Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling

被引:23
|
作者
Morrison, William [1 ]
Yin, Tiangang [2 ]
Lauret, Nicolas [3 ]
Guilleux, Jordan [3 ]
Kotthaus, Simone [1 ,4 ]
Gastellu-Etchegorry, Jean-Philippe [3 ]
Norford, Leslie [5 ]
Grimmond, Sue [1 ]
机构
[1] Univ Reading, Dept Meteorol, Reading RG6 6BB, Berks, England
[2] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD USA
[3] Toulouse Univ, CESBIO, CNRS, CNES,IRD,UPS, Toulouse, France
[4] Ecole Polytech, IPSL, Palaiseau, France
[5] MIT, Dept Architecture, 77 Massachusetts Ave, Cambridge, MA 02139 USA
基金
英国工程与自然科学研究理事会; 欧盟地平线“2020”; 新加坡国家研究基金会;
关键词
Ground-based thermography; Atmospheric correction; Emissivity correction; 3D radiative transfer; Urban meteorology; DART; SURFACE-TEMPERATURE RETRIEVAL; URBAN ENERGY BUDGET; SKY VIEW FACTOR; THERMAL ANISOTROPY; GEOMETRIC MODEL; STREET CANYONS; BALANCE; NEIGHBORHOOD; VARIABILITY; SIMULATION;
D O I
10.1016/j.rse.2019.111524
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Methods to retrieve urban surface temperature (Ts) from remote sensing observations with sub-building scale resolution are developed using the Discrete Anisotropic Radiative Transfer (DART, Gastellu-Etchegorry et al., 2012) model. Corrections account for the emission and absorption of radiation by air between the surface and instrument (atmospheric correction), and for the reflected longwave infrared (LWIR) radiation from non-black-body surfaces ("emissivity" correction) within a single modelling framework. The atmospheric correction a) can use horizontally and vertically variable distributions of atmosphere properties at high resolution (<5 m); b) is applied here with vertically extrapolated weather observations and MODTRAN atmosphere profiles; and c) is a solution to ray tracing and cross section (e.g. absorption) conflicts (e.g. cross section needs the path length but it is typically unavailable during ray tracing). The emissivity correction resolves the reflection of LWIR radiation as a series of scattering events at high spatial (<1 m) and angular (Delta Omega approximate to 0.02 sr) resolution using a heterogeneous distribution of radiation leaving the urban surfaces. The method is applied to a novel network of seven ground-based cameras measuring LWIR radiation across a dense urban area (extent: 420 m x 420 m) where a detailed 3-dimensional representation of the surface and vegetation geometry is used. Our unique observation set allows the method to be tested over a range of realistic conditions as there are variations in: path lengths, view angles, brightness temperatures, atmospheric conditions and observed surface geometry. For pixels with 250 ( +/- 10) m path length the median (5th and 95th percentile) atmospheric correction magnitude is up to 4.5 (3.1 and 8.1) K at 10:10 on a mainly clear-sky day. The detailed surface geometry resolves camera pixel path lengths accurately, even with complex features such as sloped roofs. The atmospheric correction method evaluation, with simultaneous "near" (similar to 15 m) and "far" (similar to 155 m) observations, has a mean absolute error of 0.39 K. Using broadband approximations, the emissivity correction has clear diurnal variability, particularly when a cool and shaded surface (e.g. north facing) is irradiated by warmer (up to 17.0 K) surfaces (e.g. south facing). Varying the material emissivity with bulk values common for dark building materials (epsilon = 0.89 -> 0.97) alters the corrected roof (south facing) surface temperatures by similar to 3 (1.5) K, and the corrected cooler north facing surfaces by less than 0.1 K. Corrected observations, assuming a homogeneous radiation distribution from surfaces (analogous to a sky view factor correction), differ from a heterogeneous distribution by up to 0.25 K. Our proposed correction provides more accurate T-s observations with improved uncertainty estimates. Potential applications include ground-truthing airborne or space-borne surface temperatures and evaluation of urban energy balance models.
引用
收藏
页数:24
相关论文
共 50 条
  • [1] Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling
    Morrison, William
    Yin, Tiangang
    Lauret, Nicolas
    Guilleux, Jordan
    Kotthaus, Simone
    Gastellu-Etchegorry, Jean-Philippe
    Norford, Leslie
    Grimmond, Sue
    Remote Sensing of Environment, 2020, 237
  • [2] Development of a 3D atmospheric radiative transfer model
    Lu, Zhifeng
    Li, Ge
    Guo, Gang
    Huang, Kedi
    ACMOS '08: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL, MODELLING AND SIMULATION, 2008, : 35 - +
  • [3] Evaluation of a stochastic radiative transfer model using ground-based measurements
    Lane, DE
    Somerville, RCJ
    Iacobellis, SF
    IRS 2000: CURRENT PROBLEMS IN ATMOSPHERIC RADIATION, 2001, : 245 - 248
  • [4] Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer - Part 2: Local optimization
    Loveridge, Jesse
    Levis, Aviad
    Di Girolamo, Larry
    Holodovsky, Vadim
    Forster, Linda
    Davis, Anthony B.
    Schechner, Yoav Y.
    ATMOSPHERIC MEASUREMENT TECHNIQUES, 2023, 16 (16) : 3931 - 3957
  • [5] Radiative transfer .1. Atmospheric transmission monitoring with modeling and ground-based multispectral measurements
    Kambezidis, HD
    DjepaPetrova, V
    Adamopoulos, AD
    APPLIED OPTICS, 1997, 36 (27): : 6976 - 6982
  • [6] Radiative transfer in 3D
    Juvela, M
    Padoan, P
    SCIENCE WITH THE ATACAMA LARGE MILLIMETER ARRAY, 2001, 235 : 130 - 133
  • [7] MOCASSIN: 3D photoionisation and dust radiative transfer modelling of PNe
    Ercolano, Barbara
    Barlow, M. J.
    Storey, P. J.
    Liu, X. -W.
    PLANETARY NEBULAE BEYOND THE MILKY WAY, 2006, : 196 - +
  • [8] 3D mapping of optical turbulence using an atmospheric numerical model I. A useful tool for the ground-based astronomy
    Masciadri, E
    Vernin, J
    Bougeault, P
    ASTRONOMY & ASTROPHYSICS SUPPLEMENT SERIES, 1999, 137 (01): : 185 - 202
  • [9] 3D Vibration Estimation from Ground-Based Radar
    Monti-Guarnieri, Andrea
    Falcone, Paolo
    d'Aria, Davide
    Giunta, Giuseppe
    REMOTE SENSING, 2018, 10 (11):
  • [10] 3D cumulus cloud scene modelling and shadow analysis method based on ground-based sky images
    Chen, Yuxuan
    Chen, Jing
    Huang, Wumeng
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 109