically simulating the propagation and scattering of linear waves, such as electromagnetic, acoustic, or elastic waves. The spatial operators reviewed include compact schemes, non-compact schemes, schemes on staggered grids, and schemes which are optimized to produce specific characteristics. The time-marching methods discussed include Runge-Kutta methods, Adams-Bashforth methods, and the leapfrog method. In addition, the following fourth-order fully-discrete finite-difference methods are considered: a one-step implicit scheme with a three-point spatial stencil, a one-step explicit scheme with a five-point spatial stencil, and a two-step explicit scheme with a five-point spatial stencil. For each method studied, the number of grid points per wavelength required for accurate simulation of wave propagation over large distances is presented. Recommendations are made with respect to the suitability of the methods for specific problems and practical aspects of their use, such as appropriate Courant numbers and grid densities. Avenues for future research are suggested.

A New Stratified Sampling Procedure which Decreases Error Estimation of Varroa Mite Number on Sticky Boards.

PubMed

Kretzschmar, A; Durand, E; Maisonnasse, A; Vallon, J; Le Conte, Y

2015-06-01

A new procedure of stratified sampling is proposed in order to establish an accurate estimation of Varroa destructor populations on sticky bottom boards of the hive. It is based on the spatial sampling theory that recommends using regular grid stratification in the case of spatially structured process. The distribution of varroa mites on sticky board being observed as spatially structured, we designed a sampling scheme based on a regular grid with circles centered on each grid element. This new procedure is then compared with a former method using partially random sampling. Relative error improvements are exposed on the basis of a large sample of simulated sticky boards (n=20,000) which provides a complete range of spatial structures, from a random structure to a highly frame driven structure. The improvement of varroa mite number estimation is then measured by the percentage of counts with an error greater than a given level. © 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.

Evaluation of Statistical Methodologies Used in U. S. Army Ordnance and Explosive Work

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

Ostrouchov, G

2000-02-14

Oak Ridge National Laboratory was tasked by the U.S. Army Engineering and Support Center (Huntsville, AL) to evaluate the mathematical basis of existing software tools used to assist the Army with the characterization of sites potentially contaminated with unexploded ordnance (UXO). These software tools are collectively known as SiteStats/GridStats. The first purpose of the software is to guide sampling of underground anomalies to estimate a site's UXO density. The second purpose is to delineate areas of homogeneous UXO density that can be used in the formulation of response actions. It was found that SiteStats/GridStats does adequately guide the sampling somore » that the UXO density estimator for a sector is unbiased. However, the software's techniques for delineation of homogeneous areas perform less well than visual inspection, which is frequently used to override the software in the overall sectorization methodology. The main problems with the software lie in the criteria used to detect nonhomogeneity and those used to recommend the number of homogeneous subareas. SiteStats/GridStats is not a decision-making tool in the classical sense. Although it does provide information to decision makers, it does not require a decision based on that information. SiteStats/GridStats provides information that is supplemented by visual inspections, land-use plans, and risk estimates prior to making any decisions. Although the sector UXO density estimator is unbiased regardless of UXO density variation within a sector, its variability increases with increased sector density variation. For this reason, the current practice of visual inspection of individual sampled grid densities (as provided by Site-Stats/GridStats) is necessary to ensure approximate homogeneity, particularly at sites with medium to high UXO density. Together with Site-Stats/GridStats override capabilities, this provides a sufficient mechanism for homogeneous sectorization and thus yields representative UXO density estimates. Objections raised by various parties to the use of a numerical ''discriminator'' in SiteStats/GridStats were likely because of the fact that the concerned statistical technique is customarily applied for a different purpose and because of poor documentation. The ''discriminator'', in Site-Stats/GridStats is a ''tuning parameter'' for the sampling process, and it affects the precision of the grid density estimates through changes in required sample size. It is recommended that sector characterization in terms of a map showing contour lines of constant UXO density with an expressed uncertainty or confidence level is a better basis for remediation decisions than a sector UXO density point estimate. A number of spatial density estimation techniques could be adapted to the UXO density estimation problem.« less

SU-E-P-30: Clinical Applications of Spatially Fractionated Radiation Therapy (GRID) Using Helical Tomotherapy

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

Zhang, X; Liang, X; Penagaricano, J

2015-06-15

Purpose: To present the first clinical applications of Helical Tomotherapy-based spatially fractionated radiotherapy (HT-GRID) for deep seated tumors and associated dosimetric study. Methods: Ten previously treated GRID patients were selected (5 HT-GRID and 5 LINAC-GRID using a commercially available GRID block). Each case was re-planned either in HT-GRID or LINAC-GRID for a total of 10 plans for both techniques using same prescribed dose of 20 Gy to maximum point dose of GRID GTV. For TOMO-GRID, a programmable virtual TOMOGRID template mimicking a GRID pattern was generated. Dosimetric parameters compared included: GRID GTV mean dose (Dmean) and equivalent uniform dose (EUD),more » GRID GTV dose inhomogeneity (Ratio(valley/peak)), normal tissue Dmean and EUD, and other organs-at-risk(OARs) doses. Results: The median tumor volume was 634 cc, ranging from 182 to 4646 cc. Median distance from skin to the deepest part of tumor was 22cm, ranging from 8.9 to 38cm. The median GRID GTV Dmean and EUD was 10.65Gy (9.8–12.5Gy) and 7.62Gy (4.31–11.06Gy) for HT-GRID and was 6.73Gy (4.44–8.44Gy) and 3.95Gy (0.14–4.2Gy) for LINAC-GRID. The median Ratio(valley/peak) was 0.144(0.05–0.29) for HT-GRID and was 0.055(0.0001–0.14) for LINAC-GRID. For normal tissue in HT-GRID, the median Dmean and EUD was 1.24Gy (0.34–2.54Gy) and 5.45 Gy(3.45–6.89Gy) and was 0.61 Gy(0.11–1.52Gy) and 6Gy(4.45–6.82Gy) for LINAC-GRID. The OAR doses were comparable between the HT-GRID and LINAC-GRID. However, in some cases it was not possible to avoid a critical structure in LINAC-GRID; while HT-GRID can spare more tissue doses for certain critical structures. Conclusion: HT-GRID delivers higher GRID GTV Dmean, EUD and Ratio(valley/peak) compared to LINAC-GRID. HT-GRID delivers higher Dmean and lower EUD for normal tissue compared to LINAC-GRID. TOMOGRID template can be highly patient-specific and allows adjustment of the GRID pattern to different tumor sizes and shapes when they are deeply-seated and cannot be safely treated with LINAC-GRID.« less

The State of NASA's Information Power Grid

NASA Technical Reports Server (NTRS)

Johnston, William E.; Vaziri, Arsi; Tanner, Leigh Ann; Feiereisen, William J.; Thigpen, William; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation transfers the concept of the power grid to information sharing in the NASA community. An information grid of this sort would be characterized as comprising tools, middleware, and services for the facilitation of interoperability, distribution of new technologies, human collaboration, and data management. While a grid would increase the ability of information sharing, it would not necessitate it. The onus of utilizing the grid would rest with the users.

Comprehensive framework for visualizing and analyzing spatio-temporal dynamics of racial diversity in the entire United States

PubMed Central

Netzel, Pawel

2017-01-01

The United States is increasingly becoming a multi-racial society. To understand multiple consequences of this overall trend to our neighborhoods we need a methodology capable of spatio-temporal analysis of racial diversity at the local level but also across the entire U.S. Furthermore, such methodology should be accessible to stakeholders ranging from analysts to decision makers. In this paper we present a comprehensive framework for visualizing and analyzing diversity data that fulfills such requirements. The first component of our framework is a U.S.-wide, multi-year database of race sub-population grids which is freely available for download. These 30 m resolution grids have being developed using dasymetric modeling and are available for 1990-2000-2010. We summarize numerous advantages of gridded population data over commonly used Census tract-aggregated data. Using these grids frees analysts from constructing their own and allows them to focus on diversity analysis. The second component of our framework is a set of U.S.-wide, multi-year diversity maps at 30 m resolution. A diversity map is our product that classifies the gridded population into 39 communities based on their degrees of diversity, dominant race, and population density. It provides spatial information on diversity in a single, easy-to-understand map that can be utilized by analysts and end users alike. Maps based on subsequent Censuses provide information about spatio-temporal dynamics of diversity. Diversity maps are accessible through the GeoWeb application SocScape (http://sil.uc.edu/webapps/socscape_usa/) for an immediate online exploration. The third component of our framework is a proposal to quantitatively analyze diversity maps using a set of landscape metrics. Because of its form, a grid-based diversity map could be thought of as a diversity “landscape” and analyzed quantitatively using landscape metrics. We give a brief summary of most pertinent metrics and demonstrate how they can be applied to diversity maps. PMID:28358862

Time-marching multi-grid seismic tomography

NASA Astrophysics Data System (ADS)

Tong, P.; Yang, D.; Liu, Q.

2016-12-01

From the classic ray-based traveltime tomography to the state-of-the-art full waveform inversion, because of the nonlinearity of seismic inverse problems, a good starting model is essential for preventing the convergence of the objective function toward local minima. With a focus on building high-accuracy starting models, we propose the so-called time-marching multi-grid seismic tomography method in this study. The new seismic tomography scheme consists of a temporal time-marching approach and a spatial multi-grid strategy. We first divide the recording period of seismic data into a series of time windows. Sequentially, the subsurface properties in each time window are iteratively updated starting from the final model of the previous time window. There are at least two advantages of the time-marching approach: (1) the information included in the seismic data of previous time windows has been explored to build the starting models of later time windows; (2) seismic data of later time windows could provide extra information to refine the subsurface images. Within each time window, we use a multi-grid method to decompose the scale of the inverse problem. Specifically, the unknowns of the inverse problem are sampled on a coarse mesh to capture the macro-scale structure of the subsurface at the beginning. Because of the low dimensionality, it is much easier to reach the global minimum on a coarse mesh. After that, finer meshes are introduced to recover the micro-scale properties. That is to say, the subsurface model is iteratively updated on multi-grid in every time window. We expect that high-accuracy starting models should be generated for the second and later time windows. We will test this time-marching multi-grid method by using our newly developed eikonal-based traveltime tomography software package tomoQuake. Real application results in the 2016 Kumamoto earthquake (Mw 7.0) region in Japan will be demonstrated.

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

Wiley, J.C.

The author describes a general `hp` finite element method with adaptive grids. The code was based on the work of Oden, et al. The term `hp` refers to the method of spatial refinement (h), in conjunction with the order of polynomials used as a part of the finite element discretization (p). This finite element code seems to handle well the different mesh grid sizes occuring between abuted grids with different resolutions.

Phase 2 and phase 3 presentation grids

Treesearch

Joseph McCollum; Jamie K. Cochran

2009-01-01

Many forest inventory and analysis (FIA) analysts, other researchers, and FIA Spatial Data Services personnel have expressed their desire to use the FIA Phase 2 (P2) and Phase 3 (P3), and Forest Health Monitoring (FHM) grids in presentations and other analytical reports. Such uses have been prohibited due to the necessity of keeping the actual P2, P3, and FHM grids...

Gridded National Inventory of U.S. Methane Emissions

NASA Technical Reports Server (NTRS)

Maasakkers, Joannes D.; Jacob, Daniel J.; Sulprizio, Melissa P.; Turner, Alexander J.; Weitz, Melissa; Wirth, Tom; Hight, Cate; DeFigueiredo, Mark; Desai, Mausami; Schmeltz, Rachel;

Gridded national inventory of U.S. methane emissions

DOE PAGES

Maasakkers, Joannes D.; Jacob, Daniel J.; Sulprizio, Melissa P.; ...

2016-11-16

Here we present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scaledependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show largemore » differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Finally, our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.« less

Gridded National Inventory of U.S. Methane Emissions.

PubMed

Maasakkers, Joannes D; Jacob, Daniel J; Sulprizio, Melissa P; Turner, Alexander J; Weitz, Melissa; Wirth, Tom; Hight, Cate; DeFigueiredo, Mark; Desai, Mausami; Schmeltz, Rachel; Hockstad, Leif; Bloom, Anthony A; Bowman, Kevin W; Jeong, Seongeun; Fischer, Marc L

2016-12-06

We present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

OGC and Grid Interoperability in enviroGRIDS Project

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Rodila, Denisa; Bacu, Victor; Giuliani, Gregory; Ray, Nicolas

2010-05-01

EnviroGRIDS (Black Sea Catchment Observation and Assessment System supporting Sustainable Development) [1] is a 4-years FP7 Project aiming to address the subjects of ecologically unsustainable development and inadequate resource management. The project develops a Spatial Data Infrastructure of the Black Sea Catchment region. The geospatial technologies offer very specialized functionality for Earth Science oriented applications as well as the Grid oriented technology that is able to support distributed and parallel processing. One challenge of the enviroGRIDS project is the interoperability between geospatial and Grid infrastructures by providing the basic and the extended features of the both technologies. The geospatial interoperability technology has been promoted as a way of dealing with large volumes of geospatial data in distributed environments through the development of interoperable Web service specifications proposed by the Open Geospatial Consortium (OGC), with applications spread across multiple fields but especially in Earth observation research. Due to the huge volumes of data available in the geospatial domain and the additional introduced issues (data management, secure data transfer, data distribution and data computation), the need for an infrastructure capable to manage all those problems becomes an important aspect. The Grid promotes and facilitates the secure interoperations of geospatial heterogeneous distributed data within a distributed environment, the creation and management of large distributed computational jobs and assures a security level for communication and transfer of messages based on certificates. This presentation analysis and discusses the most significant use cases for enabling the OGC Web services interoperability with the Grid environment and focuses on the description and implementation of the most promising one. In these use cases we give a special attention to issues such as: the relations between computational grid and the OGC Web service protocols, the advantages offered by the Grid technology - such as providing a secure interoperability between the distributed geospatial resource -and the issues introduced by the integration of distributed geospatial data in a secure environment: data and service discovery, management, access and computation. enviroGRIDS project proposes a new architecture which allows a flexible and scalable approach for integrating the geospatial domain represented by the OGC Web services with the Grid domain represented by the gLite middleware. The parallelism offered by the Grid technology is discussed and explored at the data level, management level and computation level. The analysis is carried out for OGC Web service interoperability in general but specific details are emphasized for Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), Web Processing Service (WPS) and Catalog Service for Web (CSW). Issues regarding the mapping and the interoperability between the OGC and the Grid standards and protocols are analyzed as they are the base in solving the communication problems between the two environments: grid and geospatial. The presetation mainly highlights how the Grid environment and Grid applications capabilities can be extended and utilized in geospatial interoperability. Interoperability between geospatial and Grid infrastructures provides features such as the specific geospatial complex functionality and the high power computation and security of the Grid, high spatial model resolution and geographical area covering, flexible combination and interoperability of the geographical models. According with the Service Oriented Architecture concepts and requirements of interoperability between geospatial and Grid infrastructures each of the main functionality is visible from enviroGRIDS Portal and consequently, by the end user applications such as Decision Maker/Citizen oriented Applications. The enviroGRIDS portal is the single way of the user to get into the system and the portal faces a unique style of the graphical user interface. Main reference for further information: [1] enviroGRIDS Project, http://www.envirogrids.net/

Research on spatio-temporal database techniques for spatial information service

NASA Astrophysics Data System (ADS)

Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

2007-06-01

Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

The color of sea level: Importance of spatial variations in spectral shape for assessing the significance of trends

NASA Astrophysics Data System (ADS)

Hughes, Chris W.; Williams, Simon D. P.

2010-10-01

We investigate spatial variations in the shape of the spectrum of sea level variability based on a homogeneously sampled 12 year gridded altimeter data set. We present a method of plotting spectral information as color, focusing on periods between 2 and 24 weeks, which shows that significant spatial variations in the spectral shape exist and contain useful dynamical information. Using the Bayesian Information Criterion, we determine that, typically, a fifth-order autoregressive model is needed to capture the structure in the spectrum. Using this model, we show that statistical errors in fitted local trends range between less than 1 and more than 5 times of what would be calculated assuming "white" noise and that the time needed to detect a 1 mm/yr trend ranges between about 5 years and many decades. For global mean sea level, the statistical error reduces to 0.1 mm/yr over 12 years, with only 2 years needed to detect a 1 mm/yr trend. We find significant regional differences in trend from the global mean. The patterns of these regional differences are indicative of a sea level trend dominated by dynamical ocean processes over this period.

SU-F-T-513: Dosimetric Validation of Spatially Fractionated Radiotherapy Using Gel Dosimetry

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

Papanikolaou, P; Watts, L; Kirby, N

2016-06-15

Purpose: Spatially fractionated radiation therapy, also known as GRID therapy, is used to treat large solid tumors by irradiating the target to a single dose of 10–20Gy through spatially distributed beamlets. We have investigated the use of a 3D gel for dosimetric characterization of GRID therapy. Methods: GRID therapy is an external beam analog of volumetric brachytherapy, whereby we produce a distribution of hot and cold dose columns inside the tumor volume. Such distribution can be produced with a block or by using a checker-like pattern with MLC. We have studied both types of GRID delivery. A cube shaped acrylicmore » phantom was filled with polymer gel and served as a 3D dosimeter. The phantom was scanned and the CT images were used to produce two plans in Pinnacle, one with the grid block and one with the MLC defined grid. A 6MV beam was used for the plan with a prescription of 1500cGy at dmax. The irradiated phantom was scanned in a 3T MRI scanner. Results: 3D dose maps were derived from the MR scans of the gel dosimeter and were found to be in good agreement with the predicted dose distribution from the RTP system. Gamma analysis showed a passing rate of 93% for 5% dose and 2mm DTA scoring criteria. Both relative and absolute dose profiles are in good agreement, except in the peripheral beamlets where the gel measured slightly higher dose, possibly because of the changing head scatter conditions that the RTP is not fully accounting for. Our results have also been benchmarked against ionization chamber measurements. Conclusion: We have investigated the use of a polymer gel for the 3D dosimetric characterization and evaluation of GRID therapy. Our results demonstrated that the planning system can predict fairly accurately the dose distribution for GRID type therapy.« less

The GIS weasel - An interface for the development of spatial information in modeling

USGS Publications Warehouse

Viger, R.J.; Markstrom, S.M.; Leavesley, G.H.; ,

2005-01-01

The GIS Weasel is a map and Graphical User Interface (GUI) driven tool that has been developed as an aid to modelers in the delineation, characterization of geographic features, and their parameterization for use in distributed or lumped parameter physical process models. The interface does not require user expertise in geographic information systems (GIS). The user does need knowledge of how the model will use the output from the GIS Weasel. The GIS Weasel uses Workstation ArcInfo and its the Grid extension. The GIS Weasel will run on all platforms that Workstation ArcInfo runs (i.e. numerous flavors of Unix and Microsoft Windows).The GIS Weasel requires an input ArcInfo grid of some topographical description of the Area of Interest (AOI). This is normally a digital elevation model, but can be the surface of a ground water table or any other data that flow direction can be resolved from. The user may define the AOI as a custom drainage area based on an interactively specified watershed outlet point, or use a previously created map. The user is then able to use any combination of the GIS Weasel's tool set to create one or more maps for depicting different kinds of geographic features. Once the spatial feature maps have been prepared, then the GIS Weasel s many parameterization routines can be used to create descriptions of each element in each of the user s created maps. Over 200 parameterization routines currently exist, generating information about shape, area, and topological association with other features of the same or different maps, as well many types of information based on ancillary data layers such as soil and vegetation properties. These tools easily integrate other similarly formatted data sets.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.

Potential biases in evapotranspiration estimates from Earth system models due to spatial heterogeneity and lateral moisture redistribution

NASA Astrophysics Data System (ADS)

Rouholahnejad, E.; Kirchner, J. W.

2016-12-01

Evapotranspiration (ET) is a key process in land-climate interactions and affects the dynamics of the atmosphere at local and regional scales. In estimating ET, most earth system models average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). This spatial averaging could potentially bias ET estimates, due to the nonlinearities in the underlying relationships. In addition, most earth system models ignore lateral redistribution of water within and between grid cells, which could potentially alter both local and regional ET. Here we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged ET as seen from the atmosphere over heterogeneous landscapes. Using a Budyko framework to express ET as a function of P and PET, we quantify how sub-grid heterogeneity affects average ET at the scale of typical earth system model grid cells. We show that averaging over sub-grid heterogeneity in P and PET, as typical earth system models do, leads to overestimates of average ET. We use a similar approach to quantify how lateral redistribution of water could affect average ET, as seen from the atmosphere. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET, implying that models that neglect lateral moisture redistribution will underestimate average ET. In contrast, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. This approach yields a simple conceptual framework and mathematical expressions for determining whether, and how much, spatial heterogeneity and lateral redistribution can affect regional ET fluxes as seen from the atmosphere. This analysis provides the basis for quantifying heterogeneity and redistribution effects on ET at regional and continental scales, which will be the focus of future work.

Diviner lunar radiometer gridded brightness temperatures from geodesic binning of modeled fields of view

NASA Astrophysics Data System (ADS)

Sefton-Nash, E.; Williams, J.-P.; Greenhagen, B. T.; Aye, K.-M.; Paige, D. A.

2017-12-01

An approach is presented to efficiently produce high quality gridded data records from the large, global point-based dataset returned by the Diviner Lunar Radiometer Experiment aboard NASA's Lunar Reconnaissance Orbiter. The need to minimize data volume and processing time in production of science-ready map products is increasingly important with the growth in data volume of planetary datasets. Diviner makes on average >1400 observations per second of radiance that is reflected and emitted from the lunar surface, using 189 detectors divided into 9 spectral channels. Data management and processing bottlenecks are amplified by modeling every observation as a probability distribution function over the field of view, which can increase the required processing time by 2-3 orders of magnitude. Geometric corrections, such as projection of data points onto a digital elevation model, are numerically intensive and therefore it is desirable to perform them only once. Our approach reduces bottlenecks through parallel binning and efficient storage of a pre-processed database of observations. Database construction is via subdivision of a geodesic icosahedral grid, with a spatial resolution that can be tailored to suit the field of view of the observing instrument. Global geodesic grids with high spatial resolution are normally impractically memory intensive. We therefore demonstrate a minimum storage and highly parallel method to bin very large numbers of data points onto such a grid. A database of the pre-processed and binned points is then used for production of mapped data products that is significantly faster than if unprocessed points were used. We explore quality controls in the production of gridded data records by conditional interpolation, allowed only where data density is sufficient. The resultant effects on the spatial continuity and uncertainty in maps of lunar brightness temperatures is illustrated. We identify four binning regimes based on trades between the spatial resolution of the grid, the size of the FOV and the on-target spacing of observations. Our approach may be applicable and beneficial for many existing and future point-based planetary datasets.

A distributed air index based on maximum boundary rectangle over grid-cells for wireless non-flat spatial data broadcast.

PubMed

Im, Seokjin; Choi, JinTak

2014-06-17

In the pervasive computing environment using smart devices equipped with various sensors, a wireless data broadcasting system for spatial data items is a natural way to efficiently provide a location dependent information service, regardless of the number of clients. A non-flat wireless broadcast system can support the clients in accessing quickly their preferred data items by disseminating the preferred data items more frequently than regular data on the wireless channel. To efficiently support the processing of spatial window queries in a non-flat wireless data broadcasting system, we propose a distributed air index based on a maximum boundary rectangle (MaxBR) over grid-cells (abbreviated DAIM), which uses MaxBRs for filtering out hot data items on the wireless channel. Unlike the existing index that repeats regular data items in close proximity to hot items at same frequency as hot data items in a broadcast cycle, DAIM makes it possible to repeat only hot data items in a cycle and reduces the length of the broadcast cycle. Consequently, DAIM helps the clients access the desired items quickly, improves the access time, and reduces energy consumption. In addition, a MaxBR helps the clients decide whether they have to access regular data items or not. Simulation studies show the proposed DAIM outperforms existing schemes with respect to the access time and energy consumption.

Assessing species distribution using Google Street View: a pilot study with the Pine Processionary Moth.

PubMed

Rousselet, Jérôme; Imbert, Charles-Edouard; Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google Street View could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google Street View. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google Street View were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google Street View network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

PubMed Central

Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant. PMID:24130675

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

Compatible Spatial Discretizations for Partial Differential Equations

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

Arnold, Douglas, N, ed.

