Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network

Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery.We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool formapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale

Žrtvama palim za Hrvatsku

Remote sensing, geographical information systems (GIS) and spatial analysis provide important tools that are as yet under-exploited in the fight against disease. As the use of such tools becomes more accepted and prevalent in epidemiological studies, so our understanding of the mechanisms of disease systems has the potential to increase. This paper introduces a range of techniques used in remote sensing, GIS and spatial analysis that are relevant to epidemiology. Possible future directions for the application of remote sensing, GIS and spatial analysis are also suggested. <br/

Triplanar Model for the Gap and Penetration Depth in YBCO

YBaCuO_7 is a trilayer material with a unit cell consisting of a CuO_2 bilayer with a CuO plane of chains in between. Starting with a model of isolated planes coupled through a transverse matrix element, we consider the possibility of intra as well as interplane pairing within a nearly antiferromagnetic Fermi liquid model. Solutions of a set of three coupled BCS equations for the gap exhibit orthorhombic symmetry with s- as well as d-wave contributions. The temperature dependence and a-b in plane anisotropy of the resulting penetration depth is discussed and compared with experiment.Comment: To appear in Physical Review B1 01Mar97; 12 pages with 10 figures; RevTeX+eps

Spin current propagation through ultra-thin insulating layers in multilayered ferromagnetic systems

Spin current pumping from a ferromagnet through an insulating layer into a heavy metal was studied in a CoFeB/SiO2/Pt system in relation to the thickness and interfacial structure of the insulating layer. The propagation of spin current from the ferromagnet into the heavy metal falls rapidly with sub-nanometer thicknesses of SiO2 and is suppressed beyond a nominal thickness of 2 nm. Structural analysis shows that SiO2 only forms a complete barrier layer beyond around 2 nm, indicating that the presence of a discontinuous insulating barrier, and not tunneling or diffusion, explains the main observations of spin-pumping with thin insulating layers

Temperature dependence of non-linear electrical conduction behavior in a screen-printed multi-component nanocomposite

Nanocomposite materials are of growing applications importance in many areas, particularly touch sensitive surfaces. Here, current-voltage measurements were performed over a range of temperatures and static compressive loadings on a new variant of a multi-component, screen-printed nanocomposite ink, in order to understand the physical nature of the electrical transport behavior. A physical model, combining a linear percolative electrical conductance and a highly non-linear conductance, that is ascribed to field assisted quantum tunneling, was successful in describing the temperature dependence of the I-V. This provides a theoretical underpinning for conduction in these functional nanocomposites

Characterisation of Charge Conduction Networks in Poly(3-hexylthiophene)/Polystyrene Blends using Noise Spectroscopy

1/f noise spectroscopy is used to investigate charge conduction networks within polymer blend space-charge-limited diodes (SCLDs) fabricated from regioregular poly(3-hexylthiophene) (P3HT) and either isotactic-polystyrene (i-PS) or amorphous-polystyrene (a-PS). Conducting AFM measurements showed that i-PS blends have heterogeneous conduction characterised by current ‘hotspots’, whereas a-PS blends showed homogeneous conduction. The difference in conducting networks between blends was clearly revealed when examining the noise spectra for the range of blend devices. Furthermore, the shape of the noise spectra suggested that as the blend composition changed, the charges sampled differing breadths of the density of states. These data suggest that noise measurements can be used as an informative technique to electrically characterise the effects of blend morphology and its effects within polymer electronic devices

Vapor sensing properties of a conductive polymer composite containing Nickel particles with nano-scale surface features

This paper presents an unusual conductive polymer composite, produced by Peratech Ltd under the trademark QTC™, which has many vapor sensing applications. Nickel particles are intimately coated by an elastomeric binder such that no percolative conduction can occur. However, the nickel particles are shown to possess spiky nanoscale surface features, which promote conduction by a field-assisted quantum tunneling mechanism. Granular QTC™ can be dispersed into a polymer matrix to produce a vapor sensor. Under exposure to vapor, the polymer swells and the resistance of the composite increases. In this work, granular sensors are subjected to acetone and tetrahydrofuran (THF) vapors. The response for THF shows an increase in resistance of a factor of 108, over a time-scale of a few seconds. This response is larger and faster than many conventional vapor sensing composites. This is a significantly larger response than that obtained historically for the same sensor, suggesting that some degree of sensor aging is desirable. The response and subsequent recovery can be explained by a case II diffusion model, and linked to Hildebrand solubility parameters of the vapor and polymer components

Effect of Interband Transitions on the c axis Penetration Depth of Layered Superconductors

The electromagnetic response of a system with two planes per unit cell involves, in addition to the usual intraband contribution, an added interband term. These transitions affect the temperature dependence and the magnitude of the zero temperature c-axis penetration depth. When the interplane hopping is sufficiently small, the interband transitions dominate the low temperature behaviour of the penetration depth which then does not reflect the linear temperature dependence of the intraband term and in comparison becomes quite flat even for a d-wave gap. It is in this regime that the pseudogap was found in our previous normal state calculations of the c-axis conductivity, and the effects are connected.Comment: 8 pages, 5 figure

Microwave conductivity of YBa2_2Cu3_3O6.99_{6.99} including inelastic scattering

The fluctuation spectrum responsible for the inelastic scattering in YBa$_2$Cu$_3$O$_{6.99}$ which was recently determined from consideration of the in-plane optical conductivity in the infrared, is used to calculate the temperature dependence of the microwave conductivity at several measured frequencies. Reasonable overall agreement can only be achieved if, in addition, some impurity scattering is included within a model potential intermediate between weak (Born) and strong (unitary) limit.Comment: 15 pages, 5 figures accepted for publication in Phys. Rev.