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1.
城市热岛遥感监测分析中,不同参数与指标得到的热岛时空分布结果不同。针对过去研究仅利用遥感反演地表温度或亮度温度监测城市热岛现象,以福建省晋江市为研究区,选择2010年与2014年夏季Landsat数据,结合数字高程数据和气象站点实测数据,反演晋江市域内地表温度与近地表气温。在此基础上,利用多源参数计算多种城市热岛监测指标,并对比分析这些指标用于晋江城市热岛研究的差异性。结果表明:1)2014年较2010年的城市热岛范围扩大,区域内热岛比例显著上升,热岛斑块面积增多且热岛等级增强;2)相对于地表温度,近地表气温用于评价城市热岛空间分布更为合理;3)不同热岛监测指标作用不同,热岛强度、归一化热场强度可以在空间上直接表明热岛空间分布及强弱,热岛比例指数则在数值上反映了不同区域热岛现象的发生概率,热岛源汇指数结合地表热参数和土地覆盖类型,反映了土地利用变化对区域内热岛效应加剧或减缓的贡献程度。  相似文献   

2.
基于遥感的长沙市城市热岛效应时空分析   总被引:1,自引:0,他引:1  
利用TM/ETM+数据,以长沙市为例,反演了地表温度,并针对不同时相的遥感数据,利用城市热岛强度来反映热岛效应强弱的变化。结果表明,长沙市的热岛空间分布与城市建成区的轮廓相吻合。城市热岛的范围随着城市建设、新建开发区以及道路交通网的发展不断增大,且在东南方向为主要增长方向。根据热岛强度鉴别并提取了强热岛区与正常区,发现长沙市强热岛区的面积已经从1993年的13.18km2扩大至2008年的68.16km2。最后,对长沙市热岛未来的发展趋势进行了预测。  相似文献   

3.
基于MODIS 数据的南京市夏季城市热岛分析   总被引:3,自引:0,他引:3       下载免费PDF全文
城市热岛效应是当前城市环境与气候主要研究内容之一。地表温度与气温之间有紧密的联系, 通过遥感反演地表温度已成为研究城市热岛的有效手段。利用MODIS 数据, 获取地表比辐射率与大气透过率2 个基本参数, 运用劈窗算法反演南京市夏季地表温度。基于不同时相的MODIS数据, 对4 幅南京市地表温度反演图像作对比分析, 较好地显示了南京市城市热岛的空间分布、热岛范围和城市热岛强度, 结果表明南京市夏季热岛问题较为严重。  相似文献   

4.
文中使用城市热异常信息提取算法(urban thermal anomaly extraction,UTAE)提取城市热岛信息.该算法使用不同大小的滑动窗口来探测整幅图像,根据稳健估计的方法设定地表温度高于全部像元以及窗口内像元温度统计均值加标准差的像元为热异常像元,并将滑动窗口的范围设置在3×3至9×9个像元之间,根据像元被记为热岛像元的次数是否为0来区别热岛区与非热岛区,在热岛区域内根据次数的多少来决定热岛强度,具有动态阈值的特点和无偏特性.研究结果表明,在城市热岛范围的提取上,2004年2月13日长沙市热岛面积在27.21—33.98km2之间;在城市热岛强度和尺度效应分析上,宏观尺度的研究应选用较大的窗口来体现城—郊热岛关系以及热岛发展的总体趋势,而小窗口在微观分析城区内热岛的具体分布、与下垫面的关系以及驱动因子方面较有优势.最后,对UTAE算法在中巴地球资源卫星后继星数据上的应用做出了展望.  相似文献   

