野大麦内生真菌共生体研究进展
English
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地表温度(land surface temperature, LST)是表征地表过程变化的重要物理量，能够反映地表能量平衡状态的时空变化信息，它综合了物质地表与大气相互作用以及大气和陆地之间能量交换的结果，是区域和全球尺度上陆地表层系统过程的关键参数，已在全球气候变化模拟、生态环境评价、干旱监测以及粮食估产等方面广泛应用[1]。准确获取LST数据对优化热惯量、地表蒸散和土壤湿度模型，以及评估草地生产力和鉴定天然牧草品质方面都具有重要的意义。
传统地面测量地表温度的结果准确，但难以满足大尺度和时空连续测量的需求。随着卫星遥感技术的迅速发展，为大尺度、高时空分辨率的LST反演提供了新途径[2]。目前基于甚高分辨率辐射计(advanced very high resolution radiometer, AVHRR)、中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer, MODIS)、先进星载热辐射与反射辐射计(advanced spaceborne thermal emission and reflection radiometer, ASTER)等传感器数据，结合多种反演算法及模型，生成了多套全球LST时间序列产品，并在科学研究和生产实践中得到广泛应用[3]。虽然，LST数据集在发布前都经过了系统性的算法处理以及较为严格的数据质量控制，但受地表特征变化、大气条件以及传感器自身等因素的影响，使得这些数据集的可靠性和连续性受到了极大挑战[4-7]。因此，在应用这些数据前，开展LST产品真实性检验与精度评价方面的工作是十分必要的。
目前国内外对遥感反演LST产品进行真实性检验的方法主要有直接利用地表温度实测数据验证、基于辐射传输模型验证以及利用高质量和高分辨率遥感数据交叉验证中低分辨率LST产品等[8]。其中直接利用站点实测数据验证的方法被广泛应用于检验大面积的平坦区域。该方法的优点是可以直接评价卫星数据的质量和检验LST产品的反演算法，但缺点是需要在地面布设大量的观测站点，投入成本较高，且精度评价结果依赖于地表站点观测精度和卫星像元尺度的代表性。基于辐射传输模型验证的优势是不依赖于地表同步测量的LST数据，但该方法严重依赖于大气辐射传输模型的精度，适合无法准确获取地表温度观测的区域验证。交叉验证方法是将已知精度的LST产品作为参考，进行比较和验证未知精度的LST反演结果。由于LST具有较强的时空异质性，因此该方法更适合具有相同或者相似观测时间和角度数据之间的验证[9]。
Wan等[10]利用野外地面实测数据验证MODIS LST产品精度的研究表明，在湖泊、草地、沙漠等平坦均质的下垫面上，MODIS LST产品具有较高精度，尤其是在晴空天气下，均方根误差小于1 ℃。Caselles等[11]利用均一农田站点观测数据对MODIS LST产品进行真实性检验，结果表明MODIS LST产品在反演25～32 ℃区间的地表温度时具有较高的精度，均方根误差在0.5～0.9 ℃。Wang等[12]研究全天候的地表温度动态变化特征后指出，白天的LST有较强空间异质性，MODIS LST夜间产品具有更好的空间一致性和较高的精度。Sabol等[13]利用北美最大高山湖泊多点实测水面温度验证ASTER LST产品精度发现，云、气溶胶以及晴空条件下大气温度和水汽廓线等环境因素对LST反演精度影响较大，均方根误差最高可达15 ℃。Wan和Li[14]以及Wan[15]基于辐射传输模型，将水汽廓线等大气环境数据作为模型输入参数，模拟卫星过境时的天顶辐射值，并与同期卫星观测的辐射值进行对比分析，从而改进了遥感反演LST产品的精度。Qian等[16]尝试利用交叉验证的方法评价欧洲气象卫星(METEOSAT second generation-1, MSG) 旋转增强可见红外成像仪(spinning enhanced visible and infrared imager, SEVIRI)和MODIS LST产品的精度，结果表明，LST具有较强的时空异质性，地表类型、不同卫星过境时间以及传感器角度等因素对交叉验证结果影响较大。王之夏等[17]发现，MODIS LST产品与常规气象站地面观测的地表0 cm温度数据在时空序列上的变化趋势一致，但平均误差较大，误差很大程度上受二者观测方法差异的影响。邹德富等[18]验证青藏高原连续多年冻土区MODIS LST产品和美国陆地卫星(Landsat)增强型专题成像仪 (enhanced thematic mapper , ETM+)反演LST数据的精度表明，白天受冻土层特性和太阳辐射的影响，遥感反演LST产品的误差较大，相比较而言，MODIS LST夜间产品具有更高的精度，均方根误差小于1.78 ℃。石亚亚等[19]利用MODIS LST产品提取青藏高原冻土分布图时发现，受植被、积雪以及高寒低温天气等因素影响，MODIS LST产品在季节冻土和多年冻土区分别存在低估和高估的现象，其产品适应性仍然需要根据下垫面特性进行检验和改进。为此，众多学者根据研究区和对象特性建立了多种基于单通道、多通道劈窗和多角度的热红外波段反演LST的方法和时间序列重建算法，并对生成的相应LST产品进行真实性检验与精度评价[20-21]。这些工作为改进和提高LST产品的精度，以及推动热红外遥感反演地表温度的研究与发展奠定了坚实基础。
