地球科学进展 ›› 2018, Vol. 33 ›› Issue (6): 555 -567. doi: 10.11867/j.issn.1001-8166.2018.06.0555

综述与评述    下一篇

广义地表热辐射方向性计算机模拟研究进展
陈云浩 1( ), 吴佳桐 2, *( ), 王丹丹 2   
  1. 1.环境遥感与数字城市北京市重点实验室,北京师范大学地理科学学部,北京 100875
    2.地理学院,北京师范大学地理科学学部,北京 100875
  • 收稿日期:2017-11-30 修回日期:2018-04-06 出版日期:2018-06-20
  • 通讯作者: 吴佳桐 E-mail:cyh@bnu.edu.cn;201521190029@mail.bnu.edu.cn
  • 基金资助:
    *国家自然科学基金项目“城市下垫面热辐射方向性的多尺度几何模型”(编号:41471348)和“面向城市场景的地表等效发射率方向性差异核驱动模型”(编号:41771448)资助.

Review of the Study on Generalized Computer Simulation of Land Surface Thermal Anisotropy

Yunhao Chen 1( ), Jiatong Wu 2, *( ), Dandan Wang 2   

  1. 1.Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    2 .School of Geography, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2017-11-30 Revised:2018-04-06 Online:2018-06-20 Published:2018-07-23
  • Contact: Jiatong Wu E-mail:cyh@bnu.edu.cn;201521190029@mail.bnu.edu.cn
  • About author:

    First author: Chen Yunhao(1974-), male, Guzhen County, Anhui Province, Professor. Research areas include application of remote sensing in resource. E-mail:cyh@bnu.edu.cn

  • Supported by:
    Project supported by the National Natural Science Foundation of China “A muli-scale geometric model for urban thermal anisotropy”(No.41471348) and “Surface-driven emissivity directivity difference nuclear drive model for urban scenes” (No.41771448).

地表温度反映了地球表面的能量变化与交换过程,是研究地球科学的一个重要指标。地表的几何结构和组分温度差异是地表热辐射在不同方向上存在差异性的主要原因,因此,大部分陆面都存在不同程度的热辐射方向性。介绍了广义热辐射方向性计算机模型的研究方法和研究现状,并从模型特点、模拟对象、模拟精度和时间复杂度等方面对常见模型进行评价,评述了耦合气候模型和地表热辐射方向性模型进行热辐射方向性研究中的应用情况,指出该领域尚未解决的问题并对未来的研究方向进行了展望。

Land surface temperature reflects the energy change and exchange process of land surface, which is an important index of the study on Earth science. The differences of surface geometrical structure and morphology are the main reasons for directional thermal radiant anisotropy. Therefore, there is thermal radiant directionality on most land surfaces in some degrees. The research methods and research status of the generalized thermal radiation directivity computer model were introduced. The common models were evaluated from the characteristics of the model, simulation objects, simulation accuracy and time complexity. The coupled climate model, the surface radiation directivity model and the application of radiation directionality were reviewed. The unsolved problems and the future research direction in this field were pointed.

中图分类号: 

图1 热辐射方向模拟领域的受关注状况
(a)每年发表的与热辐射方向性模拟有关的文献数量;(b)自1997年以来与热辐射方向性模拟
文献引用数(来自Web of Science 核心期刊,数据统计截止到2017年9月20日),文献的总引用次数为2 629次
Fig.1 Concern of computer simulation of thermal anisotropy
(a) Yearly literature count and (b) citation count related to computer simulation of thermal anisotropy, indexed by Web of Science.
The rearch was conducted in September 20,2017. The total citations are 2 629
图1 热辐射方向模拟领域的受关注状况
(a)每年发表的与热辐射方向性模拟有关的文献数量;(b)自1997年以来与热辐射方向性模拟
文献引用数(来自Web of Science 核心期刊,数据统计截止到2017年9月20日),文献的总引用次数为2 629次
Fig.1 Concern of computer simulation of thermal anisotropy
(a) Yearly literature count and (b) citation count related to computer simulation of thermal anisotropy, indexed by Web of Science.