5.
杭州市城市空间扩展及其热环境变化   总被引:2,自引:0,他引:2       下载免费PDF全文
通过Landsat卫星影像分别获取了杭州市1989、2000和2010年的城市空间扩张、地表温度及作为主要地表参数的建筑用地和植被的信息,用以研究杭州市城市扩展及其城市热环境变化。结果表明:在21 a间,杭州市建成区范围有了大幅扩展,且城市热岛区域的空间变化与建成区的空间扩展变化基本一致。研究还发现杭州市区的特高温区面积比例在逐渐减小,城市热岛比例指数(URI)从0.78降至0.71,表明城市热岛效应有一定缓解。建筑用地比例的减小与建筑用地密度的下降是城市热岛得以缓解的主要原因。定量分析表明建筑用地的升温效应要强于植被的降温效应。总的看来,杭州市的城市热岛效应现象在整个研究时段内虽有一定的改善,但仍一直处于较强烈的状态。  相似文献   

6.
城市快速扩张导致城乡梯度土地覆盖发生显著的变化,引发不透水地表的增加,植被覆盖的减少,从而加剧了城市热岛强度。研究城乡梯度土地覆盖变化引起的城市热岛效应,并揭示城市热岛的时空特征及强度的变化,对城市规划建设、人居环境改善及提升城市生态系统服务功能具有重要的意义。基于Landsat系列4期影像,利用单窗算法反演西安市地表温度,计算热场变异指数得到热力场强度图并对其进行等级划分,结合土地利用/覆盖类型数据分析城乡梯度土地覆盖变化对城市热岛强度的影响。结果表明:①2000年西安市极强热岛效应区占研究区面积的10.58%,逐渐增加到2011年极强热岛效应区域的面积占比达到16.14%,而后到2015年降低为9.00%,整体上西安市城市热岛效应呈现出了先增长后降低的趋势;②2000年到2015年城乡建设用地面积增加了412.76 km2,极强热岛强度的范围随城市建成区的扩张逐年向外扩展;③无热岛效应区约70%位于耕地和林地,水域在无热岛效应中的占比也在逐年增多,从31%增加到了47%。不透水地表面积占比与地表温度有显著相关性,城乡梯度植被和水体面积的增加可以有效地缓解城市热岛强度。  相似文献   

7.
不同地表参数变化的上海市热岛效应时空分析   总被引:1,自引:0,他引:1       下载免费PDF全文
研究地表参数变化与热岛效应的关系对优化城市功能分区以及城市可持续发展具有重要意义。采用上海市2000、2005、2009年3个时期的Landsat ETM+卫星遥感影像,使用归一化不透水面指数(NDISI)、基于指数的植被指数(IVI)、归一化差异水体指数(MNDWI)分别从遥感影像中提取不透水面、植被和水体;然后从时间、空间角度并采用回归分析方法分析了上海市地表参数在这9 a中发生的变化及其对城市热环境造成的影响。结果表明:9 a中城市不透水面面积大幅增加,不透水面增加的代价是植被和水体大范围减少,形成了城市的热岛。上海市整体热岛强度是先增强后缓慢减弱的趋势,且热岛分布从集中型向分散型发展。  相似文献   

8.
基于2014年8月15日的Landsat 8影像,通过劈窗算法反演西安中心城区地表温度,定量测算热岛中心范围。估算多种地表能量分量,分析热环境格局与地表能量分量的关系。结果表明:(1)西安中心城区城市热岛集中分布在人口、居住、商业密集区、经济技术开发区以及植被覆盖较差的区域;(2)感热、波文比与地表温度呈正相关,人为热与温度呈不显著正相关,净辐射、潜热与地表温度呈显著负相关;(3)城市热岛的地表能量结构中感热与潜热差异是构成城市热岛差异的主要原因。  相似文献   

9.
用气象卫星信息探测川西平原的城市热岛群   总被引:4,自引:0,他引:4  
由于城市与郊区有截然不同的下垫面,加之城区人口密集,活动频繁,释放大量人为热量,因此导致城市温度比郊区高,从而形成城市热岛现象。 1989年7月28—29日,川西平原晴空,利用下午过境的气象卫星探测了该区的城市热岛群。在图像上能清楚看出范围大小不等的小红圓点,它们就是城市热岛群。另外城市面积越大,红点范围就越大,即城市热岛范围越大,反之则小。特别在定量的数字资料上一般都能判释川西平原的所有县市,甚至包括部份乡镇的位置。虽然多数的面积不大,但城市热岛现象明显,边界清楚,热岛分布形态与城市建成区布局基本吻合。根据数字资料判释的城市范围,将川西平原的城市热岛群分为三类:第一类为城市热岛面积最大的成都市;第二类为热岛面积次之的绵阳、德阳等地市;第三类为热岛面积不大的一般县城(包括个别乡镇)。  相似文献   

