Spatial interpolation of high-frequency monitoring data

Climate modelers generally require meteorological information on regular grids, but monitoring stations are, in practice, sited irregularly. Thus, there is a need to produce public data records that interpolate available data to a high density grid, which can then be used to generate meteorological maps at a broad range of spatial and temporal scales. In addition to point predictions, quantifications of uncertainty are also needed. One way to accomplish this is to provide multiple simulations of the relevant meteorological quantities conditional on the observed data taking into account the various uncertainties in predicting a space-time process at locations with no monitoring data. Using a high-quality dataset of minute-by-minute measurements of atmospheric pressure in north-central Oklahoma, this work describes a statistical approach to carrying out these conditional simulations. Based on observations at 11 stations, conditional simulations were produced at two other sites with monitoring stations. The resulting point predictions are very accurate and the multiple simulations produce well-calibrated prediction uncertainties for temporal changes in atmospheric pressure but are substantially overconservative for the uncertainties in the predictions of (undifferenced) pressure.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS208 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Fluorescence monitoring of capilarry electrophoresis separation in a lab-on-a-chip with monolithically integrated waveguides

Femtosecond-laser-written optical waveguides were monolithically integrated into a commercial lab-on-a-chip to intersect a microfluidic channel. Laser excitation through these waveguides confines the excitation window to a width of 12 μm, enabling high-spatial-resolution monitoring of different fluorescent analytes, during their migration/separation in the microfluidic channel by capillary electrophoresis. Wavelength-selective monitoring of the on-chip separation of fluorescent dyes is implemented as a proof-of-principle. We envision well-controlled microfluidic plug formation, waveguide excitation, and a low limit of detection to enable monitoring of extremely small quantities with high spatial resolution

Monitoring of Spatial Data Infraestructures

SDI monitoring and evaluation is increasingly attracting the attention of both public sector bureaucrats seeking justification for providing public sources to SDI and SDI practitioners requiring a measure of success of their SDI strategy. In recent years, a shift from an intuitive to more rational SDI assessments can be observed. SDI monitoring and evaluation is becoming operational and is already part of some SDI implementations and practices. Based on an analysis of the operational monitoring systems of the Dutch national SDI (GIDEON), the European SDI (INSPIRE) and the Catalan SDI (IDEC). We describe, analyze and compare comprehensively the design and application of operational SDI monitoring systems and identify common issues to be taken into account for monitoring of SDIs. This can support further improvement of evaluation practices and operational setups of SDI monitoring systems

A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

Species prioritization for monitoring and management in regional multiple species conservation plans.

Successful conservation plans are not solely achieved by acquiring optimally designed reserves. Ongoing monitoring and management of the biodiversity in those reserves is an equally important, but often neglected or poorly executed, part of the conservation process. In this paper we address one of the first and most important steps in designing a monitoring program - deciding what to monitor. We present a strategy for prioritizing species for monitoring and management in multispecies conservation plans. We use existing assessments of threatened status, and the degree and spatial and temporal extent of known threats to link the prioritization of species to the overarching goals and objectives of the conservation plan. We consider both broad and localized spatial scales to capture the regional conservation context and the practicalities of local management and monitoring constraints. Spatial scales that are commensurate with available data are selected. We demonstrate the utility of this strategy through application to a set of 85 plants and animals in an established multispecies conservation plan in San Diego County, California, USA. We use the prioritization to identify the most prominent risk factors and the habitats associated with the most threats to species. The protocol highlighted priorities that had not previously been identified and were not necessarily intuitive without systematic application of the criteria; many high-priority species have received no monitoring attention to date, and lower-priority species have. We recommend that in the absence of clear focal species, monitoring threats in highly impacted habitats may be a way to circumvent the need to monitor all the targeted species

Sentinel-2 Data Analysis and Comparison with UAV Multispectral Images for Precision Viticulture

Precision viticulture (PV) requires the use of technologies that can detect the spatial and temporal variability of vineyards and, at the same time, allow useful information to be obtained at sustainable costs. In order to develop a cheap and easy-to-handle operational monitoring scheme for PV, the aim of this work was to evaluate the possibility of using Sentinel-2 multispectral images for long-term vineyard monitoring through the Normalized Difference Vegetation Index (NDVI). Vigour maps of two vineyards located in northeastern Italy were computed from satellite imagery and compared with those derived from UAV multispectral images; their correspondence was evaluated from qualitative and statistical points of view. To achieve this, the UAV images were roughly resampled to 10 m pixel size in order to match the spatial resolution of the satellite imagery. Preliminary results show the potential use of open source Sentinel-2 platforms for monitoring vineyards, highlighting links with the information given in the agronomic bulletins and identifying critical areas for crop production. Despite the large differences in spatial resolution, the results of the comparison between the UAV and Sentinel-2 data were promising. However, for long-term vineyard monitoring at territory scale, further studies using multispectral sensor calibration and groundtruth data are required

Monitoring of Traffic Manoeuvres with Imprecise Information

In monitoring, we algorithmically check if a single behavior satisfies a property. Here, we consider monitoring for Multi-Lane Spatial Logic (MLSL). The behavior is given as a finite transition sequence of MLSL and the property is that a spatial MLSL formula should hold at every point in time within the sequence. In our procedure we transform the transition sequence and the formula to the first-order theory of real-closed fields, which is decidable, such that the resulting formula is valid iff the MLSL formula holds throughout the transition sequence. We then assume that temporal data may have an error of up to $\varepsilon$, and that spatial data may have an error of up to $\delta$. We extend our procedure to check if the MLSL formula $\varepsilon$-$\delta$-robustly holds throughout the transition sequence.Comment: In Proceedings FVAV 2017, arXiv:1709.0212

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets