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• 方法与技术 • 上一篇    

基于MODIS的地表温度空间降尺度方法

李小军1,2,3,江涛3*,辛晓洲1,张海龙1,柳钦火1#br#   

  1. (1中国科学院遥感与数字地球研究所遥感科学国家重点实验室, 北京 100101; 2中国科学院大学, 北京 100049; 3
    山东科技大学测绘科学与工程学院, 山东青岛 266590)
  • 出版日期:2016-12-10 发布日期:2016-12-10

Spatial downscaling of land surface temperature based on MODIS data.

LI Xiao-jun1,2,3, JIANG Tao3*, XIN Xiao-zhou1, ZHANG Hai-long1, LIU Qin-huo1#br#   

  1. (1 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; 2University of Chinese Academy of Sciences, Beijing 100049, China; 3Geomatics College, Shandong University of Science and Technology, Qingdao 266590, Shandong, China).
  • Online:2016-12-10 Published:2016-12-10

摘要: 针对卫星遥感技术监测地表温度(land surface temperature,LST)存在时空分辨率矛盾这一难题,以TsHARP温度降尺度方法中的3种不同转换关系为基础,提出引入地表比辐射率ε和修正的土壤调节植被指数MSAVI的新转换关系,并用4种转换关系直接将原始1 km MODIS LST产品降尺度到250 m。为了验证4种降尺度转换关系的效果,以Landsat 8 TIRS反演的LST作为当日地表温度的参考值,从定性和定量两个角度评价了4种降尺度转换关系的精度。结果表明:4种转换关系在提高LST空间分辨率的同时又能较好地保持原始LST影像热特征的空间分布格局,消除了原始1 km影像中的“马赛克”效应;4种转换关系降尺度的250 m MODIS LST均值均接近于TIRS升尺度的LST均值,平均偏差的绝对值都小于1 ℃,降尺度结果非常接近真实地表温度,表明4种转换关系均能够达到较好的降尺度效果;原始转换关系1的降尺度结果虽然具有较高的空间变异性(SD较大),但与TIRS LST之间的RMSE是4种转换关系中最大的(2.375 ℃),而改进的转换关系4仅为1.252 ℃,并且转换关系4在描绘城市高温区和水体低温区方面具有明显的优势。

Abstract: Due to technical constrains of remotely sensed land surface temperature (LST) data, there is a tradeoff between spatial and temporal resolution, i.e., a high temporal resolution is associated with a low spatial resolution and vice versa. To solve this disadvantage, based on three different conversion models in TsHARP (an algorithm for sharpening thermal imagery) method, this study made improvements by introducing a new parameter, namely, land surface emissivity (ε), and a new conversion model was put forward by replacing the original NDVI with MSAVI. The aims of this study involved the following aspects: firstly, to improve the original low spatial resolution of MODIS LST image data (1 km) to 250 m resolution by applying four models; se-condly, to assess the accuracy of each downscaling model based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results showed that both models could effectively enhance the spatial resolution while simultaneously preserve the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image. Statistical results indicated that absolute mean basis error (MBE) in 250 m MODIS LST generated by the four models was less than 1 ℃. Thus, the results were very close to the true surface temperature, indicating that all of the four models were effective and applicable in our study area. Quantitative comparisons of the four downscaled 250 m MODIS LST images and TIRS LST showed that the new conversion model (i.e. model 4) had the lowest RMSE (1.252 ℃), while the original model 1 had the highest RMSE (2.375 ℃). In addition, model 4 had obvious advantages in the description of high temperature areas (i.e. urban area) and low temperature areas (i.e. water bodies).