The rearch was conducted in September 20,2017. The total citations are 2 629
表1 与热辐射方向性模拟有关的期刊与会议
Table 1 Relevant journals and conference proceeding that publish more than two papers related to computer simulating of thermal anisotropy
表1 与热辐射方向性模拟有关的期刊与会议
Table 1 Relevant journals and conference proceeding that publish more than two papers related to computer simulating of thermal anisotropy
图2 与广义热辐射方向性计算机模拟相关的术语云标签图及其使用频率
(a)文献中标题、关键词与摘要的云标签图,这些文献均与地表温度分解有关,字体较大的标签表明关键字的出现频率较高,标签后括号内的数字为关键字出现的频率;(b)10个表示热辐射方向性模拟相关的术语及其相应的使用频率
Fig.2 Tag cloud and usage frequency of terms related to computer simulation of thermal anisotropy
(a) A tag cloud of the literature titles, keywords and abstracts related to modeling thermal anisotropy, where a larger font denotes a higher frequency of the associated term. The number following each term is the frequency; (b) Ten key terms representing modeling thermal anisotropy and the associated percentages of utilization
图2 与广义热辐射方向性计算机模拟相关的术语云标签图及其使用频率
(a)文献中标题、关键词与摘要的云标签图,这些文献均与地表温度分解有关,字体较大的标签表明关键字的出现频率较高,标签后括号内的数字为关键字出现的频率;(b)10个表示热辐射方向性模拟相关的术语及其相应的使用频率
Fig.2 Tag cloud and usage frequency of terms related to computer simulation of thermal anisotropy
(a) A tag cloud of the literature titles, keywords and abstracts related to modeling thermal anisotropy, where a larger font denotes a higher frequency of the associated term. The number following each term is the frequency; (b) Ten key terms representing modeling thermal anisotropy and the associated percentages of utilization
图3 近20年广义热辐射方向性计算机模型的共被引关系图
文献时间总跨度1997—2017年,以5年跨度进行时间段分割;引文年轮的颜色代表相应的引文时间,一个年轮厚度和与相应时间分区内引文数量成正比;较大的节点代表较多的引用次数;颜色的连接线表示引用年份段
Fig.3 Co-cited relationship of computer simulation of thermal anisotropy in recent 20 years
Literatures are divided into five time slices from 1997 to 2017. The color of the citation ring represents the corresponding citation time, and an annual ring thickness is proportional to the number of citation in the corresponding time zone. Larger nodes represent more citations, and colored links indicate the year of reference
图3 近20年广义热辐射方向性计算机模型的共被引关系图
文献时间总跨度1997—2017年,以5年跨度进行时间段分割;引文年轮的颜色代表相应的引文时间,一个年轮厚度和与相应时间分区内引文数量成正比;较大的节点代表较多的引用次数;颜色的连接线表示引用年份段
Fig.3 Co-cited relationship of computer simulation of thermal anisotropy in recent 20 years
Literatures are divided into five time slices from 1997 to 2017. The color of the citation ring represents the corresponding citation time, and an annual ring thickness is proportional to the number of citation in the corresponding time zone. Larger nodes represent more citations, and colored links indicate the year of reference
表2 4种典型的组分分类方案
Table 2 Four typical component classification methods
表2 4种典型的组分分类方案
Table 2 Four typical component classification methods
表3 地表热辐射方向性模型对比
Table 3 Comparison of surface thermal anisotropic model
模型名称 模型特点 模拟对象 模拟精度
(验证数据)
评价 代表性文献
几何光学
模型
Kimes模型 模拟对象简化为实心的无限长箱体 规则垄行结构的农作物 RMSE=1 ℃(土壤)
RMSE=2 ℃(棉花)
(垂直投影棉花覆盖
率48%的实测数据)
考虑了影响棉花热辐射方向性的主要因素, 即行结构和投影关系 [4]
SUM 假设城市建筑物稀疏排列,计算离散面元形状因子,组分权重为视场内组分所占面积比例 城市简化地表 RMSE=3.8 ℃
(加拿大温哥华航空飞行数据)
获取的组分比例相较于平面投影精度更高,忽略多次散射效应,且计算量与场景内面元数成正比,适用于小范围建筑等辐射发射难以穿透的介质的模拟 [11]
CoMSTIR 模拟13种组分温度,基于SUM模型思路计算组分权重内置四种投影算法:辐射度、球面、水平面和中心投影 城市地表 AE<1.6 ℃
(北京北师大房山实验基地实测数据)
模拟城市目标在任意方向的方向亮温,使用灵活方便,但尚不能建立城市植被的真实场景进行模拟 [18]
MGP 将树冠简化为椭球,利用LAI量化树冠内部空隙,运用布尔模型计算孔隙率,并计算场景中树冠的各组分比例 简单形状树冠 裸土 RE<2%
(非洲南部的热带稀疏大草原的实测数据)
RMSE=0.781 ℃
(DART模型结果)
模型中的几何模型过于简化,树冠光照方向和观测方向投影重叠面积计算难度大 [7]
MGP
(2014)
积分计算单棵树冠投影面积以及光照方向和观测方向投影重叠面积 各种树冠形状 裸土 RE<0.25%
(原始MGP模型)
