The Effects of Tree Trunks on the Directional Emissivity and Brightness Temperatures of a Leaf-Off Forest Using a Geometric Optical Model

As a surface component, the tree trunk affects the top-of-canopy (TOC) emissivity and thermal infrared (TIR) radiance over a forest with fewer leaves, which is important for the inversion of land surface temperatures (LSTs) and further applications such as predicting forest fires and monitoring drought conditions. Therefore, the tree trunk effect was analyzed in this article using a thermal radiation directionality model, in which the forest structure was considered by the geometric optical (GO) theory and the spectral invariance theory was introduced into the GO framework for the single-scattering effect between components. The model used was evaluated using unmanned aerial vehicle (UAV)-based measurements with root-mean-square errors (RMSEs) lower than 0.25 °C for directional anisotropies (DAs) of brightness temperatures (BTs). Comparison with a 3-D radiative transfer model, discrete anisotropic radiative transfer (DART), also indicated an acceptable tool of the proposed model for the trunk effect with RMSEs lower than 0.003 °C and 1.2 °C for DAs of emissivity and BTs, respectively. In this study, the root-mean-squared difference (RMSD) levels between the vegetation–soil and vegetation–trunk–soil canopies, which were viewed as an equivalent indicator of the trunk effect, were provided for the TOC emissivity and BTs as well as their DAs, by combination with the changes in the leaf area index (LAI), stand density, trunk shape, and component temperatures, which can help identify the cases in which the trunk effect should be considered. According to a comprehensive analysis, for cases with sparse stand density ( $\boldsymbol {\alpha < 0.04}$ ), the tree trunk should be considered for a BT RMSD level lower than 0.5 °C when the LAI value was lower than 0.6. The corresponding LAI value was 0.8 for an RMSD level of BT DA lower than 0.3 °C. Moreover, for the cases with low soil emissivity, the difference in the TOC emissivity with and without trunk can reach up to 0.035, and the RMSD was still larger than 0.01 when the stand density and LAI were 0.05 and 0.6, respectively.

[1]  Zunjian Bian,et al.  Estimation of Upward Longwave Radiation From Vegetated Surfaces Considering Thermal Directionality , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Andres Kuusk,et al.  Improved algorithm for estimating canopy indices from gap fraction data in forest canopies , 2004 .

[3]  Frédéric Baret,et al.  Modeling directional brightness temperature over a maize canopy in row structure , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Zunjian Bian,et al.  A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives , 2019, Remote Sensing of Environment.

[5]  José A. Sobrino,et al.  Satellite-derived land surface temperature: Current status and perspectives , 2013 .

[6]  Wenjie Fan,et al.  The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) , 2015, PloS one.

[7]  Zunjian Bian,et al.  Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products Over Barren Surfaces in Northwestern China , 2021, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Jean-Pierre Lagouarde,et al.  A two parameter model to simulate thermal infrared directional effects for remote sensing applications , 2016 .

[9]  Mitchell D. Goldberg,et al.  Angular anisotropy of satellite observations of land surface temperature , 2012 .

[10]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[11]  José A. Sobrino,et al.  Canopy directional emissivity: Comparison between models , 2005 .

[12]  R. Myneni,et al.  Photon-vegetation interactions : applications in optical remote sensing and plant ecology , 1992 .

[13]  Zunjian Bian,et al.  Retrieval of Leaf, Sunlit Soil, and Shaded Soil Component Temperatures Using Airborne Thermal Infrared Multiangle Observations , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Jean-Philippe Gastellu-Etchegorry,et al.  Thermal infrared radiative transfer within three-dimensional vegetation covers , 2003 .

[15]  Eva Rubio,et al.  Emissivity measurements of several soils and vegetation types in the 8–14, μm Wave band: Analysis of two field methods , 1997 .

[16]  Mei Zhou,et al.  Using MODIS land surface temperature to evaluate forest fire risk of northeast China , 2004, IEEE Geosci. Remote. Sens. Lett..

[17]  Alan H. Strahler,et al.  An analytical hybrid GORT model for bidirectional reflectance over discontinuous plant canopies , 1999, IEEE Trans. Geosci. Remote. Sens..