From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide varietymore » of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical simulations. + Identification and design of compatible spatial discretizations of PDEs, their classification, analysis, and relations. + Relationships between different compatible spatial discretization methods and concepts which have been developed; + Impact of compatible spatial discretizations upon physical fidelity, verification and validation of simulations, especially in large-scale, multiphysics settings. + How solvers address the demands placed upon them by compatible spatial discretizations. This report provides information about the program and abstracts of all the presentations.« less

Grid-cell representations in mental simulation

PubMed Central

Bellmund, Jacob LS; Deuker, Lorena; Navarro Schröder, Tobias; Doeller, Christian F

2016-01-01

Anticipating the future is a key motif of the brain, possibly supported by mental simulation of upcoming events. Rodent single-cell recordings suggest the ability of spatially tuned cells to represent subsequent locations. Grid-like representations have been observed in the human entorhinal cortex during virtual and imagined navigation. However, hitherto it remains unknown if grid-like representations contribute to mental simulation in the absence of imagined movement. Participants imagined directions between building locations in a large-scale virtual-reality city while undergoing fMRI without re-exposure to the environment. Using multi-voxel pattern analysis, we provide evidence for representations of absolute imagined direction at a resolution of 30° in the parahippocampal gyrus, consistent with the head-direction system. Furthermore, we capitalize on the six-fold rotational symmetry of grid-cell firing to demonstrate a 60° periodic pattern-similarity structure in the entorhinal cortex. Our findings imply a role of the entorhinal grid-system in mental simulation and future thinking beyond spatial navigation. DOI: http://dx.doi.org/10.7554/eLife.17089.001 PMID:27572056

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1995-01-01

The Spatial Data Transfer Standard (SOTS) is a mechanism for the transfer of spatial data between dissimilar computer systems. The SOTS specifies exchange constructs, addressing formats, structure, and content for spatially referenced vector and raster (including gridded) data. SOTS components are a conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

Operational forecasting with the subgrid technique on the Elbe Estuary

NASA Astrophysics Data System (ADS)

Sehili, Aissa

2017-04-01

Modern remote sensing technologies can deliver very detailed land surface height data that should be considered for more accurate simulations. In that case, and even if some compromise is made with regard to grid resolution of an unstructured grid, simulations still will require large grids which can be computationally very demanding. The subgrid technique, first published by Casulli (2009), is based on the idea of making use of the available detailed subgrid bathymetric information while performing computations on relatively coarse grids permitting large time steps. Consequently, accuracy and efficiency are drastically enhanced if compared to the classical linear method, where the underlying bathymetry is solely discretized by the computational grid. The algorithm guarantees rigorous mass conservation and nonnegative water depths for any time step size. Computational grid-cells are permitted to be wet, partially wet or dry and no drying threshold is needed. The subgrid technique is used in an operational forecast model for water level, current velocity, salinity and temperature of the Elbe estuary in Germany. Comparison is performed with the comparatively highly resolved classical unstructured grid model UnTRIM. The daily meteorological forcing data are delivered by the German Weather Service (DWD) using the ICON-EU model. Open boundary data are delivered by the coastal model BSHcmod of the German Federal Maritime and Hydrographic Agency (BSH). Comparison of predicted water levels between classical and subgrid model shows a very good agreement. The speedup in computational performance due to the use of the subgrid technique is about a factor of 20. A typical daily forecast can be carried out within less than 10 minutes on standard PC-like hardware. The model is capable of permanently delivering highly resolved temporal and spatial information on water level, current velocity, salinity and temperature for the whole estuary. The model offers also the possibility to recalculate any previous situation. This can be helpful to figure out for instance the context in which a certain event occurred like an accident. In addition to measurement, the model can be used to improve navigability by adjusting the tidal transit-schedule for container vessels that are depending on the tide to approach or leave the port of Hamburg.

SU-F-T-436: A Method to Evaluate Dosimetric Properties of SFGRT in Eclipse TPS

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

Xu, M; Tobias, R; Pankuch, M

Purpose: The objective was to develop a method for dose distribution calculation of spatially-fractionated-GRID-radiotherapy (SFGRT) in Eclipse treatment-planning-system (TPS). Methods: Patient treatment-plans with SFGRT for bulky tumors were generated in Varian Eclipse version11. A virtual structure based on the GRID pattern was created and registered to a patient CT image dataset. The virtual GRID structure was positioned on the iso-center level together with matching beam geometries to simulate a commercially available GRID block made of brass. This method overcame the difficulty in treatment-planning and dose-calculation due to the lack o-the option to insert a GRID block add-on in Eclipse TPS.more » The patient treatment-planning displayed GRID effects on the target, critical structures, and dose distribution. The dose calculations were compared to the measurement results in phantom. Results: The GRID block structure was created to follow the beam divergence to the patient CT images. The inserted virtual GRID block made it possible to calculate the dose distributions and profiles at various depths in Eclipse. The virtual GRID block was added as an option to TPS. The 3D representation of the isodose distribution of the spatially-fractionated beam was generated in axial, coronal, and sagittal planes. Physics of GRID can be different from that for fields shaped by regular blocks because the charge-particle-equilibrium cannot be guaranteed for small field openings. Output factor (OF) measurement was required to calculate the MU to deliver the prescribed dose. The calculated OF based on the virtual GRID agreed well with the measured OF in phantom. Conclusion: The method to create the virtual GRID block has been proposed for the first time in Eclipse TPS. The dosedistributions, in-plane and cross-plane profiles in PTV can be displayed in 3D-space. The calculated OF’s based on the virtual GRID model compare well to the measured OF’s for SFGRT clinical use.« less

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

2017-12-01

Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more meaningful information that can be used in decision-making and planning. Future extensions and applications of these tools in a climate context will be considered.

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.

An Extensible Information Grid for Risk Management

NASA Technical Reports Server (NTRS)

Maluf, David A.; Bell, David G.

2003-01-01

This paper describes recent work on developing an extensible information grid for risk management at NASA - a RISK INFORMATION GRID. This grid is being developed by integrating information grid technology with risk management processes for a variety of risk related applications. To date, RISK GRID applications are being developed for three main NASA processes: risk management - a closed-loop iterative process for explicit risk management, program/project management - a proactive process that includes risk management, and mishap management - a feedback loop for learning from historical risks that escaped other processes. This is enabled through an architecture involving an extensible database, structuring information with XML, schemaless mapping of XML, and secure server-mediated communication using standard protocols.

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_TRMM-PFM-VIRS_Beta4)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Thematic mapper-derived mineral distribution maps of Idaho, Nevada, and western Montana

USGS Publications Warehouse

Raines, Gary L.

2006-01-01

This report provides mineral distribution maps based on TM spectral information of minerals commonly associated with hydrothermal alteration in Nevada, Idaho, and western Montana. The product of the processing is provided as four ESRI GRID files with 30 m resolution by state. UTM Zone 11 projection is used for Nevada (grid clsnv) and western Idaho (grid clsid), UTM Zone 12 is used for eastern Idaho and western Montana (grid clsid_mt). A fourth grid with a special Albers projection is used for the Headwaters project covering Idaho and western Montana (grid crccls_hs). Symbolization for all four grids is stored in the ESRI layer or LYR files and color or CLR files. Objectives of the analyses were to cover a large area very quickly and to provide data that could be used at a scale of 1:100,000 or smaller. Thus, the image processing was standardized for speed while still achieving the desired 1:100,000-scale level of detail. Consequently, some subtle features of mineralogy may be missed. The hydrothermal alteration data were not field checked to separate mineral occurrences due to hydrothermal alteration from those due to other natural occurrences. The data were evaluated by overlaying the results with 1:100,000 scale topographic maps to confirm correlation with known mineralized areas. The data were also tested in the Battle Mountain area of north-central Nevada by a weights-of-evidence correlation analysis with metallic mineral sites from the USGS Mineral Resources Data System and were found to have significant spatial correlation. On the basis of on these analyses, the data are considered useful for regional studies at scales of 1:100,000.

Elimination of artificial grid distortion and hourglass-type motions by means of Lagrangian subzonal masses and pressures

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

Caramana, E.J.; Shashkov, M.J.

1997-12-31

The bane of Lagrangian hydrodynamics calculations is premature breakdown of the grid topology that results in severe degradation of accuracy and run termination often long before the assumption of Lagrangian zonal mass ceased to be valid. At short spatial grid scales this is usually referred to by the terms hourglass mode or keystone motion associated in particular with underconstrained grids such as quadrilaterals and hexahedrons in two and three dimensions, respectively. At longer spatial scales relative to the grid spacing there is what is referred to ubiquitously as spurious vorticity, or the long-thin zone problem. In both cases the resultmore » is anomalous grid distortion and tangling that has nothing to do with the actual solution, as would be the case for turbulent flow. In this work the authors show how such motions can be eliminated by the proper use of subzonal Lagrangian masses, and associated densities and pressures. These subzonal masses arise in a natural way from the fact that they require the mass associated with the nodal grid point to be constant in time. This is addition to the usual assumption of constant, Lagrangian zonal mass in staggered grid hydrodynamics scheme. The authors show that with proper discretization of subzonal forces resulting from subzonal pressures, hourglass motion and spurious vorticity can be eliminated for a very large range of problems. Finally the authors are presenting results of calculations of many test problems.« less

Dosimetric characteristics with spatial fractionation using electron grid therapy.

PubMed

Meigooni, A S; Parker, S A; Zheng, J; Kalbaugh, K J; Regine, W F; Mohiuddin, M

2002-01-01

Recently, promising clinical results have been shown in the delivery of palliative treatments using megavoltage photon grid therapy. However, the use of megavoltage photon grid therapy is limited in the treatment of bulky superficial lesions where critical radiosensitive anatomical structures are present beyond tumor volumes. As a result, spatially fractionated electron grid therapy was investigated in this project. Dose distributions of 1.4-cm-thick cerrobend grid blocks were experimentally determined for electron beams ranging from 6 to 20 MeV. These blocks were designed and fabricated at out institution to fit into a 20 x 20-cm(2) electron cone of a commercially available linear accelerator. Beam profiles and percentage depth dose (PDD) curves were measured in Solid Water phantom material using radiographic film, LiF TLD, and ionometric techniques. Open-field PDD curves were compared with those of single holes grid with diameters of 1.5, 2.0, 2.5, 3.0, and 3.5 cm to find the optimum diameter. A 2.5-cm hole diameter was found to be the optimal size for all electron energies between 6 and 20 MeV. The results indicate peak-to-valley ratios decrease with depth and the largest ratio is found at Dmax. Also, the TLD measurements show that the dose under the blocked regions of the grid ranged from 9.7% to 39% of the dose beneath the grid holes, depending on the measurement location and beam energy.

Uncertainty in gridded CO 2 emissions estimates

DOE PAGES

Hogue, Susannah; Marland, Eric; Andres, Robert J.; ...

2016-05-19

We are interested in the spatial distribution of fossil-fuel-related emissions of CO 2 for both geochemical and geopolitical reasons, but it is important to understand the uncertainty that exists in spatially explicit emissions estimates. Working from one of the widely used gridded data sets of CO 2 emissions, we examine the elements of uncertainty, focusing on gridded data for the United States at the scale of 1° latitude by 1° longitude. Uncertainty is introduced in the magnitude of total United States emissions, the magnitude and location of large point sources, the magnitude and distribution of non-point sources, and from themore » use of proxy data to characterize emissions. For the United States, we develop estimates of the contribution of each component of uncertainty. At 1° resolution, in most grid cells, the largest contribution to uncertainty comes from how well the distribution of the proxy (in this case population density) represents the distribution of emissions. In other grid cells, the magnitude and location of large point sources make the major contribution to uncertainty. Uncertainty in population density can be important where a large gradient in population density occurs near a grid cell boundary. Uncertainty is strongly scale-dependent with uncertainty increasing as grid size decreases. In conclusion, uncertainty for our data set with 1° grid cells for the United States is typically on the order of ±150%, but this is perhaps not excessive in a data set where emissions per grid cell vary over 8 orders of magnitude.« less

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.

Soil Sampling Techniques For Alabama Grain Fields

NASA Technical Reports Server (NTRS)

Thompson, A. N.; Shaw, J. N.; Mask, P. L.; Touchton, J. T.; Rickman, D.

2003-01-01

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Lighting the World: the first application of an open source, spatial electrification tool (OnSSET) on Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Mentis, Dimitrios; Howells, Mark; Rogner, Holger; Korkovelos, Alexandros; Arderne, Christopher; Zepeda, Eduardo; Siyal, Shahid; Taliotis, Costantinos; Bazilian, Morgan; de Roo, Ad; Tanvez, Yann; Oudalov, Alexandre; Scholtz, Ernst

2017-08-01

In September 2015, the United Nations General Assembly adopted Agenda 2030, which comprises a set of 17 Sustainable Development Goals (SDGs) defined by 169 targets. ‘Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030’ is the seventh goal (SDG7). While access to energy refers to more than electricity, the latter is the central focus of this work. According to the World Bank’s 2015 Global Tracking Framework, roughly 15% of the world’s population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity services. The majority of those without access (87%) reside in rural areas. This paper presents results of a geographic information systems approach coupled with open access data. We present least-cost electrification strategies on a country-by-country basis for Sub-Saharan Africa. The electrification options include grid extension, mini-grid and stand-alone systems for rural, peri-urban, and urban contexts across the economy. At low levels of electricity demand there is a strong penetration of standalone technologies. However, higher electricity demand levels move the favourable electrification option from stand-alone systems to mini grid and to grid extensions.

A mimetic, semi-implicit, forward-in-time, finite volume shallow water model: comparison of hexagonal-icosahedral and cubed sphere grids

NASA Astrophysics Data System (ADS)

Thuburn, J.; Cotter, C. J.; Dubos, T.

2013-12-01

A new algorithm is presented for the solution of the shallow water equations on quasi-uniform spherical grids. It combines a mimetic finite volume spatial discretization with a Crank-Nicolson time discretization of fast waves and an accurate and conservative forward-in-time advection scheme for mass and potential vorticity (PV). The algorithm is implemented and tested on two families of grids: hexagonal-icosahedral Voronoi grids, and modified equiangular cubed-sphere grids. Results of a variety of tests are presented, including convergence of the discrete scalar Laplacian and Coriolis operators, advection, solid body rotation, flow over an isolated mountain, and a barotropically unstable jet. The results confirm a number of desirable properties for which the scheme was designed: exact mass conservation, very good available energy and potential enstrophy conservation, consistent mass, PV and tracer transport, and good preservation of balance including vanishing ∇ × ∇, steady geostrophic modes, and accurate PV advection. The scheme is stable for large wave Courant numbers and advective Courant numbers up to about 1. In the most idealized tests the overall accuracy of the scheme appears to be limited by the accuracy of the Coriolis and other mimetic spatial operators, particularly on the cubed sphere grid. On the hexagonal grid there is no evidence for damaging effects of computational Rossby modes, despite attempts to force them explicitly.

A mimetic, semi-implicit, forward-in-time, finite volume shallow water model: comparison of hexagonal-icosahedral and cubed-sphere grids

NASA Astrophysics Data System (ADS)

Thuburn, J.; Cotter, C. J.; Dubos, T.

2014-05-01

A new algorithm is presented for the solution of the shallow water equations on quasi-uniform spherical grids. It combines a mimetic finite volume spatial discretization with a Crank-Nicolson time discretization of fast waves and an accurate and conservative forward-in-time advection scheme for mass and potential vorticity (PV). The algorithm is implemented and tested on two families of grids: hexagonal-icosahedral Voronoi grids, and modified equiangular cubed-sphere grids. Results of a variety of tests are presented, including convergence of the discrete scalar Laplacian and Coriolis operators, advection, solid body rotation, flow over an isolated mountain, and a barotropically unstable jet. The results confirm a number of desirable properties for which the scheme was designed: exact mass conservation, very good available energy and potential enstrophy conservation, consistent mass, PV and tracer transport, and good preservation of balance including vanishing ∇ × ∇, steady geostrophic modes, and accurate PV advection. The scheme is stable for large wave Courant numbers and advective Courant numbers up to about 1. In the most idealized tests the overall accuracy of the scheme appears to be limited by the accuracy of the Coriolis and other mimetic spatial operators, particularly on the cubed-sphere grid. On the hexagonal grid there is no evidence for damaging effects of computational Rossby modes, despite attempts to force them explicitly.

USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

EPA Science Inventory

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

Constraining earthquake source inversions with GPS data: 1. Resolution-based removal of artifacts

USGS Publications Warehouse

Page, M.T.; Custodio, S.; Archuleta, R.J.; Carlson, J.M.

2009-01-01

We present a resolution analysis of an inversion of GPS data from the 2004 Mw 6.0 Parkfield earthquake. This earthquake was recorded at thirteen 1-Hz GPS receivers, which provides for a truly coseismic data set that can be used to infer the static slip field. We find that the resolution of our inverted slip model is poor at depth and near the edges of the modeled fault plane that are far from GPS receivers. The spatial heterogeneity of the model resolution in the static field inversion leads to artifacts in poorly resolved areas of the fault plane. These artifacts look qualitatively similar to asperities commonly seen in the final slip models of earthquake source inversions, but in this inversion they are caused by a surplus of free parameters. The location of the artifacts depends on the station geometry and the assumed velocity structure. We demonstrate that a nonuniform gridding of model parameters on the fault can remove these artifacts from the inversion. We generate a nonuniform grid with a grid spacing that matches the local resolution length on the fault and show that it outperforms uniform grids, which either generate spurious structure in poorly resolved regions or lose recoverable information in well-resolved areas of the fault. In a synthetic test, the nonuniform grid correctly averages slip in poorly resolved areas of the fault while recovering small-scale structure near the surface. Finally, we present an inversion of the Parkfield GPS data set on the nonuniform grid and analyze the errors in the final model. Copyright 2009 by the American Geophysical Union.

Emergence of multicellular organisms with dynamic differentiation and spatial pattern.

PubMed

Furusawa, C; Kaneko, K

1998-01-01

The origin of multicellular organisms and the mechanism of development in cell societies are studied by choosing a model with intracellular biochemical dynamics allowing for oscillations, cell-cell interaction through diffusive chemicals on a two-dimensional grid, and state-dependent cell adhesion. Cells differentiate due to a dynamical instability, as described by our "isologous diversification" theory. A fixed spatial pattern of differentiated cells emerges, where spatial information is sustained by cell-cell interactions. This pattern is robust against perturbations. With an adequate cell adhesion force, active cells are release that form the seed of a new generation of multicellular organisms, accompanied by death of the original multicellular unit as a halting state. It is shown that the emergence of multicellular organisms with differentiation, regulation, and life cycle is not an accidental event, but a natural consequence in a system of replicating cells with growth.

A new method for estimating carbon dioxide emissions from transportation at fine spatial scales

PubMed Central

Shu, Yuqin; Reams, Margaret

2016-01-01

Detailed estimates of carbon dioxide (CO2) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO2 emission estimates from the county-level scale to a 1 km2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO2 emission values by county (i.e. parish) for the state of Louisiana into 1 km2 grids. The results reveal a more realistic spatial pattern of CO2 emission from transportation, which can be used to identify the emission ‘hot spots’. Of the four highest transportation-related CO2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches. PMID:26997973

Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation

NASA Astrophysics Data System (ADS)

Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.

2017-12-01

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.

A perspective on unstructured grid flow solvers

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.

1995-01-01

This survey paper assesses the status of compressible Euler and Navier-Stokes solvers on unstructured grids. Different spatial and temporal discretization options for steady and unsteady flows are discussed. The integration of these components into an overall framework to solve practical problems is addressed. Issues such as grid adaptation, higher order methods, hybrid discretizations and parallel computing are briefly discussed. Finally, some outstanding issues and future research directions are presented.

Importance of Grid Center Arrangement

NASA Astrophysics Data System (ADS)

Pasaogullari, O.; Usul, N.

2012-12-01

In Digital Elevation Modeling, grid size is accepted to be the most important parameter. Despite the point density and/or scale of the source data, it is freely decided by the user. Most of the time, arrangement of the grid centers are ignored, even most GIS packages omit the choice of grid center coordinate selection. In our study; importance of the arrangement of grid centers is investigated. Using the analogy between "Raster Grid DEM" and "Bitmap Image", importance of placement of grid centers in DEMs are measured. The study has been conducted on four different grid DEMs obtained from a half ellipsoid. These grid DEMs are obtained in such a way that they are half grid size apart from each other. Resulting grid DEMs are investigated through similarity measures. Image processing scientists use different measures to investigate the dis/similarity between the images and the amount of different information they carry. Grid DEMs are projected to a finer grid in order to co-center. Similarity measures are then applied to each grid DEM pairs. These similarity measures are adapted to DEM with band reduction and real number operation. One of the measures gives function graph and the others give measure matrices. Application of similarity measures to six grid DEM pairs shows interesting results. These four different grid DEMs are created with the same method for the same area, surprisingly; thirteen out of 14 measures state that, the half grid size apart grid DEMs are different from each other. The results indicated that although grid DEMs carry mutual information, they have also additional individual information. In other words, half grid size apart constructed grid DEMs have non-redundant information.; Joint Probability Distributions Function Graphs

A single-cell spiking model for the origin of grid-cell patterns

PubMed Central

Kempter, Richard

2017-01-01

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity. PMID:28968386

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

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".

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

Improving a spatial rainfall product using multiple-point geostatistical simulations and its effect on a national hydrological model.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.

2016-12-01

Rainfall amount is one of the most sensitive inputs to distributed hydrological models. Its spatial representation is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the 10-km-grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network in recent years (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. Consequently, the related hydrological model shows a significantly lower prediction power. To give a better estimation of spatial rainfall at the grid points far from ground measurements, we use the direct sampling technique (DS) [1], belonging to the family of multiple-point geostatistics. DS, already applied to rainfall and spatial variable estimation [2, 3], simulates a grid value by sampling a training data set where a similar data neighborhood occurs. In this way, complex statistical relations are preserved by generating similar spatial patterns to the ones found in the training data set. Using the reliable grid product from the period 1996-2006 as training data set, we first test the technique by simulating part of this data set, then we apply the technique to the grid product of the period 2007-2014, and subsequently analyzing the uncertainty propagation to the hydrological model. We show that DS can improve the reliability of the rainfall product by generating more realistic rainfall patterns, with a significant repercussion on the hydrological model. The reduction of rain gauge networks is a global phenomenon which has huge implications for hydrological model performance and the uncertainty assessment of water resources. Therefore, the presented methodology can potentially be used in many regions where historical records can act as training data. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014. [3] G. Mariethoz et al. (2012), Water Resour. Res., 10.1029/2012WR012115.

A map of abstract relational knowledge in the human hippocampal–entorhinal cortex

PubMed Central

Garvert, Mona M; Dolan, Raymond J; Behrens, Timothy EJ

2017-01-01

The hippocampal–entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal–entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal–entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns. DOI: http://dx.doi.org/10.7554/eLife.17086.001 PMID:28448253

Potential roles of cholinergic modulation in the neural coding of location and movement speed

PubMed Central

Dannenberg, Holger; Hinman, James R.; Hasselmo, Michael E.

2016-01-01

Behavioral data suggest that cholinergic modulation may play a role in certain aspects of spatial memory, and neurophysiological data demonstrate neurons that fire in response to spatial dimensions, including grid cells and place cells that respond on the basis of location and running speed. These neurons show firing responses that depend upon the visual configuration of the environment, due to coding in visually-responsive regions of the neocortex. This review focuses on the physiological effects of acetylcholine that may influence the sensory coding of spatial dimensions relevant to behavior. In particular, the local circuit effects of acetylcholine within the cortex regulate the influence of sensory input relative to internal memory representations, via presynaptic inhibition of excitatory and inhibitory synaptic transmission, and the modulation of intrinsic currents in cortical excitatory and inhibitory neurons. In addition, circuit effects of acetylcholine regulate the dynamics of cortical circuits including oscillations at theta and gamma frequencies. These effects of acetylcholine on local circuits and network dynamics could underlie the role of acetylcholine in coding of spatial information for the performance of spatial memory tasks. PMID:27677935

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

NASA Technical Reports Server (NTRS)

Chang, Jinfeng; Ciais, Philippe; Herrero, Mario; Havlik, Petr; Campioli, Matteo; Zhang, Xianzhou; Bai, Yongfei; Viovy, Nicolas; Joiner, Joanna; Wang, Xuhui;

Observations and Modelling of Winds and Waves during the Surface Wave Dynamics Experiment. Report 1. Intensive Observation Period IOP-1, 20-31 October 1990

DTIC Science & Technology

1993-04-01

wave buoy provided by SEATEX, Norway (Figure 3). The modified Mills-cross array was designed to provide spatial estimates of the variation in wave, wind... designed for SWADE to examine the wave physics at different spatial and temporal scales, and the usefulness of a nested system. Each grid is supposed to...field specification. SWADE Model This high-resolution grid was designed to simulate the small scale wave physics and to improve and verify the source

Global Population Distribution (1990),Terrestrial Area and Country Name Information on a One by One Degree Grid Cell Basis

DOE Data Explorer

Li, Yi-Fan [Canadian Global Emissions Inventory Centre, Downsview, Ontario (Canada); Brenkert, A. L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

1996-01-01

This data base contains gridded (one degree by one degree) information on the world-wide distribution of the population for 1990 and country-specific information on the percentage of the country's population present in each grid cell (Li, 1996a). Secondly, the data base contains the percentage of a country's total area in a grid cell and the country's percentage of the grid cell that is terrestrial (Li, 1996b). Li (1996b) also developed an indicator signifying how many countries are represented in a grid cell and if a grid cell is part of the sea; this indicator is only relevant for the land, countries, and sea-partitioning information of the grid cell. Thirdly, the data base includes the latitude and longitude coordinates of each grid cell; a grid code number, which is a translation of the latitude/longitude value and is used in the Global Emission Inventory Activity (GEIA) data bases; the country or region's name; and the United Nations three-digit country code that represents that name.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

Voxel inversion of airborne electromagnetic data

NASA Astrophysics Data System (ADS)

Auken, E.; Fiandaca, G.; Kirkegaard, C.; Vest Christiansen, A.

