Riparian thermal conditions across a mixed rural and urban landscape

Riparian corridors have the potential to function as thermal refuges, moderating extremes of local temperature variation. However, although demonstrated at individual sites, and over short periods, the consistency of this effect at wider temporal and spatial scales is poorly understood. The aim of this study is to assess the temperature differences between riparian corridors and adjacent non-riparian habitats and to explore the influence of environmental characteristics on these differences. Air temperature was monitored hourly at 20 paired locations (riparian and non-riparian) for two consecutive years. Urban index and canopy cover were characterised by calculating the percentage of impervious surface area and tree canopy cover within a 100 m radius from the centre of each sampling site. Canopy cover reduced summer thermal stresses in both urban and rural areas whereas high urban index tended to increase the daily thermal indices. Rivers had a significant mitigating effect on the urban riparian thermal condition, particularly in extreme hot weather. Riparian corridors were generally 1 °C cooler than non-riparian locations in summer and could be up to 3 °C cooler at some sites in extreme hot weather. Furthermore, riparian corridors at some sites were warmer than non-riparian locations in winter. These findings suggest that the proximity of rivers can modify riparian thermal environments, potentially reducing the heat stress of riparian corridors across landscapes.     

The role of local land-use on the urban heat island effect of Tel Aviv as assessed from satellite remote sensing

Climate change in cities has received much focus in the past few decades. Heat stress in urban areas has an adverse effect on human health and is expected to worsen in the future due to the global warming. Vegetation has been shown to mitigate this effect, but introducing ‘green’ areas into the metropolitan space is a challenging task. We assessed the thermal load in terms of surface temperature in Tel Aviv, the biggest metropolitan area of Israel. The thermal effect of four different urban land uses was estimated. Specifically, we compared the cooling effect of residential areas with high vegetation cover (referred here as ‘green’ residential) to that of small to medium size (2–40 ha) public parks. To this end, we used satellite data of land surface temperature (LST) and the Normalized Difference Vegetation Index (NDVI), as a surrogate for vegetation cover. High-temporal data were combined with high spatial resolutions data to produce 10-year average LST and NDVI maps at high spatial resolution over Tel Aviv. As expected, industrial areas had the highest LST due to lowest ratio of vegetation to free space area (1%), while ‘green’ areas displayed the lowest LST. Green residential and small-medium public parks had comparable thermal loads, with green residential having slightly lower LST (by 0.5 °C). In general, small-medium public parks displayed higher LST than expected. Inefficient use of free spaces for vegetation, i.e., relatively low vegetation cover to free space ratio, was probably the main cause for this. Public parks had a higher local cooling effect, but a less continuous one on the proximate surrounding (30–90 m from the park), probably due to their relative location in the urban fabric. Our results suggest that ‘greening’ areas within the private urban space should be encouraged at the expense of building new small-medium parks in metropolitan areas that lack the sufficient free space for larger parks. The outcome of this study may have key implications for urban planners seeking to mitigate urban heat island effects under the limitation of existing dense urban layout.     

Characterizing the potential distribution of the invasive Asian longhorned beetle (Anoplophora glabripennis) in Worcester County,Massachusetts

The Asian longhorned beetle (ALB) (Anoplophora glabripennis) is an invasive insect pest that has established populations in Worcester County, Massachusetts as of 2008. ALB predominantly targets red maple (Acer rubrum), sugar maple (Acer saccharum), which are prominent in New England hardwood forests, and Norway maple (Acer platanoides), which was planted in built environments as street trees in response to severe weather and invasive insect and pathogen disturbances. Mahalanobis Typicality models related presence locations of ALB presence-only locations in Worcester County towns from 2008 to 2012 to biotic, abiotic, and anthropogenic variables to predict the potential distribution of ALB and to determine locations most characteristic of infestation. k-fold cross-validation and a continuous Boyce Index were employed to validate model performance and to identify threshold values at which continuous models of typicality could be reclassified into categorical maps. Distance-to-roads (r² = 0.19) and probability of maple presence (r² = 0.13) were the most important predictor variables in the ALB model. Locations that were most consistently susceptible to ALB infestation had significant high maple presence (p < 0.001) and significant low distance-to-roads (p < 0.001) compared to the whole study area, suggesting that ALB in Worcester County, MA, prefers maple-dominant edge habitats at the current stage of invasion. The localized ALB potential distribution model was consistently accurate (Boyce Continuous Index = 0.84) despite the lack of absence locations and incomplete knowledge of ALB niche breadth in both native and invaded ranges. The results from this study could be used as a baseline for effective adaptive management policies that could help prioritize the need for early detection/eradication measures and address the potential ecological and social ramifications of the current ALB outbreak in Worcester County. It is hoped that the model employed could be further tested for future outbreaks as they are discovered in the USA.     