10.
以长株潭城市群区域为例,利用2005年3个不同季节的TERRA/MODIS数据提取的地表温度、归一化植被指数(NDVI)和归一化建筑指数(NDBI),分析了城市热岛效应及其随季节的变化,采用归一化植被指数(NDVI)和归一化建筑指数(NDBI)作为反映地表生物物理特征的参数,分析了城市热岛时空特征与地表生物物理参数的关系。研究结果表明,研究区域城市热岛效应的季相变化明显,一年中夏季与春季的城市热岛效应相对显著,城市地表温度高出周边的郊区达8~10℃;而冬季城市热岛效应相对不太明显,城市地表温度高出周边的郊区4℃。地表温度与归一化植被指数(NDVI)的相关性随季节变化较为明显,说明通常将归一化植被指数(NDVI)作为城市地表温度或城市热岛的代用指标是不适宜的;然而,地表温度与归一化建筑指数(NDBI)在不同季节都呈显著的线性关系,而且地表温度与NDBI线性关系的斜率和截距能够很好地指示不同季节城市热岛的强度,这就为定量分析不同季节城市地表温度的变化提供了物理指数,也为利用遥感研究城市热岛效应提供了新的方法与途径。  相似文献   

11.
This paper focuses on the monitoring of the urban heat island (UHI) effect with temporal and spatial variation, combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Thematic Mapper (TM) data. Our study area is located in the central urban area of Beijing, which mainly refers to the areas within the fifth ring road. For detecting UHI changes over the years 2002–2006, three ASTER images in the summers of 2003, 2004 and 2006 and two TM datasets in the summers of 2002 and 2005 were collected. For monitoring UHI changes with the seasons, three ASTER images and one TM image in 2004 in winter, spring, summer and autumn, respectively, were employed. To calculate the urban heat island intensity, the land surface temperatures were retrieved iteratively for ASTER data and using a generalized single-channel method for the TM image. Four separated regions located in four directions outside the fifth ring road were selected as representing rural comparative regions. Their averaged land surface temperature was regarded as the rural comparative temperature. The UHI intensity was computed by the difference between the pixel urban land surface temperature in the urban area and the comparative temperature in the rural area. Detection of the UHI effect over 2002 to 2006 indicated that most of the areas with high UHI effect were the industrial land use regions and the areas having a high density of buildings, roads, transportations and residents; and the areas without UHI effect were located around the regions with large areas of grassland, trees and water bodies. Our results also showed that the UHI effect was not proportional to urbanization over time. Statistical UHI data during 20 July to 20 September in 2003–2008 also support this point. The monitoring of the UHI effect over seasons (winter, spring, summer and autumn) showed that the urban area of Beijing city had a high UHI effect except in winter, when the urban area of Beijing was in an urban heat sink; the UHI effect increased in spring, summer and autumn.  相似文献   