2013-12-01

Inversion of electromagnetic data usually refers to a model space being linked to the actual observation points, and for airborne surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space. This means that incorporating the geophysical data into the geological and/or hydrological modelling grids involves a spatial relocation of the models, which in itself is a subtle process where valuable information is easily lost. Also the integration of prior information, e.g. from boreholes, is difficult when the observation points do not coincide with the position of the prior information, as well as the joint inversion of airborne and ground-based surveys. We developed a geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models, for easier incorporation of prior information and for straightforward integration of different data types in joint inversion. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the properties is computed everywhere by means of an interpolation function f (e.g. inverse distance or kriging). The position of the nodes is fixed during the inversion and is chosen to sample the soil taking into account topography and inversion resolution. Given this definition of the voxel model space, both 1D and 2D/3D forward responses can be computed. The 1D forward responses are computed as follows: A) a 1D model subdivision, in terms of model thicknesses and direction of the "virtual" horizontal stratification, is defined for each 1D data set. For EM soundings the "virtual" horizontal stratification is set up parallel to the topography at the sounding position. B) the "virtual" 1D models are constructed by interpolating the soil properties in the medium point of the "virtual" layers. For 2D/3D forward responses the algorithm operates similarly, simply filling the 2D/3D meshes of the forward responses by computing the interpolation values in the centres of the mesh cells. The new definition of the voxel model space allows for incorporating straightforwardly the geophysical information into geological and/or hydrological models, just by using for defining the geophysical model space a voxel (hydro)geological grid. This simplify also the propagation of the uncertainty of geophysical parameters into the (hydro)geological models. Furthermore, prior information from boreholes, like resistivity logs, can be applied directly to the voxel model space, even if the borehole positions do not coincide with the actual observation points. In fact, the prior information is constrained to the model parameters through the interpolation function at the borehole locations. The presented algorithm is a further development of the AarhusInv program package developed at Aarhus University (formerly em1dinv), which manages both large scale AEM surveys and ground-based data. This work has been carried out as part of the HyGEM project, supported by the Danish Council of Strategic Research under grant number DSF 11-116763.

Numerical solution of the full potential equation using a chimera grid approach

NASA Technical Reports Server (NTRS)

Holst, Terry L.

1995-01-01

A numerical scheme utilizing a chimera zonal grid approach for solving the full potential equation in two spatial dimensions is described. Within each grid zone a fully-implicit approximate factorization scheme is used to advance the solution one interaction. This is followed by the explicit advance of all common zonal grid boundaries using a bilinear interpolation of the velocity potential. The presentation is highlighted with numerical results simulating the flow about a two-dimensional, nonlifting, circular cylinder. For this problem, the flow domain is divided into two parts: an inner portion covered by a polar grid and an outer portion covered by a Cartesian grid. Both incompressible and compressible (transonic) flow solutions are included. Comparisons made with an analytic solution as well as single grid results indicate that the chimera zonal grid approach is a viable technique for solving the full potential equation.

Smart Grid Information Clearinghouse (SGIC)

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

Rahman, Saifur

Since the Energy Independence and Security Act of 2007 was enacted, there has been a large number of websites that discusses smart grid and relevant information, including those from government, academia, industry, private sector and regulatory. These websites collect information independently. Therefore, smart grid information was quite scattered and dispersed. The objective of this work was to develop, populate, manage and maintain the public Smart Grid Information Clearinghouse (SGIC) web portal. The information in the SGIC website is comprehensive that includes smart grid information, research & development, demonstration projects, technical standards, costs & benefit analyses, business cases, legislation, policy &more » regulation, and other information on lesson learned and best practices. The content in the SGIC website is logically grouped to allow easily browse, search and sort. In addition to providing the browse and search feature, the SGIC web portal also allow users to share their smart grid information with others though our online content submission platform. The Clearinghouse web portal, therefore, serves as the first stop shop for smart grid information that collects smart grid information in a non-bias, non-promotional manner and can provide a missing link from information sources to end users and better serve users’ needs. The web portal is available at www.sgiclearinghouse.org. This report summarizes the work performed during the course of the project (September 2009 – August 2014). Section 2.0 lists SGIC Advisory Committee and User Group members. Section 3.0 discusses SGIC information architecture and web-based database application functionalities. Section 4.0 summarizes SGIC features and functionalities, including its search, browse and sort capabilities, web portal social networking, online content submission platform and security measures implemented. Section 5.0 discusses SGIC web portal contents, including smart grid 101, smart grid projects, deployment experience (i.e., use cases, lessons learned, cost-benefit analyses and business cases), in-depth information (i.e., standards, technology, cyber security, legislation, education and training and demand response), as well as international information. Section 6.0 summarizes SGIC statistics from the launch of the portal on July 07, 2010 to August 31, 2014. Section 7.0 summarizes publicly available information as a result of this work.« less

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

Maasakkers, Joannes D.; Jacob, Daniel J.; Sulprizio, Melissa P.

Here we present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scaledependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show largemore » differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Finally, our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.« less

From grid cells to place cells with realistic field sizes

PubMed Central

2017-01-01

While grid cells in the medial entorhinal cortex (MEC) of rodents have multiple, regularly arranged firing fields, place cells in the cornu ammonis (CA) regions of the hippocampus mostly have single spatial firing fields. Since there are extensive projections from MEC to the CA regions, many models have suggested that a feedforward network can transform grid cell firing into robust place cell firing. However, these models generate place fields that are consistently too small compared to those recorded in experiments. Here, we argue that it is implausible that grid cell activity alone can be transformed into place cells with robust place fields of realistic size in a feedforward network. We propose two solutions to this problem. Firstly, weakly spatially modulated cells, which are abundant throughout EC, provide input to downstream place cells along with grid cells. This simple model reproduces many place cell characteristics as well as results from lesion studies. Secondly, the recurrent connections between place cells in the CA3 network generate robust and realistic place fields. Both mechanisms could work in parallel in the hippocampal formation and this redundancy might account for the robustness of place cell responses to a range of disruptions of the hippocampal circuitry. PMID:28750005

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

Developing and Delivering National-Scale Gridded Phenology Data Products

NASA Astrophysics Data System (ADS)

Marsh, L.; Crimmins, M.; Crimmins, T. M.; Gerst, K.; Rosemartin, A.; Switzer, J.; Weltzin, J. F.

2016-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is now producing and freely delivering daily maps and short-term forecasts of accumulated growing degree days and spring onset dates (based on the Extended Spring Indices) at fine spatial scale for the conterminous United States. These data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. Accumulated growing degree day (AGDD) maps were selected because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening and migration. The Extended Spring Indices (SI-x) are based on predictive climate models for lilac and honeysuckle leaf and bloom; they have been widely used to summarize changes in the timing of spring onset. The SI-x is used as a national indicator of climate change impacts by the US Global Change Research Program and the Environmental Protection Agency. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. To best serve various audiences, the AGDD and SI-x gridded maps are available in various formats through a range of access tools, including the USA-NPN online visualization tool as well as industry standards compliant web services. We plan to expand the suite of gridded map products offered by the USA-NPN to include predictive maps of phenological transitions for additional plant and animal species at fine spatial and temporal resolution in the near future. USA-NPN invites you to use freely available daily and short-term forecast maps of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States.

Assessing and mapping spatial associations among oral cancer mortality rates, concentrations of heavy metals in soil, and land use types based on multiple scale data.

PubMed

Lin, Wei-Chih; Lin, Yu-Pin; Wang, Yung-Chieh; Chang, Tsun-Kuo; Chiang, Li-Chi

2014-02-21

In this study, a deconvolution procedure was used to create a variogram of oral cancer (OC) rates. Based on the variogram, area-to-point (ATP) Poisson kriging and p-field simulation were used to downscale and simulate, respectively, the OC rate data for Taiwan from the district scale to a 1 km × 1 km grid scale. Local cluster analysis (LCA) of OC mortality rates was then performed to identify OC mortality rate hot spots based on the downscaled and the p-field-simulated OC mortality maps. The relationship between OC mortality and land use was studied by overlapping the maps of the downscaled OC mortality, the LCA results, and the land uses. One thousand simulations were performed to quantify local and spatial uncertainties in the LCA to identify OC mortality hot spots. The scatter plots and Spearman's rank correlation yielded the relationship between OC mortality and concentrations of the seven metals in the 1 km cell grid. The correlation analysis results for the 1 km scale revealed a weak correlation between OC mortality rate and concentrations of the seven studied heavy metals in soil. Accordingly, the heavy metal concentrations in soil are not major determinants of OC mortality rates at the 1 km scale at which soils were sampled. The LCA statistical results for local indicator of spatial association (LISA) revealed that the sites with high probability of high-high (high value surrounded by high values) OC mortality at the 1 km grid scale were clustered in southern, eastern, and mid-western Taiwan. The number of such sites was also significantly higher on agricultural land and in urban regions than on land with other uses. The proposed approach can be used to downscale and evaluate uncertainty in mortality data from a coarse scale to a fine scale at which useful additional information can be obtained for assessing and managing land use and risk.

An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

NASA Astrophysics Data System (ADS)

Zhou, Chaojie; Ding, Xiaohua; Zhang, Jie; Yang, Jungang; Ma, Qiang

2017-12-01

While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.

A Methodological Inter-Comparison of Gridded Meteorological Products

NASA Astrophysics Data System (ADS)

Newman, A. J.; Clark, M. P.; Longman, R. J.; Giambelluca, T. W.; Arnold, J.

2017-12-01

Here we present a gridded meteorology inter-comparison using the state of Hawaíi as a testbed. This inter-comparison is motivated by two general goals: 1) the broad user community of gridded observation based meteorological fields should be aware of inter-product differences and the reasons they exist, which allows users to make informed choices on product selection to best meet their specific application(s); 2) we want to demonstrate the utility of inter-comparisons to meet the first goal, yet highlight that they are limited to mostly generic statements regarding attribution of differences that limits our understanding of these complex algorithms and obscures future research directions. Hawaíi is a useful testbed because it is a meteorologically complex region with well-known spatial features that are tied to specific physical processes (e.g. the trade wind inversion). From a practical standpoint, there are now several monthly climatological and daily precipitation and temperature datasets available that are being used for impact modeling. General conclusions that have emerged are: 1) differences in input station data significantly influence product differences; 2) prediction of precipitation occurrence is crucial across multiple metrics; 3) derived temperature statistics (e.g. diurnal temperature range) may have large spatial differences across products; and 4) attribution of differences to methodological choices is difficult and may limit the outcomes of these inter-comparisons, particularly from a development viewpoint. Thus, we want to continue to move the community towards frameworks that allow for multiple options throughout the product generation chain and allow for more systematic testing.

Image interpolation and denoising for division of focal plane sensors using Gaussian processes.

PubMed

Gilboa, Elad; Cunningham, John P; Nehorai, Arye; Gruev, Viktor

2014-06-16

Image interpolation and denoising are important techniques in image processing. These methods are inherent to digital image acquisition as most digital cameras are composed of a 2D grid of heterogeneous imaging sensors. Current polarization imaging employ four different pixelated polarization filters, commonly referred to as division of focal plane polarization sensors. The sensors capture only partial information of the true scene, leading to a loss of spatial resolution as well as inaccuracy of the captured polarization information. Interpolation is a standard technique to recover the missing information and increase the accuracy of the captured polarization information. Here we focus specifically on Gaussian process regression as a way to perform a statistical image interpolation, where estimates of sensor noise are used to improve the accuracy of the estimated pixel information. We further exploit the inherent grid structure of this data to create a fast exact algorithm that operates in ����(N(3/2)) (vs. the naive ���� (N³)), thus making the Gaussian process method computationally tractable for image data. This modeling advance and the enabling computational advance combine to produce significant improvements over previously published interpolation methods for polarimeters, which is most pronounced in cases of low signal-to-noise ratio (SNR). We provide the comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter.

Urban nuisance flooding and topographic wetness index: does excess runoff collect where we think it should in urban landscapes?

NASA Astrophysics Data System (ADS)

Kelleher, C.; McPhillips, L. E.

2017-12-01

Urban landscapes translate water in a variety of ways that diverge from more natural systems. In particular, due to the presence of impervious surfaces and alteration of topography, they are prone to nuisance flooding when it rains. To track the locations of areas of minor flooding and other complaints, many cities are now facilitating nuisance reports from residents via information technology services like 311. These reports provide useful information for tracking where in the landscape water may collect during rain events; we sought to use this information to test potential geospatial indices for predictively identifying locations prone to nuisance flooding in urban areas. In this study, we utilized a tool commonly applied in natural systems, topographic indices, to create spatially contiguous estimates of topographic wetness index (TWI), a value that can be used to identify areas within a watershed expected to be preferentially wetter or drier based on topographic slope and surface flow pathways. For several watersheds across Baltimore and New York City (USA), we tested three different resolutions of LiDAR-derived topography and two different methods of flow routing to calculate continuous distributions of TWI. When comparing these values to nuisance flooding locations, we found that distributions of TWI values within a radius of reported nuisance floods were higher, on average, than the distribution of TWI values across each watershed. We also employed a spatial Monte Carlo sampling strategy, randomly selecting grid cells within each watershed to determine if these randomly selected grid cells have preferentially lower TWI values than those near nuisance flooding locations. Overall, we demonstrate that topographic indices may be useful predictors of localized flooding within urban environments.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

Integrating TITAN2D Geophysical Mass Flow Model with GIS

NASA Astrophysics Data System (ADS)

Namikawa, L. M.; Renschler, C.

2005-12-01

TITAN2D simulates geophysical mass flows over natural terrain using depth-averaged granular flow models and requires spatially distributed parameter values to solve differential equations. Since a Geographical Information System (GIS) main task is integration and manipulation of data covering a geographic region, the use of a GIS for implementation of simulation of complex, physically-based models such as TITAN2D seems a natural choice. However, simulation of geophysical flows requires computationally intensive operations that need unique optimizations, such as adaptative grids and parallel processing. Thus GIS developed for general use cannot provide an effective environment for complex simulations and the solution is to develop a linkage between GIS and simulation model. The present work presents the solution used for TITAN2D where data structure of a GIS is accessed by simulation code through an Application Program Interface (API). GRASS is an open source GIS with published data formats thus GRASS data structure was selected. TITAN2D requires elevation, slope, curvature, and base material information at every cell to be computed. Results from simulation are visualized by a system developed to handle the large amount of output data and to support a realistic dynamic 3-D display of flow dynamics, which requires elevation and texture, usually from a remote sensor image. Data required by simulation is in raster format, using regular rectangular grids. GRASS format for regular grids is based on data file (binary file storing data either uncompressed or compressed by grid row), header file (text file, with information about georeferencing, data extents, and grid cell resolution), and support files (text files, with information about color table and categories names). The implemented API provides access to original data (elevation, base material, and texture from imagery) and slope and curvature derived from elevation data. From several existing methods to estimate slope and curvature from elevation, the selected one is based on estimation by a third-order finite difference method, which has shown to perform better or with minimal difference when compared to more computationally expensive methods. Derivatives are estimated using weighted sum of 8 grid neighbor values. The method was implemented and simulation results compared to derivatives estimated by a simplified version of the method (uses only 4 neighbor cells) and proven to perform better. TITAN2D uses an adaptative mesh grid, where resolution (grid cell size) is not constant, and visualization tools also uses texture with varying resolutions for efficient display. The API supports different resolutions applying bilinear interpolation when elevation, slope and curvature are required at a resolution higher (smaller cell size) than the original and using a nearest cell approach for elevations with lower resolution (larger) than the original. For material information nearest neighbor method is used since interpolation on categorical data has no meaning. Low fidelity characteristic of visualization allows use of nearest neighbor method for texture. Bilinear interpolation estimates the value at a point as the distance-weighted average of values at the closest four cell centers, and interpolation performance is just slightly inferior compared to more computationally expensive methods such as bicubic interpolation and kriging.

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-10-01

In this article we propose two grid generation methods for global ocean general circulation models. Contrary to conventional dipolar or tripolar grids, the proposed methods are based on Schwarz-Christoffel conformal mappings that map areas with user-prescribed, irregular boundaries to those with regular boundaries (i.e., disks, slits, etc.). The first method aims at improving existing dipolar grids. Compared with existing grids, the sample grid achieves a better trade-off between the enlargement of the latitudinal-longitudinal portion and the overall smooth grid cell size transition. The second method addresses more modern and advanced grid design requirements arising from high-resolution and multi-scale ocean modeling. The generated grids could potentially achieve the alignment of grid lines to the large-scale coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the grids are orthogonal curvilinear, they can be easily utilized by the majority of ocean general circulation models that are based on finite difference and require grid orthogonality. The proposed grid generation algorithms can also be applied to the grid generation for regional ocean modeling where complex land-sea distribution is present.

Space in the brain: how the hippocampal formation supports spatial cognition

PubMed Central

Hartley, Tom; Lever, Colin; Burgess, Neil; O'Keefe, John

2014-01-01

Over the past four decades, research has revealed that cells in the hippocampal formation provide an exquisitely detailed representation of an animal's current location and heading. These findings have provided the foundations for a growing understanding of the mechanisms of spatial cognition in mammals, including humans. We describe the key properties of the major categories of spatial cells: place cells, head direction cells, grid cells and boundary cells, each of which has a characteristic firing pattern that encodes spatial parameters relating to the animal's current position and orientation. These properties also include the theta oscillation, which appears to play a functional role in the representation and processing of spatial information. Reviewing recent work, we identify some themes of current research and introduce approaches to computational modelling that have helped to bridge the different levels of description at which these mechanisms have been investigated. These range from the level of molecular biology and genetics to the behaviour and brain activity of entire organisms. We argue that the neuroscience of spatial cognition is emerging as an exceptionally integrative field which provides an ideal test-bed for theories linking neural coding, learning, memory and cognition. PMID:24366125

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Section 4. The GIS Weasel User's Manual

USGS Publications Warehouse

Viger, Roland J.; Leavesley, George H.

2007-01-01

INTRODUCTION The GIS Weasel was designed to aid in the preparation of spatial information for input to lumped and distributed parameter hydrologic or other environmental models. The GIS Weasel provides geographic information system (GIS) tools to help create maps of geographic features relevant to a user's model and to generate parameters from those maps. The operation of the GIS Weasel does not require the user to be a GIS expert, only that the user have an understanding of the spatial information requirements of the environmental simulation model being used. The GIS Weasel software system uses a GIS-based graphical user interface (GUI), the C programming language, and external scripting languages. The software will run on any computing platform where ArcInfo Workstation (version 8.0.2 or later) and the GRID extension are accessible. The user controls the processing of the GIS Weasel by interacting with menus, maps, and tables. The purpose of this document is to describe the operation of the software. This document is not intended to describe the usage of this software in support of any particular environmental simulation model. Such guides are published separately.

Influence of sub-kilometer precipitation datasets on simulated snowpack and glacier winter balance in alpine terrain.

NASA Astrophysics Data System (ADS)

Vionnet, Vincent; Six, Delphine; Auger, Ludovic; Lafaysse, Matthieu; Quéno, Louis; Réveillet, Marion; Dombrowski-Etchevers, Ingrid; Thibert, Emmanuel; Dumont, Marie

2017-04-01

Capturing spatial and temporal variabilities of meteorological conditions at fine scale is necessary for modelling snowpack and glacier winter mass balance in alpine terrain. In particular, precipitation amount and phase are strongly influenced by the complex topography. In this study, we assess the impact of three sub-kilometer precipitation datasets (rainfall and snowfall) on distributed simulations of snowpack and glacier winter mass balance with the detailed snowpack model Crocus for winter 2011-2012. The different precipitation datasets at 500-m grid spacing over part of the French Alps (200*200 km2 area) are coming either from (i) the SAFRAN precipitation analysis specially developed for alpine terrain, or from (ii) operational outputs of the atmospheric model AROME at 2.5-km grid spacing downscaled to 500 m with fixed lapse rate or from (iii) a version of the atmospheric model AROME at 500-m grid spacing. Others atmospherics forcings (air temperature and humidity, incoming longwave and shortwave radiation, wind speed) are taken from the AROME simulations at 500-m grid spacing. These atmospheric forcings are firstly compared against a network of automatic weather stations. Results are analysed with respect to station location (valley, mid- and high-altitude). The spatial pattern of seasonal snowfall and its dependency with elevation is then analysed for the different precipitation datasets. Large differences between SAFRAN and the two versions of AROME are found at high-altitude. Finally, results of Crocus snowpack simulations are evaluated against (i) punctual in-situ measurements of snow depth and snow water equivalent, and (ii) maps of snow covered areas retrieved from optical satellite data (MODIS). Measurements of winter accumulation of six glaciers of the French Alps are also used and provide very valuable information on precipitation at high-altitude where the conventional observation network is scarce. This study illustrates the potential and limitations of high-resolution atmospheric models to drive simulations of snowpack and glacier winter mass balance in alpine terrain.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

SPAGETTA, a Gridded Weather Generator: Calibration, Validation and its Use for Future Climate

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Rotach, Mathias W.; Huth, Radan

2017-04-01

Spagetta is a new (started in 2016) stochastic multi-site multi-variate weather generator (WG). It can produce realistic synthetic daily (or monthly, or annual) weather series representing both present and future climate conditions at multiple sites (grids or stations irregularly distributed in space). The generator, whose model is based on the Wilks' (1999) multi-site extension of the parametric (Richardson's type) single site M&Rfi generator, may be run in two modes: In the first mode, it is run as a classical generator, which is calibrated in the first step using weather data from multiple sites, and only then it may produce arbitrarily long synthetic time series mimicking the spatial and temporal structure of the calibration weather data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. In the second mode, the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the surface weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying autoregressive model, which produces the multi-site weather series. In the latter mode of operation, the user is allowed to prescribe the spatially varying trend, which is superimposed to the values produced by the generator; this feature has been implemented for use in developing the methodology for assessing significance of trends in multi-site weather series (for more details see another EGU-2017 contribution: Huth and Dubrovsky, 2017, Evaluating collective significance of climatic trends: A comparison of methods on synthetic data; EGU2017-4993). This contribution will focus on the first (classical) mode. The poster will present (a) model of the generator, (b) results of the validation tests made in terms of the spatial hot/cold/dry/wet spells, and (c) results of the pilot climate change impact experiment, in which (i) the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and then (ii) the effect on the above spatial validation indices derived from the synthetic series produced by the modified WG is analysed. In this experiment, the generator is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulation (taken from the CORDEX database).

GIEMS-D3: A new long-term, dynamical, high-spatial resolution inundation extent dataset at global scale

NASA Astrophysics Data System (ADS)

Aires, Filipe; Miolane, Léo; Prigent, Catherine; Pham Duc, Binh; Papa, Fabrice; Fluet-Chouinard, Etienne; Lehner, Bernhard

2017-04-01

The Global Inundation Extent from Multi-Satellites (GIEMS) provides multi-year monthly variations of the global surface water extent at 25kmx25km resolution. It is derived from multiple satellite observations. Its spatial resolution is usually compatible with climate model outputs and with global land surface model grids but is clearly not adequate for local applications that require the characterization of small individual water bodies. There is today a strong demand for high-resolution inundation extent datasets, for a large variety of applications such as water management, regional hydrological modeling, or for the analysis of mosquitos-related diseases. A new procedure is introduced to downscale the GIEMS low spatial resolution inundations to a 3 arc second (90 m) dataset. The methodology is based on topography and hydrography information from the HydroSHEDS database. A new floodability index is adopted and an innovative smoothing procedure is developed to ensure the smooth transition, in the high-resolution maps, between the low-resolution boxes from GIEMS. Topography information is relevant for natural hydrology environments controlled by elevation, but is more limited in human-modified basins. However, the proposed downscaling approach is compatible with forthcoming fusion with other more pertinent satellite information in these difficult regions. The resulting GIEMS-D3 database is the only high spatial resolution inundation database available globally at the monthly time scale over the 1993-2007 period. GIEMS-D3 is assessed by analyzing its spatial and temporal variability, and evaluated by comparisons to other independent satellite observations from visible (Google Earth and Landsat), infrared (MODIS) and active microwave (SAR).

Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

NASA Astrophysics Data System (ADS)

Fu, W. J.; Jiang, P. K.; Zhou, G. M.; Zhao, K. L.

2014-04-01

Spatial pattern information of carbon density in forest ecosystem including forest litter carbon (FLC) plays an important role in evaluating carbon sequestration potentials. The spatial variation of FLC density in the typical subtropical forests in southeastern China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (south-north) × 6 km (east-west) grid system in Zhejiang province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha-1 to 8841.3 kg ha-1, with an average of 1786.7 kg ha-1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) Basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS, could be used to study spatial patterns of environmental variables related to forest ecosystem.

The Space-Wise Global Gravity Model from GOCE Nominal Mission Data

NASA Astrophysics Data System (ADS)

Gatti, A.; Migliaccio, F.; Reguzzoni, M.; Sampietro, D.; Sanso, F.

2011-12-01

In the framework of the GOCE data analysis, the space-wise approach implements a multi-step collocation solution for the estimation of a global geopotential model in terms of spherical harmonic coefficients and their error covariance matrix. The main idea is to use the collocation technique to exploit the spatial correlation of the gravity field in the GOCE data reduction. In particular the method consists of an along-track Wiener filter, a collocation gridding at satellite altitude and a spherical harmonic analysis by integration. All these steps are iterated, also to account for the rotation between local orbital and gradiometer reference frame. Error covariances are computed by Montecarlo simulations. The first release of the space-wise approach was presented at the ESA Living Planet Symposium in July 2010. This model was based on only two months of GOCE data and partially contained a priori information coming from other existing gravity models, especially at low degrees and low orders. A second release was distributed after the 4th International GOCE User Workshop in May 2011. In this solution, based on eight months of GOCE data, all the dependencies from external gravity information were removed thus giving rise to a GOCE-only space-wise model. However this model showed an over-regularization at the highest degrees of the spherical harmonic expansion due to the combination technique of intermediate solutions (based on about two months of data). In this work a new space-wise solution is presented. It is based on all nominal mission data from November 2009 to mid April 2011, and its main novelty is that the intermediate solutions are now computed in such a way to avoid over-regularization in the final solution. Beyond the spherical harmonic coefficients of the global model and their error covariance matrix, the space-wise approach is able to deliver as by-products a set of spherical grids of potential and of its second derivatives at mean satellite altitude. These grids have an information content that is very similar to the original along-orbit data, but they are much easier to handle. In addition they are estimated by local least-squares collocation and therefore, although computed by a unique global covariance function, they could yield more information at local level than the spherical harmonic coefficients of the global model. For this reason these grids seem to be useful for local geophysical investigations. The estimated grids with their estimated errors are presented in this work together with proposals on possible future improvements. A test to compare the different information contents of the along-orbit data, the gridded data and the spherical harmonic coefficients is also shown.

A Data Miner for the Information Power Grid

NASA Technical Reports Server (NTRS)

Hinke, Thomas H.; Parks, John W. (Technical Monitor)

2002-01-01

Grid Miner (GM) is one of the early data mining applications developed by NASA to help users obtain information from the Information Power Grid (IPG). Topics cover include: benefits of data mining, potential use of grids in data mining activities, an overview of the GM application, and a brief review of GM architecture and implementation issues. The current status of the GM system is also discussed.

High-resolution grids of hourly meteorological variables for Germany

NASA Astrophysics Data System (ADS)

Krähenmann, S.; Walter, A.; Brienen, S.; Imbery, F.; Matzarakis, A.

2018-02-01

We present a 1-km2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down- and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km2. This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted. The Rhine River Valley, for example, exhibited more than 100 summer days in 2003, whereas in 1996, the number was low everywhere in Germany. The dataset is useful for applications in various climate-related studies, hazard management and for solar or wind energy applications and it is available via doi: 10.5676/DWD_CDC/TRY_Basis_v001.

Redistribution population data across a regular spatial grid according to buildings characteristics

NASA Astrophysics Data System (ADS)

Calka, Beata; Bielecka, Elzbieta; Zdunkiewicz, Katarzyna

2016-12-01

Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1999-01-01

The American National Standards Institute?s (ANSI) Spatial Data Transfer Standard (SDTS) is a mechanism for archiving and transferring of spatial data (including metadata) between dissimilar computer systems. The SDTS specifies exchange constructs, such as format, structure, and content, for spatially referenced vector and raster (including gridded) data. The SDTS includes a flexible conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

Overset grid applications on distributed memory MIMD computers

NASA Technical Reports Server (NTRS)

Chawla, Kalpana; Weeratunga, Sisira

1994-01-01

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

Mathematical Investigation of Gamma Ray and Neutron Absorption Grid Patterns for Homeland Defense Related Fourier Imaging Systems

NASA Technical Reports Server (NTRS)

Boccio, Dona

2003-01-01

Terrorist suitcase nuclear devices typically using converted Soviet tactical nuclear warheads contain several kilograms of plutonium. This quantity of plutonium emits a significant number of gamma rays and neutrons as it undergoes radioactive decay. These gamma rays and neutrons normally penetrate ordinary matter to a significant distance. Unfortunately this penetrating quality of the radiation makes imaging with classical optics impractical. However, this radiation signature emitted by the nuclear source may be sufficient to be imaged from low-flying aerial platforms carrying Fourier imaging systems. The Fourier imaging system uses a pair of co-aligned absorption grids to measure a selected range of spatial frequencies from an object. These grids typically measure the spatial frequency in only one direction at a time. A grid pair that looks in all directions simultaneously would be an improvement over existing technology. A number of grid pairs governed by various parameters were investigated to solve this problem. By examining numerous configurations, it became apparent that an appropriate spiral pattern could be made to work. A set of equations was found to describe a grid pattern that produces straight fringes. Straight fringes represent a Fourier transform of a point source at infinity. An inverse Fourier transform of this fringe pattern would provide an accurate image (location and intensity) of a point source.

Visualizing Spatially Varying Distribution Data

NASA Technical Reports Server (NTRS)

Kao, David; Luo, Alison; Dungan, Jennifer L.; Pang, Alex; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Box plot is a compact representation that encodes the minimum, maximum, mean, median, and quarters information of a distribution. In practice, a single box plot is drawn for each variable of interest. With the advent of more accessible computing power, we are now facing the problem of visual icing data where there is a distribution at each 2D spatial location. Simply extending the box plot technique to distributions over 2D domain is not straightforward. One challenge is reducing the visual clutter if a box plot is drawn over each grid location in the 2D domain. This paper presents and discusses two general approaches, using parametric statistics and shape descriptors, to present 2D distribution data sets. Both approaches provide additional insights compared to the traditional box plot technique

Striking the balance: Privacy and spatial pattern preservation in masked GPS data

NASA Astrophysics Data System (ADS)

Seidl, Dara E.

Volunteered location and trajectory data are increasingly collected and applied in analysis for a variety of academic fields and recreational pursuits. As access to personal location data increases, issues of privacy arise as individuals become identifiable and linked to other repositories of information. While the quality and precision of data are essential to accurate analysis, there is a tradeoff between privacy and access to data. Obfuscation of point data is a solution that aims to protect privacy and maximize preservation of spatial pattern. This study explores two methods of location obfuscation for volunteered GPS data: grid masking and random perturbation. These methods are applied to travel survey GPS data in the greater metropolitan regions of Chicago and Atlanta in the first large-scale GPS masking study of its kind.

Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity

PubMed Central

2018-01-01

Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. PMID:29465399

Impact of land-use on groundwater quality: GIS-based study from an alluvial aquifer in the western Ganges basin

NASA Astrophysics Data System (ADS)

Khan, Arina; Khan, Haris Hasan; Umar, Rashid

2017-12-01

In this study, groundwater quality of an alluvial aquifer in the western Ganges basin is assessed using a GIS-based groundwater quality index (GQI) concept that uses groundwater quality data from field survey and laboratory analysis. Groundwater samples were collected from 42 wells during pre-monsoon and post-monsoon periods of 2012 and analysed for pH, EC, TDS, Anions (Cl, SO4, NO3), and Cations (Ca, Mg, Na). To generate the index, several parameters were selected based on WHO recommendations. The spatially variable grids of each parameter were modified by normalizing with the WHO standards and finally integrated into a GQI grid. The mean GQI values for both the season suggest good groundwater quality. However, spatial variations exist and are represented by GQI map of both seasons. This spatial variability was compared with the existing land-use, prepared using high-resolution satellite imagery available in Google earth. The GQI grids were compared to the land-use map using an innovative GIS-based method. Results indicate that the spatial variability of groundwater quality in the region is not fully controlled by the land-use pattern. This probably reflects the diffuse nature of land-use classes, especially settlements and plantations.

Application of Geographical Information System Arc/info Grid-Based Surface Hyrologic Modeling to the Eastern Hellas Region, Mars

NASA Astrophysics Data System (ADS)

Mest, S. C.; Harbert, W.; Crown, D. A.

2001-05-01

Geographical Information System GRID-based raster modeling of surface water runoff in the eastern Hellas region of Mars has been completed. We utilized the 0.0625 by 0.0625 degree topographic map of Mars collected by the Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA) instrument to model watershed and surface runoff drainage systems. Scientific interpretation of these models with respect to ongoing geological mapping is presented in Mest et al., (2001). After importing a region of approximately 77,000,000 square kilometers into Arc/Info 8.0.2 we reprojected this digital elevation model (DEM) from a Mars sphere into a Mars ellipsoid. Using a simple cylindrical geographic projection and horizontal spatial units of decimal degrees and then an Albers projection with horizontal spatial units of meters, we completed basic hydrological modeling. Analysis of the raw DEM to determine slope, aspect, flow direction, watershed and flow accumulation grids demonstrated the need for correction of single pixel sink anomalies. After analysis of zonal elevation statistics associated with single pixel sinks, which identified 0.8 percent of the DEM points as having undefined surface water flow directions, we filled single pixel sink values of 89 meters or less. This correction is comparable with terrestrial DEMs that contain 0.9 percent to 4.7 percent of cells, which are sinks (Tarboton et al., 1991). The fill-corrected DEM was then used to determine slope, aspect, surface water flow direction and surface water flow accumulation. Within the region of interest 8,776 watersheds were identified. Using Arc/Info GRID flow direction and flow accumulation tools, regions of potential surface water flow accumulation were identified. These networks were then converted to a Strahler ordered stream network. Surface modeling produced Strahler orders one through six. As presented in Mest et al., (2001) comparisons of mapped features may prove compatible with drainage networks and watersheds derived using this methodology. Mest, Scott C., Crown, David A., and Harbert, William, 2001, Highland drainage basins and valley networks in the eastern Hellas Region of Mars, Abstract 1419, Lunar and Planetary Science XXXII Meeting Houston (CDROM). Tarboton D. G., Bras, R. L., and Rodriguez-Iturbe, 1991, On the Extraction of Channel Networks from Digital Elevation Data, Hydrological Processes, v. 5, 81-100. http://viking.eps.pitt.edu

Towards understanding of the spatio-temporal composition of Terrestrial Water Storage variations in Northern Latitudes using a model-data fusion approach

NASA Astrophysics Data System (ADS)

Trautmann, Tina; Koirala, Sujan; Carvalhais, Nuno; Niemann, Christoph; Fink, Manfred; Jung, Martin

2017-04-01

Understanding variations in the terrestrial water storage (TWS) and its components is essential to gain insights into the dynamics of the hydrological cycle, and to assess temporal and spatial variations of water availability under global changes. We investigated spatio-temporal patterns of TWS variations and their composition in the humid regions of northern mid-to-high latitudes during 2001-2014 by using a simple hydrological model with few effective parameters. Compared to traditional modelling studies, our simple model was informed and constrained by multiple state-of-the-art earth observation products including TWS from Gravity Recovery and Climate Experiment (GRACE) satellites (Wiese 2015), Snow Water Equivalent (SWE) from GlobSnow project (Loujous et al. 2014), evapotranspiration fluxes from eddy covariance measurements (Tramontana et al. 2016), and gridded runoff estimates for Europe (Gudmundsson & Seneviratne 2016). Thorough evaluation of model demonstrates that the model reproduces the observed patterns of hydrological fluxes and states well. The validated model results are then used to assess the contributions of snow pack, soil moisture and groundwater on the integrated TWS across spatial (local grid scale, spatially integrated) and temporal (seasonal, inter-annual) scales. Interestingly, our results show that TWS variations on different scales are dominated by different components. On both, seasonal and inter-annual time scales, the spatially integrated TWS signal mainly originates from dynamics of snow pack. On the local grid scale, mean seasonal TWS variations are driven by snow dynamics as well, whereas inter-annual variations are found to originate from soil moisture availability. Thus, we show that the determinants of TWS variations are scale-dependent, while coincidently underline the potential of model-data fusion techniques to gain insights into the complex hydrological system. References: Gudmundsson, L. and S. I. Seneviratne (2016): Observation-based gridded runoff estimates for Europe (E-RUN version 1.1). -Earth System Science Data, 8, 279-295. doi: 10.5194/essd-8-279-201. Loujous, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Kangwa, M., Eskelinen, M., Metsämäki, S., Solberg, R., Salberg, A.-B., Bippus, G., Ripper, E., Nagler, T., Derksen, C., Wiesmann, A., Wunderle, S., Hüsler, F., Fontana, F., and Foppa, N., 2014: GlobSnow-2 Final Report, European Space Agency. Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D. (2016): Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms. -Biogeosciences, 13, 4291-4313. doi:10.5194/bg-13-4291-2016. D.N. Wiese (2015): GRACE monthly global water mass grids. NETCDF RELEASE 5.0. Ver. 5.0. PO.DAAC, CA, USA. Dataset accessed [2016-01-03] at http://dx.doi.org/10.5067/TEMSC-OCL05.

Exploratory spatial analysis of pilot fatality rates in general aviation crashes using geographic information systems.

PubMed

Grabowski, Jurek G; Curriero, Frank C; Baker, Susan P; Li, Guohua

2002-03-01

Geographic information systems and exploratory spatial analysis were used to describe the geographic characteristics of pilot fatality rates in 1983-1998 general aviation crashes within the continental United States. The authors plotted crash sites on a digital map; rates were computed at regular grid intersections and then interpolated by using geographic information systems. A test for significance was performed by using Monte Carlo simulations. Further analysis compared low-, medium-, and high-rate areas in relation to pilot characteristics, aircraft type, and crash circumstance. Of the 14,051 general aviation crashes studied, 31% were fatal. Seventy-four geographic areas were categorized as having low fatality rates and 53 as having high fatality rates. High-fatality-rate areas tended to be mountainous, such as the Rocky Mountains and the Appalachian region, whereas low-rate areas were relatively flat, such as the Great Plains. Further analysis comparing low-, medium-, and high-fatality-rate areas revealed that crashes in high-fatality-rate areas were more likely than crashes in other areas to have occurred under instrument meteorologic conditions and to involve aircraft fire. This study demonstrates that geographic information systems are a valuable tool for injury prevention and aviation safety research.

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

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

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

Linking the open source, spatial electrification tool (ONSSET) and the open source energy modelling system (OSeMOSYS), with a focus on Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Mentis, Dimitrios; Howells, Mark; Rogner, Holger; Korkovelos, Alexandros; Arderne, Christopher; Siyal, Shahid; Zepeda, Eduardo; Taliotis, Constantinos; Bazilian, Morgan; de Roo, Ad; Tanvez, Yann; Oudalov, Alexandre; Scholtz, Ernst

2017-04-01

In September 2015, the United Nations General Assembly adopted Agenda 2030, which comprises a set of 17 Sustainable Development Goals (SDGs) defined by 169 targets. "Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030" is the seventh goal (SDG7). While access to energy refers to more than electricity, the latter is the central focus of this work. According to the World Bank's 2015 Global Tracking Framework, roughly 15% of world population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity services. The majority of those without access (87%) reside in rural areas. This paper presents results of a Geographic Information Systems (GIS) approach coupled with open access data and linked to the Electricity Model Base for Africa (TEMBA), a model that represents each continental African country's electricity supply system. We present least-cost electrification strategies on a country-by-country basis for Sub-Saharan Africa. The electrification options include grid extension, mini-grid and stand-alone systems for rural, peri-urban, and urban contexts across the economy. At low levels of electricity demand there is a strong penetration of standalone technologies. However, higher electricity demand levels move the favourable electrification option from stand-alone systems to mini grid and to grid extensions.

The Effect of DEM Source and Grid Size on the Index of Connectivity in Savanna Catchments

NASA Astrophysics Data System (ADS)

Jarihani, Ben; Sidle, Roy; Bartley, Rebecca; Roth, Christian

2017-04-01

The term "hydrological connectivity" is increasingly used instead of sediment delivery ratio to describe the linkage between the sources of water and sediment within a catchment to the catchment outlet. Sediment delivery ratio is an empirical parameter that is highly site-specific and tends to lump all processes, whilst hydrological connectivity focuses on the spatially-explicit hydrologic drivers of surficial processes. Detailed topographic information plays a fundamental role in geomorphological interpretations as well as quantitative modelling of sediment fluxes and connectivity. Geomorphometric analysis permits a detailed characterization of drainage area and drainage pattern together with the possibility of characterizing surface roughness. High resolution topographic data (i.e., LiDAR) are not available for all areas; however, remotely sensed topographic data from multiple sources with different grid sizes are used to undertake geomorphologic analysis in data-sparse regions. The Index of Connectivity (IC), a geomorphometric model based only on DEM data, is applied in two small savanna catchments in Queensland, Australia. The influence of the scale of the topographic data is explored by using DEMs from LiDAR ( 1 m), WorldDEM ( 10 m), raw SRTM and hydrologically corrected SRTM derived data ( 30 m) to calculate the index of connectivity. The effect of the grid size is also investigated by resampling the high resolution LiDAR DEM to multiple grid sizes (e.g. 5, 10, 20 m) and comparing the extracted IC.

Using Grid Benchmarks for Dynamic Scheduling of Grid Applications

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Hood, Robert

2003-01-01

Navigation or dynamic scheduling of applications on computational grids can be improved through the use of an application-specific characterization of grid resources. Current grid information systems provide a description of the resources, but do not contain any application-specific information. We define a GridScape as dynamic state of the grid resources. We measure the dynamic performance of these resources using the grid benchmarks. Then we use the GridScape for automatic assignment of the tasks of a grid application to grid resources. The scalability of the system is achieved by limiting the navigation overhead to a few percent of the application resource requirements. Our task submission and assignment protocol guarantees that the navigation system does not cause grid congestion. On a synthetic data mining application we demonstrate that Gridscape-based task assignment reduces the application tunaround time.

Satellite-aided evaluation of population exposure to air pollution

USGS Publications Warehouse

Todd, William J.; George, Anthony J.; Bryant, Nevin A.

1979-01-01

The Clean Air Act Amendments of 1977 set schedules for states to implement regional, spatial assessments of air quality impacts. Accordingly, the U.S. Environmental Protection Agency recently published guidelines for quantifying population exposure to adverse air quality impact by using air quality and population data by census tracts. Our research complements the EPA guidelines in that it demonstrates the ability to determine population exposure to air pollution through computer processing that utilizes Landsat satellite-derived land use information. Three variables-a 1985 estimate of total suspended particulates for 2-km2 grid cells, Landsat-derived residential land cover data for 0.45-ha cells, and population totals for census tracts-were spatially registered and cross-tabulated to produce tabular and map products illustrating relative air quality exposure for residential population by 2-km2 cells. It would cost $20,000 to replicate our analysis for an area similar in size to the 4000-km2 Portland area. Once completed, the spatially fine, computer-compatible air quality and population data are amenable to the timely and efficient generation of population-at-risk tabular and map information on a continuous or periodic basis.

Domain decomposition by the advancing-partition method for parallel unstructured grid generation

NASA Technical Reports Server (NTRS)

Banihashemi, legal representative, Soheila (Inventor); Pirzadeh, Shahyar Z. (Inventor)

2012-01-01

In a method for domain decomposition for generating unstructured grids, a surface mesh is generated for a spatial domain. A location of a partition plane dividing the domain into two sections is determined. Triangular faces on the surface mesh that intersect the partition plane are identified. A partition grid of tetrahedral cells, dividing the domain into two sub-domains, is generated using a marching process in which a front comprises only faces of new cells which intersect the partition plane. The partition grid is generated until no active faces remain on the front. Triangular faces on each side of the partition plane are collected into two separate subsets. Each subset of triangular faces is renumbered locally and a local/global mapping is created for each sub-domain. A volume grid is generated for each sub-domain. The partition grid and volume grids are then merged using the local-global mapping.

A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields.

PubMed

Agarwal, Rahul; Chen, Zhe; Kloosterman, Fabian; Wilson, Matthew A; Sarma, Sridevi V

2016-07-01

Pyramidal neurons recorded from the rat hippocampus and entorhinal cortex, such as place and grid cells, have diverse receptive fields, which are either unimodal or multimodal. Spiking activity from these cells encodes information about the spatial position of a freely foraging rat. At fine timescales, a neuron's spike activity also depends significantly on its own spike history. However, due to limitations of current parametric modeling approaches, it remains a challenge to estimate complex, multimodal neuronal receptive fields while incorporating spike history dependence. Furthermore, efforts to decode the rat's trajectory in one- or two-dimensional space from hippocampal ensemble spiking activity have mainly focused on spike history-independent neuronal encoding models. In this letter, we address these two important issues by extending a recently introduced nonparametric neural encoding framework that allows modeling both complex spatial receptive fields and spike history dependencies. Using this extended nonparametric approach, we develop novel algorithms for decoding a rat's trajectory based on recordings of hippocampal place cells and entorhinal grid cells. Results show that both encoding and decoding models derived from our new method performed significantly better than state-of-the-art encoding and decoding models on 6 minutes of test data. In addition, our model's performance remains invariant to the apparent modality of the neuron's receptive field.

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM1-MODIS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Analytical Computation of Effective Grid Parameters for the Finite-Difference Seismic Waveform Modeling With the PREM, IASP91, SP6, and AK135

NASA Astrophysics Data System (ADS)

Toyokuni, G.; Takenaka, H.

2007-12-01

We propose a method to obtain effective grid parameters for the finite-difference (FD) method with standard Earth models using analytical ways. In spite of the broad use of the heterogeneous FD formulation for seismic waveform modeling, accurate treatment of material discontinuities inside the grid cells has been a serious problem for many years. One possible way to solve this problem is to introduce effective grid elastic moduli and densities (effective parameters) calculated by the volume harmonic averaging of elastic moduli and volume arithmetic averaging of density in grid cells. This scheme enables us to put a material discontinuity into an arbitrary position in the spatial grids. Most of the methods used for synthetic seismogram calculation today receives the blessing of the standard Earth models, such as the PREM, IASP91, SP6, and AK135, represented as functions of normalized radius. For the FD computation of seismic waveform with such models, we first need accurate treatment of material discontinuities in radius. This study provides a numerical scheme for analytical calculations of the effective parameters for an arbitrary spatial grids in radial direction as to these major four standard Earth models making the best use of their functional features. This scheme can analytically obtain the integral volume averages through partial fraction decompositions (PFDs) and integral formulae. We have developed a FORTRAN subroutine to perform the computations, which is opened to utilization in a large variety of FD schemes ranging from 1-D to 3-D, with conventional- and staggered-grids. In the presentation, we show some numerical examples displaying the accuracy of the FD synthetics simulated with the analytical effective parameters.

Assessing the quality of open spatial data for mobile location-based services research and applications

NASA Astrophysics Data System (ADS)

Ciepłuch, C.; Mooney, P.; Jacob, R.; Zheng, J.; Winstanely, A. C.

2011-12-01

New trends in GIS such as Volunteered Geographical Information (VGI), Citizen Science, and Urban Sensing, have changed the shape of the geoinformatics landscape. The OpenStreetMap (OSM) project provided us with an exciting, evolving, free and open solution as a base dataset for our geoserver and spatial data provider for our research. OSM is probably the best known and best supported example of VGI and user generated spatial content on the Internet. In this paper we will describe current results from the development of quality indicators for measures for OSM data. Initially we have analysed the Ireland OSM data in grid cells (5km) to gather statistical data about the completeness, accuracy, and fitness for purpose of the underlying spatial data. This analysis included: density of user contributions, spatial density of points and polygons, types of tags and metadata used, dominant contributors in a particular area or for a particular geographic feature type, etc. There greatest OSM activity and spatial data density is highly correlated with centres of large population. The ability to quantify and assess if VGI, such as OSM, is of sufficient quality for mobile mapping applications and Location-based services is critical to the future success of VGI as a spatial data source for these technologies.

