To assess the value of satellite photographs in resource evaluation on a national scale

The author has identified the following significant results. The limit of resolution on ERTS imagery is normally acknowledged to be about 60 miles although very long features such as roads and railways which are often less than 10 miles long are easily detectable. An example is the north-south road and railway from Lobatse to Francistown. Vegetation growth from winter to summer is readily monitored on false color imagery. The limits of government ranches and special farming areas can be quite accurately ascertained from ERTS imagery. Another aspect to which ERTS imagery lends itself is the location and demarcation of bush fires, many of which were seen on the first imagery which was acquired at the end of the cold, dry season. As a whole, MSS 7 offers maximum reflectance contrast among black and white imagery and is the wavelength used most for interpretation

To assess the value of satellite photographs in resource evaluation on a national scale

The author has identified the following significant results. Small scale ERTS-1 imagery has enabled investigators to study large areas at a time. The imagery appears to confirm a new theory that Archean greenstone belts in NE Botswanna and SW Rhodesia are co-extensive and that these so-called schist relics formerly covered a much wider area than is apparent now. The central parts of the region bounded by the schist relics are believed to have suffered granitization. A remnant of an older drainage system to the southwest of the Okavango Swamps, which seems to have been newly discovered on the imagery, may be an indication of the seismic instability of the region. Even quite small earth movements in the swamps could radically affect the direction of water flow. The imagery has proved successful in showing areas infested by the water weed Salvinia Auriculata in the Chobe and Zambesi rivers. This will be immensely valuable in later surveys on the ground. If the satellite was to have continued working, the imagery would have enabled workers to determine the extent of encroachment of the weed without recourse to field observations

Categorifying the magnitude of a graph

The magnitude of a graph can be thought of as an integer power series associated to a graph; Leinster introduced it using his idea of magnitude of a metric space. Here we introduce a bigraded homology theory for graphs which has the magnitude as its graded Euler characteristic. This is a categorification of the magnitude in the same spirit as Khovanov homology is a categorification of the Jones polynomial. We show how properties of magnitude proved by Leinster categorify to properties such as a Kunneth Theorem and a Mayer-Vietoris Theorem. We prove that joins of graphs have their homology supported on the diagonal. Finally, we give various computer calculated examples

Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures.

Traditionally, Special Nuclear Material (SNM) at Sellafield has been stored in multi-layered packages, consisting of metallic cans and an over-layer of plasticized Polyvinyl Chloride (PVC) as an intermediate layer when transitioning between areas of different radiological classification. However, it has been found that plasticized PVC can break down in the presence of both radiation and heat, releasing hydrochloric acid which can corrode these metallic containers. Therefore, internal repackaging procedures at Sellafield have focused recently on the removal of these PVC films from containers, where as much degraded and often adhered PVC as possible is manually removed based on visual inspection. This manual operation is time-consuming and it is possible that residual fragments of PVC could remain, leading to corrosion-related issues in future. In this work, Hyperspectral Imaging (HSI) was evaluated as a new tool for detecting PVC on metallic surfaces. Samples of stainless steel type 1.4404 – also known as 316L, the same as is used to construct SNM cans – and PVC were imaged in our experiments, and Support Vector Machine (SVM) classification models were used to generate detection maps. In these maps, pixels were classified into either PVC or 316L based on their spectral responses in the range 954-1700nm of the electromagnetic spectrum. Results suggest that HSI could be used for an effective automated detection and quantification of PVC during repackaging procedures, detection and quantification that could be extended to other similar applications

Systematic Assessment of the Climate Sensitivity of Important Human and Domestic Animals Pathogens in Europe

Climate change is expected to threaten human health and well-being via its effects on climate-sensitive infectious diseases, potentially changing their spatial distributions, affecting annual/seasonal cycles, or altering disease incidence and severity. Climate sensitivity of pathogens is a key indicator that diseases might respond to climate change, but the proportion of pathogens that is climate-sensitive, and their characteristics, are not known. The climate sensitivity of European human and domestic animal infectious pathogens, and the characteristics associated with sensitivity, were assessed systematically in terms of selection of pathogens and choice of literature reviewed. Sixty-three percent (N = 157) of pathogens were climate sensitive; 82% to primary drivers such as rainfall and temperature. Protozoa and helminths, vector-borne, foodborne, soilborne and waterborne transmission routes were associated with larger numbers of climate drivers. Zoonotic pathogens were more climate sensitive than human- or animal-only pathogens. Thirty-seven percent of disability-adjusted-life-years arise from human infectious diseases that are sensitive to primary climate drivers. These results help prioritize surveillance for pathogens that may respond to climate change. Although this study identifies a high degree of climate sensitivity among important pathogens, their response to climate change will be dependent on the nature of their association with climate drivers and impacts of other drivers

Chesapeake Bay wave climate : Thimble Shoals wave station, report and summary of wave observations, September 27, 1988 through October 17, 1989

The Virginia Institute of Marine Science, in cooperation with the Virginia Department of Conservation and Recreation, Division of Soil and Water Conservation, has identified as one of its major goals the systematic study of hydrodynamic processes that affect recreational, shoreline and benthic resources in the coastal zone of the Commonwealth. In pursuit of that goal, a long-term study of the wave climate in the Virginia portion of Chesapeake Bay was initiated in 1988 with support from the National Oceanographic and Atmospheric Administration through the Coastal Zone Management Program administered by the Virginia Council on the Environment (Grant Ho. HA88AA-D-CZ092). Past knowledge of wave properties in the Chesapeake Bay region has been conspicuous in its lack of an observational basis. Although inner shelf and deep water wave measurements have been made outside the Chesapeake Bay entrance, none of these have produced reliable directional information (Seymour et al., 1985). Therefore, before addressing certain long-term wave monitoring objectives, it was deemed essential to develop a basis for them by obtaining a representative (year-long) series of wave observations at one or more selected locations. The first of these has recently been completed for a station designated as VIMS BAY! located near Thimble Shoals to the west of the Chesapeake Bay entrance (Fig. 1). This report contains a summary of data for the initial year of continuous directional wave measurements made at the Thimble Shoals station

Least Economic Cost Regional Water Supply Planning – Optimising Infrastructure Investments and Demand Management for South East England’s 17.6 Million People

This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, demand management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for demand management schemes are allowed. Multiple water demand scenarios are considered simultaneously to ensure the supply–demand balance is preserved across high demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the ‘Water Resources in the South East’ stakeholder group to select which of the 316 available supply schemes (including imports) and 511 demand management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows demand management options can play a significant role in the region’s water supply and should be considered alongside new supplies and regional transfers. Considering demand management schemes reduced overall total discounted economic costs by 10 % and removed two large reservoirs from the least-cost plan. This case-study optimisation model was built using a generalised data management software platform and solved using a mixed integer linear programme