12.
The urban heat island (UHI) effect is the phenomenon of increased surface temperatures in urban environments compared to their surroundings. It is linked to decreased vegetation cover, high proportions of artificial impervious surfaces, and high proportions of anthropogenic heat discharge. We evaluated the surface heat balance to clarify the contribution of anthropogenic heat discharges into the urban thermal environment. We used a heat balance model and satellite images (Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images acquired in 1989 and 2001), together with meteorological station data to assess the urban thermal environment in the city of Fuzhou, China. The objective of this study was to estimate the anthropogenic heat discharge in the form of sensible heat flux in complex urban environments. In order to increase the accuracy of the anthropogenic heat flux analysis, the sub-pixel fractional vegetation cover (FVC) was calculated by linear spectral unmixing. The results were then used to estimate latent heat flux in urban areas and to separate anthropogenic heat discharge from heat radiation due to insolation. Spatial and temporal distributions of anthropogenic heat flux were analysed as a function of land-cover type, percentage of impervious surface area, and FVC. The accuracy of heat fluxes was assessed using the ratios of sensible heat flux (H), latent heat flux (L), and ground heat flux (G) to net radiation (R n), which were compared to the results from other studies. It is apparent that the contribution of anthropogenic heat is smaller in suburban areas and larger in high-density urban areas. However, seasonal disparities of anthropogenic heat discharge are small, and the variance of anthropogenic heat discharge is influenced by urban expansion, land-cover change, and increasing energy consumption. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban climate change adaptation strategies. Remote sensing can play a role in mapping the spatial and temporal patterns of UHIs and can differentiate the anthropogenic heat from the solar radiative fluxes. The findings presented here have important implications for urban development planning.  相似文献   

13.
Urbanization is typically accompanied by the reconstruction or relocation of heavy industrial areas due to limited space and high standard environmental requirements.Taking "environment\|friendly relocation" of Chongqing Iron and Steel Group as an example,this study quantitatively compares and analyzes changes of the thermal and ecological conditions before and after the relocation.Main biophysical properties of the study area and land surface temperature(LST) were retrieved from the multi\|temporal Landsat serial satellite images.Urban Heat Island Index(URI) and Remote Sensing based Ecological Index(RSEI) were employed for the study.The results reveal that urban heat island effect of the industrial area was significantly mitigated and the ecological quality was significantly improved after the relocation,suggested by the decline of URI value from 0.387 in 2005 to 0.128 in 2014(a drop of 66.7%),and the rise of RSEI value from 0.398 to 0.553 during the same period(an increased of 38.9%).This is due largely to the halting of steel production,change of land cover types and properties caused by the “environment\|friendly relocation” of the industrial area.In general,the halting of steel production,the decrease of impervious surface and the increase of vegetation coverage can mitigate the heat island effect and improve the ecological quality.The result of this study can provide a useful case for reconstruction or relocation of urban heavy industrial area and promotion of city’s healthy sustainable development.  相似文献   

14.
利用2007年10月5日覆盖合肥市的TM影像反演了NDVI和LST,并结合GIS技术和城市形态分维理论,分析了合肥市热环境布局以及不同热环境等级与各土地利用类型的关系.结果表明:合肥市地表温度具有东南高、西北低的热岛效应存在,热岛效应的中心并未出现在城市中心区域.LST与NDVI呈明显负相关关系(相关系数为-0.734...  相似文献   

15.
At present,the automatic extraction of urban built\|up area is still a problem.Taking Shanghai city as an example,this research uses the binary image,which was derived from an IBI(index\|based built\|up index)image,as the geographical cellular automaton initial input data.This was then imported to the extended cellular automata model for further processing.After a series of processing such as thresholding,corrosion and connectivity test,the urban built\|up area was simulated and can be extracted.Based on this method,the urban built\|up area of Shanghai in five different years between 1987 and 2015 was extracted using multi\|temporal Landsat images of Shanghai.In addition,the urban growth intensity index,the concentric buffers analysis and radar chart analysis were calculated and used to analysis spatiotemporal pattern of Shanghai urban expansion in the 28 study years.The result shows that the built\|up area of Shanghai was expanded from 195 km2 in 1987 to 1759 km2 in 2015,which is eight times as large as that in 1987.In the period between 1987 and 2002,the urban built\|up area expanded mainly along the North\|South axis of the Huangpu River.However,after 2002 the expansion rate was increased more quickly,and the direction of the expansion was shifted to an east to west direction.Generally speaking,Shanghai has experienced a rapid urban expansion in the recent three decades.  相似文献   

