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MODIS/LST Product Validation for Mixed Pixels at Linzhi of Tibet
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摘要: 西藏林芝地区地形复杂、土地覆盖类型多样，MODIS地表温度 (land surface temperature，LST) 产品验证面临处理混合像元的难题，为获得与像元尺度 (1 km) 相匹配的地表温度数据，该文提出采用多点同时观测结合面积加权的方法，将该方法应用于验证林芝地区2013年6月10日夜间晴空MODIS/LST产品。结果显示：单点观测对像元的代表性不足，容易低估产品精度 (10个样本均方根误差为2.2 K)，面积加权法可获得综合性更好的地面LST信息，对MODIS/LST产品的精度给出更高的评价 (30个样本均方根误差为1.40 K)。对于地表类型混杂程度高且地势较为平坦的像元，面积加权法的优势更为明显，可将卫星LST产品与地面LST之间的差异由3 K降至1 K以内。Abstract: Southeastern part of Tibet is featured with complicated terrain and diverse land cover types. Validation of MODIS/LST product (1-km spatial resolution) in this region is faced with mixed pixel issue. Point-based LST measurements cannot represent the pixel well. To obtain ground LST measurements at pixel scale, traditional method usually depends on the high spatial resolution of thermal images, such as Aster and TM. However, these data are often unavailable due to persistent cloud cover and long repeat cycle. Therefore, a new simple method called area-weighted average (AWA) method is proposed, in which land cover map at high spatial resolution is combined with multi-site field observations to model the hypothetical observations at moderate pixel scale. The assumption of AWA method is that field observations can be shared within the same land cover. The AWA method is applied and analyzed on the case of Linzhi (with an area of 20 km2) which locates in southeastern part of Tibet. First, 5 field stations are set up on 5 typical land covers: Grassland, farmland, floodplain, forest at sunny slope, and forest at shadowy slope. The upward and downward long-wave radiations are measured simultaneously. Then the land cover map at 30 m spatial resolution is derived from TM image using maximum likelihood classification method. For every 1-km MODIS pixel, the fraction of each typical land cover is calculated, and the radiation at MODIS pixel-scale is estimated through area-weighted averaging. The broadband emissivity is calculated using linear combination of narrowband emissivity of MODIS band 31 and 32. Finally, LST at MODIS pixel-scale can be calculated based on Stefan-Boltzmann law. The AWA method is used for validating daily product of MODIS/LST from Terra and Aqua platforms on 10 June 2013 (LST at night is used because it changes slowly both in temporal and spatial domain). Results show that the RMSE of MODIS/LST is below 1.4 K (n=30) when applying the AWA method. If a point-based measurement is used to directly represent a MODIS pixel, the RMSE is more than 2.2 K (n=10), showing a tendency of over-estimation. The error of Aqua LST is slightly greater than that of Terra LST, probably due to a larger sensor view zenith angle during overpass. Superiority of the AWA method is more noticeable for pixels with high land cover heterogeneity and gentle terrain. The difference in LST between satellite and field observations can be decreased from 3 K to 1 K. However, for pixels with homogeneous land covers or with very tough terrains, the advantage of AWA method is limited. To further improve the AWA method, terrain adjustment should be taken into account when extrapolating point-based measurements to the same land cover but from another region, because the slope and aspect will influence the surface energy balance process even when the land cover stays the same. Results also indicate MODIS/LST data at nighttime in Linzhi Area are accurate, which are very meaningful considering the low density of meteorological stations in this area.