计算速度相较于原始MGP有所提高,但仍无法应用于复杂地表的表达 [15]
MGP
(2014)
考虑混合像元的LST是道路和农作物共同作用产生 连续农作物
道路,裸土
AE<1.1 ℃
(黑河流域机载热像仪数据)
相较于原始MGP在特定场景下处理更加细致 [16]
CLAMP-GO模型 基于GO理论,三维结构组分温度通过在冠层方向上的面积比例和组分温度的乘积计算方向亮温 植被冠层 基于CLAMP模型,植被三维结构构建简单;可以应用于全波段(可见光—近红外和热红外波段)辐射方向性模拟 [35]
辐射传输
模型
TRGM 基于热辐射理论和植被冠层发射率方向性,可模拟面元热辐射和多次散射效应,考虑了三维冠层结构、植被的影响、组分温度分布 所有地表 RMSE ≈0.52 ℃
(法国南部地区地面观测数据)
输入参数较多,模拟面元相对精细,大场景应用时计算量大,应用难度较大,适用于模拟微尺度结构,且冠层结构对精度影响较大,而叶片大小和形状影响较小 [26]
SAIL扩展模型 考虑了植被和土壤温度的差异性(阴影土壤、光照叶片、阴影叶片) 稀疏植被 RMSE=1.25 ℃
(DART模型结果)
可以模拟多个非均匀同质冠层的发射和散射 [24]
植被冠层
三维辐射
传输模型
基于辐射传输机理,以“微分体元”为辐射传输计算基准,考虑体元内和体元间的多次散射 植被 RMSE(生长拔期)=0.4
RMSE(灌浆期)=0.44
(北京小汤山精准农业
基地冬小麦数据)
主要考虑辐射传输过程,但未考虑热红外复杂的辐射平衡或热交换过程 [23]
DART 基于光子追踪法,模拟TIR(热红外)的辐射能量平衡和上行的方向分谱辐射 所有地表 AE<1.2 ℃
(行种棉花冠层实测
亮温数据)
考虑光子多次散射效应和穿透性,但输入参数较多,计算时间复杂度大,适用于地面小范围模拟 [27,28]
DART
(2015)
增加了透视投影功能 所有地表 适用于各种传感器角度和视场类型 [36]
集成模型 修正FR97模型 改进了FR97(的组分分类方法,对原来土壤组分温度重新划分为光照土壤和阴影土壤 植被冠层 RMSE=0.72 ℃/1.55 ℃/2.73 ℃(黑河流域玉米区域的叶子、光照土壤和阴影土壤3种组分温度的实测数据)RMSE=0.5 ℃/0.65 ℃(4-SAIL和TRGM对应的模拟数据) 可用于模拟连续冠层、非连续作物和森林 [10]
冠层热辐射
三维模型
观测几何参数对离散面元间多次散射及发射辐射传输计算, 积分运算冠层面元在半球空间上对观测方向上的热辐射 植被 RMSE=0.31 ℃
(河北省怀来实验场测量的玉米热红外多角度数据)
用理念株刻画模拟对象,可模拟不同浓密程度的植被 [34]
表3 地表热辐射方向性模型对比
Table 3 Comparison of surface thermal anisotropic model
模型名称 模型特点 模拟对象 模拟精度
(验证数据)
评价 代表性文献
几何光学
模型
Kimes模型 模拟对象简化为实心的无限长箱体 规则垄行结构的农作物 RMSE=1 ℃(土壤)
RMSE=2 ℃(棉花)
(垂直投影棉花覆盖
率48%的实测数据)
考虑了影响棉花热辐射方向性的主要因素, 即行结构和投影关系 [4]
SUM 假设城市建筑物稀疏排列,计算离散面元形状因子,组分权重为视场内组分所占面积比例 城市简化地表 RMSE=3.8 ℃
(加拿大温哥华航空飞行数据)
获取的组分比例相较于平面投影精度更高,忽略多次散射效应,且计算量与场景内面元数成正比,适用于小范围建筑等辐射发射难以穿透的介质的模拟 [11]
CoMSTIR 模拟13种组分温度,基于SUM模型思路计算组分权重内置四种投影算法:辐射度、球面、水平面和中心投影 城市地表 AE<1.6 ℃
(北京北师大房山实验基地实测数据)
模拟城市目标在任意方向的方向亮温,使用灵活方便,但尚不能建立城市植被的真实场景进行模拟 [18]
MGP 将树冠简化为椭球,利用LAI量化树冠内部空隙,运用布尔模型计算孔隙率,并计算场景中树冠的各组分比例 简单形状树冠 裸土 RE<2%
(非洲南部的热带稀疏大草原的实测数据)
RMSE=0.781 ℃
(DART模型结果)
模型中的几何模型过于简化,树冠光照方向和观测方向投影重叠面积计算难度大 [7]
MGP
(2014)
积分计算单棵树冠投影面积以及光照方向和观测方向投影重叠面积 各种树冠形状 裸土 RE<0.25%
(原始MGP模型)
计算速度相较于原始MGP有所提高,但仍无法应用于复杂地表的表达 [15]
MGP
(2014)
考虑混合像元的LST是道路和农作物共同作用产生 连续农作物
道路,裸土
AE<1.1 ℃
(黑河流域机载热像仪数据)
相较于原始MGP在特定场景下处理更加细致 [16]
CLAMP-GO模型 基于GO理论,三维结构组分温度通过在冠层方向上的面积比例和组分温度的乘积计算方向亮温 植被冠层 基于CLAMP模型,植被三维结构构建简单;可以应用于全波段(可见光—近红外和热红外波段)辐射方向性模拟 [35]
辐射传输
模型
TRGM 基于热辐射理论和植被冠层发射率方向性,可模拟面元热辐射和多次散射效应,考虑了三维冠层结构、植被的影响、组分温度分布 所有地表 RMSE ≈0.52 ℃
(法国南部地区地面观测数据)
输入参数较多,模拟面元相对精细,大场景应用时计算量大,应用难度较大,适用于模拟微尺度结构,且冠层结构对精度影响较大,而叶片大小和形状影响较小 [26]
SAIL扩展模型 考虑了植被和土壤温度的差异性(阴影土壤、光照叶片、阴影叶片) 稀疏植被 RMSE=1.25 ℃
(DART模型结果)
可以模拟多个非均匀同质冠层的发射和散射 [24]
植被冠层
三维辐射
传输模型
基于辐射传输机理,以“微分体元”为辐射传输计算基准,考虑体元内和体元间的多次散射 植被 RMSE(生长拔期)=0.4
RMSE(灌浆期)=0.44
(北京小汤山精准农业
基地冬小麦数据)
主要考虑辐射传输过程,但未考虑热红外复杂的辐射平衡或热交换过程 [23]
DART 基于光子追踪法,模拟TIR(热红外)的辐射能量平衡和上行的方向分谱辐射 所有地表 AE<1.2 ℃
(行种棉花冠层实测
亮温数据)
考虑光子多次散射效应和穿透性,但输入参数较多,计算时间复杂度大,适用于地面小范围模拟 [27,28]
DART
(2015)
增加了透视投影功能 所有地表 适用于各种传感器角度和视场类型 [36]
集成模型 修正FR97模型 改进了FR97(的组分分类方法,对原来土壤组分温度重新划分为光照土壤和阴影土壤 植被冠层 RMSE=0.72 ℃/1.55 ℃/2.73 ℃(黑河流域玉米区域的叶子、光照土壤和阴影土壤3种组分温度的实测数据)RMSE=0.5 ℃/0.65 ℃(4-SAIL和TRGM对应的模拟数据) 可用于模拟连续冠层、非连续作物和森林 [10]
冠层热辐射
三维模型
观测几何参数对离散面元间多次散射及发射辐射传输计算, 积分运算冠层面元在半球空间上对观测方向上的热辐射 植被 RMSE=0.31 ℃
(河北省怀来实验场测量的玉米热红外多角度数据)
用理念株刻画模拟对象,可模拟不同浓密程度的植被 [34]
续表3
续表3
图4 不同场景的组分温度分布情况
场景A:冬季多层建筑群场景;场景B:夏季多层建筑群场景;场景C:夏季高层建筑群场景;(a)和(b)分别为白天(10:00,14:00)与 夜间(22:00、2:00)各组分在3种场景中的温度值
Fig.4 Distribution of component temperatures at different times in three scenes
Scene A:Multi-storey buildings in winter; Scene B: Multi-storey buildings in summer; Scene C: Multi-storey buildings in summer. (a)Component temperature value in the daytime(10:00,14:00) and (b) Component temperatures in the daytime the nighttime(22:00,2:00) in the three scenes