[18]  Hua Li,et al.  A New Directional Canopy Emissivity Model Based on Spectral Invariants , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Jeffrey L. Privette,et al.  Directional effects in a daily AVHRR land surface temperature dataset over Africa , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Isabel F. Trigo,et al.  Assessing the potential of parametric models to correct directional effects on local to global remotely sensed LST , 2018 .

[21]  Sofia L. Ermida,et al.  Validation of remotely sensed surface temperature over an oak woodland landscape — The problem of viewing and illumination geometries , 2014 .

[22]  I. Wing,et al.  Net carbon uptake has increased through warming-induced changes in temperate forest phenology , 2014 .

[23]  L. Balick,et al.  Directional Thermal Infrared Exitance Distributions from a Leafless Deciduous Forest , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Hoam Chung,et al.  Adaptive Estimation of Crop Water Stress in Nectarine and Peach Orchards Using High-Resolution Imagery from an Unmanned Aerial Vehicle (UAV) , 2017, Remote. Sens..

[25]  Gérard Dedieu,et al.  Discrete Anisotropic Radiative Transfer (DART 5) for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes , 2015, Remote. Sens..

[26]  Ji Zhou,et al.  Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures , 2016 .

[27]  C. Woodcock,et al.  Modeling the hemispherical scanning, below-canopy lidar and vegetation structure characteristics with a geometric-optical and radiative-transfer model , 2008 .

[28]  V. Caselles,et al.  Influence of soil water content on the thermal infrared emissivity of bare soils: Implication for land surface temperature determination , 2007 .

[29]  Sigrid Netherer,et al.  Potential effects of climate change on insect herbivores in European forests - general aspects and the pine processionary moth as specific example. , 2010 .

[30]  Christophe François,et al.  The potential of directional radiometric temperatures for monitoring soil and leaf temperature and soil moisture status , 2002 .

[31]  A. Kuusk,et al.  A Directional Multispectral Forest Reflectance Model , 2000 .

[32]  Zunjian Bian,et al.  An analytical four-component directional brightness temperature model for crop and forest canopies , 2018 .

[33]  Guangjian Yan,et al.  Impact of sensor footprint on measurement of directional brightness temperature of row crop canopies , 2013 .

[34]  Hua Li,et al.  Modeling Directional Brightness Temperature Over Mixed Scenes of Continuous Crop and Road: A Case Study of the Heihe River Basin , 2015, IEEE Geoscience and Remote Sensing Letters.

[35]  N. Kiang,et al.  A clumped-foliage canopy radiative transfer model for a global dynamic terrestrial ecosystem model. I: Theory , 2010 .

[36]  J. Lagouarde,et al.  Experimental study of brightness surface temperature angular variations of maritime pine (Pinus pinaster) stands. , 2000 .

[37]  R. N. Sturrocka,et al.  Climate change and forest diseases , 2011 .

[38]  Jeffrey L. Privette,et al.  Modeling the observed angular anisotropy of land surface temperature in a Savanna , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[39]  Catherine Ottlé,et al.  Analytical parameterization of canopy directional emissivity and directional radiance in the thermal infrared. Application on the retrieval of soil and foliage temperatures using two directional measurements , 1997 .

[40]  Isabel F. Trigo,et al.  An assessment of remotely sensed land surface temperature , 2008 .

[41]  Sylvain G. Leblanc,et al.  A four-scale bidirectional reflectance model based on canopy architecture , 1997, IEEE Trans. Geosci. Remote. Sens..

[42]  R. Seager,et al.  Temperature as a potent driver of regional forest drought stress and tree mortality , 2013 .

[43]  José A. Sobrino,et al.  Thermal infrared radiance model for interpreting the directional radiometric temperature of a vegetative surface , 1990 .

[44]  Qiang Liu,et al.  Modeling Directional Brightness Temperature of the Winter Wheat Canopy at the Ear Stage , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Qing Xiao,et al.  Unified Optical-Thermal Four-Stream Radiative Transfer Theory for Homogeneous Vegetation Canopies , 2007, IEEE Transactions on Geoscience and Remote Sensing.