然而，由于陆地表面的复杂性，其组成和结构等均存在差异，导致陆地表面温度遥感反演仍然具有较多的不确定性。目前，对LST产品进行真实性检验的工作主要集中在单一下垫面上，在不同下垫面上对同一遥感反演LST产品进行适应性分析和精度评价的工作仍然需要进一步完善。虽然MODIS LST标准产品已结合云掩膜产品和辐射传输模型进行了质量控制，但为了简化遥感反演过程，部分地区采用了平均状况下的环境参数设置，这与我国祁连山区的气候、地形、植被覆盖、纬度等诸多方面还存在着较大差异[22]，尤其是对生态环境监测更有意义的MODIS LST白天产品，其质量仍然需要进一步检验。同时由于缺少相应的地表温度实测验证数据，导致LST产品在一些区域的精度和适用性暂无定论，极大限制了祁连山自然保护区生态环境遥感监测研究与应用相关工作的开展。
祁连山自然保护区是我国西部重要的生态安全屏障，其水源涵养功能区不仅具有拦蓄降水、缩小温差、保持土壤湿度等作用，而且在消洪补枯、涵养水源、水土保持等方面作用显著[23]。草地资源是该地区生态系统的重要组成部分，但自20世纪80年代以来，由于全球气候变化的影响和人为造成的生态破坏，导致祁连山生态保护区面临着草原退化严重、生态环境恶化、冰川萎缩等严峻的生态环境问题。目前，亟需利用高质量、长时序卫星遥感资料开展祁连山草地生态环境监测和治理评估方面的工作，为近年来国家实施的增强生态环境保护、推进水资源集约利用和推动生态功能区高质量发展等一系列政策措施提供决策支持。
因此，本研究利用祁连山区自动站实测地表温度数据，对MODIS LST日产品(MOD/MYD11A1)进行精度验证和对比分析，评价不同下垫面上MODIS LST标准产品的适用性，尝试订正由地表类型变化而引起的遥感反演地表温度产品的误差，为时间序列卫星遥感产品有效地应用于祁连山自然保护区生态环境监测研究提供科学参考。
1. 研究区概况
祁连山位于青藏高原东北缘，在青海省和甘肃省交界处，祁连山不仅是我国西北干旱区的水源涵养功能区和国家重点生态功能区，同时也是我国西部重要的生物多样性保护区域，其主要保护对象有高山生态系统、水源涵养林、草原植被及野生动物。该地区属于典型高原大陆性气候，海拔高度1 674～5 584 m，年平均气温较低，常年处于0 ℃以下，年降水量250～700 mm，且降水主要集中在5月 − 9月[24-25]。研究区内地形起伏较大，主要山脉均为西北–东南走向，其间分布山间谷地。受地形影响，祁连山东、中、西段降水和气温的垂直变化显著，且复杂的地貌和气候变化使得区内植被类型多样。根据刘钟龄[26]中国草地资源图，该地区主要植被类型有高寒草地、山地草甸、荒漠草地、灌丛草地、林地等(图1)。该地区特殊的地理位置以及气候地形条件，孕育了丰富的积雪和冰川资源，不仅是河西地区经济建设的基础，也是人民赖以生存的命脉。
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图 1 祁连山植被类型和生态定位站位置图Figure 1. Vegetation types and ecological positioning stations location in the Qilian Mountains2. 数据与方法
2.1 地表温度自动站建设与实测数据获取
为准确估计MODIS LST产品的精度，尽可能降低由空间异质性引起的尺度效应，通过前期调研，在祁连山东、中、西各段分别选取植被空间分布较为均一、代表性强、地势相对平坦，且面积大于1 km × 1 km的下垫面作为建站观测样区。其中在祁连山东段选取张掖市肃南县皇城镇(Huangcheng, HC)附近山地草甸下垫面(101°48′36.00″ E；37°54′44.00″ N；海拔2 920 m)、中段选取张掖市肃南县康乐乡(Kangle, KL)附近的高寒草地下垫面(99°49′20.00″ E；38°46′16.00″ N；海拔3 730 m)、西段选取张掖市肃南县祁丰乡(Qifeng, QF)附近的荒漠草地下垫面(98°8′6.35″ E；39°40′44.39" N；海拔1 900 m)为代表(图1)。3个自动站自2019年6月1日开工建设，于2019年6月6日全部安装完毕，并于同日开始运行，目前设备运行正常，数据接收正常。