Policy-relevant indicators for mapping the vulnerability of urban populations to extreme heat events: A case study of Philadelphia

The recent global increase in extreme heat events linked to climate change is projected to continue. The additive effect of urban heat islands from impervious surfaces and urban heat emissions (e.g., from transportation and building cooling) exacerbates extreme heat events in urban areas, exposing dense populations to extreme heat with implications for human health. Ground- and satellite-based data on urban and suburban temperatures and vegetation over a historical period can help identify temporal and geospatial trends in heat exposure. A set of indicators has been developed to map the exposure, social sensitivity, and vulnerability of urban populations to heat wave health impacts. Guided by an Advisory Group of local planners in the pilot city of Philadelphia, localized trends of increasing urban extreme heat events using MODIS Land Surface Temperature (LST) data, confirmed with urban and non-urban temperature monitor data were identified. For the Philadelphia study area, the number of heat-event days in the urban setting has increased from approximately 4 days in 1980 to almost 12 days in 2013, while the non-urban setting has consistently experienced 5 days of heat events per year across the time period. Warmer micro-climates with limited vegetative cooling and elevated LSTs were also identified. The exposure indicator was combined with areas of high social sensitivity (e.g., low-income and elderly) to create a vulnerability indicator, showing significant overlap between highly exposed and highly sensitive populations. As a measure of the adaptive capacity of local governments to reduce the urban heat island, evidence of targeted vegetation increases or reduced localized temperatures linked to urban greening and cooling programs were sought, though none were of a scale to be identified by the 1 km satellite data utilized. The indicators have helped local decision makers to understand patterns of vulnerability, and may be used in the future to target adaptation actions and measure results (LST reduction or vegetation increase) from existing adaptation actions.     

Predicting air temperature simultaneously for multiple locations in an urban environment: A bottom up approach

Cities are characterized by high heterogeneity that results in varied microclimate effects. The current study introduces a new bottom–up approach linking the urban Canyon Air Temperature (CAT) model with spatially distributed inputs extracted from a GIS data-base and remote sensing products to predict intra-urban temperature variability simultaneously for multiple locations in an urban environment. To provide proof of concept, the model was applied for the city of Bat-Yam, Israel. Simulation shows a maximum nighttime urban heat island (UHI) intensity of 2–2.25 °C, relative to a rural reference point, during both summer and winter, with significant spatial variability related to the height-to-width ratio of urban street canyons and to the surface land cover. The CAT simulation also highlighted the important influence of the local wind regime on the development and persistence of the nocturnal UHI. We conclude that linking CAT to a GIS data-base supports simulations at the city scale that reflect the local intra-urban variability. The model can be used to investigate both macro and micro scale spatio-temporal characteristics of the UHI in various urban development scenarios, which may be applied to generate appropriate geographically-explicit mitigation and adaptation measures.     

Combined vegetation volume and “greenness” affect urban air temperature

Cities are often substantially warmer than their surrounding rural areas. This ‘urban heat island effect’ can negatively affect the health of urban residents, increase energy usage, and alter ecological processes. While the effect of land use and land cover on urban heat islands has been extensively studied, little is known about the role of vegetation volume or built-area volume about this phenomenon. We ask whether the 3-dimensional structure of urban landscapes influences variations in temperature across a city. Using heights-above-ground information derived from LiDAR data and the Normalized Difference Vegetation Index (NDVI) calculated from multispectral (4 band: Blue, Green, Red, and Near Infrared) aerial images, we estimated vegetation volume and built-area volume (non-vegetated) in Chicago, Illinois (USA). Daily minimum temperature data were obtained from 36 weather stations for summer 2011. The differences in urban air temperature across the study area were as large as 3 °C. Maximum likelihood models indicated that a combination of NDVI and vegetation volume best predicted nighttime temperature in Chicago, and that vegetation growing within 250–500 m of the weather station was most influential. Our results indicate that vegetation in “the matrix”, i.e. the area outside parks and preserves, is important in temperature mitigation since the majority of the vegetation volume in the study area occurs within residential, commercial/industrial, and institutional land uses. However, open space, which covers only 15% of the study area, has nearly as much total vegetation volume as residential land, which covers 61% of the study area. Clearly, both large wooded parks within a city and large trees scattered across residential areas are needed to best mitigate the urban heat island effect.     