图4 不同场景的组分温度分布情况
场景A:冬季多层建筑群场景;场景B:夏季多层建筑群场景;场景C:夏季高层建筑群场景;(a)和(b)分别为白天(10:00,14:00)与 夜间(22:00、2:00)各组分在3种场景中的温度值
Fig.4 Distribution of component temperatures at different times in three scenes
Scene A:Multi-storey buildings in winter; Scene B: Multi-storey buildings in summer; Scene C: Multi-storey buildings in summer. (a)Component temperature value in the daytime(10:00,14:00) and (b) Component temperatures in the daytime the nighttime(22:00,2:00) in the three scenes
图5 不同场景的方向亮温在半球空间上的分布情况
Fig.5 Distribution of the directional bright temperature in different scenes
图5 不同场景的方向亮温在半球空间上的分布情况
Fig.5 Distribution of the directional bright temperature in different scenes
[1] Fang Yingbo, Zhan Wenfeng, Huang Fan, et al. Hourly variation of surface urban heat island over the Yangtze River delta urban agglomeration[J]. Advances in Earth Science, 2017, 32(2): 187-198.[方迎波,占文凤,黄帆,等. 长三角城市群表面城市热岛日内逐时变化规律[J]. 地球科学进展, 2017, 32(2): 187-198.]
[2] Monteith J L, Szeicz G.Radiative temperature in the heat balance of natural surfaces[J]. Quarterly Journal of the Royal Meteorological Society, 1962, 88(378): 496-507.
[3] Kimes D S, Idso S B, Pinter Jr P J, et al.View angle effects in the radiometric measurement of plant canopy temperatures[J]. Remote Sensing of Environment,1980, 10(4): 273-284.
[4] Kimes D S.Dynamics of directional reflectance factor distributions for vegetation canopies[J]. Applied Optics, 1983, 22(9): 1 364.
[5] Lagouarde J P, Kerr Y H, Brunet Y.An experimental study of angular effects on surface temperature for various plant canopies and bare soils[J]. 1995, 77(3/4): 167-190.
[6] Lagouarde J, Dayau S, Moreau P, et al. Directional anisotropy of brightness surface temperature over vineyards: Case study over the medoc region (SW France)[J]. IEEE Geoscience & Remote Sensing Letters, 2013, 11(2): 574-578.
URL    
[7] Pinheiro A C T, Privette J L, Guillevic P. Modeling the observed angular anisotropy of land surface temperature in a Savanna[J]. IEEE Transactions on Geoscience & Remote Sensing, 2006, 44(4): 1 036-1 047.
URL    
[8] Liu Qiang, Chen Liangfu, Liu Qinhuo, et al. Thermal infrared radiation transmission model of crop canopy[J]. Remote Sensing, 2003, 7(3): 161-167.[刘强,陈良富,柳钦火,等. 作物冠层的热红外辐射传输模型[J]. 遥感学报, 2003, 7(3): 161-167.]
[9] Du Y, Liu Q, Chen L, et al. Modeling directional brightness temperature of the winter wheat canopy at the ear stage[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(11): 3 721-3 739.
URL    
[10] Bian Z, Cao B, Li H, et al. An analytical four-component directional brightness temperature model for crop and forest canopies[J]. Remote Sensing of Environment, 2018, 209:731-746.
URL    
[11] Soux A, Voogt J A, Oke T R.A model to calculate what a remote sensor sees' of an urban surface[J]. Boundary-Layer Meteorology, 2004, 111(1): 109-132.
[12] Voogt J A.Assessment of an Urban sensor view model for thermal anisotropy[J]. Remote Sensing of Environment, 2008, 112(2): 482-495.
[13] Sun Hao, Chen Yunhao, Zhan Wenfeng, et al. A directional nucleus-driven nuclear model and uncertainty analysis for the application of high-emissivity urban surface infrared equivalent emissivity[J]. Journal of Infrared Millimeter Waves, 2015, 34(1): 66-73.[孙灏,陈云浩,占文凤,等. 一种近似用于高发射率城市地表热红外等效发射率的方向性变异核驱动模型及其不确定性分析[J]. 红外与毫米波学报, 2015, 34(1): 66-73.]
[14] Yu Tao, Tian Qiyan, Gu Xingfa, et al. Research on the simple target directional radiance temperature of city[J]. Remote Sensing, 2006, 10(5): 661-669.[余涛,田启燕,顾行发,等. 城市简单目标方向亮温研究[J]. 遥感学报, 2006, 10(5): 661-669.]