为避免由于观测方法差异引起的误差，尽可能得保持与卫星遥感观测原理相一致，自动站由美国CSI公司生产的高分辨通用采集器CR1000、美国APOGEE公司生产的SI-411表面温度传感器以及英国SKYE公司的SKR 1800红光–近红外双通道光量子传感器等仪器设备组成(图2)。在设备安装时，保持SI-411表面温度传感器与待测地面样方垂直，安装在距离地面1.5 m高度的支架上，并设置观测数据时间分辨率为0.25 h (表1)。每个站点均配置通用无线分组业务(general packet radio service, GPRS)远传数据传输模块，可实现无人值守、传感器故障远程自动报警和数据远程控制下载。同时，对每日台站观测数据进行自相关分析和方差检验，判断数据的连续性和可靠性。本研究通过选取自相关系数的绝对值大于0，且置信度为95%时通过显著性检验的数据，作为实测数据集。
为与MODIS/Terra (上午星)和MODIS/Aqua (下午星)的过境时间相匹配，同时考虑卫星轨道漂移以及降低观测数据噪声等情况，从实测数据集中分别选取3个自动站2019年6月6日 − 12月31日10:30 − 11:30和13:30 − 14:30时段的地表温度数据，结合MOD11A1和MYD11A1卫星过境时间信息，选取与卫星过境时差最小的地表温度观测数据作为逐日上、下午的地表温度实测数据(图3)。
表 1 自动站安装介绍Table 1. Introduction of automatic weather station installation观测项目
Item仪器型号
Sensor安装高度
Sensor height/m观测时段
Observation time/d观测频次
Observation frequency/h地表温度 Land surface temperature SI-411 1.5 2019年6月至今
2019– 06 to now0.25 归一化植被指数
Normalized differential vegetation indexSKR 1800 1.5 土壤温湿度(5层) Soil temperature
and moisture (5 Layers)Campbell 107/CS616 −0.05、−0.1、
−0.2、−0.3、−0.42019年7月至今
2019– 07 to now2.2 MODIS LST产品
本研究使用的MODIS地表温度产品包括Terra星(MOD11A1)和Aqua星(MYD11A1)2种。该产品以Wan和Dozier[27]提出的广义劈窗算法为基础，详细算法可参考Wan[28]编写的MODIS地表温度产品用户手册。通过美国宇航局地球观测系统(Earth Observing System Data and Information System, EOSDIS)的陆表过程分布式数据档案中心(https://lpdaac.usgs.gov/)下载了2019年6月6日 − 12月31日V006版的MOD11A1和MYD11A1 LST日产品。
覆盖整个祁连山研究区需要3幅MODIS影像，轨道号分别为h25v04、h25v05和h26v05。利用MODIS L3级产品处理工具软件(MODIS reprojection tools, MRT)分别对MOD11A1和MYD11A1地表温度产品进行接边和坐标变换处理。最后将图像处理成grid格式，空间分辨率为1 km，采用Albers等积圆锥投影。
分别提取3个站点所在地理位置上的MODIS LST值和相应质量控制信息，剔除空值和异常值，选取质量控制字段为0的数据，即保证每个像元上数据质量为优的样本进行精度评价(图3)。最终获取MOD11A1和MYD11A1的有效样本数分别为151和145 (皇城镇)、123和121 (康乐乡)、161和149 (祁丰乡)，分别占总样本数的70.52%和69.04%、58.57%和57.61%、76.35%和70.79%。
2.3 精度评价方法
首先，用MODIS LST采样值同自动站实测地表温度值进行对比，分析不同下垫面上采样值与实测值之间的误差分布状况。然后，计算采样值与实测值在不同下垫面上的平均误差(Pa)、绝对平均误差(Pd)、均方根误差(root mean square error, RMSE)，用以评价不同下垫面上MODIS遥感反演LST产品的精度。
$ {P}_{a}=\frac{1}{n}{\sum _{i=1}^{n}}({x}_{i}-{y}_{i}){\text{；}} $
(1) $ {P}_{d}=\frac{1}{n}{\sum _{i=1}^{n}}\left|{x}_{i}-{y}_{i}\right|{\text{；}} $
(2) $ RMSE=\sqrt{\frac{{\displaystyle\sum _{i=1}^{n}}({x}_{i}-{y}_{i}{)}^{2}}{n}} {\text{。}}$
(3) 式中：xi和yi分别表示MODIS LST采样值及其对应的实际观测值，n为用于验证的样本数目。
