帮助 关于我们

返回检索结果

基于DEM修正的MODIS地表温度产品空间插值
Spatial Interpolation of MODIS Land Surface Temperature Products Based on DEM Correction

查看参考文献30篇

崔晓临 1   程贇 1 *   张露 2   卫晓庆 1  
文摘 地表温度是资源环境、气候变化、陆地生态系统等科学研究的重要参数之一。MODIS LST(Land Surface Temperature, LST)产品是地表温度相关研究的重要数据源。而现有MODIS LST产品均存在云覆盖区域,因此云覆盖区域地表温度估计已成为热红外遥感的前沿性研究难题。为解决MODIS LST产品云遮挡区域地表温度信息缺失,以秦岭地区为研究区,选用2001-2017年的MOD11A2数据,在传统的反距离权重(IDW)、规则样条函数(SPLINE)、普通克里金(OK)、趋势面(TREND)空间插值方法中引入高程因子,通过反复试验形成基于DEM修正的MODIS LST空间插值方法。分析空间插值结果表明: ①空间插值精度由高到低为:OK>SPLINE>IDW>TREND,基于DEM修正后精度分别提高了约0.38、0.31、0.32和0.78℃; ②空间插值结果的精度呈现季节差异,夏季6、7、8月的精度较高,1月的精度最低;③插值精度与云区的范围存在一定的关系,当云覆盖区域<1.1 km~2时,DEM+OK方法的插值误差<0.55 ℃,当云覆盖区域<3.1 km~2,插值误差<1 ℃;DEM+SPLINE方法在云覆盖区域<2.7 km~2时,插值误差<0.55 ℃,云覆盖区域<10.4 km~2,插值误差<1℃;当云覆盖为1.1~2.7 km~2时,DEM+SPLINE方法的插值精度高于DEM+OK方法。
其他语种文摘 Land surface temperature is one of the important parameters of scientific research such as resource environment, climate change and terrestrial ecosystem. MODIS LST(Land Surface Temperature, LST) products are important data sources for land surface temperature related research. The land surface temperature information of MODIS LST products is lost in the cloud coverage area. Therefore, the land surface temperature estimation of cloud coverage areas has become a frontier research problem of thermal infrared remote sensing. In order to solve the problem of missing land surface temperature information in the cloud occlusion area of MODIS LST products. In this paper, the Qinling area is used as the research area and the experimental data of MOD11A2 from 2001 to 2017 is selected. In the traditional Inverse Distance Weighting(IDW), Regular Spline(SPLINE), Ordinary Kriging(OK) and Trend Surface(TREND) spatial interpolation method, the important influence factor of elevation is introduced. Through a large number of spatial interpolation experiments, the traditional spatial interpolation method is improved, and a MODIS LST spatial interpolation method based on DEM correction is formed. Analysis of spatial interpolation results indicates:(1) The spatial interpolation accuracy is from high to low: OK> SPLINE > IDW>TREND, and the accuracy of the OK, SPLINE, IDW, and TREND methods based on DEM correction is increased by about 0.38°C, 0.31°C, 0.32°C, and 0.78°C, respectively;(2) The accuracy of spatial interpolation results shows seasonal differences. The interpolation accuracy is higher in summer, July, and August, and the interpolation accuracy is the lowest in January.(3)The interpolation accuracy has a certain relationship with the cloud area. When the cloud coverage area is less than 1.1km~2, the interpolation error of the DEM+OK interpolation method is less than 0.55°C, and when the cloud coverage area is less than 3.1km~2, the spatial interpolation error is less than 1°C. When the cloud coverage area is less than 2.7 km~2, the interpolation error of the DEM+SPLINE method is less than 0.55°C, and the interpolation error of the DEM+SPLINE method is less than 1°C when the cloud coverage area is less than 10.4 km~2. When the cloud coverage is 1.1~2.7 km~2, the interpolation accuracy of DEM+SPLINE interpolation method is higher than of the DEM+OK interpolation method.
来源 地球信息科学学报 ,2018,20(12):1768-1776 【核心库】
DOI 10.12082/dqxxkx.2018.180340
关键词 MODIS LST ; 空间插值 ; 地表温度 ; DEM ; 秦岭地区
地址

