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基于GWR模型的土地覆盖与地表温度的关系——以京津唐城市群为例
引用本文:王佳,钱雨果,韩立建,周伟奇.基于GWR模型的土地覆盖与地表温度的关系——以京津唐城市群为例[J].生态学杂志,2016,27(7):2128-2136.
作者姓名:王佳  钱雨果  韩立建  周伟奇
作者单位:1.中国科学院生态环境研究中心城市与区域生态国家重点实验室, 北京 100085;;2.中国科学院大学, 北京 100049
基金项目:本文由国家自然科学基金项目(41371197)和全国生态环境十年变化(2000—2010年)遥感调查与评估项目(STSN-12-01)资助
摘    要:基于Landsat TM土地覆盖分类数据和MODIS地表温度数据,探讨京津唐城市群不同土地覆盖的地表温度(7日),并采用常用的普通线性回归(OLS)和地理加权回归(GWR)方法分别拟合土地覆盖比例与地表温度的关系.结果表明: 研究区不同土地覆盖类型的地表温度差异明显,人工表面(40.92±3.49 ℃)和耕地(39.74±3.74 ℃)的平均温度较高,林地(34.43±4.16 ℃)和湿地(35.42±4.33 ℃)的平均温度较低;土地覆盖比例与地表温度显著相关,且两者之间的定量关系存在空间非稳定性,地理位置以及周围环境影响的差异是空间非稳定性产生的主要原因;GWR模型的拟合结果优于OLS模型(RGWR2>ROLS2),并且GWR模型可以量化土地覆盖比例与地表温度两者关系的空间非稳定性特征.

关 键 词:京津唐城市群  土地覆盖  地表温度  地理加权回归  空间非平稳性
收稿时间:2016-01-04

Relationship between land surface temperature and land cover types based on GWR model: A case of Beijing-Tianjin-Tangshan urban agglomeration,China.
WANG Jia,QIAN Yu-guo,HAN Li-jian,ZHOU Wei-qi.Relationship between land surface temperature and land cover types based on GWR model: A case of Beijing-Tianjin-Tangshan urban agglomeration,China.[J].Chinese Journal of Ecology,2016,27(7):2128-2136.
Authors:WANG Jia  QIAN Yu-guo  HAN Li-jian  ZHOU Wei-qi
Institution:1.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;;2.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:We used land cover data derived from Landsat thematic mapper (TM) and land surface temperature (LST) data from moderate-resolution imaging spectro-radiometer (MODIS) satellite images to study the variations in LST in July of different land cover types in Beijing-Tianjin-Tangshan urban agglomeration. Ordinary linear regressions (OLS) models and geographically weighted regressions (GWR) models were used to investigate the relationships between the proportions of land cover types and LST. The results showed that great variations in LST occurred among different land cover types. The average LST ranged from high to low in the order of developed land (40.92±3.49 ℃), cultivated land (39.74±3.74 ℃), wetland (35.42±4.33 ℃), and forested land (34.43±4.16 ℃). The proportions of land cover types were significantly related to LST, but with spatial non-stationarity. This might be due to inherent difference in land cover across locations, and the surrounding environments. GWR models had higher R2 values, compared to OLS, indicating better model performance. In addition, GWR models could reveal the spatial non-stationarity of the relations between LST and the proportions of different land cover types.
Keywords:Beijing-Tianjin-Tangshan urban agglomeration  land cover  land surface temperature (LST)  geographically weighted regression (GWR)  spatial non-stationarity  
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