本研究根据随机数表法，在2019年6月 − 12月实测数据集和MODIS LST采样数据集中，随机抽取30对时空相一致的有效样本作为订正数据，用于对祁连山不同下垫面上的MODIS LST产品进行订正和改进，其他数据作为验证数据，用于对MODIS LST产品进行精度评价。同时，考虑白天的地表温度变化对祁连山生态环境监测与评估更有意义，因此本研究选取白天的MODIS LST产品同自动站实测数据进行对比分析研究。
3. 结果与分析
3.1 祁连山地表温度变化特征分析
为避免数据噪声扰动，参考同期质量更好的MODIS LST 8日产品，利用自动站8日平均实测数据分析地表温度(LST)变化特征。结果表明，在2019年6月 − 12月3个站点监测的地表温度结果差异较大，但总体符合各下垫面类型的地表温度变化特点。其中在祁连山中段康乐乡(KL)的高寒草地植被区，由于海拔高、下垫面均一，植被覆盖度相对较高，因此该样区的地表温度相对较低，上、下午数值分别介于−14.71～21.94 ℃和− 13.11～26.01 ℃。在6月 − 9月间LST数值变化幅度小，生态环境较为稳定，但在9月以后，随着环境温度和日照强度的逐渐降低，LST数值也迅速降低，变化幅度较大。在祁连山西段祁丰乡(QF)荒漠植被区，海拔相对较低、植被生长状况整体较差，植被覆盖度低，因此该样区LST变化幅度大、对日照强度敏感，LST数值相对较高，上、下午LST数值分别介于−0.12～38.63 ℃和0.72～47.61 ℃，自然环境较为恶劣。祁连山东段皇城镇(HC)山地草甸植被区的LST变化情况介于中段和西段之间，生态环境状况处于2个样区的中间水平，但具有明显的月份差异。当在植被返青和生长前期(7月前)且覆盖度较低时，LST变化与祁连山西段荒漠植被样区相类似；当在盛草期(7月 − 8月)时，植被覆盖度较高，LST变化趋于稳定，与祁连山中段高寒草地样区相类似；当植被开始逐渐枯黄(9月后)时，随着环境温度和日照强度的降低，LST数值也在迅速降低(图4)。
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图 4 2019年6月5日−12月31日自动站实测地表温度数据Figure 4. Land surface temperature data at automatic stations between June 5 to December 31, 2019总体而言，3个自动站的LST监测结果较为稳定，下午温度平均高出上午2～5 ℃，且符合各下垫面上环境温度、日照强度以及植被生长特征规律，具有较好的代表性，适合开展祁连山区卫星遥感反演LST产品的校验工作。
根据MODIS LST产品质量控制文件，选取每个月同期质量最好的MOD11A1和MYD11A1 LST产品，通过空间对比分析可以看出，MODIS MOD11A1 (上午)和MYD11A1 (下午)产品的地表温度空间分布基本一致，但部分地区和不同月份LST数值存在空间差异。在2019年6月 − 12月期间，MODIS上、下午星过境整个祁连山地区的时间段在10:39 − 11:13和13:33 − 14:07，且在同一时间和区域内，MYD11A1 LST数值普遍高于MOD11A1 LST数值(图5)。
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图 5 中分辨率成像光谱仪地表温度产品MOD11A1和MYD11A1空间分布图Figure 5. Results of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) products3.2 MODIS LST产品精度分析
利用地表温度实测数据与相应时期MODIS LST产品采样值进行对比，结果表明：与MODIS/Terra (上午星)相比，祁连山东段皇城站和中段康乐站的实测值与MYD11A1 LST产品的采样值具有较高的线性相关，决定系数(R2)分别达到0.74和0.65。在祁连山西段祁丰站的实测值与MOD11A1 LST产品具有较高的线性相关，R2达到0.80 (图6)。
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图 6 地表温度实测数据与MODIS LST产品采样值对比Figure 6. Comparison between the MODIS LST sampled values and the LST observed values in automatic stations根据误差分析结果表明，在各下垫面上MODIS LST产品表现出不同的高估或低估现象。其中，在祁连山东段皇城站代表的山地草甸上，MODIS LST产品精度受到植被生长状况和实际地表温度变化的影响。当在盛草期(7月 − 8月)植被覆盖度相对较高，且上午实际地表温度小于25 ℃时，MOD11A1 LST产品易出现低估的现象。当在植被返青(6月)和枯黄期(10月 − 12月)，植被覆盖度相对较低，且上午实际地表温度大于35 ℃时，又频繁出现高估现象，其中Pa、Pd和RMSE分别为−2.77、4.07和5.52 ℃。