Clouds Optically Gridded by Stereo COGS product

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

Oktem, Rusen; Romps, David

COGS product is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube centered at the central facility of SGP site at a spatial resolution of 50 meters and a temporal resolution of 20 seconds. The dimensions are X, Y, Z, and time, where X,Y, Z, correspond to east-west, north-south, and altitude of the grid point, respectively. COGS takes on values 0, 1, and -1 denoting "cloud", "no cloud", and "not available". 

NIFTY - Numerical Information Field Theory. A versatile PYTHON library for signal inference

NASA Astrophysics Data System (ADS)

Selig, M.; Bell, M. R.; Junklewitz, H.; Oppermann, N.; Reinecke, M.; Greiner, M.; Pachajoa, C.; Enßlin, T. A.

2013-06-01

NIFTy (Numerical Information Field Theory) is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTy offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically without concerning the user. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTy permits its user to rapidly prototype algorithms in 1D, and then apply the developed code in higher-dimensional settings of real world problems. The set of spaces on which NIFTy operates comprises point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those. The functionality and diversity of the package is demonstrated by a Wiener filter code example that successfully runs without modification regardless of the space on which the inference problem is defined. NIFTy homepage http://www.mpa-garching.mpg.de/ift/nifty/; Excerpts of this paper are part of the NIFTy source code and documentation.

HappyFace as a generic monitoring tool for HEP experiments

NASA Astrophysics Data System (ADS)

Kawamura, Gen; Magradze, Erekle; Musheghyan, Haykuhi; Quadt, Arnulf; Rzehorz, Gerhard

2015-12-01

The importance of monitoring on HEP grid computing systems is growing due to a significant increase in their complexity. Computer scientists and administrators have been studying and building effective ways to gather information on and clarify a status of each local grid infrastructure. The HappyFace project aims at making the above-mentioned workflow possible. It aggregates, processes and stores the information and the status of different HEP monitoring resources into the common database of HappyFace. The system displays the information and the status through a single interface. However, this model of HappyFace relied on the monitoring resources which are always under development in the HEP experiments. Consequently, HappyFace needed to have direct access methods to the grid application and grid service layers in the different HEP grid systems. To cope with this issue, we use a reliable HEP software repository, the CernVM File System. We propose a new implementation and an architecture of HappyFace, the so-called grid-enabled HappyFace. It allows its basic framework to connect directly to the grid user applications and the grid collective services, without involving the monitoring resources in the HEP grid systems. This approach gives HappyFace several advantages: Portability, to provide an independent and generic monitoring system among the HEP grid systems. Eunctionality, to allow users to perform various diagnostic tools in the individual HEP grid systems and grid sites. Elexibility, to make HappyFace beneficial and open for the various distributed grid computing environments. Different grid-enabled modules, to connect to the Ganga job monitoring system and to check the performance of grid transfers among the grid sites, have been implemented. The new HappyFace system has been successfully integrated and now it displays the information and the status of both the monitoring resources and the direct access to the grid user applications and the grid collective services.

High Precision Grids for Neutron, Hard X-Ray, and Gamma-Ray Imaging Systems

NASA Technical Reports Server (NTRS)

Campbell, Jonathan W. (Inventor)

2002-01-01

Fourier telescopes permit observations over a very broad band of energy. They generally include synthetic spatial filtering structures, known as multilayer grids or grid pairs consisting of alternate layers of absorbing and transparent materials depending on whether neutrons or photons are being imaged. For hard x-rays and gamma rays high (absorbing) and low (transparent) atomic number elements, termed high-Z and low-Z materials may be used. Fabrication of these multilayer grid structures is not without its difficulties. Herein the alternate layers of the higher material and the lower material are inserted in a polyhedron, transparent to photons of interest, through an open face of the polyhedron. The inserted layers are then uniformly compressed to form a multilayer grid.

Medial Entorhinal Grid Cells and Head Direction Cells Rotate with a T-Maze More Often During Less Recently Experienced Rotations

PubMed Central

Gupta, Kishan; Beer, Nathan J.; Keller, Lauren A.; Hasselmo, Michael E.

2014-01-01

Prior studies of head direction (HD) cells indicate strong landmark control over the preferred firing direction of these cells, with few studies exhibiting shifts away from local reference frames over time. We recorded spiking activity of grid and HD cells in the medial entorhinal cortex of rats, testing correlations of local environmental cues with the spatial tuning curves of these cells' firing fields as animals performed continuous spatial alternation on a T-maze that shared the boundaries of an open-field arena. The environment was rotated into configurations the animal had either seen or not seen in the past recording week. Tuning curves of both cell types demonstrated commensurate shifts of tuning with T-maze rotations during less recent rotations, more so than recent rotations. This strongly suggests that animals are shifting their reference frame away from the local environmental cues over time, learning to use a different reference frame more likely reliant on distal or idiothetic cues. In addition, grid fields demonstrated varying levels of “fragmentation” on the T-maze. The propensity for fragmentation does not depend on grid spacing and grid score, nor animal trajectory, indicating the cognitive treatment of environmental subcompartments is likely driven by task demands. PMID:23382518

Contour Error Map Algorithm

NASA Technical Reports Server (NTRS)

Merceret, Francis; Lane, John; Immer, Christopher; Case, Jonathan; Manobianco, John

2005-01-01

The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.

Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard

NASA Astrophysics Data System (ADS)

Hubbard, S.; Pierce, L.; Grote, K.; Rubin, Y.

2003-12-01

Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.

The functional micro-organization of grid cells revealed by cellular-resolution imaging

PubMed Central

Heys, James G.; Rangarajan, Krsna V.; Dombeck, Daniel A.

2015-01-01

Summary Establishing how grid cells are anatomically arranged, on a microscopic scale, in relation to their firing patterns in the environment would facilitate a greater micro-circuit level understanding of the brain’s representation of space. However, all previous grid cell recordings used electrode techniques that provide limited descriptions of fine-scale organization. We therefore developed a technique for cellular-resolution functional imaging of medial entorhinal cortex (MEC) neurons in mice navigating a virtual linear track, enabling a new experimental approach to study MEC. Using these methods, we show that grid cells are physically clustered in MEC compared to non-grid cells. Additionally, we demonstrate that grid cells are functionally micro-organized: The similarity between the environment firing locations of grid cell pairs varies as a function of the distance between them according to a “Mexican Hat” shaped profile. This suggests that, on average, nearby grid cells have more similar spatial firing phases than those further apart. PMID:25467986

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

Martínez-Rovira, I., E-mail: immamartinez@gmail.com; Prezado, Y.; Fois, G.

Purpose: Spatial fractionation of the dose has proven to be a promising approach to increase the tolerance of healthy tissue, which is the main limitation of radiotherapy. A good example of that is GRID therapy, which has been successfully used in the management of large tumors with low toxicity. The aim of this work is to explore new avenues using nonconventional sources: GRID therapy by using kilovoltage (synchrotron) x-rays, the use of very high-energy electrons, and proton GRID therapy. They share in common the use of the smallest possible grid sizes in order to exploit the dose–volume effects. Methods: Montemore » Carlo simulations (PENELOPE/PENEASY and GEANT4/GATE codes) were used as a method to study dose distributions resulting from irradiations in different configurations of the three proposed techniques. As figure of merit, percentage (peak and valley) depth dose curves, penumbras, and central peak-to-valley dose ratios (PVDR) were evaluated. As shown in previous biological experiments, high PVDR values are requested for healthy tissue sparing. A superior tumor control may benefit from a lower PVDR. Results: High PVDR values were obtained in the healthy tissue for the three cases studied. When low energy photons are used, the treatment of deep-seated tumors can still be performed with submillimetric grid sizes. Superior PVDR values were reached with the other two approaches in the first centimeters along the beam path. The use of protons has the advantage of delivering a uniform dose distribution in the tumor, while healthy tissue benefits from the spatial fractionation of the dose. In the three evaluated techniques, there is a net reduction in penumbra with respect to radiosurgery. Conclusions: The high PVDR values in the healthy tissue and the use of small grid sizes in the three presented approaches might constitute a promising alternative to treat tumors with such spatially fractionated radiotherapy techniques. The dosimetric results presented here support the interest of performing radiobiology experiments in order to evaluate these new avenues.« less

Directional kriging implementation for gridded data interpolation and comparative study with common methods

NASA Astrophysics Data System (ADS)

Mahmoudabadi, H.; Briggs, G.

2016-12-01

Gridded data sets, such as geoid models or datum shift grids, are commonly used in coordinate transformation algorithms. Grid files typically contain known or measured values at regular fixed intervals. The process of computing a value at an unknown location from the values in the grid data set is called "interpolation". Generally, interpolation methods predict a value at a given point by computing a weighted average of the known values in the neighborhood of the point. Geostatistical Kriging is a widely used interpolation method for irregular networks. Kriging interpolation first analyzes the spatial structure of the input data, then generates a general model to describe spatial dependencies. This model is used to calculate values at unsampled locations by finding direction, shape, size, and weight of neighborhood points. Because it is based on a linear formulation for the best estimation, Kriging it the optimal interpolation method in statistical terms. The Kriging interpolation algorithm produces an unbiased prediction, as well as the ability to calculate the spatial distribution of uncertainty, allowing you to estimate the errors in an interpolation for any particular point. Kriging is not widely used in geospatial applications today, especially applications that run on low power devices or deal with large data files. This is due to the computational power and memory requirements of standard Kriging techniques. In this paper, improvements are introduced in directional kriging implementation by taking advantage of the structure of the grid files. The regular spacing of points simplifies finding the neighborhood points and computing their pairwise distances, reducing the the complexity and improving the execution time of the Kriging algorithm. Also, the proposed method iteratively loads small portion of interest areas in different directions to reduce the amount of required memory. This makes the technique feasible on almost any computer processor. Comparison between kriging and other standard interpolation methods demonstrated more accurate estimations in less denser data files.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

PubMed

Wang, W; Degenhart, A D; Collinger, J L; Vinjamuri, R; Sudre, G P; Adelson, P D; Holder, D L; Leuthardt, E C; Moran, D W; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Weber, D J

2009-01-01

In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

Evaluation of Aquarius Version-5 Sea Surface Salinity on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2017-12-01

Sea surface salinity (SSS) products from Aquarius have had three public releases with progressive improvement in data quality: Versions 2, 3, and 4, with the last one being released in October 2015. A systematic assessment of the Version-4, Level-3 Aquarius SSS product was performed on various spatial and temporal scales by comparing it with gridded Argo products (Lee 2016, Geophys. Res. Lett.). The comparison showed that the consistency of Aquarius Version-4 SSS with gridded Argo products is comparable to that between two different gridded Argo products. However, significant seasonal biases remain in high-latitude oceans. Further improvements are being made by the Aquarius team. Aquarius Version 5.0 SSS is scheduled to be released in October 2017 as the final version of the Aquarius Project. This presentation provides a similar evaluation of Version-5 SSS as reported by Lee (2016) and contrast it with the current Version-4 SSS.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

Producing custom regional climate data sets for impact assessment with xarray

NASA Astrophysics Data System (ADS)

Simcock, J. G.; Delgado, M.; Greenstone, M.; Hsiang, S. M.; Kopp, R. E.; Carleton, T.; Hultgren, A.; Jina, A.; Nath, I.; Rising, J. A.; Rode, A.; Yuan, J.; Chong, T.; Dobbels, G.; Hussain, A.; Song, Y.; Wang, J.; Mohan, S.; Larsen, K.; Houser, T.

2017-12-01

Research in the field of climate impact assessment and valuation frequently requires the pairing of economic observations with historical or projected weather variables. Impact assessments with large geographic scope or spatially aggregated data frequently require climate variables to be prepared for use with administrative/political regions, economic districts such as utility service areas, physical regions such as watersheds, or other larger, non-gridded shapes. Approaches to preparing such data in the literature vary from methods developed out of convenience to more complex measures intended to account for spatial heterogeneity. But more sophisticated methods are difficult to implement, from both a theoretical and a technical standpoint. We present a new python package designed to assist researchers in the preparation of historical and projected climate data for arbitrary spatial definitions. Users specify transformations by providing (a) sets of regions in the form of shapefiles, (b) gridded data to be transformed, and, optionally, (c) gridded weights to use in the transformation. By default, aggregation to regions is conducted such that the resulting regional data draws from each grid cell according to the cell's share of total region area. However, researchers can provide alternative weighting schemes, such that the regional data is weighted by, for example, the population or planted agricultural area within each cell. An advantage of this method is that it enables easy preparation of nonlinear transformations of the climate data before aggregation to regions, allowing aggregated variables to more accurately capture the spatial heterogeneity within a region in the transformed data. At this session, we will allow attendees to view transformed climate projections, examining the effect of various weighting schemes and nonlinear transformations on aggregate regional values, highlighting the implications for climate impact assessment work.

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.

Influence of Gridded Standoff Measurement Resolution on Numerical Bathymetric Inversion

NASA Astrophysics Data System (ADS)

Hesser, T.; Farthing, M. W.; Brodie, K.

2016-02-01

The bathymetry from the surfzone to the shoreline incurs frequent, active movement due to wave energy interacting with the seafloor. Methodologies to measure bathymetry range from point-source in-situ instruments, vessel-mounted single-beam or multi-beam sonar surveys, airborne bathymetric lidar, as well as inversion techniques from standoff measurements of wave processes from video or radar imagery. Each type of measurement has unique sources of error and spatial and temporal resolution and availability. Numerical bathymetry estimation frameworks can use these disparate data types in combination with model-based inversion techniques to produce a "best-estimate of bathymetry" at a given time. Understanding how the sources of error and varying spatial or temporal resolution of each data type affect the end result is critical for determining best practices and in turn increase the accuracy of bathymetry estimation techniques. In this work, we consider an initial step in the development of a complete framework for estimating bathymetry in the nearshore by focusing on gridded standoff measurements and in-situ point observations in model-based inversion at the U.S. Army Corps of Engineers Field Research Facility in Duck, NC. The standoff measurement methods return wave parameters computed using linear wave theory from the direct measurements. These gridded datasets can range in temporal and spatial resolution that do not match the desired model parameters and therefore could lead to a reduction in the accuracy of these methods. Specifically, we investigate the affect of numerical resolution on the accuracy of an Ensemble Kalman Filter bathymetric inversion technique in relation to the spatial and temporal resolution of the gridded standoff measurements. The accuracies of the bathymetric estimates are compared with both high-resolution Real Time Kinematic (RTK) single-beam surveys as well as alternative direct in-situ measurements using sonic altimeters.

Development of a grid-independent approximate Riemannsolver. Ph.D. Thesis - Michigan Univ.

NASA Technical Reports Server (NTRS)

Rumsey, Christopher Lockwood

1991-01-01

A grid-independent approximate Riemann solver for use with the Euler and Navier-Stokes equations was introduced and explored. The two-dimensional Euler and Navier-Stokes equations are described in Cartesian and generalized coordinates, as well as the traveling wave form of the Euler equations. The spatial and temporal discretization are described for both explicit and implicit time-marching schemes. The grid-aligned flux function of Roe is outlined, while the 5-wave grid-independent flux function is derived. The stability and monotonicity analysis of the 5-wave model are presented. Two-dimensional results are provided and extended to three dimensions. The corresponding results are presented.

Sparse grid techniques for particle-in-cell schemes

NASA Astrophysics Data System (ADS)

Ricketson, L. F.; Cerfon, A. J.

2017-02-01

We propose the use of sparse grids to accelerate particle-in-cell (PIC) schemes. By using the so-called ‘combination technique’ from the sparse grids literature, we are able to dramatically increase the size of the spatial cells in multi-dimensional PIC schemes while paying only a slight penalty in grid-based error. The resulting increase in cell size allows us to reduce the statistical noise in the simulation without increasing total particle number. We present initial proof-of-principle results from test cases in two and three dimensions that demonstrate the new scheme’s efficiency, both in terms of computation time and memory usage.

Merging gauge and satellite rainfall with specification of associated uncertainty across Australia

NASA Astrophysics Data System (ADS)

Woldemeskel, Fitsum M.; Sivakumar, Bellie; Sharma, Ashish

2013-08-01

Accurate estimation of spatial rainfall is crucial for modelling hydrological systems and planning and management of water resources. While spatial rainfall can be estimated either using rain gauge-based measurements or using satellite-based measurements, such estimates are subject to uncertainties due to various sources of errors in either case, including interpolation and retrieval errors. The purpose of the present study is twofold: (1) to investigate the benefit of merging rain gauge measurements and satellite rainfall data for Australian conditions and (2) to produce a database of retrospective rainfall along with a new uncertainty metric for each grid location at any timestep. The analysis involves four steps: First, a comparison of rain gauge measurements and the Tropical Rainfall Measuring Mission (TRMM) 3B42 data at such rain gauge locations is carried out. Second, gridded monthly rain gauge rainfall is determined using thin plate smoothing splines (TPSS) and modified inverse distance weight (MIDW) method. Third, the gridded rain gauge rainfall is merged with the monthly accumulated TRMM 3B42 using a linearised weighting procedure, the weights at each grid being calculated based on the error variances of each dataset. Finally, cross validation (CV) errors at rain gauge locations and standard errors at gridded locations for each timestep are estimated. The CV error statistics indicate that merging of the two datasets improves the estimation of spatial rainfall, and more so where the rain gauge network is sparse. The provision of spatio-temporal standard errors with the retrospective dataset is particularly useful for subsequent modelling applications where input error knowledge can help reduce the uncertainty associated with modelling outcomes.

Minimizing the Standard Deviation of Spatially Averaged Surface Cross-Sectional Data from the Dual-Frequency Precipitation Radar

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Kim, Hyokyung

2016-01-01

For an airborne or spaceborne radar, the precipitation-induced path attenuation can be estimated from the measurements of the normalized surface cross section, sigma 0, in the presence and absence of precipitation. In one implementation, the mean rain-free estimate and its variability are found from a lookup table (LUT) derived from previously measured data. For the dual-frequency precipitation radar aboard the global precipitation measurement satellite, the nominal table consists of the statistics of the rain-free 0 over a 0.5 deg x 0.5 deg latitude-longitude grid using a three-month set of input data. However, a problem with the LUT is an insufficient number of samples in many cells. An alternative table is constructed by a stepwise procedure that begins with the statistics over a 0.25 deg x 0.25 deg grid. If the number of samples at a cell is too few, the area is expanded, cell by cell, choosing at each step that cell that minimizes the variance of the data. The question arises, however, as to whether the selected region corresponds to the smallest variance. To address this question, a second type of variable-averaging grid is constructed using all possible spatial configurations and computing the variance of the data within each region. Comparisons of the standard deviations for the fixed and variable-averaged grids are given as a function of incidence angle and surface type using a three-month set of data. The advantage of variable spatial averaging is that the average standard deviation can be reduced relative to the fixed grid while satisfying the minimum sample requirement.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical levels

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2011-12-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2012-05-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

A Corner-Point-Grid-Based Voxelization Method for Complex Geological Structure Model with Folds

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Mariethoz, Gregoire; Liu, Gang

2017-04-01

3D voxelization is the foundation of geological property modeling, and is also an effective approach to realize the 3D visualization of the heterogeneous attributes in geological structures. The corner-point grid is a representative data model among all voxel models, and is a structured grid type that is widely applied at present. When carrying out subdivision for complex geological structure model with folds, we should fully consider its structural morphology and bedding features to make the generated voxels keep its original morphology. And on the basis of which, they can depict the detailed bedding features and the spatial heterogeneity of the internal attributes. In order to solve the shortage of the existing technologies, this work puts forward a corner-point-grid-based voxelization method for complex geological structure model with folds. We have realized the fast conversion from the 3D geological structure model to the fine voxel model according to the rule of isocline in Ramsay's fold classification. In addition, the voxel model conforms to the spatial features of folds, pinch-out and other complex geological structures, and the voxels of the laminas inside a fold accords with the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation based on the spatial voxels. Ultimately, we use examples and the contrastive analysis between the examples and the Ramsay's description of isoclines to discuss the effectiveness and advantages of the method proposed in this work when dealing with the voxelization of 3D geologic structural model with folds based on corner-point grids.

Gridded precipitation fields at high temporal and spatial resolution for operational flood forecasting in the Rhine basin

NASA Astrophysics Data System (ADS)

van Osnabrugge, Bart; Weerts, Albrecht; Uijlenhoet, Remko

2017-04-01

Gridded areal precipitation, as one of the most important hydrometeorological input variables for initial state estimation in operational hydrological forecasting, is available in the form of raster data sets (e.g. HYRAS and EOBS) for the River Rhine basin. These datasets are compiled off-line on a daily time step using station data with the highest possible spatial density. However, such a product is not available operationally and at an hourly discretisation. Therefore, we constructed an hourly gridded precipitation dataset at 1.44 km2 resolution for the Rhine basin for the period from 1998 to present using a REGNIE-like interpolation procedure (Weerts et al., 2008) using a low and a high density rain gauge network. The datasets were validated against daily HYRAS (Rauthe, 2013) and EOBS (Haylock, 2008) data. The main goal of the operational procedure is to emulate the HYRAS dataset as good as possible, as the daily HYRAS dataset is used in the off-line calibration of the hydrological model. Our main findings are that even with low station density, the spatial patterns found in the HYRAS data set are well reproduced. With low station density (years 1999-2006) our dataset underestimates precipitation compared to HYRAS and EOBS, notably during the winter. However, interpolation based on the same set of stations overestimates precipitation compared to EOBS for the years 2006-2014. This discrepancy disappears when switching to the high station density. We also analyze the robustness of the hourly precipitation fields by comparing with stations not used during interpolation. Specific issues regarding the data when creating the gridded precipitation fields will be highlighted. Finally, the datasets are used to drive an hourly and daily gridded WFLOW_HBV model of the Rhine at the same spatial resolution. Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201 Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., Gratzki, A. 2013: A Central European precipitation climatology - Part 1: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift, 22(3), 235 256 Weerts, A.H., D. Meißner, and S. Rademacher, 2008. Input data rainfall-runoff model operational system FEWS-NL & FEWS-DE. Technical report, Deltares.

Designing efficient surveys: spatial arrangement of sample points for detection of invasive species

Treesearch

Ludek Berec; John M. Kean; Rebecca Epanchin-Niell; Andrew M. Liebhold; Robert G. Haight

2015-01-01

Effective surveillance is critical to managing biological invasions via early detection and eradication. The efficiency of surveillance systems may be affected by the spatial arrangement of sample locations. We investigate how the spatial arrangement of sample points, ranging from random to fixed grid arrangements, affects the probability of detecting a target...

Communicating and Evaluating the Causes of Seismicity in Oklahoma Using ArcGIS Online Story Map Web Applications

NASA Astrophysics Data System (ADS)

Justman, D.; Rose, K.; Bauer, J. R.; Miller, R., III; Vasylkivska, V.; Romeo, L.

2016-12-01

ArcGIS Online story maps allows users to communicate complex topics with geospatially enabled stories. This story map web application entitled "Evaluating the Mysteries of Seismicity in Oklahoma" has been employed as part of a broader research effort investigating the relationships between spatiotemporal systems and seismicity to understand the recent increase in seismicity by reviewing literature, exploring, and performing analyses on key datasets. It offers information about the unprecedented increase in seismic events since 2008, earthquake history, the risk to the population, physical mechanisms behind earthquakes, natural and anthropogenic earthquake factors, and individual & cumulative spatial extents of these factors. The cumulative spatial extents for natural, anthropogenic, and all combined earthquake factors were determined using the Cumulative Spatial Impact Layers (CSILs) tool developed at the National Energy Technology Laboratory (NETL). Results show positive correlations between the average number of influences (datasets related to individual factors) and the number of earthquakes for every 100 square mile grid cell in Oklahoma, along with interesting spatial correlations for the individual & cumulative spatial extents of these factors when overlaid with earthquake density and a hotspot analysis for earthquake magnitude from 2010 to 2015.