近30年北京市ISP-LST空间特征及其变化

本文聚焦长时序地表的不透水与温度特征,利用Landsat影像数据,获取1991—2015年北京市的不透水地表盖度（Impervious Surface Percentage, ISP）与地表温度（Land Surface Temperature, LST）数据,构建不透水地表盖度-地表温度（ISP-LST）二维空间。结合标准差椭圆法,对ISP-LST空间密度分布的聚集特性进行分析,定量化表述各时期的特征与变化。研究发现：① ISP-LST二维空间特征表现为三种类型：弱相关、非完全正相关和显著正相关。② ISP-LST标准差椭圆的方向性和离散性均值为11.26和2.87,空间聚集性良好。随时间推移,高温现象受不透水地表的影响过程趋于复杂化。③ ISP-LST聚集区是城市热环境的重要表征,其在各功能区年际增长率为：功能扩展区（2.97%）>核心功能区（1.75%）>发展新区（1.63%）>生态涵养区（0.18%）。聚集区在东南方向增长明显,研究时段内累计增长14.77%。④ ISP-LST聚集区的斑块密度及形状复杂度的景观格局变化不大,但斑块连接性随时间推移有所降低。本文研究结果可为缓解城市热岛效应、制定生态环境调控政策提供相应参考。     

半干旱区典型工业城市热岛时空分布及演变特征——以包头市为例

基于2000 年、2008 年和2015 年landsat5 TM影像和Landsat8 OLI影像,以单窗算法反演地表温度,研究包头市区近15 a 的城市热岛时空分布及演变特征,并对下垫面土地利用/覆盖类型、 NDVI 与城市热岛的关系进行了定量分析。研究结论表明：包头城市热岛15 a 来呈逐步扩展趋势,且主要集中于裸地区、工矿区、商业和人口密集区三类区域,空间演变趋势与城市扩张格局呈现出高度的一致性;城市热岛效应强度增强,但2008-2015 年以来,市中心区高温区面积比重大大降低;下垫面土地利用/覆盖类型是影响城市热岛空间分布的重要因子,地表温度呈现出裸地>工矿用地>建设用地>城市绿地>农用地>水体的规律;地表温度与 NDVI 呈现显著的负相关关系,即植被指数越高,城市的地表温度越低。     

城市不同下垫面的能量平衡及温度差异模拟

城市能量平衡是研究城市热岛效应的物理基础。利用北京市教学植物园2010年的实测数据,设置不同类型下垫面(植被覆盖类型:林地、草地和不透水层覆盖类型:道路、房屋),利用局地尺度城市气象参数化方案模拟并分析了相同气象条件和净辐射通量输入下,不同类型下垫面的显热、潜热通量及蒸散降温效应的差异。结果显示:(1)不同类型下垫面的各能量支出项有明显差异,植被覆盖区域和不透水层覆盖区域的波文比年均值分别为0.28和4.60,且在植被生长季差异较大;(2)城市扩展过程中道路、房屋替换林地、草地的过程,也是显热增加而潜热减少的过程。植被层向不透水层转换的过程中,显热通量年均增加32.74W/m²,潜热通量减少38.87W/m²,储热通量增加7.95W/m²;(3)理论上,植被蒸散的年降温效应使单位面积植被覆盖区域的气温比不透水层区域可低2.63℃。     

What controls the magnitude of the daytime heat sink in a desert city?

The aim of this study was to increase knowledge of the causes of cooling in desert cities. We used a time-series of Landsat images to characterize the changes in daytime land surface temperature during the period of rapid urbanization in Dubai. Changes in land cover and albedo were also quantified from Landsat data and the development of different land use types and variations in urban geometry were characterized. The results demonstrate that urban growth has promoted a heat sink and that all urban land use types contributed to this effect. Vegetation generated the largest cooling effect per unit surface area but impervious surfaces dominated the urban environment and are responsible for the majority of the heat sink created by the city. Changes in albedo were not causally related to the urban heat sink, however, variations in urban geometry, particularly the amount of shading cast by buildings, had some influence on the magnitude of cooling. This study provides evidence that the expansion of the heat sink during urbanization in a desert environment is influenced by the forms of land cover transition, the type of urban land use that is developed, the thermal properties of construction materials used and the geometry of the city environment that is constructed. Future research should concentrate upon understanding these mechanisms in order to plan future developments which maximize cooling and reduce the environmental impacts of desert cities.     