与此同时，在该下垫面上，MYD11A1 LST产品与实测数据的变化趋势较为接近，误差相对较低，Pa、Pd和RMSE分别为2.02、3.73和5.12 ℃，但普遍存在高估的现象。在祁连山西段祁丰站的荒漠草原上，MOD11A1和MYD11A1 LST产品与实测数据均具有较高的一致性，其中MODIS/Aqua(下午星)与实测数据具有基本相同的变化趋势，能够敏感地反映出该地区地表温度的变化特征，但该产品存在高估现象，Pa、Pd和RMSE分别为1.92、3.04和4.11 ℃。与其相比较，MOD11A1 LST产品与实测数据更加接近，具有较高的精度，Pa、Pd和RMSE分别为1.62、2.89和3.88 ℃。在祁连山中段康乐站代表的高寒草原草地上，由于实际地表温度较低，MOD11A1和MYD11A1 LST产品与实测数据的平均误差较大，且均存在严重的高估现象。与MOD11A1相比较，在该下垫面上，MYD11A1具有较好的精度，Pa、Pd和RMSE分别为3.72、5.14和6.92 ℃ (表2和图6)。
表 2 中分辨率成像光谱仪地表温度产品精度分析Table 2. Accuracy analysis of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) products站点
Station植被类型
Vegetation type地表温度上午星产品
Land surface temperature products
in the morning (MOD11A1)/℃地表温度下午星产品
Land Surface temperature products
in the afternoon (MYD11A1)/℃Pa Pd RMSE Pa Pd RMSE 皇城镇 Huangcheng (HC) 山地草甸 Mountain meadow −2.77 4.07 5.52 2.02 3.73 5.12 康乐乡 Kangle (KL) 高寒草地 Alpine grassland 4.03 5.91 7.16 3.72 5.14 6.92 祁丰乡 Qifeng (QF) 荒漠草地 Desert grassland 1.62 2.89 3.88 1.92 3.04 4.11 总体而言，在祁连山西段海拔较低的荒漠草原上，MODIS/Terra (上午星) LST产品与实测LST数据具有较高的一致性，且具有更好的空间适应性；在祁连山海拔相对较高的东段山地草甸和中段高寒草原草地上，MODIS/Aqua (下午星)反演的LST结果具有更高的精度，更加能反映该地区地表温度的变化特征。但在各下垫面上，MODIS LST产品均存在不同程度的误差，需要对其进行订正。
3.3 MODIS LST产品的订正
根据以上MODIS LST产品适应性分析结果，选取2019年6月 − 12月祁连山东段皇城镇和中段康乐乡站点实测地表温度数据与相应MYD11A1 LST采样值，以及祁连山西段祁丰乡站点实测数据与同期MOD11A1 LST采样值，分别建立线性统计模型(表3)，并将订正数据带入相应模型。通过改进MODIS LST产品可以看出，MODIS LST产品在祁连山山地草甸、高寒草地和荒漠草地上的精度均有所提高，其中在高寒草地上改进最为明显，Pa、Pd和RMSE由3.72、5.14和6.92 ℃分别降低为2.82、3.57和4.26 ℃；在荒漠草地上，改进后的MODIS LST产品精度达到最高，与改进前相比，Pa、Pd和RMSE分别降低了0.45、0.24和0.91 ℃；在山地草甸上，改进后MODIS LST产品精度优于在高寒草地上，但低于在荒漠草地上，Pa、Pd和RMSE分别为1.84、2.97和3.83 ℃ (表4)。
表 3 祁连山中分辨率成像光谱仪地表温度产品订正Table 3. Revision of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) products in Qilian Mountains站点
Station植被类型
Vegetation type公式
Linear formulaR2 适用数据 Applicable data 皇城镇
Huangcheng (HC)山地草甸
Mountain meadowy = 0.65x + 0.72 0.74 地表温度下午星产品
Land surface temperature products
in the afternoon (MYD11A1)康乐乡
Kangle (KL)高寒草地
Alpine grasslandy = 0.74x − 2.61 0.65 地表温度下午星产品
Land surface temperature products
in the afternoon (MYD11A1)祁丰乡
Qifeng (QF)荒漠草地
Desert grasslandy = 0.82x + 0.745 0.80 地表温度上午星产品
Land surface temperature products
