New fire diurnal cycle characterizations to improve fire radiative energy assessments made from low-Earth orbit satellites sampling

Accurate near real time fire emissions estimates are required for air quality forecasts. To date, most approaches are based on satellite-derived estimates of fire radiative power (FRP), which can be converted to fire radiative energy (FRE) which is directly related to fire emissions. Uncertainties in these FRE estimations are often substantial. This is for a large part because the most often used low-Earth orbit satellite-based instruments like the MODerate-resolution Imaging Spectroradiometer (MODIS) have a relatively poor sampling of the usually pronounced fire diurnal cycle. In this paper we explore the spatial variation of this fire diurnal cycle and its drivers. Specifically, we assess how representing the fire diurnal cycle affects FRP and FRE estimations when using data collected at MODIS overpasses. Using data assimilation we explored three different methods to estimate hourly FRE, based on an incremental sophistication of parameterizing the fire diurnal cycle. We sampled data from the geostationary Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) at MODIS detection opportunities to drive the three approaches. The full SEVIRI time-series, providing full coverage of the diurnal cycle, were used to evaluate the results. Our study period comprised three years (2010–2012), and we focussed on Africa and the Mediterranean basin to avoid the use of potentially lower quality SEVIRI data obtained at very far off-nadir view angles. We found that the fire diurnal cycle varies substantially over the study region, and depends on both fuel and weather conditions. For example, more "intense" fires characterized by a fire diurnal cycle with high peak fire activity, long duration over the day, and with nighttime fire activity are most common in areas of large fire size (i.e., large burned area per fire event). These areas are most prevalent in relatively arid regions. Ignoring the fire diurnal cycle as done currently in some approaches caused structural errors, while generally overestimating FRE. Including information on the climatology of the fire diurnal cycle provided the most promising avenue to improve FRE estimations. This approach also improved the performance on relatively high spatiotemporal resolutions, although only when aggregating model results to coarser spatial and/or temporal scale good correlation was found with the full SEVIRI hourly reference dataset. In general model performance was best in areas of frequent fire and low errors of omission. We recommend the use of regionally varying fire diurnal cycle information within the Global Fire Assimilation System (GFAS) used in the Copernicus Atmosphere Monitoring Services, which will improve FRE estimates and may allow for further reconciliation of biomass burning emission estimates from different inventories

Arthroscopic hip labral repair: the iberian suture technique

Arthroscopic hip labral repair has beneficial short-term outcomes; however, debate exists regarding ideal surgical labral repair technique. This technical note presents an arthroscopic repair technique that uses intrasubstance labral suture passage to restore the chondrolabral interface. This Iberian suture technique allows for an anatomic repair while posing minimal risk of damage to the labral and chondral tissues

Radiometric calibration of ‘Commercial off the shelf’ cameras for UAV-based high-resolution temporal phenotyping of reflectance and NDVI

Vegetation indices, such as the Normalised Difference Vegetation Index (NDVI), are 13 common metrics used for measuring traits of interest in crop phenotyping. However traditional 14 measurements of these indices are often influenced by multiple confounding factors such as canopy 15 cover and reflectance of underlying soil, visible in canopy gaps. Digital cameras mounted to 16 Unmanned Aerial Vehicles offer the spatial resolution to investigate these confounding factors, 17 however incomplete methods for radiometric calibration into reflectance units limits how the data 18 can be applied to phenotyping. In this study, we assess the applicability of very high spatial 19 resolution (1cm) UAV-based imagery taken with commercial off the shelf (COTS) digital cameras 20 for both deriving calibrated reflectance imagery, and isolating vegetation canopy reflectance from 21 that of the underlying soil. We present new methods for successfully normalising the imagery for 22 exposure and solar irradiance effects, generating multispectral (RGB-NIR) orthomosaics of our 23 target field based wheat crop trial. Validation against measurements from a ground spectrometer 24 showed good results for reflectance (R2 ≥ 0.6) and NDVI (R2 ≥ 0.88). Application of imagery collected 25 through the growing season and masked using the Excess Green Red index was used to assess the 26 impact of canopy cover on NDVI measurements. Results showed the impact of canopy cover 27 artificially reducing plot NDVI values in the early season, where canopy development is low