南京市热场分布特征及其与土地利用/覆被关系研究

文章采用Landsat ETM⁺热红外波段反演LST,分析南京市热场分布规律,构建了土地覆被指数LCI定量表示热场分布特征与土地利用/覆被的关系。结果表明:南京市存在三个连续分布且范围较广的热岛中心,主要分布在工业区;建成区平均温度比郊区高0.972℃;土地利用/类型的空间格局总体上决定了城市热场的空间分布,下垫面介质的热特征和生物学特征差异是地表温度不同的根本原因,工业热源是南京市热岛形成的重要因素;LCI可以和城市气候模型、水文模型结合起来运用,为城市热岛提供一种新分析方法。对某一特定区域而言,随着城市化水平的提高,单位面积内LCI值逐渐减小。     

厦门城市不透水面及其热环境效应的遥感分析

当前,城市空间的快速扩展使得原来以植被、水体为主的自然景观逐渐消失,取而代之的是以不透水面为主的人工建筑物,这一改变已对区域乃至全球的生态环境造成了显著的影响.本研究以海峡西岸中心城市——厦门市为研究区,以1989年、1996年和2009年的Landsat-5 TM影像为主要数据源,采用归一化差值不透水面指数(NDISI),研究了厦门市在这期间的不透水面分布的时空变化.结果发现,厦门市不透水面面积在这20年间扩展了近7倍,其增长主要占用了大面积的植被和水体.回归分析表明城市不透水面与地表温度呈明显的指数型正相关关系,而与植被、水体面积呈线性负相关关系.     

Impact of urbanization level on the interactions of urban area,the urban climate,and human thermal comfort

One significant effect of urbanization is the modification of natural surfaces, local environment, and thermal comfort. Farmland and agricultural land in Klang Valley conurbation, Malaysia have been replaced with engineered surfaces and infrastructures to accommodate the rapid population growth witnessed in the past decades. To understand the current environmental conditions of the conurbation, numerical Weather Research and Forecasting (WRF) model coupled to the Urban Canopy Model (UCM) was used. A model evaluation conducted against a network of observations showed an overall good performance of the model in predicting near-surface meteorological parameters. Also, an examination of spatiotemporal variability of urban parameters revealed a diurnal dependence of human physiological thermal conditions on urbanization level. A maximum urban heat island intensity (UHII) of ∼2.64 °C was observed. In an effort to investigate the effect of urbanization level on the extremities of urban climatic conditions, two different experiments with varying urban/vegetation fractions were further simulated. The latter results indicate that urbanization level has a significant effect on the extremities of urban climatological parameters and spatial extent of the induced impacts. Furthermore, the effect of urbanization level on the mean urban outdoor thermal discomfort (UOTD) level was significant (with an increase of 0.7 °C, 0.64 °C and 0.04 observed) for temperature humidity index (THI), effective temperature index (ETI) and relative strain index (RSI), respectively. However, a non-significant (at 95% level) effect of urbanization level on the extremities of UOTD indices was observed.     

Spatio-temporal dynamics of land cover and land surface temperature in Ganges-Brahmaputra delta: A comparative analysis between India and Bangladesh

Land use and land cover (LULC) change in the Ganges-Brahmaputra delta (GBD) poses significant challenges towards future environmental sustainability of the region and requires regional scale monitoring of key bio-physical variables and changes in their inter-relationship over space and time. Focusing on the southern part of the lower GBD region along the international border of India and Bangladesh, this study examined the spatio-temporal variability of LULC change and its relationship with Land Surface Temperature (LST). Furthermore, LULC-LST relationships were compared between Indian and Bangladesh part and its trend in and around big cities (with more than 1 million population) and towns (with more than 100,000 population) was investigated. Results showed that LST changes were predominantly driven by LULC changes on both sides of the border. Urban growth is the dominant form of LULC change, and the rate of land change was faster in 2005–2010 time period than 1989–2005. Over the period of 21 years, mean January LST decreased by approximately 1.83 °C in Indian part and 1.85 °C in the Bangladesh part. Areas that changed from to rural from agricultural experienced decrease in mean LST, whereas those areas that changed to urban from either agriculture or rural, experienced increase in mean LST. The relationship between LULC and LST are same on both sides of the Indo-Bangladesh border. In bigger cities like Kolkata (in India) and Khulna (in Bangladesh), there is a high spatial variability in relationship between LULC and LST compared to large towns. The LULC-LST relationship in large towns in India was influenced by proximity to Kolkata and coastal areas, whereas in Bangladesh no such influence was evident. The results and the data produced in this study are crucial for monitoring LULC changes, for developing spatial decision support system, and thus will be helpful to address the current challenges of land management in the GBD region. Changes in the LULC and LST are important indicators of GBD's environmental health and access its vulnerability and thus the present findings serve as baseline information for future studies seeking to examine the impact of differential policies on the LULC change in the region.     