in the morning (MOD11A1)表 4 订正后的中分辨率成像光谱仪地表温度产品精度Table 4. Accuracy analysis of orrected moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) products℃ 站点 Station Pa Pd RMSE 皇城镇 Huangcheng (HC) 1.84 2.97 3.83 康乐乡 Kangle (KL) 2.82 3.57 4.26 祁丰乡 Qifeng (QF) 1.17 2.65 2.97 4. 讨论
虽然MODIS LST产品在祁连山不同下垫面上具有较好的精度，但仍存在高估或低估的现象，其精度具有明显的空间差异性。其中在祁连山西段祁丰站代表的荒漠草原上，由于海拔相对较低且植被较为稀疏，白天地表升温速度快，当上午实际地表温度达到25～30 ℃时，在晴空天气条件下MOD11A1 LST产品与实测数据具有较高的一致性，Pa、Pd和RMSE分别为1.62、2.89和3.88 ℃；当地表继续升温，并超过30 ℃时，MODIS LST产品精度开始降低，MYD11A1 LST出现明显高估的现象，Pa、Pd和RMSE分别达到1.92、3.04和4.11 ℃，因此在该下垫面上MOD11A1 LST产品具有更高的精度和空间适应性。这也进一步证明了MODIS数据在反演25～30 ℃区间的地表温度时，具有较高精度[11]。同时，本研究还发现，MODIS LST产品精度不仅受地表类型的影响，同时还可能受植被盖度和海拔高度的影响。在海拔相对较高的祁连山东段山地草甸上，由于植被覆盖度较高，MODIS LST产品会出现低估该地区实际地表温度的情况，且MYD11A1 LST产品与实测数据具有更高的一致性。在海拔最高的祁连山中段高寒草原草地上，由于地表升温速度慢，植被类型结构单一，MODIS LST产品精度较差，整体高估了该地区的实际地表温度。这也从另一方面说明了MODIS LST产品应用于高原冻土等研究中误差较大的问题[19]。
目前，对白天和复杂下垫面LST产品进行精度检验的工作仍然较少，特别是在祁连山地区，LST产品的质量和精度问题比平原等均质区域更为复杂。在MODIS Terra和MODIS/Aqua白天过境观测时，地球表面正处在一天中升温较快或最高温的时间段，这段时间比夜间温度波动更大，且与站点实际观测时间会存在一定的过境时差。根据统计，3个站点实际观测时间与卫星过境的时差在8 min以内。通过选取与MODIS/Terra和MODIS/Aqua卫星过境有不同时差的站点观测数据，进行对比可以看出，当选取与MODIS过境时差 ≤ 8 min的站点观测数据时，观测值与上、下午星LST产品采样值的样本数分别为435和415，R2分别为0.707和0.752；当选取与MODIS过境时差 ≤ 1 min的站点观测数据时，观测值与上、下午星LST产品采样值的样本对分别为143和157，R2分别为0.720和0.794 (图7)。由此可以看出，MODIS过境时间与站点实际观测数据时间不匹配会引起一定的误差。但是，为了保证在不同下垫面上拥有足够多的验证样本数据，本研究采取了尽可能多保留站点观测数据的方法，这是造成白天数据验证偏差的一个重要来源。因此，后期在实际使用过程中，应当进一步采取提高地面观测资料的时间分辨率、增加遥感产品像元尺度内地面观测点数量、亚像元分解等方法对产品精度有进一步的评价、研究，从而改进MODIS反演地表温度算法和产品精度。
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图 7 和中分辨率成像光谱仪(MODIS)卫星过境有不同时差的站点观测数据与地表温度产品采样值Figure 7. Comparison of observation data from stations with different time from moderate-resolution imaging spectroradiometer (MODIS) satellites transit and sampling value of MODIS land surface temperature (LST) products本研究通过误差订正可有效提高MODIS LST产品在祁连山山地草甸、高寒草地和荒漠草地上的精度，但仍存在验证点少和验证数据时间序列短等问题，使得订正公式在各下垫面的普适性还有待更多观测数据加以验证和完善。同时，用有限足迹范围内的地面测量值来检验像元尺度上的MODIS LST产品时，空间代表性和两套数据集之间的差异均有可能会对MODIS温度产品精度验证产生影响。后期仍然需要借助空基遥感平台作为中介桥梁，进一步开展尺度转换方面的研究，尽可能减少由空间异质性而引起的误差。
5. 结论
为了促进MODIS卫星反演LST产品在祁连山地区的应用，本研究利用祁连山不同下垫面上的实测地表温度数据，对MODIS LST日产品(MOD/MYD11A1)进行精度验证和适应性分析，订正MODIS LST产品的误差，得出如下结论：
