High-Resolution Semantic Segmentation of Woodland Fires Using Residual Attention UNet and Time Series of Sentinel-2

Southern Africa experiences a great number of wildfires, but the dependence on low-resolution products to detect and quantify fires means both that there is a time lag and that many small fire events are never identified. This is particularly relevant in miombo woodlands, where fires are frequent and predominantly small. We developed a cutting-edge deep-learning-based approach that uses freely available Sentinel-2 data for near-real-time, high-resolution fire detection in Mozambique. The importance of Sentinel-2 main bands and their derivatives was evaluated using TreeNet, and the top five variables were selected to create three training datasets. We designed a UNet architecture, including contraction and expansion paths and a bridge between them with several layers and functions. We then added attention gate units (AUNet) and residual blocks and attention gate units (RAUNet) to the UNet architecture. We trained the three models with the three datasets. The efficiency of all three models was high (intersection over union (IoU) > 0.85) and increased with more variables. This is the first time an RAUNet architecture has been used to detect fire events, and it performed better than the UNet and AUNet models-especially for detecting small fires. The RAUNet model with five variables had IoU = 0.9238 and overall accuracy = 0.985. We suggest that others test the RAUNet model with large datasets from different regions and other satellites so that it may be applied more broadly to improve the detection of wildfires.Peer reviewe

Tree biomass equations from terrestrial LiDAR : a case study in Guyana

Large uncertainties in tree and forest carbon estimates weaken national efforts to accurately estimate aboveground biomass (AGB) for their national monitoring, measurement, reporting and verification system. Allometric equations to estimate biomass have improved, but remain limited. They rely on destructive sampling; large trees are under-represented in the data used to create them; and they cannot always be applied to different regions. These factors lead to uncertainties and systematic errors in biomass estimations. We developed allometric models to estimate tree AGB in Guyana. These models were based on tree attributes (diameter, height, crown diameter) obtained from terrestrial laser scanning (TLS) point clouds from 72 tropical trees and wood density. We validated our methods and models with data from 26 additional destructively harvested trees. We found that our best TLS-derived allometric models included crown diameter, provided more accurate AGB estimates (R-2 = 0.92-0.93) than traditional pantropical models (R-2 = 0.85-0.89), and were especially accurate for large trees (diameter > 70 cm). The assessed pantropical models underestimated AGB by 4 to 13%. Nevertheless, one pantropical model (Chave et al. 2005 without height) consistently performed best among the pantropical models tested (R-2 = 0.89) and predicted AGB accurately across all size classes-which but for this could not be known without destructive or TLS-derived validation data. Our methods also demonstrate that tree height is difficult to measure in situ, and the inclusion of height in allometric models consistently worsened AGB estimates. We determined that TLS-derived AGB estimates were unbiased. Our approach advances methods to be able to develop, test, and choose allometric models without the need to harvest trees

The Discrete Representation of Continuously Moving Indeterminate Objects

AbstractTo incorporate indeterminacy in spatio-temporal database systems, grey modeling method is used for the calculations of the discrete models of indeterminate two dimension continuously moving objects. The Grey Model GM (1, 1) model generated from the snapshot sequence reduces the randomness of discrete snapshot and generates the holistic measure of object's movements. Comparisons to traditional linear models show that when information is limited this model can be used in the interpolation and near future prediction of uncertain continuously moving spatio-temporal objects

All-particle cosmic ray energy spectrum measured by the HAWC experiment from 10 to 500 TeV

We report on the measurement of the all-particle cosmic ray energy spectrum with the High Altitude Water Cherenkov (HAWC) Observatory in the energy range 10 to 500 TeV. HAWC is a ground based air-shower array deployed on the slopes of Volcan Sierra Negra in the state of Puebla, Mexico, and is sensitive to gamma rays and cosmic rays at TeV energies. The data used in this work were taken from 234 days between June 2016 to February 2017. The primary cosmic-ray energy is determined with a maximum likelihood approach using the particle density as a function of distance to the shower core. Introducing quality cuts to isolate events with shower cores landing on the array, the reconstructed energy distribution is unfolded iteratively. The measured all-particle spectrum is consistent with a broken power law with an index of $-2.49\pm0.01$ prior to a break at $(45.7\pm0.1$) TeV, followed by an index of $-2.71\pm0.01$. The spectrum also respresents a single measurement that spans the energy range between direct detection and ground based experiments. As a verification of the detector response, the energy scale and angular resolution are validated by observation of the cosmic ray Moon shadow's dependence on energy.Comment: 16 pages, 11 figures, 4 tables, submission to Physical Review