1. 西安科技大学测绘科学与技术学院, 西安, 710054  

2. 中国科学院遥感与数字地球研究所, 北京, 100094

语种 中文
文献类型 研究性论文
ISSN 1560-8999
学科 大气科学(气象学)
文献收藏号 CSCD:6388655

参考文献 共 30 共2页

1.  石玉. 基于MODIS数据的乌昌地区地表温度反演. 沙漠与绿洲气象,2010,4(4):48-50 被引 1 次    
2.  陈姚. 遥感图像中云层遮挡影响消除方法研究述评. 国土资源遥感,2006,18(1):64-68 被引 1 次    
3.  Lu L. Estimating land-surface temperature under clouds using MSG/SEVIRI observations. International Journal of Applied Earth Observation & Geoinformation,2011,13(2):265-276 被引 10 次    
4.  刘梅. 利用NDVI估算云覆盖地区的植被表面温度研究. 遥感技术与应用,2011,26(5):689-697 被引 7 次    
5.  涂丽丽. 基于空间内插的云下地表温度估计及精度分析. 遥感信息,2011(4):59-63 被引 8 次    
6.  张军. 利用空间插值法估算云覆盖像元地表温度的可行性研究. 地理与地理信息科学,2011,27(6):45-49 被引 11 次    
7.  Tu L L. Estimation and error analysis of land surface temperature under the cloud based on spatial interpolation. Remote Sensing Information,2011,31(4):59-58 被引 1 次    
8.  Yu W P. Estimating the land-surface temperature of pixels covered by clouds in MODIS products. Journal of Applied Remote Sensing,2014,8(14):083525 被引 2 次    
9.  Hengl T. Spatio temporal prediction of daily temperatures using time-series of MODIS LST images. Theoretical & Applied Climatology,2012,107(1/2):265-277 被引 12 次    
10.  Nguyen O V. Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery. Environmental Monitoring & Assessment,2015,187(7):1-11 被引 5 次    
11.  Hassan Q K. A wetness index using terrain-corrected surface temperature and normalized difference vegetation index derived from standard MODIS products: An evaluation of its use in a humid forest-dominated region of eastern Canada. Sensors,2007,7(10):2028-2048 被引 5 次    
12.  Rahaman K R. Quantification of local warming trend: A remote sensing-based approach. Plos One,2017,12(1):e0169423 被引 1 次    
13.  Xu Y. Reconstruction of the land surface temperature time series using harmonic analysis. Computers & Geosciences,2013,61(4):126-132 被引 5 次    
14.  Weiss D J. An effective approach for gap-filling continental scale remotely sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing,2014,98(98):106-118 被引 5 次    
15.  Zhang G. Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data. Isprs J Photogramm Remote Sens,2015,106:157-171 被引 14 次    
16.  . https://ladsweb.modaps.eosdis.nasa.gov/data/search.html 被引 1 次    
17.  . http://datamirror.csdb.cn 被引 1 次    
18.  杜文涛. 山地冰川区气温重建比较研究-以祁连山老虎沟冰川区为例. 干旱区资源与环境,2011,25(10):149-154 被引 3 次    
19.  乔治. 基于MODIS的2001年-2012年北京热岛足迹及容量动态监测. 遥感学报,2015,19(3):476-484 被引 28 次    
20.  段长春. 太阳活动异常与降水和地面气温的关系. 气象科技,2006,34(4):381-386 被引 17 次    
引证文献 9 篇

1 张连成 基于不同数据的新疆山洪淹没模拟及致灾阈值分析 高原气象,2020,39(1):80-89
被引 0 次

2 杨耘 稀疏样本下冬春季月平均气温空间插值研究———以新疆玛纳斯河流域为例 水资源与水工程学报,2020,31(1):248-253
被引 1 次

显示所有9篇文献

论文科学数据集
PlumX Metrics
相关文献

 作者相关
 关键词相关
 参考文献相关

版权所有 ©2008 中国科学院文献情报中心 制作维护：中国科学院文献情报中心
地址：北京中关村北四环西路33号 邮政编码：100190 联系电话：(010)82627496 E-mail:cscd@mail.las.ac.cn 京ICP备05002861号-4 | 京公网安备11010802043238号