1)本研究在祁连山东段山地草甸、中段高寒草地和西段荒漠草地建立的LST自动监测站的结果较为稳定，且符合各下垫面上植被生长特征，具有较好的代表性，适合开展祁连山区卫星遥感反演LST产品的校验工作。
2)与MODIS/Terra (上午星)相比，在祁连山东段山地草甸和中段高寒草地上，MYD11A1 LST产品与实测数据具有较高的时空一致性，RMSE分别为5.12和6.92 ℃。在祁连山西段，MOD11A1 LST产品与实测数据具有较高的时空一致性，Pa、Pd和RMSE分别为1.62、2.89和3.88 ℃。
3) MODIS LST产品精度不仅受下垫面类型的影响，同时还受植被盖度和海拔高度的影响。当在海拔相对较低、植被较少的荒漠草地上，MODIS LST产品具有较高的精度。在海拔相对较高的祁连山东段山地草甸和中段高寒草原草地上，由于地表升温速度慢，植被盖度较高，MODIS LST产品精度较低，且整体高估了该地区的实际地表温度。
4) 误差订正有效提高了MODIS LST产品在祁连山山地草甸、高寒草地和荒漠草地上的精度，RMSE分别由5.12、6.92和3.88 ℃降低到3.83、4.26和2.97 ℃。
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表 1 新疆、甘肃和内蒙古三省(区)野大麦内生真菌带菌率与分布
Table 1 Infection rate and distribution of endophytic fungi in wild barley in Xinjiang, Gansu, and Inner Mongolia
省（区）Province 海拔 Altitude/m 经度 Longitude 纬度 Latitude 显微镜检验 Microscopic examination/% PDA分离 PDA isolation/% 新疆 Xinjiang 502～1 689 81°17′– 94°20′ E 41°47′– 44°55′ N 92(86～100) 95(92～100) 甘肃 Gansu 2 100～3 100 100°03′– 102°54′ E 37°29′– 39°15′ N 97(92～100) 99(96～100) 内蒙古 Inner Mongolia 1 770～1 980 105°52′– 105°54′ E 38°54′– 38°58′ N 77.5(67～88) 83(75～90) 括号内为带菌率范围。表格数据由文献[35]整理计算得出。
The range of the infection rate is shown in parentheses. Data in the table are from Wang[35].
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表 2 光学显微镜下内生真菌在野大麦体内的分布特征
Table 2 Characteristics of endophytic fungi in wild barley under an optical microscope
指标 Index 种子 Seed 茎髓 Stem 叶片 Blade 叶鞘 Sheath 密集度 Density 比较密集 Relatively dense 密集 Dense 比较稀疏
Relatively sparse密度最大
Maximally dense排列 Arrangement 平行或网状排列(种皮) Parallel or mesh arrangement (seed coat) 沿植物轴平行生长，不规则排列 Parallel growth along the plant axis, irregularly arranged 沿植物轴平行生长 Parallel growth along the plant axis 沿叶脉平行排列
Parallel along the veins形状
Shape线型(种皮)、粗短、高度弯曲(糊粉层) Linear (seed coat), short and thick, highly curved (seed aleurone layer) 微弯曲、粗细均匀
Micro-curved, uniform thickness比较弯曲
Relatively curved比较弯曲
Relatively curved分枝
Branch较少(种皮) Few (seed coat)
几乎没有(糊粉层) Hardly any (seed aleurone layer)少 Few 少 Few 多数不分叉
Most are not forked表格内容由文献[41]整理得出；表3同。
The data in the table are from Zhao et al [41]; This is applicable for Table 3 as well.