Very high energy particle acceleration powered by the jets of the microquasar SS 433

SS 433 is a binary system containing a supergiant star that is overflowing its Roche lobe with matter accreting onto a compact object (either a black hole or neutron star). Two jets of ionized matter with a bulk velocity of $\sim0.26c$ extend from the binary, perpendicular to the line of sight, and terminate inside W50, a supernova remnant that is being distorted by the jets. SS 433 differs from other microquasars in that the accretion is believed to be super-Eddington, and the luminosity of the system is $\sim10^{40}$ erg s$^{-1}$. The lobes of W50 in which the jets terminate, about 40 pc from the central source, are expected to accelerate charged particles, and indeed radio and X-ray emission consistent with electron synchrotron emission in a magnetic field have been observed. At higher energies (>100 GeV), the particle fluxes of $\gamma$ rays from X-ray hotspots around SS 433 have been reported as flux upper limits. In this energy regime, it has been unclear whether the emission is dominated by electrons that are interacting with photons from the cosmic microwave background through inverse-Compton scattering or by protons interacting with the ambient gas. Here we report TeV $\gamma$-ray observations of the SS 433/W50 system where the lobes are spatially resolved. The TeV emission is localized to structures in the lobes, far from the center of the system where the jets are formed. We have measured photon energies of at least 25 TeV, and these are certainly not Doppler boosted, because of the viewing geometry. We conclude that the emission from radio to TeV energies is consistent with a single population of electrons with energies extending to at least hundreds of TeV in a magnetic field of $\sim16$~micro-Gauss.Comment: Preprint version of Nature paper. Contacts: S. BenZvi, B. Dingus, K. Fang, C.D. Rho , H. Zhang, H. Zho

Measurement of the Crab Nebula Spectrum Past 100 TeV with HAWC

We present TeV gamma-ray observations of the Crab Nebula, the standard reference source in ground-based gamma-ray astronomy, using data from the High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory. In this analysis we use two independent energy-estimation methods that utilize extensive air shower variables such as the core position, shower angle, and shower lateral energy distribution. In contrast, the previously published HAWC energy spectrum roughly estimated the shower energy with only the number of photomultipliers triggered. This new methodology yields a much improved energy resolution over the previous analysis and extends HAWC's ability to accurately measure gamma-ray energies well beyond 100 TeV. The energy spectrum of the Crab Nebula is well fit to a log parabola shape $\left(\frac{dN}{dE} = \phi_0 \left(E/\textrm{7 TeV}\right)^{-\alpha-\beta\ln\left(E/\textrm{7 TeV}\right)}\right)$ with emission up to at least 100 TeV. For the first estimator, a ground parameter that utilizes fits to the lateral distribution function to measure the charge density 40 meters from the shower axis, the best-fit values are $\phi_o$=(2.35$\pm$0.04$^{+0.20}_{-0.21}$)$\times$10$^{-13}$ (TeV cm$^2$ s)$^{-1}$, $\alpha$=2.79$\pm$0.02$^{+0.01}_{-0.03}$, and $\beta$=0.10$\pm$0.01$^{+0.01}_{-0.03}$. For the second estimator, a neural network which uses the charge distribution in annuli around the core and other variables, these values are $\phi_o$=(2.31$\pm$0.02$^{+0.32}_{-0.17}$)$\times$10$^{-13}$ (TeV cm$^2$ s)$^{-1}$, $\alpha$=2.73$\pm$0.02$^{+0.03}_{-0.02}$, and $\beta$=0.06$\pm$0.01$\pm$0.02. The first set of uncertainties are statistical; the second set are systematic. Both methods yield compatible results. These measurements are the highest-energy observation of a gamma-ray source to date.Comment: published in Ap