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Key words:
- MODIS/LST;
- validation;
- mixed pixel;
- Linzhi Area
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图 1 研究区30 m分辨率假彩色图像
(研究区面积约20 km2, 蓝色星状标识为观测站点，数字为站点编号，白色网格为1 km MODIS网格位置)
Fig. 1 The false color composite image of the study region
(with an area of 20 km2, blue stars denote field experiment stations, numbers denote corresponding stations, white box denotes the MODIS pixel of 1 km)
图 2 基于30 m分辨率TM数据获取的研究区土地覆盖分类
Fig. 2 Land cover classification map derived from TM image with 30 m spatial resolution
图 3 研究区MODIS/LST与面积加权法估算的地面LST散点图
Fig. 3 Comparison of MODIS/LST with field LST measurements obtained with AWA method for the study region
表 1 观测站点信息汇总
Table 1 Information summary of observation stations
站点信息 农田站点 阴坡林地站点 草地站点 河滩站点 阳坡林地站点 纬度 29.4459°N 29.4502°N 29.4487°N 29.4589°N 29.4685°N 经度 94.6980°E 94.6859°E 94.6914°E 94.6947°E 94.7006°E 高程/m 2939 3022 2965 2904 3166 坡度/(°) 16.9 21.7 2.5 15.5 32.7 坡向/(°) 356.5 105.5 343.7 235.8 212 辐射计距地面距离 距农田地面1.7 m 距冠层1.5 m 距地面1.5 m 距地面1.6 m 距离冠层1.2 m 
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表 2 研究区内 (面积约20 km2) 各种土地覆盖类型所占面积比例
Table 2 Fraction occupied by each land cover type in the study region (with an area of 20 km2)
土地覆盖类型 比例/% 农田 17.73 阴坡森林 21.91 草地 24.35 河滩 15.21 水体 6.21 阳坡森林 14.58
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表 3 每个站点所在的1 km像元内的各种土地覆盖类型所占比例
Table 3 Fraction occupied by each land cover type for the pixel of 1 km where the observation station locates
土地覆盖类型 农田覆盖比例/% 阴坡森林覆盖比例/% 草地覆盖比例/% 河滩覆盖比例/% 阳坡森林覆盖比例/% 水体覆盖比例/% 农田站点像元 35.27 16.34 13.55 32.69 2.15 0 阴坡森林站点像元 21.93 36.67 40.54 0.86 0 0 草地站点像元 10.75 0 36.02 53.12 0.11 0 河滩站点像元 14.95 1.61 25.81 32.04 0 25.59 阳坡森林站点像元 0 0 8.90 3.11 87.99 0
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表 4 基于30 m ASTER高程数据计算的每个站点所在1 km像元范围内的地形起伏度以及坡度标准差
Table 4 Terrain index and standard deviation of slope for the pixel of 1 km with the observation station located
像元类型 地形起伏度/m 坡度标准差/m 农田站点像元 148 7.75 阴坡森林站点像元 209 10.13 草地站点像元 85 4.99 河滩站点像元 118 8.98 阳坡森林站点像元 617 6.64 注：地形起伏度的定义是一定范围内最高海拔和最低海拔之差。
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表 5 卫星过境时刻站点所测的上行长波辐射和下行长波辐射 (单位：W·m-2)
Table 5 Upward and downward long wave radiation measurements of each observation station obtained at satellite overpass time (unit:W·m-2)
站点类型 Terra卫星过境时刻 Aqua卫星过境时刻 上行长波辐射 下行长波辐射 上行长波辐射 下行长波辐射 农田站点 338.6 263.8 330.1 261.7 阴坡森林站点 356.2 259.0 345.9 257.0 草地站点 344.8 249.1 336.4 249.1 河滩站点 367.2 248.8 354.9 248.9 阳坡森林站点 355.8 252.2 346.3 255.8
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表 6 Terra MODIS/LST与面积加权法和单点法估算地面LST对比
Table 6 Comparison of Terra MODIS/LST observations with field LST measurements, including AWA (area-weighted average) method and point-based method
像元类型 LST/K Terra卫星发射率 面积加权法 单点法 MOD11A1产品 农田站点像元 281.01 278.23 281.64 0.9843 阴坡森林站点像元 280.24 281.92 283.08 0.9803 草地站点像元 281.95 279.67 283.02 0.9793 河滩站点像元 284.31 284.31 284.32 0.9733 阳坡森林站点像元 281.74 281.87 282.52 0.9803 注：河滩1 km像元内有约25.59%的水体，因为没有水体上方的辐射观测值，无法基于面积加权法计算LST，故采用单点法计算的LST代替。
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表 7 Aqua MODIS/LST与面积加权法和单点法估算地面LST对比
Table 7 Comparison of Aqua MODIS/LST observations with field LST measurements, including AWA (area-weighted average) method and point-based method
像元类型 LST/K Aqua卫星发射率 面积加权法 单点法 MYD11A1产品 农田站点像元 278.95 276.44 280.02 0.9851 阴坡森林站点像元 278.35 279.84 279.92 0.9803 草地站点像元 279.84 277.94 279.92 0.9783 河滩站点像元 281.77 281.77 280.78 0.9773 阳坡森林站点像元 279.80 279.93 282.32 0.9803
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