The eGo grid model: An open source approach towards a model of German high and extra-high voltage power grids

NASA Astrophysics Data System (ADS)

Mueller, Ulf Philipp; Wienholt, Lukas; Kleinhans, David; Cussmann, Ilka; Bunke, Wolf-Dieter; Pleßmann, Guido; Wendiggensen, Jochen

2018-02-01

There are several power grid modelling approaches suitable for simulations in the field of power grid planning. The restrictive policies of grid operators, regulators and research institutes concerning their original data and models lead to an increased interest in open source approaches of grid models based on open data. By including all voltage levels between 60 kV (high voltage) and 380kV (extra high voltage), we dissolve the common distinction between transmission and distribution grid in energy system models and utilize a single, integrated model instead. An open data set for primarily Germany, which can be used for non-linear, linear and linear-optimal power flow methods, was developed. This data set consists of an electrically parameterised grid topology as well as allocated generation and demand characteristics for present and future scenarios at high spatial and temporal resolution. The usability of the grid model was demonstrated by the performance of exemplary power flow optimizations. Based on a marginal cost driven power plant dispatch, being subject to grid restrictions, congested power lines were identified. Continuous validation of the model is nescessary in order to reliably model storage and grid expansion in progressing research.

Object Persistence Enhances Spatial Navigation: A Case Study in Smartphone Vision Science.

PubMed

Liverence, Brandon M; Scholl, Brian J

2015-07-01

Violations of spatiotemporal continuity disrupt performance in many tasks involving attention and working memory, but experiments on this topic have been limited to the study of moment-by-moment on-line perception, typically assessed by passive monitoring tasks. We tested whether persisting object representations also serve as underlying units of longer-term memory and active spatial navigation, using a novel paradigm inspired by the visual interfaces common to many smartphones. Participants used key presses to navigate through simple visual environments consisting of grids of icons (depicting real-world objects), only one of which was visible at a time through a static virtual window. Participants found target icons faster when navigation involved persistence cues (via sliding animations) than when persistence was disrupted (e.g., via temporally matched fading animations), with all transitions inspired by smartphone interfaces. Moreover, this difference occurred even after explicit memorization of the relevant information, which demonstrates that object persistence enhances spatial navigation in an automatic and irresistible fashion. © The Author(s) 2015.

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

A Climatology of Global Aerosol Mixtures to Support Sentinel-5P and Earthcare Mission Applications

NASA Astrophysics Data System (ADS)

Taylor, M.; Kazadzis, S.; Amaridis, V.; Kahn, R. A.

2015-11-01

Since constraining aerosol type with satellite remote sensing continues to be a challenge, we present a newly derived global climatology of aerosol mixtures to support atmospheric composition studies that are planned for Sentinel-5P and EarthCARE.The global climatology is obtained via application of iterative cluster analysis to gridded global decadal and seasonal mean values of the aerosol optical depth (AOD) of sulfate, biomass burning, mineral dust and marine aerosol as a proportion of the total AOD at 500nm output from the Goddard Chemistry Aerosol Radiation and Transport (GOCART). For both the decadal and seasonal means, the number of aerosol mixtures (clusters) identified is ≈10. Analysis of the percentage contribution of the component aerosol types to each mixture allowed development of a straightforward naming convention and taxonomy, and assignment of primary colours for the generation of true colour-mixing and easy-to-interpret maps of the spatial distribution of clusters across the global grid. To further help characterize the mixtures, aerosol robotic network (AERONET) Level 2.0 Version 2 inversion products were extracted from each cluster‟s spatial domain and used to estimate climatological values of key optical and microphysical parameters.The aerosol type climatology represents current knowledge that would be enhanced, possibly corrected, and refined by high temporal and spectral resolution, cloud-free observations produced by Sentinel-5P and EarthCARE instruments. The global decadal mean and seasonal gridded partitions comprise a preliminary reference framework and global climatology that can help inform the choice of components and mixtures in aerosol retrieval algorithms used by instruments such as TROPOMI and ATLID, and to test retrieval results.

Spatiotemporal comparison of highly-resolved emissions and concentrations of carbon dioxide and criteria pollutants in Salt Lake City, Utah for health and policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Fasoli, B.; Bares, R.; o'Keefe, D.; Song, T.; Huang, J.; Horel, J.; Crosman, E.; Ehleringer, J. R.

2015-12-01

This study addresses the need for robust highly-resolved emissions and concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are dependent on proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present emissions inventories and modeled concentrations for CO2 and CAPs: carbon monoxide (CO), lead (Pb), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10), and sulfur oxides (SOx) for Salt Lake County, Utah. We compare the resulting concentrations against stationary and mobile measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at an hourly, building and road link resolution as well as hourly gridded emissions with a 0.002o x 0.002o spatial resolution. Two methods for deriving criteria pollutant emission inventories were compared. One was constructed using methods similar to Hestia but downscales total emissions based on the 2011 National Emissions Inventory (NEI). The other used Emission Modeling Clearinghouse spatial and temporal surrogates to downscale the NEI data from annual and county-level resolution to hourly and 0.002o x 0.002o grid cells. The gridded emissions from both criteria pollutant methods were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The CALPUFF dispersion model was used to transport emissions and estimate air pollutant concentrations at an hourly 0.002o x 0.002o resolution. The resulting concentrations were spatially compared in the same manner as the emissions. Modeled results were compared against stationary measurements and from equipment mounted atop a light rail car in the Salt Lake City area. The comparison between both approaches to emissions estimation and resulting concentrations highlights spatial locations and hours of high variability and uncertainty.

Considering the spatial-scale factor when modelling sustainable land management.

NASA Astrophysics Data System (ADS)

Bouma, Johan

2015-04-01

Considering the spatial-scale factor when modelling sustainable land management. J.Bouma Em.prof. soil science, Wageningen University, Netherlands. Modelling soil-plant processes is a necessity when exploring future effects of climate change and innovative soil management on agricultural productivity. Soil data are needed to run models and traditional soil maps and the associated databases (based on various soil Taxonomies ), have widely been applied to provide such data obtained at "representative" points in the field. Pedotransferfunctions (PTF)are used to feed simulation models, statistically relating soil survey data ( obtained at a given point in the landscape) to physical parameters for simulation, thus providing a link with soil functionality. Soil science has a basic problem: their object of study is invisible. Only point data are obtained by augering or in pits. Only occasionally roadcuts provide a better view. Extrapolating point to area data is essential for all applications and presents a basic problem for soil science, because mapping units on soil maps, named for a given soil type,may also contain other soil types and quantitative information about the composition of soil map units is usually not available. For detailed work at farm level ( 1:5000-1:10000), an alternative procedure is proposed. Based on a geostatistical analysis, onsite soil observations are made in a grid pattern with spacings based on a geostatistical analysis. Multi-year simulations are made for each point of the functional properties that are relevant for the case being studied, such as the moisture supply capacity, nitrate leaching etc. under standardized boundary conditions to allow comparisons. Functional spatial units are derived next by aggregating functional point data. These units, which have successfully functioned as the basis for precision agriculture, do not necessarily correspond with Taxonomic units but when they do the Taxonomic names should be noted . At lower landscape and watershed scale ( 1:25.000 -1:50000) digital soil mapping can provide soil data for small grids that can be used for modeling, again through pedotransferfunctions. There is a risk, however, that digital mapping results in an isolated series of projects that don't increase the knowledge base on soil functionality, e.g.linking Taxonomic names ( such as soil series) to functionality, allowing predictions of soil behavior at new sites where certain soil series occur. We therefore suggest that aside from collecting 13 soil characteristics for each grid, as occurs in digital soil mapping, also the Taxonomic name of the representative soil in the grid is recorded. At spatial scales of 1:50000 and smaller, use of Taxonomic names becomes ever more attractive because at such small scales relations between soil types and landscape features become more pronounced. But in all cases, selection of procedures should not be science-based but based on the type of questions being asked including their level of generalization. These questions are quite different at the different spatial-scale levels and so should be the procedures.

Persistence of Rift Valley fever virus in East Africa

NASA Astrophysics Data System (ADS)

Gachohi, J.; Hansen, F.; Bett, B.; Kitala, P.

2012-04-01

Rift Valley fever virus (RVFv) is a mosquito-borne pathogen of livestock, wildlife and humans that causes severe outbreaks in intervals of several years. One of the open questions is how the virus persists between outbreaks. We developed a spatially-explicit, individual-based simulation model of the RVFv transmission dynamics to investigate this question. The model, is based on livestock and mosquito population dynamics. Spatial aspects are explicitly represented by a set of grid cells that represent mosquito breeding sites. A grid cell measures 500 by 500m and the model considers a grid of 100 by 100 grid cells; the model thus operates on the regional scale of 2500km2. Livestock herds move between grid cells, and provide connectivity between the cells. The model is used to explore the spatio-temporal dynamics of RVFv persistence in absence of a wildlife reservoir in an east African semi-arid context. Specifically, the model assesses the importance of local virus persistence in mosquito breeding sites relative to global virus persistence mitigated by movement of hosts. Local persistence is determined by the length of time the virus remains in a mosquito breeding site once introduced. In the model, this is a function of the number of mosquitoes that emerge infected and their lifespan. Global persistence is determined by the level of connectivity between isolated grid cells. Our work gives insights into the ecological and epidemiological conditions under which RVFv persists. The implication for disease surveillance and management are discussed.

Does topological information matter for power grid vulnerability?

PubMed

Ouyang, Min; Yang, Kun

2014-12-01

Power grids, which are playing an important role in supporting the economy of a region as well as the life of its citizens, could be attacked by terrorists or enemies to damage the region. Depending on different levels of power grid information collected by the terrorists, their attack strategies might be different. This paper groups power grid information into four levels: no information, purely topological information (PTI), topological information with generator and load nodes (GLNI), and full information (including component physical properties and flow parameters information), and then identifies possible attack strategies for each information level. Analyzing and comparing power grid vulnerability under these attack strategies from both terrorists' and utility companies' point of view give rise to an approach to quantify the relative values of these three types of information, including PTI, GLNI, and component parameter information (CPI). This approach can provide information regarding the extent to which topological information matters for power system vulnerability decisions. Taking several test systems as examples, results show that for small attacks with p ≤ 0.1, CPI matters the most; when taking attack cost into consideration and assuming that the terrorists take the optimum cost-efficient attack intensity, then CPI has the largest cost-based information value.

Does topological information matter for power grid vulnerability?

NASA Astrophysics Data System (ADS)

Ouyang, Min; Yang, Kun

2014-12-01

Power grids, which are playing an important role in supporting the economy of a region as well as the life of its citizens, could be attacked by terrorists or enemies to damage the region. Depending on different levels of power grid information collected by the terrorists, their attack strategies might be different. This paper groups power grid information into four levels: no information, purely topological information (PTI), topological information with generator and load nodes (GLNI), and full information (including component physical properties and flow parameters information), and then identifies possible attack strategies for each information level. Analyzing and comparing power grid vulnerability under these attack strategies from both terrorists' and utility companies' point of view give rise to an approach to quantify the relative values of these three types of information, including PTI, GLNI, and component parameter information (CPI). This approach can provide information regarding the extent to which topological information matters for power system vulnerability decisions. Taking several test systems as examples, results show that for small attacks with p ≤ 0.1, CPI matters the most; when taking attack cost into consideration and assuming that the terrorists take the optimum cost-efficient attack intensity, then CPI has the largest cost-based information value.

Unit Planning Grids for Visual Arts--Grade 9-12 Advanced.

ERIC Educational Resources Information Center

Delaware State Dept. of Education, Dover.

This planning grid for teaching visual arts (advanced) in grades 9-12 in Delaware outlines the following six standards for students to complete: (1) students will select and use form, media, techniques, and processes to create works of art and communicate meaning; (2) students will create ways to use visual, spatial, and temporal concepts in…

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.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou, China.

PubMed

Mao, Yingming; Sang, Shuxun; Liu, Shiqi; Jia, Jinlong

2014-05-01

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Spatially continuous interpolation of water stage and water depths using the Everglades depth estimation network (EDEN)

USGS Publications Warehouse

Pearlstine, Leonard; Higer, Aaron; Palaseanu, Monica; Fujisaki, Ikuko; Mazzotti, Frank

2007-01-01

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level monitoring, ground-elevation modeling, and water-surface modeling that provides scientists and managers with current (2000-present), online water-stage and water-depth information for the entire freshwater portion of the Greater Everglades. Continuous daily spatial interpolations of the EDEN network stage data are presented on a 400-square-meter grid spacing. EDEN offers a consistent and documented dataset that can be used by scientists and managers to (1) guide large-scale field operations, (2) integrate hydrologic and ecological responses, and (3) support biological and ecological assessments that measure ecosystem responses to the implementation of the Comprehensive Everglades Restoration Plan (CERP) The target users are biologists and ecologists examining trophic level responses to hydrodynamic changes in the Everglades.

Spatial distribution of sporocarps of stipitate hydnoid fungi and their belowground mycelium.

PubMed

van der Linde, Sietse; Alexander, Ian J; Anderson, Ian C

2009-09-01

Interest in stipitate hydnoid fungi of the genera Bankera, Hydnellum, Phellodon and Sarcodon has increased due to the decline in numbers of sporocarps in Europe. Conservation of these fungi is hindered by a lack of understanding of their basic ecology. In particular, a better understanding of their belowground ecology is required. Real-time PCR in conjunction with spatially explicit sampling was used to quantify the relationship between sporocarps and mycelium of Hydnellum peckii and Phellodon tomentosus. Species-specific DNA of the target species was quantified in 100 soil samples collected on a 360 x 360 cm grid at five locations where sporocarps were present. All sporocarps within the grid and up to 2 m around the grid were mapped. Sporocarp production did not occur over the whole extent of the belowground mycelium of these two species, and mycelium extended up to 330 cm away from the immediate site of sporocarp production. Spatial analyses using Kernel-smoothing and Moran's I correlograms showed that, with a single exception, there was no quantitative relationship between sporocarp distribution and the belowground abundance of mycelium. These findings have important implications for the conservation of this rare group of fungi.

Examination about the Spatial Representation of PM2.5 Obtained from Limited Stations Using a Network Observation

NASA Astrophysics Data System (ADS)

Shi, X.; Zhao, C.

2017-12-01

Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.

Research and design of smart grid monitoring control via terminal based on iOS system

NASA Astrophysics Data System (ADS)

Fu, Wei; Gong, Li; Chen, Heli; Pan, Guangji

2017-06-01

Aiming at a series of problems existing in current smart grid monitoring Control Terminal, such as high costs, poor portability, simple monitoring system, poor software extensions, low system reliability when transmitting information, single man-machine interface, poor security, etc., smart grid remote monitoring system based on the iOS system has been designed. The system interacts with smart grid server so that it can acquire grid data through WiFi/3G/4G networks, and monitor each grid line running status, as well as power plant equipment operating conditions. When it occurs an exception in the power plant, incident information can be sent to the user iOS terminal equipment timely, which will provide troubleshooting information to help the grid staff to make the right decisions in a timely manner, to avoid further accidents. Field tests have shown the system realizes the integrated grid monitoring functions, low maintenance cost, friendly interface, high security and reliability, and it possesses certain applicable value.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling

NASA Astrophysics Data System (ADS)

Sasai, T.; Murakami, K.; Kato, S.; Matsunaga, T.; Saigusa, N.; Hiraki, K.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. However, most studies, which aimed at the estimation of carbon exchanges between ecosystem and atmosphere, remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. In this study, we show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. As methodology for computing the exchanges, we 1) developed a global 1km-grid climate and satellite dataset based on the approach in Setoyama and Sasai (2013); 2) used the satellite-driven biosphere model (Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data: BEAMS) (Sasai et al., 2005, 2007, 2011); 3) simulated the carbon exchanges by using the new dataset and BEAMS by the use of a supercomputer that includes 1280 CPU and 320 GPGPU cores (GOSAT RCF of NIES). As a result, we could develop a global uniform system for realistically estimating terrestrial carbon exchange, and evaluate net ecosystem production in each community level; leading to obtain highly detailed understanding of terrestrial carbon exchanges.

Grid artifact reduction for direct digital radiography detectors based on rotated stationary grids with homomorphic filtering

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

Kim, Dong Sik; Lee, Sanggyun

2013-06-15

Purpose: Grid artifacts are caused when using the antiscatter grid in obtaining digital x-ray images. In this paper, research on grid artifact reduction techniques is conducted especially for the direct detectors, which are based on amorphous selenium. Methods: In order to analyze and reduce the grid artifacts, the authors consider a multiplicative grid image model and propose a homomorphic filtering technique. For minimal damage due to filters, which are used to suppress the grid artifacts, rotated grids with respect to the sampling direction are employed, and min-max optimization problems for searching optimal grid frequencies and angles for given sampling frequenciesmore » are established. The authors then propose algorithms for the grid artifact reduction based on the band-stop filters as well as low-pass filters. Results: The proposed algorithms are experimentally tested for digital x-ray images, which are obtained from direct detectors with the rotated grids, and are compared with other algorithms. It is shown that the proposed algorithms can successfully reduce the grid artifacts for direct detectors. Conclusions: By employing the homomorphic filtering technique, the authors can considerably suppress the strong grid artifacts with relatively narrow-bandwidth filters compared to the normal filtering case. Using rotated grids also significantly reduces the ringing artifact. Furthermore, for specific grid frequencies and angles, the authors can use simple homomorphic low-pass filters in the spatial domain, and thus alleviate the grid artifacts with very low implementation complexity.« less

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions

NASA Astrophysics Data System (ADS)

Oda, Tomohiro; Maksyutov, Shamil; Andres, Robert J.

2018-01-01

The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial-resolution gridded emissions data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emissions spatial distributions are estimated at a 1 × 1 km spatial resolution over land using power plant profiles (emissions intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emissions data product (ODIAC2016) and presents analyses that help guide data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emissions modeling framework in order to deliver a comprehensive global gridded emissions data product. Major changes from the 2011 publication are (1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring, and international aviation and marine bunkers); (2) the use of multiple spatial emissions proxies by fuel type such as (a) nighttime light data specific to gas flaring and (b) ship/aircraft fleet tracks; and (3) the inclusion of emissions temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emissions data product that covers 2000-2015. Our emissions data can be viewed as an extended version of CDIAC gridded emissions data product, which should allow data users to impose global fossil fuel emissions in a more comprehensive manner than the original CDIAC product. Our new emissions modeling framework allows us to produce future versions of the ODIAC emissions data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. The ODIAC data product could play an important role in supporting carbon cycle science, especially modeling studies with space-based CO2 data collected in near real time by ongoing carbon observing missions such as the Japanese Greenhouse gases Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory-2 (OCO-2), and upcoming future missions. The ODIAC emissions data product including the latest version of the ODIAC emissions data (ODIAC2017, 2000-2016) is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI (https://doi.org/10.17595/20170411.001).

Development of the Vista Methane Emissions Inventory for Southern California: A GIS-Based Approach for Mapping Methane Emissions

NASA Astrophysics Data System (ADS)

Carranza, V.; Frausto-Vicencio, I.; Rafiq, T.; Verhulst, K. R.; Hopkins, F. M.; Rao, P.; Duren, R. M.; Miller, C. E.

2016-12-01

Atmospheric methane (CH4) is the second most prevalent anthropogenic greenhouse gas. Improved estimates of CH4 emissions from cities is essential for carbon cycle science and climate mitigation efforts. Development of spatially-resolved carbon emissions data sets may offer significant advances in understanding and managing carbon emissions from cities. Urban CH4 emissions in particular require spatially resolved emission maps to help resolve uncertainties in the CH4 budget. This study presents a Geographic Information System (GIS)-based approach to mapping CH4 emissions using locations of infrastructure known to handle and emit methane. We constrain the spatial distribution of sources to the facility level for the major CH4 emitting sources in the South Coast Air Basin. GIS spatial modeling was combined with publicly available datasets to determine the distribution of potential CH4 sources. The datasets were processed and validated to ensure accuracy in the location of individual sources. This information was then used to develop the Vista emissions prior, which is a one-year long, spatially-resolved CH4 emissions estimate. Methane emissions were calculated and spatially allocated to produce 1 km x 1 km gridded CH4 emission map spanning the Los Angeles Basin. In future work, the Vista CH4 emissions prior will be compared with existing, coarser-resolution emissions estimates and will be evaluated in inverse modeling studies using atmospheric observations. The Vista CH4 emissions inventory presents the first detailed spatial maps of CH4 sources and emissions estimates in the Los Angeles Basin and is a critical step towards sectoral attribution of CH4 emissions at local to regional scales.

A Security Architecture for Grid-enabling OGC Web Services

NASA Astrophysics Data System (ADS)

Angelini, Valerio; Petronzio, Luca

2010-05-01

In the proposed presentation we describe an architectural solution for enabling a secure access to Grids and possibly other large scale on-demand processing infrastructures through OGC (Open Geospatial Consortium) Web Services (OWS). This work has been carried out in the context of the security thread of the G-OWS Working Group. G-OWS (gLite enablement of OGC Web Services) is an international open initiative started in 2008 by the European CYCLOPS , GENESI-DR, and DORII Project Consortia in order to collect/coordinate experiences in the enablement of OWS's on top of the gLite Grid middleware. G-OWS investigates the problem of the development of Spatial Data and Information Infrastructures (SDI and SII) based on the Grid/Cloud capacity in order to enable Earth Science applications and tools. Concerning security issues, the integration of OWS compliant infrastructures and gLite Grids needs to address relevant challenges, due to their respective design principles. In fact OWS's are part of a Web based architecture that demands security aspects to other specifications, whereas the gLite middleware implements the Grid paradigm with a strong security model (the gLite Grid Security Infrastructure: GSI). In our work we propose a Security Architectural Framework allowing the seamless use of Grid-enabled OGC Web Services through the federation of existing security systems (mostly web based) with the gLite GSI. This is made possible mediating between different security realms, whose mutual trust is established in advance during the deployment of the system itself. Our architecture is composed of three different security tiers: the user's security system, a specific G-OWS security system, and the gLite Grid Security Infrastructure. Applying the separation-of-concerns principle, each of these tiers is responsible for controlling the access to a well-defined resource set, respectively: the user's organization resources, the geospatial resources and services, and the Grid resources. While the gLite middleware is tied to a consolidated security approach based on X.509 certificates, our system is able to support different kinds of user's security infrastructures. Our central component, the G-OWS Security Framework, is based on the OASIS WS-Trust specifications and on the OGC GeoRM architectural framework. This allows to satisfy advanced requirements such as the enforcement of specific geospatial policies and complex secure web service chained requests. The typical use case is represented by a scientist belonging to a given organization who issues a request to a G-OWS Grid-enabled Web Service. The system initially asks the user to authenticate to his/her organization's security system and, after verification of the user's security credentials, it translates the user's digital identity into a G-OWS identity. This identity is linked to a set of attributes describing the user's access rights to the G-OWS services and resources. Inside the G-OWS Security system, access restrictions are applied making use of the enhanced Geospatial capabilities specified by the OGC GeoXACML. If the required action needs to make use of the Grid environment the system checks if the user is entitled to access a Grid infrastructure. In that case his/her identity is translated to a temporary Grid security token using the Short Lived Credential Services (IGTF Standard). In our case, for the specific gLite Grid infrastructure, some information (VOMS Attributes) is plugged into the Grid Security Token to grant the access to the user's Virtual Organization Grid resources. The resulting token is used to submit the request to the Grid and also by the various gLite middleware elements to verify the user's grants. Basing on the presented framework, the G-OWS Security Working Group developed a prototype, enabling the execution of OGC Web Services on the EGEE Production Grid through the federation with a Shibboleth based security infrastructure. Future plans aim to integrate other Web authentication services such as OpenID, Kerberos and WS-Federation.

Evaluating the Information Power Grid using the NAS Grid Benchmarks

NASA Technical Reports Server (NTRS)

VanderWijngaartm Rob F.; Frumkin, Michael A.

2004-01-01

The NAS Grid Benchmarks (NGB) are a collection of synthetic distributed applications designed to rate the performance and functionality of computational grids. We compare several implementations of the NGB to determine programmability and efficiency of NASA's Information Power Grid (IPG), whose services are mostly based on the Globus Toolkit. We report on the overheads involved in porting existing NGB reference implementations to the IPG. No changes were made to the component tasks of the NGB can still be improved.

Spatial heterogeneity in the carrying capacity of sika deer in Japan.

PubMed

Iijima, Hayato; Ueno, Mayumi

2016-06-09

Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area.

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

Tang, Q; Xie, S

This report describes the Atmospheric Radiation Measurement (ARM) Best Estimate (ARMBE) 2-dimensional (2D) gridded surface data (ARMBE2DGRID) value-added product. Spatial variability is critically important to many scientific studies, especially those that involve processes of great spatial variations at high temporal frequency (e.g., precipitation, clouds, radiation, etc.). High-density ARM sites deployed at the Southern Great Plains (SGP) allow us to observe the spatial patterns of variables of scientific interests. The upcoming megasite at SGP with its enhanced spatial density will facilitate the studies at even finer scales. Currently, however, data are reported only at individual site locations at different time resolutionsmore » for different datastreams. It is difficult for users to locate all the data they need and requires extra effort to synchronize the data. To address these problems, the ARMBE2DGRID value-added product merges key surface measurements at the ARM SGP sites and interpolates the data to a regular 2D grid to facilitate the data application.« less

The functional micro-organization of grid cells revealed by cellular-resolution imaging.