[15] Ma Wei, Chen Yunhao, Zhan Wenfeng, et al. 3D thermal radiation directional model of urban simulation target[J]. Remote Sensing, 2013, 17(1): 62-76.[马伟,陈云浩,占文凤,等. 城市模拟目标的3维热辐射方向性模型[J]. 遥感学报, 2013, 17(1): 62-76.]
[16] Li X, Strahler A H.Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing[J]. IEEE Transactions on Geoscience & Remote Sensing, 1992, 30(2):276-292.
URL    
[17] Ermida S L, Trigo I F, Dacamara C C, et al. Validation of remotely sensed surface temperature over an oak woodland landscape—The problem of viewing and illumination geometries[J]. Remote Sensing of Environment, 2014, 148: 16-27.
URL    
[18] Cao B, Liu Q, Du Y, et al. Modeling directional brightness temperature over mixed scenes of continuous crop and road: A case study of the Heihe River Basin[J]. IEEE Geoscience & Remote Sensing Letters, 2014, 12(2): 234-238.
URL    
[19] Zhan Wenfeng, Chen Yunhao, Ma Wei, et al. Analysis of the field of view effect of bright temperature observation in urban target direction[J]. Remote Sensing, 2010, 14(2): 372-395.[占文凤,陈云浩,马伟,等. 城市目标方向亮温观测的视场效应分析[J]. 遥感学报, 2010, 14(2): 372-395.]
[20] Qin W, Gerstl S A W. 3-D scene modeling of semidesert vegetation cover and its radiation regime[J]. Remote Sensing of Environment, 2000, 74(1): 145-162.
[21] Suits G H.The calculation of the directional reflectance of a vegetative canopy[J]. Remote Sensing of Environment, 1971, 2: 117-125.
URL    
[22] Verhoef W.Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model[J]. Remote Sensing of Environment, 1984, 16(2): 125-141.
[23] Yang Guijun, Liu Qinhuo, Liu Qiang, et al.3D radiation transmission model of vegetation canopy and simulation of thermal radiation directionality[J]. Journal of Infrared Millimeter Waves, 2010, 29(1): 38-44.[杨贵军,柳钦火,刘强,等. 植被冠层3D辐射传输模型及热辐射方向性模拟[J]. 红外与毫米波学报, 2010, 29(1): 38-44.]
[24] Verhoef W, Jia L, Xiao Q, et al. Unified optical-thermal four-stream radiative transfer theory for homogeneous vegetation canopies[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(6): 1 808-1 822.
URL    
[25] Huang Huaguo, Dou Baocheng, Hu Ni.Effect of tassel on the directionality of corn canopy heat radiation[J]. Journal of Infrared Millimeter Waves, 2011, 30(2): 120-123.[黄华国,窦宝成,胡妮. 雄穗对玉米冠层热辐射方向性的影响分析[J]. 红外与毫米波学报, 2011, 30(2): 120-123.]
[26] Liu Q, Huang H, Qin W, et al. An extended 3-D radiosity-graphics combined model for studying thermal-emission directionality of crop canopy[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(9): 2 900-2 918.
URL    
[27] Gastelluetchegorry J P, Demarez V, Pinel V, et al. Modeling radiative transfer in heterogeneous 3-D vegetation canopies[J]. Remote Sensing of Environment, 1996, 58(2): 131-156.
[28] Guillevic P, Gastellu-Etchegorry J P, Demarty J, et al. Thermal infrared radiative transfer within three-dimensional vegetation covers[J]. Journal of Geophysical Research Atmospheres, 2003, 108(D8):4 248.
[29] Norman J M.Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies[R]. Lincoln,Nebraska: University of Nebraska, 1987.
[30] Yan Guangjian, Jiang Lingmei, Wang Jindi, et al. Model and validation of radiated radiated rejected rate for row crops[J]. Science in China (Series D), 2002, 32(10): 857-863.[阎广建,蒋玲梅,王锦地,等. 行播作物热辐射双向间隙率模型及验证[J]. 中国科学:D辑, 2002, 32(10): 857-863.]
[31] Li X, Strahler A H.Modeling the gap probability of a discontinuous vegetation canopy[J]. IEEE Transactions on Geoscience & Remote Sensing, 1988, 26(2): 161-170.
URL    
[32] Chen Liangfu, Liu Qinhuo, Fan Wenjie, et al. Thermo-directional directional porosity model of row crops[J]. Science in China (Series D), 2002, 32(4): 290-298.[陈良富,柳钦火,范闻捷,等. 行播作物热辐射方向性孔隙率模型[J]. 中国科学:D辑, 2002, 32(4): 290-298.]
[33] Huang H, Qin W, Liu Q.RAPID: A radiosity applicable to porous indivi dual objects for directional reflectance over complex vegetated scenes[J]. Remote Sensing of Environment, 2013, 132(10):221-237.
[34] Ma Hongzhang, Liu Sumei, Sun Genyun, et al. Three-dimensional simulation model for thermal radiation directivity of nonuniform canopy: A case study of corn canopy[J]. Remote Sensing, 2016, 20(3): 374-381.[马红章,刘素美,孙根云,等. 非匀一冠层热辐射方向性3维模型构建——以玉米冠层为例[J]. 遥感学报, 2016, 20(3): 374-381.]
