(m,k)-Gur game: Exploiting message discards in order to increase the lifetime and spatial diversity in autonomic wireless sensor networks

The main concern in Wireless Sensor Networks (WSN) algorithms and protocols are the energy consumption. Thus, the WSN lifetime is one of the most important metric used to measure the performance of the WSN approaches. Another important metric is the WSN spatial coverage, where the main goal is to obtain sensed data in a uniform way. This paper has proposed an approach called (m,k)-Gur Game that aims a trade-off between quality of service and the increasement of spatial coverage diversity. Simulation results have shown the effectiveness of this approach. © 2012 IEEE.

AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients

Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Fast unsupervised extraction of endmembers spectra from hyperspectral data

Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.

Development of a satellite based PM10 concentration product for urban areas

Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente

Safety classification using GIS in decision-making process to define priority road interventions

Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.

Evaluación técnica de la red de encierre activada por buzos o bolichito de fondo

La “red de encierre activada por buzos” o “bolichito de fondo” es un arte de pesca que por sus características técnicas y de operación es clasificado como no determinado y no reglamentado. Se realizó una evaluación técnica de este arte de pesca, que indica que su cobertura espacial está limitada a la capacidad de buceo, restringida a zonas muy someras, presenta baja respuesta de selectividad y alto poder de pesca al compararla con otras artes de pesca artesanales utilizadas en la misma área costera; tiene elevada extracción de juveniles y de fauna acompañante los que generalmente están en mayores porcentajes de estadios inmaduros (II) y maduración inicial (III). Se recomienda prohibir su uso.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.

fNIRS-EEG study of focal interictal epileptiform discharges

Functional near-infrared spectroscopy (fNIRS) acquired with electroencephalography (EEG) is a relatively new non-invasive neuroimaging technique with potential for long term monitoring of the epileptic brain. Simultaneous EEG-fNIRS recording allows the spatio-temporal reconstruction of the hemodynamic response in terms of the concentration changes in oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) associated with recorded epileptic events such as interictal epileptic discharges (IEDs) or seizures. While most previous studies investigating fNIRS in epilepsy had limitations due to restricted spatial coverage and small sample sizes, this work includes a sufficiently large number of channels to provide an extensive bilateral coverage of the surface of the brain for a sample size of 40 patients with focal epilepsies. Topographic maps of significant activations due to each IED type were generated in four different views (dorsal, frontal, left and right) and were compared with the epileptic focus previously identified by an epileptologist. After excluding 5 patients due to the absence of IEDs and 6 more with mesial temporal foci too deep for fNIRS, we report that significant HbR (respectively HbO) concentration changes corresponding to IEDs were observed in 62% (resp. 38%) of patients with neocortical epilepsies. This HbR/HbO response was most significant in the epileptic focus region among all the activations in 28%/21% of patients.

Organic inputs and farmers' management strategies in millet fields of western Niger

Research on soil fertility management in sub-Saharan Africa was criticized lately for largely ignoring farmers’ management strategies and the underlying principles. To fill this gap of knowledge, detailed interviews were conducted with 108 farm households about their rationale in managing the soil fertility of 307 individual fields in the agro-pastoral village territory of Chikal in western Niger. To amplify the farmers’ information on manuring and corralling practices, repeated measurements of applied amounts of manure were carried out within six 1-km^2 monitoring areas from February to October 1998. The interviews revealed that only 2% of the fields were completely fallowed for a period of 1–15 years, but 40% of the fields were at least partially fallowed. Mulching of crop residues was mainly practiced to fight wind erosion but was restricted to 36% of the surveyed fields given the alternative use of straw as livestock feed. Manure application and livestock corralling, as most effective tools to enhance soil fertility, were targeted to less than 30% of the surveyed fields. The application of complete fallow and manuring and corralling practices were strongly related to the households’ endowment with resources, especially with land and livestock. Within particular fields, measures were mainly applied to spots of poor soil fertility, while the restoration of the productivity of hard pans was of secondary importance. Given the limited spatial coverage of indigenous soil fertility measures and their strong dependence on farmers’ wealth, supplementary strategies to restrict the decline of soil fertility in the drought prone areas of Niger with their heavily weathered soils are needed.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Estimating discharge from inundation imagery

Remote sensing from space-borne platforms is often seen as an appealing method of monitoring components of the hydrological cycle, including river discharge, due to its spatial coverage. However, data from these platforms is often less than ideal because the geophysical properties of interest are rarely measured directly and the measurements that are taken can be subject to significant errors. This study assimilated water levels derived from a TerraSAR-X synthetic aperture radar image and digital aerial photography with simulations from a two dimensional hydraulic model to estimate discharge, inundation extent, depths and velocities at the confluence of the rivers Severn and Avon, UK. An ensemble Kalman filter was used to assimilate spot heights water levels derived by intersecting shorelines from the imagery with a digital elevation model. Discharge was estimated from the ensemble of simulations using state augmentation and then compared with gauge data. Assimilating the real data reduced the error between analyzed mean water levels and levels from three gauging stations to less than 0.3 m, which is less than typically found in post event water marks data from the field at these scales. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows where gauge data are unavailable or of poor quality. Posterior estimates of discharge had standard deviations between 63.3 m3s-1 and 52.7 m3s-1, which were below 15% of the gauged flows along the reach. Therefore, assuming a roughness uncertainty of 0.03-0.05 and no model structural errors discharge could be estimated by the EnKF with accuracy similar to that arguably expected from gauging stations during flood events. Quality control prior to assimilation, where measurements were rejected for being in areas of high topographic slope or close to tall vegetation and trees, was found to be essential. The study demonstrates the potential, but also the significant limitations of currently available imagery to reduce discharge uncertainty in un-gauged or poorly gauged basins when combined with model simulations in a data assimilation framework.

A comparative study of satellite and ground-based phenology

Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

Interpreting Differential Temperature Trends at the Surface and in the Lower Troposphere

Estimated global-scale temperature trends at Earth's surface (as recorded by thermometers) and in the lower troposphere (as monitored by satellites) diverge by up to 0.14°C per decade over the period 1979 to 1998. Accounting for differences in the spatial coverage of satellite and surface measurements reduces this differential, but still leaves a statistically significant residual of roughly 0.1°C per decade. Natural internal climate variability alone, as simulated in three state-of-the-art coupled atmosphere-ocean models, cannot completely explain this residual trend difference. A model forced by a combination of anthropogenic factors and volcanic aerosols yields surface-troposphere temperature trend differences closest to those observed.

Correlations of long-lived chemical species in a middle atmosphere general circulation model

Correlations between various chemical species simulated by the Canadian Middle Atmosphere Model, a general circulation model with fully interactive chemistry, are considered in order to investigate the general conditions under which compact correlations can be expected to form. At the same time, the analysis serves to validate the model. The results are compared to previous work on this subject, both from theoretical studies and from atmospheric measurements made from space and from aircraft. The results highlight the importance of having a data set with good spatial coverage when working with correlations and provide a background against which the compactness of correlations obtained from atmospheric measurements can be confirmed. It is shown that for long-lived species, distinct correlations are found in the model in the tropics, the extratropics, and the Antarctic winter vortex. Under these conditions, sparse sampling such as arises from occultation instruments is nevertheless suitable to define a chemical correlation within each region even from a single day of measurements, provided a sufficient range of mixing ratio values is sampled. In practice, this means a large vertical extent, though the requirements are less stringent at more poleward latitudes.