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表 3 透射电子显微镜下内生真菌在野大麦体内的分布特征
Table 3 Characteristics of endophytic fungi in wild barley under a transmission electron microscope
指标 Index 种子 Seed 茎髓 Stem 叶片 Blade 叶鞘 Sheath 分布
Distribution种皮细胞间隙
Gap of seed coat cells茎组织细胞的间隙
Gap of stem tissue cells叶肉细胞间隙
Gap of mesophyll cells厚壁细胞附近
Near thick-walled cells形状
Shape呈圆形或椭圆形(种皮)
Round or oval (seed coat)圆形或椭圆形
Round or oval圆形或椭圆形
Round or oval圆形
Round
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表 4 分离自野大麦的3株Epichloë bromicola菌株的菌落和分生孢子特征
Table 4 Characteristics of colonies and conidia of three Epichloë bromicola strains isolated from wild barley
菌株 Strain 直径1)
Diameter1)/cm菌落正面 Colony upper face 菌落反面 Colony reverse 分生孢子 Conidia WBE1 2.75～2.90 白色、凸起、稍弯曲、棉絮状至蓬松状；边缘为棕褐色
White, raised, slightly convoluted, cottony to fluffy; colony margins tan棕褐色，边缘亮棕色
Tan centrally to light tan marginally呈肾状至椭圆形，光滑，透明，无隔膜，(3～5.5) μm × (2.5～3.75) μm，每个分生孢子细胞仅产生一个分生孢子
Reniform to ellipsoidal, smooth, hyaline, aseptate, (3～5.5) μm × (2.5～3.75) μm，a single conidium produced by a single conidiogenous cellWBE3 2.30～3.75 白色、扁平、略呈毛毡状
White, flattened, lightly felted中央浅棕色，边缘奶油状
Light brown centrally to cream at marginallyWBE4 2.80～2.90 白色、棉絮状至蓬松状；中间略微卷曲，四周平整
White, cottony to fluffy, slightly convoluted in the center and flattened toward the perimeter黄色 Yellow 1) 25 ℃下在 PDA培养基上培养至32 d时测量。表格内容由文献[40]整理得出。
1) Measured on PDA medium at 25 ℃ until 32 days. Data in the table are from Chen et al. [40]
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表 5 E+植株对不同非生物胁迫的响应
Table 5 Specific response of E+ plants to different abiotic stresses
胁迫类型
Type of stresses胁迫部位
Stress site响应 Response 参考文献 Reference 生长发育 Growth and development 生理变化 Physiological change 酸
Acid种子、植株
Seed, plant提高发芽势和幼苗干重，异状发芽率降低
Increased germination potential and seedling dry weight but reduced germination rate of the abnormally shaped seeds[45] 碱
Alkali种子、植株
Seed, plant促进胚芽生长，提高胚根长、发芽势
和幼苗干重
Enhanced shoot growth and increased root length, germination potential, and seedling dry weight提高蒸腾速率、光合速率、气孔导度、甘氨酸甜菜碱含量以及总抗氧化能力
Increased transpiration rate, photosynthetic rate, stomatal conductance, glycine betaine content, and total antioxidant capacity[44-45] 干旱
Drought种子、幼苗
Seed, seedling提高发芽率和发芽指数以及胚芽长
和胚根长
Enhanced shoot growth and increased root length, germination potential, and seedling dry weight提高幼苗含水量
Increased sedling water content[47] 水涝
Waterlogging植株 Plant 提高分蘖、株高和地下生物量
Increased tillering, plant height, and underground biomass提高叶绿素、脯氨酸含量，降低丙二醛含量和电解质渗漏
Increased chlorophyll and proline content but reduced malondialdehyde content and electrolyte leakage[19] 人工老化
Artificial aging种子 Seed 促进发芽，提高芽长和根长
Enhanced germination and shoot and root growth降低膜的损伤，减少浸出液电导率和可溶性糖的含量
Reduced membrane damage, leachate conductivity, and soluble sugar content[46] 温度
Temperature种子、幼苗
Seed, seedling提高发芽率和发芽指数以及胚芽长
和胚根长
Increased germination rate and germination index as well as shoot and root length提高幼苗含水量
Increased seedling water content[47] 盐 Salt 种子、植株
Seed, plant提高发芽率、胚芽胚根长以及植株的株高、分蘖能力和生物量积累。促进 N、P吸收，C含量没有显著变化
Increased germination rate, germination index, shoot and root length, plant height, tillering, and biomass accumulation. Promoted N and P absorption; no significant change in C contentNa+降低，K+升高，Ca2+在芽中升高，在根中降低；提高可溶性糖、脯氨酸、亚精胺和精胺、叶绿素、甘氨酸甜菜碱的含量，同时降低丙二醛、腐胺含量和腐胺：(亚精胺精胺)；提高植株 SOD、POD 酶活性、光合作用和总抗氧化能力
Decreased Na+, increased K+, increased Ca2+ in the bud, and decreases Ca2+ in the root. Increased soluble sugar, valine, spermidine and spermine, chlorophyll, glycine, and betaine content but reduced malondialdehyde, putrescine content, and putrescine (spermidine) content. Improved plant SOD enzyme activity, photosynthesis, and total antioxidant capacity[44, 48-
51, 53]
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1. 王佳岚，李春杰. 不同水分条件下内生真菌对野大麦生长的影响. 草业科学. 2022(06): 1176-1184 . 
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2. 刘叶飞，刘亚玲，韩慧杰，邱锐，周昕越，赵彦. 野大麦研究进展. 草原与草业. 2021(03): 1-5 . 百度学术
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