[35] Zhao Feng, Gu Xingfa, Liu Qiang, et al. Modeling of 3D canopy’s radiation transfer in the VNIR and TIR domains[J]. Journal of Remote Sensing, 2006, 10(5):670-675.[赵峰, 顾行发, 刘强,等. 基于3D真实植被场景的全波段辐射传输模型研究[J]. 遥感学报, 2006, 10(5):670-675.]
[36] Yin T, Lauret N, Gastellu-Etchegorry J P. Simulating images of passive sensors with finite field of view by coupling 3-D radiative transfer model and sensor perspective projection[J]. Remote Sensing of Environment, 2015, 162:169-185.
URL    
[37] Yu T, Gu X, Tian G, et al. Modeling directional brightness temperature over a maize canopy in row structure[J]. IEEE Transactions on Geoscience & Remote Sensing, 2004, 42(10): 2 290-2 304.
URL    
[38] Coudert B, Ottlé C, Boudevillain B, et al. Contribution of thermal infrared remote sensing data in multiobjective calibration of a dual-source SVAT model[J]. Journal of Hydrometeorology, 2006, 7(3):404-420.
[39] Peng Zhixing, Zhou Ji, Li Mingsong.Review of methods for simulating land surface temperature at the pixel scale based on ground measurements over heterogeneous surface[J]. Advances in Earth Science, 2016, 31(5): 471-480.[彭志兴,周纪,李明松. 基于地面观测的异质性下垫面像元尺度地表温度模拟研究进展[J]. 地球科学进展, 2016, 31(5): 471-480.]
[40] Zhan Wenfeng,Zhou Ji,Ma Wei.Computer simulating of land surface thermal anisotropy based on realistic structure: A review[J]. Advances in Earth Science, 2009, 24(12): 1 309-1 317.[占文凤,周纪,马伟. 基于真实结构的地表热辐射方向性计算机模拟研究进展[J]. 地球科学进展, 2009, 24(12): 1 309-1 317.]
[41] Chehbouni A, Nouvellon Y, Kerr Y H, et al. Directional effect on radiative surface temperature measurements over a semiarid grassland site[J]. Remote Sensing of Environment, 2001, 76(3):360-372.
[42] Guillevic P, Gastellu-Etchegorry J P, Demarty J, et al. Thermal infrared radiative transfer within three-dimensional vegetation covers[J]. Journal of Geophysical Research Atmospheres, 2003, 108(D8).DOI:10.1029/2002JD00247.
URL    
[43] Krayenhoff E, Voogt J.Daytime thermal anisotropy of urban neighbourhoods: Morphological causation[J]. Remote Sensing, 2016, 8(2): 108.
[44] Jie Weijia.Dynamics Simulation of Angular Effects on the Forest Canopy Temperature Observed by Remote Sensing Methods[D]. Beijing: Beijing Forestry University, 2016.[解潍嘉. 遥感观测林冠温度的角度效应动态模拟研究[D]. 北京:北京林业大学, 2016.]
[45] Huang Huaguo, Liu Qinhuo, Liu Qiang, et al. Simulation of time effect on thermal emission directionality measurement[J]. Journal of System Simulation, 2007, 19(15): 3 586-3 590.[黄华国,柳钦火,刘强,等. 热辐射方向性测量中的时间效应模拟[J]. 系统仿真学报, 2007, 19(15): 3 586-3 590.]
[46] Huang H, Liu Q, Qin W.Thermal emission hot-spot effect of crop canopies—Part I: Simulation[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2010, 3(3): 313-322.
URL    
[1] Fang Yingbo, Zhan Wenfeng, Huang Fan, et al. Hourly variation of surface urban heat island over the Yangtze River delta urban agglomeration[J]. Advances in Earth Science, 2017, 32(2): 187-198.
[方迎波,占文凤,黄帆,等. 长三角城市群表面城市热岛日内逐时变化规律[J]. 地球科学进展, 2017, 32(2): 187-198.]
doi: 10.11867/j.issn.1001-8166.2017.02.0187     URL    
[2] Monteith J L, Szeicz G.Radiative temperature in the heat balance of natural surfaces[J]. Quarterly Journal of the Royal Meteorological Society, 1962, 88(378): 496-507.
doi: 10.1002/(ISSN)1477-870X     URL    
[3] Kimes D S, Idso S B, Pinter Jr P J, et al.View angle effects in the radiometric measurement of plant canopy temperatures[J]. Remote Sensing of Environment,1980, 10(4): 273-284.
doi: 10.1016/0034-4257(80)90087-5     URL    
[4] Kimes D S.Dynamics of directional reflectance factor distributions for vegetation canopies[J]. Applied Optics, 1983, 22(9): 1 364.
doi: 10.1364/AO.22.001364     URL     pmid: 18195970
[5] Lagouarde J P, Kerr Y H, Brunet Y.An experimental study of angular effects on surface temperature for various plant canopies and bare soils[J]. 1995, 77(3/4): 167-190.
[6] Lagouarde J, Dayau S, Moreau P, et al. Directional anisotropy of brightness surface temperature over vineyards: Case study over the medoc region (SW France)[J]. IEEE Geoscience & Remote Sensing Letters, 2013, 11(2): 574-578.
[7] Pinheiro A C T, Privette J L, Guillevic P. Modeling the observed angular anisotropy of land surface temperature in a Savanna[J]. IEEE Transactions on Geoscience & Remote Sensing, 2006, 44(4): 1 036-1 047.
doi: 10.1109/TGRS.2005.863827     URL    
[8] Liu Qiang, Chen Liangfu, Liu Qinhuo, et al. Thermal infrared radiation transmission model of crop canopy[J]. Remote Sensing, 2003, 7(3): 161-167.