PubMed

Heys, James G; Rangarajan, Krsna V; Dombeck, Daniel A

2014-12-03

Establishing how grid cells are anatomically arranged, on a microscopic scale, in relation to their firing patterns in the environment would facilitate a greater microcircuit-level understanding of the brain's representation of space. However, all previous grid cell recordings used electrode techniques that provide limited descriptions of fine-scale organization. We therefore developed a technique for cellular-resolution functional imaging of medial entorhinal cortex (MEC) neurons in mice navigating a virtual linear track, enabling a new experimental approach to study MEC. Using these methods, we show that grid cells are physically clustered in MEC compared to nongrid cells. Additionally, we demonstrate that grid cells are functionally micro-organized: the similarity between the environment firing locations of grid cell pairs varies as a function of the distance between them according to a "Mexican hat"-shaped profile. This suggests that, on average, nearby grid cells have more similar spatial firing phases than those further apart. Copyright © 2014 Elsevier Inc. All rights reserved.

Status and understanding of groundwater quality in the northern San Joaquin Basin, 2005

USGS Publications Warehouse

Bennett, George L.; Fram, Miranda S.; Belitz, Kenneth; Jurgens, Bryant C.

2010-01-01

Groundwater quality in the 2,079 square mile Northern San Joaquin Basin (Northern San Joaquin) study unit was investigated from December 2004 through February 2005 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Project was developed in response to the Groundwater Quality Monitoring Act of 2001 that was passed by the State of California and is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory. The Northern San Joaquin study unit was the third study unit to be designed and sampled as part of the Priority Basin Project. Results of the study provide a spatially unbiased assessment of the quality of raw (untreated) groundwater, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 61 wells in parts of Alameda, Amador, Calaveras, Contra Costa, San Joaquin, and Stanislaus Counties; 51 of the wells were selected using a spatially distributed, randomized grid-based approach to provide statistical representation of the study area (grid wells), and 10 of the wells were sampled to increase spatial density and provide additional information for the evaluation of water chemistry in the study unit (understanding/flowpath wells). The primary aquifer systems (hereinafter, primary aquifers) assessed in this study are defined by the depth intervals of the wells in the California Department of Public Health database for each study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to contamination from the surface. Two types of assessments were made: (1) status, assessment of the current quality of the groundwater resource; and (2) understanding, identification of the natural and human factors affecting groundwater quality. Relative-concentrations (sample concentrations divided by benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. Benchmarks used in this study were either health-based (regulatory and non-regulatory) or aesthetic based (non-regulatory). For inorganic constituents, relative-concentrations were classified as high (equal to or greater than 1.0), indicating relative-concentrations greater than benchmarks; moderate (equal to or greater than 0.5, and less than 1.0); or, low (less than 0.5). For organic and special- interest constituents [1,2,3-trichloropropane (1,2,3-TCP), N-nitrosodimethylamine (NDMA), and perchlorate], relative- concentrations were classified as high (equal to or greater than 1.0); moderate (equal to or greater than 0.1 and less than 1.0); or, low (less than 0.1). Aquifer-scale proportion was used as the primary metric in the status assessment for groundwater quality. High aquifer- scale proportion is defined as the percentage of the primary aquifer with relative-concentrations greater than 1.0; moderate and low aquifer-scale proportions are defined as the percentage of the primary aquifer with moderate and low relative- concentrations, respectively. The methods used to calculate aquifer-scale proportions are based on an equal-area grid; thus, the proportions are areal rather than volumetric. Two statistical approaches - grid-based, which used one value per grid cell, and spatially weighted, which used the full dataset - were used to calculate aquifer-scale proportions for individual constituents and classes of constituents. The spatially weighted estimates of high aquifer-scale proportions were within the 90-percent confidence intervals of the grid-based estimates in all cases. The understanding assessment used statistical correlations between constituent relative-concentrations and

Navigation Patterns and Scent Marking: Underappreciated Contributors to Hippocampal and Entorhinal Spatial Representations?

PubMed

Lebedev, Mikhail A; Pimashkin, Alexey; Ossadtchi, Alexei

2018-01-01

According to the currently prevailing theory, hippocampal formation constructs and maintains cognitive spatial maps. Most of the experimental evidence for this theory comes from the studies on navigation in laboratory rats and mice, typically male animals. While these animals exhibit a rich repertoire of behaviors associated with navigation, including locomotion, head movements, whisking, sniffing, raring and scent marking, the contribution of these behavioral patterns to the hippocampal spatially-selective activity has not been sufficiently studied. Instead, many publications have considered animal position in space as the major variable that affects the firing of hippocampal place cells and entorhinal grid cells. Here we argue that future work should focus on a more detailed examination of different behaviors exhibited during navigation to better understand the mechanism of spatial tuning in hippocampal neurons. As an inquiry in this direction, we have analyzed data from two datasets, shared online, containing recordings from rats navigating in square and round arenas. Our analyses revealed patchy navigation patterns, evident from the spatial maps of animal position, velocity and acceleration. Moreover, grid cells available in the datasets exhibited similar periodicity as the navigation parameters. These findings indicate that activity of grid cells could affect navigation parameters and/or vice versa. Additionally, we speculate that scent marks left by navigating animals could contribute to neuronal responses while rats and mice sniff their environment; the act of sniffing could modulate neuronal discharges even in virtual visual environments. Accordingly, we propose that future experiments should contain additional controls for navigation patterns, whisking, sniffing and maps composed of scent marks.

Large Area Coverage of a TPC Endcap with GridPix Detectors

NASA Astrophysics Data System (ADS)

Kaminski, Jochen

2018-02-01

The Large Prototype TPC at DESY, Hamburg, was built by the LCTPC collaboration as a testbed for new readout technologies of Time Projection Chambers. Up to seven modules of about 400 cm2 each can be placed in the endcap. Three of these modules were equipped with a total of 160 GridPix detectors. This is a combination of a highly pixelated readout ASIC and a Micromegas built on top. GridPix detectors have a very high efficiency of detecting primary electrons, which leads to excellent spatial and energy resolutions. For the first time a large number of GridPix detectors has been operated and long segments of tracks have been recorded with excellent precision.

Spatial Data Exploring by Satellite Image Distributed Processing

NASA Astrophysics Data System (ADS)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands. Also this Web application does not require any kind of install for what the house-hold user is concerned. It is a remote application which may be accessed over the Internet. Currently the GreenLand application is available through the BSC-OS Portal provided by the enviroGRIDS FP7 project [3]. This presentation aims to highlight the challenges and issues of flexible description of the Grid based processing of satellite images, interoperability with other software platforms available in the portal, as well as the particular requirements of the Black Sea related use cases.

Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation.

PubMed

VoPham, Trang; Hart, Jaime E; Bertrand, Kimberly A; Sun, Zhibin; Tamimi, Rulla M; Laden, Francine

2016-11-24

Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model by downscaling from an area- to point-level spatial resolution using fine-scale ancillary data. A stratified ATP residual kriging approach was used to predict average July noon-time erythemal UV (UV Ery ) (mW/m 2 ) biennially from 1998 to 2012 by downscaling National Aeronautics and Space Administration (NASA) Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) gridded remote sensing images to a 1 km spatial resolution. Ancillary data were incorporated in random intercept linear mixed-effects regression models. Modeling was performed separately within nine U.S. regions to satisfy stationarity and account for locally varying associations between UV Ery and predictors. Cross-validation was used to compare ATP residual kriging models and NASA grids to UV-B Monitoring and Research Program (UVMRP) measurements (gold standard). Predictors included in the final regional models included surface albedo, aerosol optical depth (AOD), cloud cover, dew point, elevation, latitude, ozone, surface incoming shortwave flux, sulfur dioxide (SO 2 ), year, and interactions between year and surface albedo, AOD, cloud cover, dew point, elevation, latitude, and SO 2 . ATP residual kriging models more accurately estimated UV Ery at UVMRP monitoring stations on average compared to NASA grids across the contiguous U.S. (average mean absolute error [MAE] for ATP, NASA: 15.8, 20.3; average root mean square error [RMSE]: 21.3, 25.5). ATP residual kriging was associated with positive percent relative improvements in MAE (0.6-31.5%) and RMSE (3.6-29.4%) across all regions compared to NASA grids. ATP residual kriging incorporating fine-scale spatial predictors can provide more accurate, high-resolution UV Ery estimates compared to using NASA grids and can be used in epidemiologic studies examining the health effects of ambient UV.

Qualitative analysis of precipiation distribution in Poland with use of different data sources

NASA Astrophysics Data System (ADS)

Walawender, J.; Dyras, I.; Łapeta, B.; Serafin-Rek, D.; Twardowski, A.

2008-04-01

Geographical Information Systems (GIS) can be used to integrate data from different sources and in different formats to perform innovative spatial and temporal analysis. GIS can be also applied for climatic research to manage, investigate and display all kinds of weather data. The main objective of this study is to demonstrate that GIS is a useful tool to examine and visualise precipitation distribution obtained from different data sources: ground measurements, satellite and radar data. Three selected days (30 cases) with convective rainfall situations were analysed. Firstly, scalable GRID-based approach was applied to store data from three different sources in comparable layout. Then, geoprocessing algorithm was created within ArcGIS 9.2 environment. The algorithm included: GRID definition, reclassification and raster algebra. All of the calculations and procedures were performed automatically. Finally, contingency tables and pie charts were created to show relationship between ground measurements and both satellite and radar derived data. The results were visualised on maps.

Critical review: Uncharted waters? The future of the electricity-water nexus.

PubMed

Sanders, Kelly T

2015-01-06

Electricity generation often requires large amounts of water, most notably for cooling thermoelectric power generators and moving hydroelectric turbines. This so-called "electricity-water nexus" has received increasing attention in recent years by governments, nongovernmental organizations, industry, and academics, especially in light of increasing water stress in many regions around the world. Although many analyses have attempted to project the future water requirements of electricity generation, projections vary considerably due to differences in temporal and spatial boundaries, modeling frameworks, and scenario definitions. This manuscript is intended to provide a critical review of recent publications that address the future water requirements of electricity production and define the factors that will moderate the water requirements of the electric grid moving forward to inform future research. The five variables identified include changes in (1) fuel consumption patterns, (2) cooling technology preferences, (3) environmental regulations, (4) ambient climate conditions, and (5) electric grid characteristics. These five factors are analyzed to provide guidance for future research related to the electricity-water nexus.

Study on Global GIS architecture and its key technologies

NASA Astrophysics Data System (ADS)

Cheng, Chengqi; Guan, Li; Lv, Xuefeng

2009-09-01

Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.

Study on Global GIS architecture and its key technologies

NASA Astrophysics Data System (ADS)

Cheng, Chengqi; Guan, Li; Lv, Xuefeng

2010-11-01

Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.

Documentation of a spatial data-base management system for monitoring pesticide application in Washington

USGS Publications Warehouse

Schurr, K.M.; Cox, S.E.

1994-01-01

The Pesticide-Application Data-Base Management System was created as a demonstration project and was tested with data submitted to the Washington State Department of Agriculture by pesticide applicators from a small geographic area. These data were entered into the Department's relational data-base system and uploaded into the system's ARC/INFO files. Locations for pesticide applica- tions are assigned within the Public Land Survey System grids, and ARC/INFO programs in the Pesticide-Application Data-Base Management System can subdivide each survey section into sixteen idealized quarter-quarter sections for display map grids. The system provides data retrieval and geographic information system plotting capabilities from a menu of seven basic retrieval options. Additionally, ARC/INFO coverages can be created from the retrieved data when required for particular applications. The Pesticide-Application Data-Base Management System, or the general principles used in the system, could be adapted to other applica- tions or to other states.

Particle simulation of plasmas on the massively parallel processor

NASA Technical Reports Server (NTRS)

Gledhill, I. M. A.; Storey, L. R. O.

1987-01-01

Particle simulations, in which collective phenomena in plasmas are studied by following the self consistent motions of many discrete particles, involve several highly repetitive sets of calculations that are readily adaptable to SIMD parallel processing. A fully electromagnetic, relativistic plasma simulation for the massively parallel processor is described. The particle motions are followed in 2 1/2 dimensions on a 128 x 128 grid, with periodic boundary conditions. The two dimensional simulation space is mapped directly onto the processor network; a Fast Fourier Transform is used to solve the field equations. Particle data are stored according to an Eulerian scheme, i.e., the information associated with each particle is moved from one local memory to another as the particle moves across the spatial grid. The method is applied to the study of the nonlinear development of the whistler instability in a magnetospheric plasma model, with an anisotropic electron temperature. The wave distribution function is included as a new diagnostic to allow simulation results to be compared with satellite observations.

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

grid-model: Semi-numerical reionization code

NASA Astrophysics Data System (ADS)

Hutter, Anne

2018-05-01

grid-model computes the time and spatially dependent ionization of neutral hydrogen (HI), neutral (HeI) and singly ionized helium (HeII) in the intergalactic medium (IGM). It accounts for recombinations and provides different descriptions for the photoionization rate that are used to calculate the residual HI fraction in ionized regions. The ionizing emissivity is directly derived from the RT simulation spectra.

To Grid or Not to Grid… Precipitation Data and Hydrological Modeling in the Khangai Mountain Region of Mongolia

NASA Astrophysics Data System (ADS)

Venable, N. B. H.; Fassnacht, S. R.; Adyabadam, G.

2014-12-01

Precipitation data in semi-arid and mountainous regions is often spatially and temporally sparse, yet it is a key variable needed to drive hydrological models. Gridded precipitation datasets provide a spatially and temporally coherent alternative to the use of point-based station data, but in the case of Mongolia, may not be constructed from all data available from government data sources, or may only be available at coarse resolutions. To examine the uncertainty associated with the use of gridded and/or point precipitation data, monthly water balance models of three river basins across forest steppe (the Khoid Tamir River at Ikhtamir), steppe (the Baidrag River at Bayanburd), and desert steppe (the Tuin River at Bogd) ecozones in the Khangai Mountain Region of Mongolia were compared. The models were forced over a 10-year period from 2001-2010, with gridded temperature and precipitation data at a 0.5 x 0.5 degree resolution. These results were compared to modeling using an interpolated hybrid of the gridded data and additional point data recently gathered from government sources; and with point data from the nearest meteorological station to the streamflow gage of choice. Goodness-of-fit measures including the Nash-Sutcliff Efficiency statistic, the percent bias, and the RMSE-observations standard deviation ratio were used to assess model performance. The results were mixed with smaller differences between the two gridded products as compared to the differences between gridded products and station data. The largest differences in precipitation inputs and modeled runoff amounts occurred between the two gridded datasets and station data in the desert steppe (Tuin), and the smallest differences occurred in the forest steppe (Khoid Tamir) and steppe (Baidrag). Mean differences between water balance model results are generally smaller than mean differences in the initial input data over the period of record. Seasonally, larger differences in gridded versus station-based precipitation products and modeled outputs occur in summer in the desert-steppe, and in spring in the forest steppe. Choice of precipitation data source in terms of gridded or point-based data directly affects model outcomes with greater uncertainty noted on a seasonal basis across ecozones of the Khangai.

Intrapersonal, interpersonal, and physical space in anorexia nervosa: a virtual reality and repertory grid investigation.

PubMed

Cipolletta, Sabrina; Malighetti, Clelia; Serino, Silvia; Riva, Giuseppe; Winter, David

2017-06-01

Anorexia nervosa (AN) is an eating disorder characterized by severe body image disturbances. Recent studies from spatial cognition showed a connection between the experience of body and of space. The objectives of this study were to explore the meanings that characterize AN experience and to deepen the examination of spatiality in relational terms, through the study of how the patient construes herself and her interpersonal world. More specifically this study aimed (1) to verify whether spatial variables and aspects of construing differentiate patients with AN and healthy controls (HCs) and are related to severity of anorexic symptomatology; (2) to explore correlations between impairments in spatial abilities and interpersonal construing. A sample of 12 AN patients and 12 HCs participated in the study. The Eating Disorder Inventory, a virtual reality-based procedure, traditional measures of spatial abilities, and repertory grids were administered. The AN group compared to HCs showed significant impairments in spatial abilities, more unidimensional construing, and more extreme construing of the present self and of the self as seen by others. All these dimensions correlated with the severity of symptomatology. Extreme ways of construing characterized individuals with AN and might represent the interpersonal aspect of impairment in spatial reference frames. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

2012-12-01

ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

Military Cyberspace: From Evolution to Revolution

DTIC Science & Technology

2012-02-08

support the GCCs and enable USCYBERCOM to accomplish its mission? 15. SUBJECT TERMS Network Operations, Global Information Grid ( GIG ), Network...DATE: 08 February 2012 WORD COUNT: 5,405 PAGES: 30 KEY TERMS: Network Operations, Global Information Grid ( GIG ), Network Architecture...defense of the DOD global information grid ( GIG ). The DOD must pursue an enterprise approach to network management in the cyberspace domain to

Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

NASA Astrophysics Data System (ADS)

Hiebl, Johann; Frei, Christoph

2018-04-01

Spatial precipitation datasets that are long-term consistent, highly resolved and extend over several decades are an increasingly popular basis for modelling and monitoring environmental processes and planning tasks in hydrology, agriculture, energy resources management, etc. Here, we present a grid dataset of daily precipitation for Austria meant to promote such applications. It has a grid spacing of 1 km, extends back till 1961 and is continuously updated. It is constructed with the classical two-tier analysis, involving separate interpolations for mean monthly precipitation and daily relative anomalies. The former was accomplished by kriging with topographic predictors as external drift utilising 1249 stations. The latter is based on angular distance weighting and uses 523 stations. The input station network was kept largely stationary over time to avoid artefacts on long-term consistency. Example cases suggest that the new analysis is at least as plausible as previously existing datasets. Cross-validation and comparison against experimental high-resolution observations (WegenerNet) suggest that the accuracy of the dataset depends on interpretation. Users interpreting grid point values as point estimates must expect systematic overestimates for light and underestimates for heavy precipitation as well as substantial random errors. Grid point estimates are typically within a factor of 1.5 from in situ observations. Interpreting grid point values as area mean values, conditional biases are reduced and the magnitude of random errors is considerably smaller. Together with a similar dataset of temperature, the new dataset (SPARTACUS) is an interesting basis for modelling environmental processes, studying climate change impacts and monitoring the climate of Austria.

Development of flood routing simulation system of digital Qingjiang based on integrated spatial information technology

NASA Astrophysics Data System (ADS)

Yuan, Yanbin; Zhou, You; Zhu, Yaqiong; Yuan, Xiaohui; Sælthun, N. R.

2007-11-01

Based on digital technology, flood routing simulation system development is an important component of "digital catchment". Taking QingJiang catchment as a pilot case, in-depth analysis on informatization of Qingjiang catchment management being the basis, aiming at catchment data's multi-source, - dimension, -element, -subject, -layer and -class feature, the study brings the design thought and method of "subject-point-source database" (SPSD) to design system structure in order to realize the unified management of catchments data in great quantity. Using the thought of integrated spatial information technology for reference, integrating hierarchical structure development model of digital catchment is established. The model is general framework of the flood routing simulation system analysis, design and realization. In order to satisfy the demands of flood routing three-dimensional simulation system, the object-oriented spatial data model are designed. We can analyze space-time self-adapting relation between flood routing and catchments topography, express grid data of terrain by using non-directed graph, apply breadth first search arithmetic, set up search method for the purpose of dynamically searching stream channel on the basis of simulated three-dimensional terrain. The system prototype is therefore realized. Simulation results have demonstrated that the proposed approach is feasible and effective in the application.

Linear Look-Ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation

PubMed Central

Kubie, John L.; Fenton, André A.

2012-01-01

The crisp organization of the “firing bumps” of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed “linear look-ahead,” by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies on “rigid modules” of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-min walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: the pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look-ahead starting in any location and extending in any direction. We speculate that this process may: (1) compute linear paths to goals; (2) update grid cell firing during navigation; and (3) stabilize the rigid modules of grid cells and conjunctive cells. PMID:22557948

Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

2015-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively working with our Early Adopters to finalize content and format of this new, consistently-processed high-quality satellite passive microwave ESDR.

Grid Data Management and Customer Demands at MeteoSwiss

NASA Astrophysics Data System (ADS)

Rigo, G.; Lukasczyk, Ch.

2010-09-01

Data grids constitute the required input form for a variety of applications. Therefore, customers increasingly expect climate services to not only provide measured data, but also grids of these with the required configurations on an operational basis. Currently, MeteoSwiss is establishing a production chain for delivering data grids by subscription directly from the data warehouse in order to meet the demand for precipitation data grids by governmental, business and science customers. The MeteoSwiss data warehouse runs on an Oracle database linked with an ArcGIS Standard edition geodatabase. The grids are produced by Unix-based software written in R called GRIDMCH which extracts the station data from the data warehouse and stores the files in the file system. By scripts, the netcdf-v4 files are imported via an FME interface into the database. Currently daily and monthly deliveries of daily precipitation grids are available from MeteoSwiss with a spatial resolution of 2.2km x 2.2km. These daily delivered grids are a preliminary based on 100 measuring sites whilst the grid of the monthly delivery of daily sums is calculated out of about 430 stations. Crucial for the absorption by the customers is the understanding of and the trust into the new grid product. Clearly stating needs which can be covered by grid products, the customers require a certain lead time to develop applications making use of the particular grid. Therefore, early contacts and a continuous attendance as well as flexibility in adjusting the production process to fulfill emerging customer needs are important during the introduction period. Gridding over complex terrain can lead to temporally elevated uncertainties in certain areas depending on the weather situation and coverage of measurements. Therefore, careful instructions on the quality and use and the possibility to communicate the uncertainties of gridded data proofed to be essential especially to the business and science customers who require near-real-time datasets to build up trust in the product in different applications. The implementation of a new method called RSOI for the daily production allowed to bring the daily precipitation field up to the expectations of customers. The main use of the grids were near-realtime and past event analysis in areas scarcely covered with stations, and inputs for forecast tools and models. Critical success factors of the product were speed of delivery and at the same time accuracy, temporal and spatial resolution, and configuration (coordinate system, projection). To date, grids of archived precipitation data since 1961 and daily/monthly precipitation gridsets with 4h-delivery lag of Switzerland or subareas are available.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.

Development Considerations for the ICESat-2 ATL18 Terrain and Canopy Global Gridded Product

NASA Astrophysics Data System (ADS)

Pitts, K. L.; Neuenschwander, A. L.

2016-12-01

The ICESat-2 mission, expected to launch in late 2017 or early 2018, will provide estimates of terrain and canopy heights along the satellite ground track which will provide a significant benefit to society through a variety of applications ranging from improved global digital terrain models to mapping the distribution of above ground vegetation structure. Shortly after launch of ICESat-2, the Global Ecosystem Dynamics Investigation (GEDI) mission will be placed on the International Space Station (ISS) and will also derive terrain and canopy heights using laser altimetry for latitudes covered by the ISS. NASA's GEDI mission is designed to capture forest structure in densely covered regions over a period of 12-18 months. This study will present the factors required to produce a global gridded product that fuses information from both ICESat-2 and GEDI. The gridded values from ICESat-2 will be calculated from the along-track geodetic measurements of the terrain and relative canopy heights (ATL08), but considerations must be made on how best to combine ICESat-2 terrain and canopy height estimates with GEDI terrain and canopy height estimates. In particular, factors such as phenology, spatial and temporal resolution, surface interpolation methods, and error propagation are presented.

Uncertainty modelling and analysis of volume calculations based on a regular grid digital elevation model (DEM)

NASA Astrophysics Data System (ADS)

Li, Chang; Wang, Qing; Shi, Wenzhong; Zhao, Sisi

2018-05-01

The accuracy of earthwork calculations that compute terrain volume is critical to digital terrain analysis (DTA). The uncertainties in volume calculations (VCs) based on a DEM are primarily related to three factors: 1) model error (ME), which is caused by an adopted algorithm for a VC model, 2) discrete error (DE), which is usually caused by DEM resolution and terrain complexity, and 3) propagation error (PE), which is caused by the variables' error. Based on these factors, the uncertainty modelling and analysis of VCs based on a regular grid DEM are investigated in this paper. Especially, how to quantify the uncertainty of VCs is proposed by a confidence interval based on truncation error (TE). In the experiments, the trapezoidal double rule (TDR) and Simpson's double rule (SDR) were used to calculate volume, where the TE is the major ME, and six simulated regular grid DEMs with different terrain complexity and resolution (i.e. DE) were generated by a Gauss synthetic surface to easily obtain the theoretical true value and eliminate the interference of data errors. For PE, Monte-Carlo simulation techniques and spatial autocorrelation were used to represent DEM uncertainty. This study can enrich uncertainty modelling and analysis-related theories of geographic information science.

