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基于遥感的近20年银川市热力景观变化研究

Urban Thermal Landscape Pattern Variation in Yinchuan City Based on Remote Sensing from1989to2011

【作者】 王鹏龙

【导师】 张建明;

【作者基本信息】 兰州大学 , 地球系统科学, 2013, 硕士

【摘要】 城市化改变了地表土地利用/覆被类型和格局,使得城市热环境发生改变,引起一系列生态问题。研究典型地区城市热环境变化,可以从热环境的角度反映城市化强度的空间分布,评价城市化对生态与环境的影响,亦可为提出调控城市热岛效应措施提供理论依据,同时,为同类城市的生态规划、环境监测以及城市化可持续发展提供有意义参考。基于遥感,本文以单窗算法反演了银川市的地表温度,利用探索性空间统计分析的原理与方法,结合半变异函数,分析了地表温度热场的结构、空间特征表达和空间异质性。同时,应用景观生态学理论与方法,分析了整个研究区的热环境景观格局特征与演化规律,研究了土地利用/覆被对热环境的影响,得到以下结论:1.研究区热场:近20年,研究区热场发生了很大变化,裸地和建设用地形成了主要的高温区域。随城区面积扩大,城区高温区范围亦扩大。地表温度热场均有显著的空间自相关性,表现为随土地利用/覆被的不同,高温区域和低温区域呈空间聚集分布,热场存在很好的空间依赖性。2.热力景观格局分布:研究区大范围为绿岛和弱热岛,生态环境良好。近20年绿岛面积在下降,热岛范围扩大,高等级热力斑块面积在1989年最大,2000年较小,2011年又有所增加;从城区来看,热岛范围在扩大,但主城区中心出现低等级热力斑块,生态与环境改善。3.热力景观格局演变:类型水平上,各类热力景观斑块基本上在2000年之前趋于破碎化,2000年之后趋于聚集,斑块形状趋于规则化;景观水平上,热力景观整体经历了2000的破碎化后,逐渐趋于聚集,斑块的形状亦趋于规则化,景观面积在各类斑块间的分配趋向均匀,反映了对城市的规划等人为活动加强。4.热力景观转化规律:在人为活动的干扰下,由水域和绿地形成的绿岛是最稳定的热力景观类型;低等级景观类型(绿岛和弱绿岛)和高等级景观类型(强热岛和极强热岛)两者内部较容易转化,但两者之间难转化。中等热岛较易转化为低等级景观类型和高一级的强热岛,较难转化为极强热岛。5.地表温度和土地利用/覆被类型的关系:裸地的平均地温最高,其次是建设用地,绿地和水体平均地温较低。裸地和建设用地对高等级热力景观有很大贡献,是城市热环境强度的主要贡献因子。绿地和水体的降温作用对分割和控制城市热岛效应分布具有重要的实际意义,因此,合理的规划绿地和水体有助于改善城市的热环境。6.地表温度和土地利用/覆被格局的关系:在整个景观水平,地表温度和土地利用/覆被景观格局指数之间没有很好的整体相关性。较之景观整体水平,在类型水平上,土地利用/覆被的景观格局指数和地表温度的相关性更好,反映出不同的土地利用/覆被格局对地表温度的影响大小不同。所以,同类土地利用/覆被的空间格局对地表温度的影响更大。7.在一定尺度和辐射背景假设下,建立了土地利用/覆被格局和地表温度之间的的回归模型,从而定量的分析了不同土地利用/覆被及其格局对地表温度的影响程度。并在同样假设下,分析表明,近20年,主要城区的地表温度升高了约16.89%。

【Abstract】 With the process of urbanization, land use/cover types and pattern changes a lot, which alters the urban thermal environment and arouses a series of ecological problems. Studying the mechanism of urban thermal environment change in typical zones can reflect the distribution of urbanization intensity from the perspective of urban thermal environment, evaluate the impact of urbanization on ecology and environment, provide theoretical basis for measures of regulating and controlling urban heat island effect (UHI), and finally provide good references for ecological urban planning, environmental monitoring, and sustainable development of similar scale cities.Based on3LandsatETM+/TM images of Yinchuan from1989to2011, this paper retrieved land surface temperature (LST) by Qin’s mono-window algorithm. With exploratory spatial data analysis (ESDA) method and variograms, LST thermal pattern, spatial characteristic and spatial heterogeneity were analyzed. Moreover, by the theories and method of Landscape ecology, thermal landscape pattern and variation rule were studied, and impact of land use/covers on thermal environment were also analyzed, and finally some results were attained as follows:1. Thermal environment characteristics of study area:In recent20years, thermal environment alters a lot, and high-LST area consist of built land and bare land. As urban area expands, high-LST area of urban area enlarges. LST distribution has positive spatial autocorrelation, namely, with the change of land use/covers, high-LST area and low-LST area have spatial aggregation in distribution, and LST distribution has good spatial dependence.2. Thermal landscape pattern:Cool island and weak heat island patches account for large area in study area, which shows ecology and environment in study area are well. In recent20years, cool island area decreased and urban heat island area increased. High-grade thermal patches area was maximum in1989, had a little area reduction, and increased in2011; Urban heat island area in all urban areas are expanding, but there exist low-grade thermal patches in main urban areas, which improve the ecology and environment in main urban areas.3. Thermal landscape pattern variation:At class level, all thermal patch types mainly tended to be more fragmented from1989to2000, more aggregated from2000to2011, and patches shape tended to be simplified; At landscape level, urban thermal landscape pattern saw a turning point in2000:urban thermal landscape pattern was more fragmented from1989to2000, but, it became more aggregated and patches shape tended to be simplified from2000to2011. Each grade of urban thermal patch types became even-distributed. These changes indicate the increase of human activities intensity.4. Thermal patches transition:Under the influence of human intervention, cool island consisting of green land and waterbody was the stablest urban thermal patches. The low-grade thermal patches (cool island and weak heat island) were easy to transfer among themselves, but they were difficult to transfer to high-grade thermal patches. Moderate heat island was easy to transfer to the low-grade thermal patches or higher-level thermal patches. The high-grade thermal patches (strong heat island and Strongest heat island) were easy to transfer among themselves, but they were difficult to transfer to low-grade thermal patches.5. Relationship between LST and land use/cover types:Average LST of bare land is highest, and average LST of green land and waterbody are lower. Bare land and built land contribute much to the formation of high-grade thermal patches, hence, they are main contributor to urban heat island intensity. Green land and built land with cooling effect have actual significance on segmenting and controlling urban heat island distribution, therefore, rational planning of green land and waterbody pattern conduce to improve urban thermal environment.6. Relationship between LST and land use/covers pattern:At the landscape level, LST and landscape metrics have little significant correlation. Compared with landscape level, at the class level, correlation between LST and landcape metrics is more significant, which indcates different land use/covers patterns have different impact on LST. Hence, pattern of the same land use/cover influence LST more.7. Under the certain scale and radiation background, through building regression model, the effect degree of land use/cover types and pattern on LST were analyzed quantitatively. Given the same hypothesis, the results showed:in recent20years, the average LST in main urban areas increased by16.89%.

  • 【网络出版投稿人】 兰州大学
  • 【网络出版年期】2013年 11期
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