[刘强,陈良富,柳钦火,等. 作物冠层的热红外辐射传输模型[J]. 遥感学报, 2003, 7(3): 161-167.]
doi: 10.3321/j.issn:1007-4619.2003.03.001     URL    
[9] Du Y, Liu Q, Chen L, et al. Modeling directional brightness temperature of the winter wheat canopy at the ear stage[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(11): 3 721-3 739.
doi: 10.1109/TGRS.2007.903401     URL    
[10] Bian Z, Cao B, Li H, et al. An analytical four-component directional brightness temperature model for crop and forest canopies[J]. Remote Sensing of Environment, 2018, 209:731-746.
doi: 10.1016/j.rse.2018.03.010     URL    
[11] Soux A, Voogt J A, Oke T R.A model to calculate what a remote sensor sees' of an urban surface[J]. Boundary-Layer Meteorology, 2004, 111(1): 109-132.
doi: 10.1023/B:BOUN.0000027978.21230.b7     URL    
[12] Voogt J A.Assessment of an Urban sensor view model for thermal anisotropy[J]. Remote Sensing of Environment, 2008, 112(2): 482-495.
doi: 10.1016/j.rse.2007.05.013     URL    
[13] Sun Hao, Chen Yunhao, Zhan Wenfeng, et al. A directional nucleus-driven nuclear model and uncertainty analysis for the application of high-emissivity urban surface infrared equivalent emissivity[J]. Journal of Infrared Millimeter Waves, 2015, 34(1): 66-73.
[孙灏,陈云浩,占文凤,等. 一种近似用于高发射率城市地表热红外等效发射率的方向性变异核驱动模型及其不确定性分析[J]. 红外与毫米波学报, 2015, 34(1): 66-73.]
URL    
[14] Yu Tao, Tian Qiyan, Gu Xingfa, et al. Research on the simple target directional radiance temperature of city[J]. Remote Sensing, 2006, 10(5): 661-669.
[余涛,田启燕,顾行发,等. 城市简单目标方向亮温研究[J]. 遥感学报, 2006, 10(5): 661-669.]
doi: 10.11834/jrs.20060598    
[15] Ma Wei, Chen Yunhao, Zhan Wenfeng, et al. 3D thermal radiation directional model of urban simulation target[J]. Remote Sensing, 2013, 17(1): 62-76.
[马伟,陈云浩,占文凤,等. 城市模拟目标的3维热辐射方向性模型[J]. 遥感学报, 2013, 17(1): 62-76.]
doi: 10.11834/jrs.20131361    
[16] Li X, Strahler A H.Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing[J]. IEEE Transactions on Geoscience & Remote Sensing, 1992, 30(2):276-292.
[17] Ermida S L, Trigo I F, Dacamara C C, et al. Validation of remotely sensed surface temperature over an oak woodland landscape—The problem of viewing and illumination geometries[J]. Remote Sensing of Environment, 2014, 148: 16-27.
doi: 10.1016/j.rse.2014.03.016     URL    
[18] Cao B, Liu Q, Du Y, et al. Modeling directional brightness temperature over mixed scenes of continuous crop and road: A case study of the Heihe River Basin[J]. IEEE Geoscience & Remote Sensing Letters, 2014, 12(2): 234-238.
[19] Zhan Wenfeng, Chen Yunhao, Ma Wei, et al. Analysis of the field of view effect of bright temperature observation in urban target direction[J]. Remote Sensing, 2010, 14(2): 372-395.
[占文凤,陈云浩,马伟,等. 城市目标方向亮温观测的视场效应分析[J]. 遥感学报, 2010, 14(2): 372-395.]
URL    
[20] Qin W, Gerstl S A W. 3-D scene modeling of semidesert vegetation cover and its radiation regime[J]. Remote Sensing of Environment, 2000, 74(1): 145-162.
doi: 10.1016/S0034-4257(00)00129-2     URL    
[21] Suits G H.The calculation of the directional reflectance of a vegetative canopy[J]. Remote Sensing of Environment, 1971, 2: 117-125.
doi: 10.1016/0034-4257(71)90085-X     URL    
[22] Verhoef W.Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model[J]. Remote Sensing of Environment, 1984, 16(2): 125-141.
doi: 10.1016/0034-4257(84)90057-9     URL    
[23] Yang Guijun, Liu Qinhuo, Liu Qiang, et al.3D radiation transmission model of vegetation canopy and simulation of thermal radiation directionality[J]. Journal of Infrared Millimeter Waves, 2010, 29(1): 38-44.
[杨贵军,柳钦火,刘强,等. 植被冠层3D辐射传输模型及热辐射方向性模拟[J]. 红外与毫米波学报, 2010, 29(1): 38-44.]
URL    
[24] Verhoef W, Jia L, Xiao Q, et al. Unified optical-thermal four-stream radiative transfer theory for homogeneous vegetation canopies[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(6): 1 808-1 822.
[25] Huang Huaguo, Dou Baocheng, Hu Ni.Effect of tassel on the directionality of corn canopy heat radiation[J]. Journal of Infrared Millimeter Waves, 2011, 30(2): 120-123.
[黄华国,窦宝成,胡妮. 雄穗对玉米冠层热辐射方向性的影响分析[J]. 红外与毫米波学报, 2011, 30(2): 120-123.]
URL    
[26] Liu Q, Huang H, Qin W, et al. An extended 3-D radiosity-graphics combined model for studying thermal-emission directionality of crop canopy[J]. IEEE Transactions on Geoscience & Remote Sensing, 2007, 45(9): 2 900-2 918.