16.
Examination of the diurnal variations in surface urban heat islands (UHIs) has been hindered by incompatible spatial and temporal resolutions of satellite data. In this study, a diurnal temperature cycle genetic algorithm (DTC-GA) approach was used to generate the hourly 1 km land-surface temperature (LST) by integrating multi-source satellite data. Diurnal variations of the UHI in ‘ideal’ weather conditions in the city of Beijing were examined. Results show that the DTC-GA approach was applicable for generating the hourly 1 km LSTs. In the summer diurnal cycle, the city experienced a weak UHI effect in the early morning and a significant UHI effect from morning to night. In the diurnal cycles of the other seasons, the city showed transitions between a significant UHI effect and weak UHI or urban heat sink effects. In all diurnal cycles, daytime UHIs varied significantly but night-time UHIs were stable. Heating/cooling rates, surface energy balance, and local land use and land cover contributed to the diurnal variations in UHI. Partial analysis shows that diurnal temperature range had the most significant influence on UHI, while strong negative correlations were found between UHI signature and urban and rural differences in the normalized difference vegetation index, albedo, and normalized difference water index. Different contributions of surface characteristics suggest that various strategies should be used to mitigate the UHI effect in different seasons.  相似文献   

17.
According to the UN Population Reference Bureau, 1.4 billion more people will have settled in urban areas by 2030. One of the key environmental effects of rapid urbanization is the urban heat island (UHI) effect. Understanding the mechanism of surface UHIs associated with land-use/land-cover (LULC) change patterns is important for improving the ecology and sustainability of cities. In this article, time series Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) data were used to extract LULC data and land surface temperature (LST) data for the city of Jinan, China, from 1987 to 2011, a period during which the city experienced rapid urbanization. With the aid of a geographical information system (GIS) and remote sensing (RS) approach, the changes in this urban area’s LULC were explored, and the impact of these changes on the spatiotemporal patterns and underlying driving forces of the surface UHI effect were further quantitatively characterized. The results show that significant changes in land use and land cover occurred over the study period, with loss of farmland, forest, and shrub vegetation to urban use, leading to spatial growth of impervious surfaces. Consequently, the land surface characteristics and spatiotemporal patterns of the UHI have changed drastically. According to the seasonal and inter-annual variations in intensity of UHIs, mean differences in UHI intensity between city centre, peri-urban, and nearby rural areas were stronger during summer and spring and weaker during winter and autumn. Spatially, there were significant LST gradients from the city centre to surrounding rural areas. The city centre exhibited higher LSTs and remarkable variation in LSTs, while the surrounding rural areas exhibited lower LSTs and lower variation in LSTs. Moreover, the analysis of LSTs and indices showed that great differences of temperature even existed in a LULC type except for variations between different LULC types. In addition, a local-level analysis revealed that the intensity of the UHI effect is proportional to the size of the urban area, the population density, and the frequent occurrence of certain activities.  相似文献   

18.
基于DSM和影像特征的城市变化检测   总被引:6,自引:0,他引:6  
随着城市的快速发展,城市的变化也越来越明显。为了能更好地为城市规划人员、城市管理决策人员及时提供信息,有必要对城市的变化发展进行适时地监测。利用大比例尺的航空影像来对城市地区的人工建筑物的变化进行检测,根据城市地区人工建筑物的变化主要反映在高度上的变化这一特点,利用两个不同时期的立体像对,从而生成两个不同时期的数字表面模型(DSM),在此基础上来检测出城市地区人工建筑物的变化区域。由于DSM影像上不仅有人工建筑物的变化反映在高度变化上,而且也有其它如树木等的变化反映在高度变化上。由于检测的目的是了解城市地区内人工建筑物的变化情况,所以利用DSM提出待选变化区域,在待选变化的区域中利用了梯度方向直方图、灰度匹配、及直线特征匹配等方法来针对城市地区人工建筑物的变化进行进一步的分析。利用日本的两个不同时期的1∶1万的航空影像进行了实验,从实验结果来看,所提出的方法是可行的,同时该方法简单、直观且易于操作。  相似文献   

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