期刊信息

  • 刊名： 河北师范大学学报（自然科学版）Journal of Hebei Normal University (Natural Science)
  • 主办： 河北师范大学
  • ISSN： 1000-5854
  • CN： 13-1061/N
  • 中国科技核心期刊
  • 中国期刊方阵入选期刊
  • 中国高校优秀科技期刊
  • 华北优秀期刊
  • 河北省优秀科技期刊

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友情链接

2010—2022年河北省地表温度时空变化研究

  • 1.河北师范大学 地理科学学院，河北 石家庄 050024; 2.兰州大学 资源与环境科学学院，甘肃 兰州 730000; 3.河北省环境变化遥感识别技术创新中心，河北省环境演变与生态建设实验室，河北 石家庄 050024
  • DOI： 10.13763/j.cnki.jhebnu.nse.202505005

Study on Spatial and Temporal Variation of Land Surface Temperature in Hebei Province from 2010 to 2022

摘要/Abstract

摘要：

地表温度(LST)是研究气候变化的关键参数，掌握其最新变化特征对河北省气候、生态等领域的研究具有重要意义.选取每年4个典型月份(1、4、7、11月)中数据缺失率最低天的 MOD02 数据，采用 MST 软件完成数据预处理，基于 MATLAB 软件，运用劈窗算法实现 2010—2022 年河北省地表温度批量反演.结合温度反演过程中获取的归一化植被指数(NDVI)数据以及数字高程模型(DEM),采用 AreGIS 空间分析与数理统计方法，分析 2010—2022 年河北省地表温度在不同季节尺度上的时空变化趋势及其影响因素.结果表明：1) 河北省 2010—2022 年地表温度变化以升温趋势为主，其中冬季与秋季升温趋势更显著;春季和夏季则存在局部降温区域，且该类区域主要集中在河北省中南部区域；2) 河北省地表温度的变化与植被动态演变关系密切，NDVI 年际变化率与 LST 年际变化率呈正相关，相关系数达 0.41,由于 NDVI 与人类活动密切相关，因此合理保护生态环境可作为调控地表温度升温的有效途径之一；3) 河北省地表温度与高程呈负相关，相关系数为 -0.93,地表温度的空间分布特征明显受该省地势格局影响；4) 本研究将劈窗算法与 MODIS 数据相结合，反演精度在一定程度上高于 MODIS 地表温度产品(MOD11_L2),更能精准反映具体时刻的地表温度特征.研究结果可为河北省生态可持续发展提供最新数据支撑与科学依据.

Abstract：

Land surface temperature(LST)is an important parameter in the study of climate change,and the latest changes in LST is essential in the study of many fields such as climate,hydrology,ecology and biogeochemistry in Hebei Province.In this paper,MOD02 data of the day with the lowest data missing rate in four typical months(January,April,July and November)of each year were selected,and the data were preprocessed by MST software,and the batch inversion of surface temperature in Hebei Province from 2010 to 2022 was completed by using the split-window algorithm based on MATLAB software.Combining the normalized difference vegetation index(NDVI)data and dgital elevation model(DEM)in the temperature inversion process,AreGIS spatial analysis and mathematical statistics were used to explore the spatial and temporal trends of surface temperature in Hebei Province from 2010 to 2022 at different seasonal scales and their influencing factors.The results showed that:1) Surface temperature changes in Hebei Province from 2010 to 2022 were dominated by warming trends,with more obvious warming trends in winter and autumn,and cooling trends in a small number of regions in spring and summer,mostly concentrated in the central and southern regions of Hebei Province;2) Surface temperature changes in Hebei Province were closely related to vegetation changes,and the interannual rates of NDVI change were positively correlated with LST,and correlation cofficient was 0.41.Since NDVI is closely related to human activities,reasonable protection of ecological environment is one of the solutions to control surface temperature warming;3) Surface temperature was negatively correlated with elevation,and correlation coefficient was as high as -0.93.Therefore,the spatial distribution of surface temperature was significantly influenced by the topographic characteristics of Hebei Province;4)The advantages of this research are mainly for the realization of the split-window algorithm combined with MODIS data and applied to the study of Hebei Province,and the inversion accuracy is somehow higher than the MODIS surface temperature product,which can better reflect the surface temperature inversion at specific moments.The above study can provide the latest data support and scientific basis for the sustainable ecological development of Hebei Province.

关键词

关键词： 地表温度；MODIS ; 劈窗算法；时空变化
Key words： land surface temperature ; MODIS ; split-window algorithm ; spatial and temporal variation

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