地球科学进展 ›› 2020, Vol. 35 ›› Issue (1): 88 -100. doi: 10.11867/j.issn.1001-8166.2020.008.

研究论文 上一篇    下一篇

福州城市地表温度时空变化与贡献度研究
康文敏 1( ),蔡芫镔 1( ),郑慧祯 1, 2   
  1. 1.福州大学环境与资源学院,福建 福州 350116
    2.福州市规划设计研究院,福建 福州 350108
  • 收稿日期:2019-09-02 修回日期:2019-12-31 出版日期:2020-01-20
  • 通讯作者: 蔡芫镔 E-mail:wenmin_k1994@126.com;caiyuanbin82@163.com
  • 基金资助:
    晋江市福州大学科教园区发展中心科研项目“基于3S技术的闽江河口湿地表面温度扰动特性及驱动机制研究”(2019-JJFDKY-72)

Spatial-temporal Patterns of Land Surface Temperature and Influencing Factors Contribution in Fuzhou City

Wenmin Kang 1( ),Yuanbin Cai 1( ),Huizhen Zheng 1, 2   

  1. 1.College of Environment and Resources, Fuzhou University, Fuzhou 350116, China
    2.Fuzhou Planning Design and Research Institute, Fuzhou 350108, China
  • Received:2019-09-02 Revised:2019-12-31 Online:2020-01-20 Published:2020-02-27
  • Contact: Yuanbin Cai E-mail:wenmin_k1994@126.com;caiyuanbin82@163.com
  • About author:Kang Wenmin (1994-), female, Nanping City, Fujian Province, Master student. Research area include urban ecological research. E-mail: wenmin_k1994@126.com
  • Supported by:
    the Jinjiang-Fuzhou University Science and Education Development Center Research “Study on land surface temperature disturbance characteristics and driving mechanism of wetland in Minjiang estuary based on 3S technology”(2019-JJFDKY-72)

随着全球变暖和城市化进程的加快,城市区域的热环境问题日益凸显。以福州为例,基于遥感、地理信息系统和地统计学等方法,通过多尺度空间模式,定量分析以地表温度贡献度为表征的城市热环境时空变化及其特征。结果表明: 1993—2016年,研究区的土地利用/覆盖类型发生了显著变化,建设用地净增长1 231.04 km2,变化率高达295.33%;耕地被建设用地占用。 地表温度空间格局变化明显,中高温区以闽江水域为轴向周边区域逐渐蔓延,低温区和次低温区面积显著减少。 1993—2016年,福州所辖各县市区地表温度贡献时空分布不均。其中,中心城区(鼓楼区、台江区、仓山区、晋安区和马尾区)对地表温度上升表现为正贡献,闽清县和永泰县表现为负贡献。从不同土地利用/覆盖类型来看,林/草地、耕地、水体对地表温度升高有负贡献,建设用地表现为正贡献。 多距离空间聚类分析(Ripley’s K函数)显示,地表温度集聚与分散存在尺度效应;1993—2016年,研究区的地表温度集聚范围逐步扩大、集聚程度增强。

With the intensification of urbanization and global warming, the problems of urban thermal environment are increasingly prominent. On the basis of the remote sensing, geographic information system, geostatistics and multiscale spatial pattern, the spatial-temporal variation characteristics of land surface temperature in urban thermal environment were quantitatively analyzed. The results are as follows: Dramatic changes in land use/land cover had occurred from 1993 to 2016 in the study area. The net increase area of construction land was 1 231.04 km2, with a change rate of 295.33%. Cultivated land was occupied by construction land. The area of middle, sub-high and high temperature zones spread to the surrounding areas gradually with the Minjiang River. The area of sub-low and low temperature zones decreased markedly. From 1993 to 2016, the contribution of land surface temperature in different urban districts had the characteristics of uneven spatial and temporal distribution. Meanwhile, there was a positive contribution in the process of land surface temperature rise in Fuzhou while there was a negative contribution in Minqing and Yongtai. Forest/grassland, cultivated land, water body and wetland had a negative contribution during land surface temperature rise while construction land contributed positively. According to the multi-distance spatial cluster analysis (Ripley's K function), there was a certain scale in the aggregation and dispersion of land surface temperature, in which the aggregation range and degree of aggregation increased in the study area in 24 years.

中图分类号: 

图1 研究区地理位置图(a)及其Landsat 5影像(b)(1993-06-26
Fig.1 Location of the study area a and its Landsat 5 image b) (1993-06-26)
表1 19932016年遥感影像数据
Table 1 Landsat data used from 1993 to 2016
图2 19932016年研究区土地利用/覆盖图
Fig.2 Land use/cover map of the study area from 1993 to 2016
表2 19932016年土地利用 /覆盖分类精度评价
Table 2 Land use/cover classification accuracy evaluation from 1993 to 2016
图3 19932016年地表温度等级分布图
Fig.3 Land surface temperature zones from 1993 to 2016
图4 19932016年相对地表温度等级分布图
Fig.4 Relative land surface temperature zones from 1993 to 2016
图5 研究区地表温度采样点位置图
Fig.5 Location of land surface temperature sampling points in the study area
表3 19932016年土地利用 /覆盖类型面积变化统计
Table 3 Area statistics of land use/cover types from 1993 to 2016
表4 19932016TN等级分区面积统计
Table 4 Area statistics of TN grades from 1993 to 2016
图6 19932016年各地区贡献度指数
Fig.6 Contribution index of different regions from 1993 to 2016
图7 19932016年各地类贡献度指数
Fig.7 Contribution index of different land use/cover types from 1993 to 2016
图8 19932016年土地利用/覆盖类型与地表温度回归分析(单个网格面积:360 000 m2
Fig.8 The regression analysis between land use/cover types and LST from 1993 to 2016 (per grid area:360 000 m2)
表5 19932016年平均最近邻比率 (RLST>2) (300 m×300 m)
Table 5 Average nearest neighbor ratio from 1993 to 2016( RLST>2) (300 m×300 m)
图9 19932016年不同RLST等级的NNR
Fig.9 NNR of different RLST grades from 1993 to 2016
表6 19932016RLST等级分区面积统计
Table 6 Area statistic of RLST grades from 1993 to 2016
图10 19932016RLSTRipleys Ld)函数(300 m×300 m
Fig.10 Ripleys L (d) functions of RLST from 1993 to 2016 (300 m×300 m)
表7 19932016年不同空间分辨率下的空间尺度临界值 km
Table 7 Critical values of spatial scale under different spatial resolutions from 1993 to 2016 km
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