Modelling the variation of land surface temperature as determinant of risk of heat-related health events

<p>Abstract</p> <p>Background</p> <p>The evaluation of exposure to ambient temperatures in epidemiological studies has generally been based on records from meteorological stations which may not adequately represent local temperature variability. Here we propose a spatially explicit model to estimate local exposure to temperatures of large populations under various meteorological conditions based on satellite and meteorological data.</p> <p>Methods</p> <p>A general linear model was used to estimate surface temperatures using 15 LANDSAT 5 and LANDSAT 7 images for Quebec Province, Canada between 1987 and 2002 and spanning the months of June to August. The images encompassed both rural and urban landscapes and predictors included: meteorological records of temperature and wind speed, distance to major water bodies, Normalized Differential Vegetation Index (NDVI), land cover (built and bare land, water, or vegetation), latitude, longitude, and week of the year.</p> <p>Results</p> <p>The model explained 77% of the variance in surface temperature, accounting for both temporal and spatial variations. The standard error of estimates was 1.42°C. Land cover and NDVI were strong predictors of surface temperature.</p> <p>Conclusions</p> <p>This study suggests that a statistical approach to estimating surface temperature incorporating both spatially explicit satellite data and time-varying meteorological data may be relevant to assessing exposure to heat during the warm season in the Quebec. By allowing the estimation of space- and time-specific surface temperatures, this model may also be used to assess the possible impacts of land use changes under various meteorological conditions. It can be applied to assess heat exposure within a large population and at relatively fine-grained scale. It may be used to evaluate the acute health effect of heat exposure over long time frames. The method proposed here could be replicated in other areas around the globe for which satellite data and meteorological data is available.</p

Application of Airborne, Laboratory, and Field Hyperspectral Methods to Mineral Exploration in the Canadian Arctic: Recognition and Characterization of Volcanogenic Massive Sulfide-Associated Hydrothermal Alteration in the Izok Lake Deposit Area, Nunavut, Canada

We have investigated the application of ground, laboratory, and airborne optical remote sensing methods for the detection of hydrothermal alteration zones associated with the Izok Lake volcanogenic massive sulfide (VMS) deposit in Nunavut, Canada. This bimodal-felsic Zn-Cu-Pb-Ag deposit is located above the tree line in a subarctic environment where lichens are the dominant cryptogamic species coating the rocks. The immediate host rhyolitic rocks have been hydrothermally altered and contain biotite, chlorite, and white micas as dominant alteration minerals. These minerals have spectral Al-OH and Fe-OH absorption features in the shortwave infrared wavelength region that display wavelength shifts, which are documented to be due to chemical compositional changes. Our ground spectrometer measurements indicate that there is a systematic trend in the Fe-OH absorption feature wavelength position of biotite/chlorite with increasing distance from the VMS deposit: the average Fe-OH absorption feature wavelength position of the proximal areas (398–3,146 m from mineralization) is observed at 2,254 nm, and that of the distal areas (5,782–6,812 m) at 2,251 nm. Moreover, the proximal areas have an average Al-OH absorption feature wavelength position at 2,203 nm, in contrast with the average wavelength position at 2,201 nm in the distal areas, implying a spectral shift of 2 nm. These findings indicate that hydrothermal alteration zones can be detected by hyperspectral remote sensing, despite the presence of abundant lichen cover. However, the airborne results discussed in this study required the screening out of more than 99% of the pixels in the area