[27] Gastelluetchegorry J P, Demarez V, Pinel V, et al. Modeling radiative transfer in heterogeneous 3-D vegetation canopies[J]. Remote Sensing of Environment, 1996, 58(2): 131-156.
doi: 10.1016/0034-4257(95)00253-7     URL    
[28] Guillevic P, Gastellu-Etchegorry J P, Demarty J, et al. Thermal infrared radiative transfer within three-dimensional vegetation covers[J]. Journal of Geophysical Research Atmospheres, 2003, 108(D8):4 248.
doi: 10.1029/2002JD002247     URL    
[29] Norman J M.Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies[R]. Lincoln,Nebraska: University of Nebraska, 1987.
[30] Yan Guangjian, Jiang Lingmei, Wang Jindi, et al. Model and validation of radiated radiated rejected rate for row crops[J]. Science in China (Series D), 2002, 32(10): 857-863.
[阎广建,蒋玲梅,王锦地,等. 行播作物热辐射双向间隙率模型及验证[J]. 中国科学:D辑, 2002, 32(10): 857-863.]
[31] Li X, Strahler A H.Modeling the gap probability of a discontinuous vegetation canopy[J]. IEEE Transactions on Geoscience & Remote Sensing, 1988, 26(2): 161-170.
doi: 10.1109/36.3017     URL    
[32] Chen Liangfu, Liu Qinhuo, Fan Wenjie, et al. Thermo-directional directional porosity model of row crops[J]. Science in China (Series D), 2002, 32(4): 290-298.
[陈良富,柳钦火,范闻捷,等. 行播作物热辐射方向性孔隙率模型[J]. 中国科学:D辑, 2002, 32(4): 290-298.]
doi: 10.3321/j.issn:1006-9267.2002.04.004     URL    
[33] Huang H, Qin W, Liu Q.RAPID: A radiosity applicable to porous indivi dual objects for directional reflectance over complex vegetated scenes[J]. Remote Sensing of Environment, 2013, 132(10):221-237.
doi: 10.1016/j.rse.2013.01.013     URL    
[34] Ma Hongzhang, Liu Sumei, Sun Genyun, et al. Three-dimensional simulation model for thermal radiation directivity of nonuniform canopy: A case study of corn canopy[J]. Remote Sensing, 2016, 20(3): 374-381.
[马红章,刘素美,孙根云,等. 非匀一冠层热辐射方向性3维模型构建——以玉米冠层为例[J]. 遥感学报, 2016, 20(3): 374-381.]
[35] Zhao Feng, Gu Xingfa, Liu Qiang, et al. Modeling of 3D canopy’s radiation transfer in the VNIR and TIR domains[J]. Journal of Remote Sensing, 2006, 10(5):670-675.
[赵峰, 顾行发, 刘强,等. 基于3D真实植被场景的全波段辐射传输模型研究[J]. 遥感学报, 2006, 10(5):670-675.]
doi: 10.3321/j.issn:1007-4619.2006.05.010     URL    
[36] Yin T, Lauret N, Gastellu-Etchegorry J P. Simulating images of passive sensors with finite field of view by coupling 3-D radiative transfer model and sensor perspective projection[J]. Remote Sensing of Environment, 2015, 162:169-185.
doi: 10.1016/j.rse.2015.02.020     URL    
[37] Yu T, Gu X, Tian G, et al. Modeling directional brightness temperature over a maize canopy in row structure[J]. IEEE Transactions on Geoscience & Remote Sensing, 2004, 42(10): 2 290-2 304.
doi: 10.1109/TGRS.2004.834196     URL    
[38] Coudert B, Ottlé C, Boudevillain B, et al. Contribution of thermal infrared remote sensing data in multiobjective calibration of a dual-source SVAT model[J]. Journal of Hydrometeorology, 2006, 7(3):404-420.
doi: 10.1175/JHM503.1     URL    
[39] Peng Zhixing, Zhou Ji, Li Mingsong.Review of methods for simulating land surface temperature at the pixel scale based on ground measurements over heterogeneous surface[J]. Advances in Earth Science, 2016, 31(5): 471-480.
[彭志兴,周纪,李明松. 基于地面观测的异质性下垫面像元尺度地表温度模拟研究进展[J]. 地球科学进展, 2016, 31(5): 471-480.]
doi: 10.11867/j.issn.1001-8166.2016.05.0471     URL    
[40] Zhan Wenfeng,Zhou Ji,Ma Wei.Computer simulating of land surface thermal anisotropy based on realistic structure: A review[J]. Advances in Earth Science, 2009, 24(12): 1 309-1 317.
[占文凤,周纪,马伟. 基于真实结构的地表热辐射方向性计算机模拟研究进展[J]. 地球科学进展, 2009, 24(12): 1 309-1 317.]
doi: 10.11867/j.issn.1001-8166.2009.12.1309     URL    
[41] Chehbouni A, Nouvellon Y, Kerr Y H, et al. Directional effect on radiative surface temperature measurements over a semiarid grassland site[J]. Remote Sensing of Environment, 2001, 76(3):360-372.
doi: 10.1016/S0034-4257(01)00183-3     URL    
[42] Guillevic P, Gastellu-Etchegorry J P, Demarty J, et al. Thermal infrared radiative transfer within three-dimensional vegetation covers[J]. Journal of Geophysical Research Atmospheres, 2003, 108(D8).DOI:10.1029/2002JD00247.
doi: 10.1029/2002JD002247     URL    
[43] Krayenhoff E, Voogt J.Daytime thermal anisotropy of urban neighbourhoods: Morphological causation[J]. Remote Sensing, 2016, 8(2): 108.
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