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

New multigrid approach for three-dimensional unstructured, adaptive grids

NASA Technical Reports Server (NTRS)

Parthasarathy, Vijayan; Kallinderis, Y.

1994-01-01

A new multigrid method with adaptive unstructured grids is presented. The three-dimensional Euler equations are solved on tetrahedral grids that are adaptively refined or coarsened locally. The multigrid method is employed to propagate the fine grid corrections more rapidly by redistributing the changes-in-time of the solution from the fine grid to the coarser grids to accelerate convergence. A new approach is employed that uses the parent cells of the fine grid cells in an adapted mesh to generate successively coaser levels of multigrid. This obviates the need for the generation of a sequence of independent, nonoverlapping grids as well as the relatively complicated operations that need to be performed to interpolate the solution and the residuals between the independent grids. The solver is an explicit, vertex-based, finite volume scheme that employs edge-based data structures and operations. Spatial discretization is of central-differencing type combined with a special upwind-like smoothing operators. Application cases include adaptive solutions obtained with multigrid acceleration for supersonic and subsonic flow over a bump in a channel, as well as transonic flow around the ONERA M6 wing. Two levels of multigrid resulted in reduction in the number of iterations by a factor of 5.

A Unified Framework for Periodic, On-Demand, and User-Specified Software Information

NASA Technical Reports Server (NTRS)

Kolano, Paul Z.

2004-01-01

Although grid computing can increase the number of resources available to a user; not all resources on the grid may have a software environment suitable for running a given application. To provide users with the necessary assistance for selecting resources with compatible software environments and/or for automatically establishing such environments, it is necessary to have an accurate source of information about the software installed across the grid. This paper presents a new OGSI-compliant software information service that has been implemented as part of NASA's Information Power Grid project. This service is built on top of a general framework for reconciling information from periodic, on-demand, and user-specified sources. Information is retrieved using standard XPath queries over a single unified namespace independent of the information's source. Two consumers of the provided software information, the IPG Resource Broker and the IPG Neutralization Service, are briefly described.

Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension

NASA Astrophysics Data System (ADS)

Szabó, S.; Bódis, K.; Huld, T.; Moner-Girona, M.

2011-07-01

Three rural electrification options are analysed showing the cost optimal conditions for a sustainable energy development applying renewable energy sources in Africa. A spatial electricity cost model has been designed to point out whether diesel generators, photovoltaic systems or extension of the grid are the least-cost option in off-grid areas. The resulting mapping application offers support to decide in which regions the communities could be electrified either within the grid or in an isolated mini-grid. Donor programs and National Rural Electrification Agencies (or equivalent governmental departments) could use this type of delineation for their program boundaries and then could use the local optimization tools adapted to the prevailing parameters. The views expressed in this paper are those of the authors and do not necessarily represent European Commission and UNEP policy.

Work step indication with grid-pattern projection for demented senior people.

PubMed

Uranishi, Yuki; Yamamoto, Goshiro; Asghar, Zeeshan; Pulli, Petri; Kato, Hirokazu; Oshiro, Osamu

2013-01-01

This paper proposes a work step indication method for supporting daily work with a grid-pattern projection. To support an independent life of demented senior people, it is desirable that an instruction is easy to understand visually and not complicated. The proposed method in this paper uses a range image sensor and a camera in addition to a projector. A 3D geometry of a target scene is measured by the range image sensor, and the grid-pattern is projected onto the scene directly. Direct projection of the work step is easier to be associated with the target objects around the assisted person, and the grid-pattern is a solution to indicate the spatial instruction. A prototype has been implemented and has demonstrated that the proposed grid-pattern projection is easy to show the work step.

Ray tracing a three dimensional scene using a grid

DOEpatents

Wald, Ingo; Ize, Santiago; Parker, Steven G; Knoll, Aaron

2013-02-26

Ray tracing a three-dimensional scene using a grid. One example embodiment is a method for ray tracing a three-dimensional scene using a grid. In this example method, the three-dimensional scene is made up of objects that are spatially partitioned into a plurality of cells that make up the grid. The method includes a first act of computing a bounding frustum of a packet of rays, and a second act of traversing the grid slice by slice along a major traversal axis. Each slice traversal includes a first act of determining one or more cells in the slice that are overlapped by the frustum and a second act of testing the rays in the packet for intersection with any objects at least partially bounded by the one or more cells overlapped by the frustum.

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.

Spatial resolution limits for the isotropic-3D PET detector X’tal cube

NASA Astrophysics Data System (ADS)

Yoshida, Eiji; Tashima, Hideaki; Hirano, Yoshiyuki; Inadama, Naoko; Nishikido, Fumihiko; Murayama, Hideo; Yamaya, Taiga

2013-11-01

Positron emission tomography (PET) has become a popular imaging method in metabolism, neuroscience, and molecular imaging. For dedicated human brain and small animal PET scanners, high spatial resolution is needed to visualize small objects. To improve the spatial resolution, we are developing the X’tal cube, which is our new PET detector to achieve isotropic 3D positioning detectability. We have shown that the X’tal cube can achieve 1 mm3 uniform crystal identification performance with the Anger-type calculation even at the block edges. We plan to develop the X’tal cube with even smaller 3D grids for sub-millimeter crystal identification. In this work, we investigate spatial resolution of a PET scanner based on the X’tal cube using Monte Carlo simulations for predicting resolution performance in smaller 3D grids. For spatial resolution evaluation, a point source emitting 511 keV photons was simulated by GATE for all physical processes involved in emission and interaction of positrons. We simulated two types of animal PET scanners. The first PET scanner had a detector ring 14.6 cm in diameter composed of 18 detectors. The second PET scanner had a detector ring 7.8 cm in diameter composed of 12 detectors. After the GATE simulations, we converted the interacting 3D position information to digitalized positions for realistic segmented crystals. We simulated several X’tal cubes with cubic crystals from (0.5 mm)3 to (2 mm)3 in size. Also, for evaluating the effect of DOI resolution, we simulated several X’tal cubes with crystal thickness from (0.5 mm)3 to (9 mm)3. We showed that sub-millimeter spatial resolution was possible using cubic crystals smaller than (1.0 mm)3 even with the assumed physical processes. Also, the weighted average spatial resolutions of both PET scanners with (0.5 mm)3 cubic crystals were 0.53 mm (14.6 cm ring diameter) and 0.48 mm (7.8 cm ring diameter). For the 7.8 cm ring diameter, spatial resolution with 0.5×0.5×1.0 mm3 crystals was improved 39% relative to the (1 mm)3 cubic crystals. On the other hand, spatial resolution with (0.5 mm)3 cubic crystals was improved 47% relative to the (1 mm)3 cubic crystals. The X’tal cube promises better spatial resolution for the 3D crystal block with isotropic resolution.

Image processing operations achievable with the Microchannel Spatial Light Modulator

NASA Astrophysics Data System (ADS)

Warde, C.; Fisher, A. D.; Thackara, J. I.; Weiss, A. M.

1980-01-01

The Microchannel Spatial Light Modulator (MSLM) is a versatile, optically-addressed, highly-sensitive device that is well suited for low-light-level, real-time, optical information processing. It consists of a photocathode, a microchannel plate (MCP), a planar acceleration grid, and an electro-optic plate in proximity focus. A framing rate of 20 Hz with full modulation depth, and 100 Hz with 20% modulation depth has been achieved in a vacuum-demountable LiTaO3 device. A halfwave exposure sensitivity of 2.2 mJ/sq cm and an optical information storage time of more than 2 months have been achieved in a similar gridless LiTaO3 device employing a visible photocathode. Image processing operations such as analog and digital thresholding, real-time image hard clipping, contrast reversal, contrast enhancement, image addition and subtraction, and binary-level logic operations such as AND, OR, XOR, and NOR can be achieved with this device. This collection of achievable image processing characteristics makes the MSLM potentially useful for a number of smart sensor applications.

Influences of traffic on Pb, Cu and Zn concentrations in roadside soils of an urban park in Dublin, Ireland.

PubMed

Dao, Ligang; Morrison, Liam; Zhang, Hongxuan; Zhang, Chaosheng

2014-06-01

Soils in the vicinity of roads are recipients of contaminants from traffic emissions. In order to obtain a better understanding of the impacts of traffic on soils, a total of 225 surface soil samples were collected from an urban park (Phoenix Park, Dublin, Ireland) in a grid system. Metal (Pb, Cu and Zn) concentrations were determined using a portable X-ray fluorescence analyzer. Strong spatial variations for the concentrations of Pb, Cu and Zn were observed. The spatial distribution maps created using geographical information system techniques revealed elevated metal concentrations close to the main traffic route in the park. The relationships between the accumulation of Pb, Cu and Zn in the roadside soils and the distance from the road were well fitted with an exponential model. Elevated metal concentrations from traffic pollution extended to a distance of approximately 40 m from the roadside. The results of this study provide useful information for the management of urban parks particularly in relation to policies aimed at reducing the impact of traffic related pollution on soils.

Transparent, conformable, active multielectrode array using organic electrochemical transistors.

PubMed

Lee, Wonryung; Kim, Dongmin; Matsuhisa, Naoji; Nagase, Masae; Sekino, Masaki; Malliaras, George G; Yokota, Tomoyuki; Someya, Takao

2017-10-03

Mechanically flexible active multielectrode arrays (MEA) have been developed for local signal amplification and high spatial resolution. However, their opaqueness limited optical observation and light stimulation during use. Here, we show a transparent, ultraflexible, and active MEA, which consists of transparent organic electrochemical transistors (OECTs) and transparent Au grid wirings. The transparent OECT is made of Au grid electrodes and has shown comparable performance with OECTs with nontransparent electrodes/wirings. The transparent active MEA realizes the spatial mapping of electrocorticogram electrical signals from an optogenetic rat with 1-mm spacing and shows lower light artifacts than noise level. Our active MEA would open up the possibility of precise investigation of a neural network system with direct light stimulation.

CHARACTERISTIC LENGTH SCALE OF INPUT DATA IN DISTRIBUTED MODELS: IMPLICATIONS FOR MODELING GRID SIZE. (R824784)

EPA Science Inventory

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model resp...

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

2002-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

A big data geospatial analytics platform - Physical Analytics Integrated Repository and Services (PAIRS)

NASA Astrophysics Data System (ADS)

Hamann, H.; Jimenez Marianno, F.; Klein, L.; Albrecht, C.; Freitag, M.; Hinds, N.; Lu, S.

2015-12-01

A big data geospatial analytics platform:Physical Analytics Information Repository and Services (PAIRS)Fernando Marianno, Levente Klein, Siyuan Lu, Conrad Albrecht, Marcus Freitag, Nigel Hinds, Hendrik HamannIBM TJ Watson Research Center, Yorktown Heights, NY 10598A major challenge in leveraging big geospatial data sets is the ability to quickly integrate multiple data sources into physical and statistical models and be run these models in real time. A geospatial data platform called Physical Analytics Information and Services (PAIRS) is developed on top of open source hardware and software stack to manage Terabyte of data. A new data interpolation and re gridding is implemented where any geospatial data layers can be associated with a set of global grid where the grid resolutions is doubling for consecutive layers. Each pixel on the PAIRS grid have an index that is a combination of locations and time stamp. The indexing allow quick access to data sets that are part of a global data layers and allowing to retrieve only the data of interest. PAIRS takes advantages of parallel processing framework (Hadoop) in a cloud environment to digest, curate, and analyze the data sets while being very robust and stable. The data is stored on a distributed no-SQL database (Hbase) across multiple server, data upload and retrieval is parallelized where the original analytics task is broken up is smaller areas/volume, analyzed independently, and then reassembled for the original geographical area. The differentiating aspect of PAIRS is the ability to accelerate model development across large geographical regions and spatial resolution ranging from 0.1 m up to hundreds of kilometer. System performance is benchmarked on real time automated data ingestion and retrieval of Modis and Landsat data layers. The data layers are curated for sensor error, verified for correctness, and analyzed statistically to detect local anomalies. Multi-layer query enable PAIRS to filter different data layers based on specific conditions (e.g analyze flooding risk of a property based on topography, soil ability to hold water, and forecasted precipitation) or retrieve information about locations that share similar weather and vegetation patterns during extreme weather events like heat wave.

First Gridded Spatial Field Reconstructions of Snow from Tree Rings

NASA Astrophysics Data System (ADS)

Coulthard, B. L.; Anchukaitis, K. J.; Pederson, G. T.; Alder, J. R.; Hostetler, S. W.; Gray, S. T.

2017-12-01

Western North America's mountain snowpacks provide critical water resources for human populations and ecosystems. Warmer temperatures and changing precipitation patterns will increasingly alter the quantity, extent, and persistence of snow in coming decades. A comprehensive understanding of the causes and range of long-term variability in this system is required for forecasting future anomalies, but snowpack observations are limited and sparse. While individual tree ring-based annual snowpack reconstructions have been developed for specific regions and mountain ranges, we present here the first collection of spatially-explicit gridded field reconstructions of seasonal snowpack within the American Rocky Mountains. Capitalizing on a new western North American snow-sensitive network of over 700 tree-ring chronologies, as well as recent advances in PRISM-based snow modeling, our gridded reconstructions offer a full space-time characterization of snow and associated water resource fluctuations over several centuries. The quality of reconstructions is evaluated against existing observations, proxy-records, and an independently-developed first-order monthly snow model.

Entropy-conservative spatial discretization of the multidimensional quasi-gasdynamic system of equations

NASA Astrophysics Data System (ADS)

Zlotnik, A. A.

2017-04-01

The multidimensional quasi-gasdynamic system written in the form of mass, momentum, and total energy balance equations for a perfect polytropic gas with allowance for a body force and a heat source is considered. A new conservative symmetric spatial discretization of these equations on a nonuniform rectangular grid is constructed (with the basic unknown functions—density, velocity, and temperature—defined on a common grid and with fluxes and viscous stresses defined on staggered grids). Primary attention is given to the analysis of entropy behavior: the discretization is specially constructed so that the total entropy does not decrease. This is achieved via a substantial revision of the standard discretization and applying numerous original features. A simplification of the constructed discretization serves as a conservative discretization with nondecreasing total entropy for the simpler quasi-hydrodynamic system of equations. In the absence of regularizing terms, the results also hold for the Navier-Stokes equations of a viscous compressible heat-conducting gas.

High resolution global gridded data for use in population studies

NASA Astrophysics Data System (ADS)

Lloyd, Christopher T.; Sorichetta, Alessandro; Tatem, Andrew J.

2017-01-01

Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.

High resolution global gridded data for use in population studies.

PubMed

Lloyd, Christopher T; Sorichetta, Alessandro; Tatem, Andrew J

2017-01-31

Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.

Mapping malaria risk and vulnerability in the United Republic of Tanzania: a spatial explicit model.

PubMed

Hagenlocher, Michael; Castro, Marcia C

2015-01-01

Outbreaks of vector-borne diseases (VBDs) impose a heavy burden on vulnerable populations. Despite recent progress in eradication and control, malaria remains the most prevalent VBD. Integrative approaches that take into account environmental, socioeconomic, demographic, biological, cultural, and political factors contributing to malaria risk and vulnerability are needed to effectively reduce malaria burden. Although the focus on malaria risk has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria risk including malaria vulnerability in a spatial explicit manner. Building on a conceptual risk and vulnerability framework, we propose a spatial explicit approach for modeling relative levels of malaria risk - as a function of hazard, exposure, and vulnerability - in the United Republic of Tanzania. A logistic regression model was employed to identify a final set of risk factors and their contribution to malaria endemicity based on multidisciplinary geospatial information. We utilized a Geographic Information System for the construction and visualization of a malaria vulnerability index and its integration into a spatially explicit malaria risk map. The spatial pattern of malaria risk was very heterogeneous across the country. Malaria risk was higher in Mainland areas than in Zanzibar, which is a result of differences in both malaria entomological inoculation rate and prevailing vulnerabilities. Areas of high malaria risk were identified in the southeastern part of the country, as well as in two distinct "hotspots" in the northwestern part of the country bordering Lake Victoria, while concentrations of high malaria vulnerability seem to occur in the northwestern, western, and southeastern parts of the mainland. Results were visualized using both 10×10 km(2) grids and subnational administrative units. The presented approach makes an important contribution toward a decision support tool. By decomposing malaria risk into its components, the approach offers evidence on which factors could be targeted for reducing malaria risk and vulnerability to the disease. Ultimately, results offer relevant information for place-based intervention planning and more effective spatial allocation of resources.

Regionalisation of statistical model outputs creating gridded data sets for Germany

NASA Astrophysics Data System (ADS)

Höpp, Simona Andrea; Rauthe, Monika; Deutschländer, Thomas

2016-04-01

The goal of the German research program ReKliEs-De (regional climate projection ensembles for Germany, http://.reklies.hlug.de) is to distribute robust information about the range and the extremes of future climate for Germany and its neighbouring river catchment areas. This joint research project is supported by the German Federal Ministry of Education and Research (BMBF) and was initiated by the German Federal States. The Project results are meant to support the development of adaptation strategies to mitigate the impacts of future climate change. The aim of our part of the project is to adapt and transfer the regionalisation methods of the gridded hydrological data set (HYRAS) from daily station data to the station based statistical regional climate model output of WETTREG (regionalisation method based on weather patterns). The WETTREG model output covers the period of 1951 to 2100 with a daily temporal resolution. For this, we generate a gridded data set of the WETTREG output for precipitation, air temperature and relative humidity with a spatial resolution of 12.5 km x 12.5 km, which is common for regional climate models. Thus, this regionalisation allows comparing statistical to dynamical climate model outputs. The HYRAS data set was developed by the German Meteorological Service within the German research program KLIWAS (www.kliwas.de) and consists of daily gridded data for Germany and its neighbouring river catchment areas. It has a spatial resolution of 5 km x 5 km for the entire domain for the hydro-meteorological elements precipitation, air temperature and relative humidity and covers the period of 1951 to 2006. After conservative remapping the HYRAS data set is also convenient for the validation of climate models. The presentation will consist of two parts to present the actual state of the adaptation of the HYRAS regionalisation methods to the statistical regional climate model WETTREG: First, an overview of the HYRAS data set and the regionalisation methods for precipitation (REGNIE method based on a combination of multiple linear regression with 5 predictors and inverse distance weighting), air temperature and relative humidity (optimal interpolation) will be given. Finally, results of the regionalisation of WETTREG model output will be shown.

Spatial properties of snow cover in the Upper Merced River Basin: implications for a distributed snow measurement network

NASA Astrophysics Data System (ADS)

Bouffon, T.; Rice, R.; Bales, R.

2006-12-01

The spatial distributions of snow water equivalent (SWE) and snow depth within a 1, 4, and 16 km2 grid element around two automated snow pillows in a forested and open- forested region of the Upper Merced River Basin (2,800 km2) of Yosemite National Park were characterized using field observations and analyzed using binary regression trees. Snow surveys occurred at the forested site during the accumulation and ablation seasons, while at the open-forest site a survey was performed only during the accumulation season. An average of 130 snow depth and 7 snow density measurements were made on each survey, within the 4 km2 grid. Snow depth was distributed using binary regression trees and geostatistical methods using the physiographic parameters (e.g. elevation, slope, vegetation, aspect). Results in the forest region indicate that the snow pillow overestimated average SWE within the 1, 4, and 16 km2 areas by 34 percent during ablation, but during accumulation the snow pillow provides a good estimate of the modeled mean SWE grid value, however it is suspected that the snow pillow was underestimating SWE. However, at the open forest site, during accumulation, the snow pillow was 28 percent greater than the mean modeled grid element. In addition, the binary regression trees indicate that the independent variables of vegetation, slope, and aspect are the most influential parameters of snow depth distribution. The binary regression tree and multivariate linear regression models explain about 60 percent of the initial variance for snow depth and 80 percent for density, respectively. This short-term study provides motivation and direction for the installation of a distributed snow measurement network to fill the information gap in basin-wide SWE and snow depth measurements. Guided by these results, a distributed snow measurement network was installed in the Fall 2006 at Gin Flat in the Upper Merced River Basin with the specific objective of measuring accumulation and ablation across topographic variables with the aim of providing guidance for future larger scale observation network designs.

Repeated surveys by acoustic Doppler current profiler for flow and sediment dynamics in a tidal river

USGS Publications Warehouse

Dinehart, R.L.; Burau, J.R.

2005-01-01

A strategy of repeated surveys by acoustic Doppler current profiler (ADCP) was applied in a tidal river to map velocity vectors and suspended-sediment indicators. The Sacramento River at the junction with the Delta Cross Channel at Walnut Grove, California, was surveyed over several tidal cycles in the Fall of 2000 and 2001 with a vessel-mounted ADCP. Velocity profiles were recorded along flow-defining survey paths, with surveys repeated every 27 min through a diurnal tidal cycle. Velocity vectors along each survey path were interpolated to a three-dimensional Cartesian grid that conformed to local bathymetry. A separate array of vectors was interpolated onto a grid from each survey. By displaying interpolated vector grids sequentially with computer animation, flow dynamics of the reach could be studied in three-dimensions as flow responded to the tidal cycle. Velocity streamtraces in the grid showed the upwelling of flow from the bottom of the Sacramento River channel into the Delta Cross Channel. The sequential display of vector grids showed that water in the canal briefly returned into the Sacramento River after peak flood tides, which had not been known previously. In addition to velocity vectors, ADCP data were processed to derive channel bathymetry and a spatial indicator for suspended-sediment concentration. Individual beam distances to bed, recorded by the ADCP, were transformed to yield bathymetry accurate enough to resolve small bedforms within the study reach. While recording velocity, ADCPs also record the intensity of acoustic backscatter from particles suspended in the flow. Sequential surveys of backscatter intensity were interpolated to grids and animated to indicate the spatial movement of suspended sediment through the study reach. Calculation of backscatter flux through cross-sectional grids provided a first step for computation of suspended-sediment discharge, the second step being a calibrated relation between backscatter intensity and sediment concentration. Spatial analyses of ADCP data showed that a strategy of repeated surveys and flow-field interpolation has the potential to simplify computation of flow and sediment discharge through complex waterways. The use of trade, product, industry, or firm names in this report is for descriptive purposes only and does not constitute endorsement of products by the US Government. ?? 2005 Elsevier B.V. All rights reserved.

Universal access to electricity in Burkina Faso: scaling-up renewable energy technologies

NASA Astrophysics Data System (ADS)

Moner-Girona, M.; Bódis, K.; Huld, T.; Kougias, I.; Szabó, S.

2016-08-01

This paper describes the status quo of the power sector in Burkina Faso, its limitations, and develops a new methodology that through spatial analysis processes with the aim to provide a possible pathway for universal electricity access. Following the SE4All initiative approach, it recommends the more extensive use of distributed renewable energy systems to increase access to electricity on an accelerated timeline. Less than 5% of the rural population in Burkina Faso have currently access to electricity and supply is lacking at many social structures such as schools and hospitals. Energy access achievements in Burkina Faso are still very modest. According to the latest SE4All Global Tracking Framework (2015), the access to electricity annual growth rate in Burkina Faso from 2010 to 2012 is 0%. The rural electrification strategy for Burkina Faso is scattered in several electricity sector development policies: there is a need of defining a concrete action plan. Planning and coordination between grid extension and the off-grid electrification programme is essential to reach a long-term sustainable energy model and prevent high avoidable infrastructure investments. This paper goes into details on the methodology and findings of the developed Geographic Information Systems tool. The aim of the dynamic planning tool is to provide support to the national government and development partners to define an alternative electrification plan. Burkina Faso proves to be paradigm case for the methodology as its national policy for electrification is still dominated by grid extension and the government subsidising fossil fuel electricity production. However, the results of our analysis suggest that the current grid extension is becoming inefficient and unsustainable in order to reach the national energy access targets. The results also suggest that Burkina Faso’s rural electrification strategy should be driven local renewable resources to power distributed mini-grids. We find that this approach would connect more people to power more quickly, and would reduce fossil fuel use that would otherwise be necessary for grid extension options.

Solar Integration Data Sets | Grid Modernization | NREL

Science.gov Websites

modeled solar data to study the operational impacts of solar on the electric power grid. Solar Power Data need to estimate power production from hypothetical solar power plants. Solar Integration National Dataset (SIND) Toolkit The next generation of modeled solar data with higher temporal and spatial