基于Landsat TM的2001~2015年哈尔滨市地表温度变化特征分析

以哈尔滨市为例,基于2001年、2004年、2008年和2015年夏季Landsat TM 5 /OLI 8遥感影像为基础数据源,采用“单窗算法”遥感技术手段定量反演瞬时地表温度格局,并深入分析温度特征,分区差异和重心变化。研究表明：2001~2015年研究区温度增加1.44℃,平均温年增0.10℃,3时段（2001~2004年、2005~2008年、2009~2015年）年均温分别增加0.08℃、0.09℃、0.12℃,具有加速上升趋势;最高温增加2.74℃,始终位于香坊区,最低温基本恒定,始终位于道里区;2001~2015年极高、高、极低温度分区面积增加4.92 km²、104.07 km²、87.71 km²,年均增量均具有持续增加趋势,中、低分区面积减少110.61 km²、84.94 km²,具有波动降低趋势,极高、高、中、低分区格局总体按照城区-城乡结合地区-乡村的水平梯度扩展;地表温度重心向东偏南70.58°方向移动536.90 m,其中6个市辖区迁移方向和距离差异明显,表明地表能量移动方向和温度重新分布的活跃程度不同。总体来看,研究区地表温度上升明显,分区时空变化剧烈,能量的轨迹移动过程具有折返特征。     

基于FSDAF模型的干旱区典型绿洲城市夏季地表热岛效应时空演变研究

全球城市化进程加快引起的干旱区绿洲城市热岛效应变化及其生态环境问题已成为当前国内外城市气候、环境和生态等领域的研究热点之一.基于遥感热红外通道反演的地表温度(Land surface temperature,LST)是开展城市地表热岛(Surface urban heat island,SUHI)效应监测研究的关键参数...     

Effects of seasonal heat on the activity rhythm,habitat use,and space use of the beira antelope in southern Djibouti

In hot, arid environments, non-burrowing mammals are at risk of overheating and dehydration, so human-induced reduction in thermal cover may constitute a threat for their survival. We studied the daytime activity rhythm, habitat use, and space use of the beira (Dorcatragus megalotis), a threatened antelope living in arid hills of the Horn of Africa, where tree cover is shrinking because of logging, and overgrazing by livestock. During the cool season (Nov.–Mar.; mean midday temperature: 28.5 °C), beira did not particularly seek shade, and alternated in the course of the day between short phases of activity and rest (median duration in Dec.–Feb.: 57.5 and 42.5 min, respectively). In contrast, during the hot season (May–Sep.; mean midday temperature: 39.1 °C), beira often foraged in a hill's shade, and midday resting phases were especially long (median duration in May–Jul.: 280 min) and spent in the shade of trees, or of rock shelters when available in the home range. Because of reduced diurnal movements when temperature was high, beira home ranges were smaller during the hot than during the cool season (mean ± SE: 0.25 ± 0.05 km² in May–Jul. vs 0.42 ± 0.10 km² in Dec.–Feb.). Whatever the season, beira mainly used areas supporting trees. The obtained results suggest that the decrease of tree cover in the areas inhabited by the beira constitutes a threat for the species survival.     

城市地表水体时空演变及其对热环境的影响

以福州市建成区为例,基于Landsat遥感影像对水体类型进行分类,并提取出1989、1996、2006和2014年的地表水体信息,然后与不透水面、植被和地表温度信息结合,运用回归模型定量分析了1989~2014年间福州城市地表水体的时空变化及其对城市热环境的影响。结果表明：① 1989~2014年间,福州建成区各类地表水体均呈不断减少趋势,25 a间水体总面积减少了1 490.67 hm²,其中有70.0%转变成不透水面;② 1989~2014年减少的1 490.67 hm²水体对福州建成区温度上升的贡献达1.03℃,而在水体减少的具体区域,其升温效应可达3.6℃。     

伊犁河谷2001-2014年地表温度时空分异特征

地表温度是地表能量平衡、区域和全球尺度地表物理过程的一个重要因子。为了辨析中国西北干旱区“天山湿岛”——伊犁河谷的地表温度时空分异,采用趋势分析法和空间数据统计法,探讨了2001-2014年不同土地利用/覆盖类型下地表温度时空变化规律,分析地表温度的时空分异特征及原因。结果表明：（1） MODIS LST产品的精度（平均R²=0.90）能够满足伊犁河谷地表温度时空变化分析的要求;（2）空间上,地表温度呈现出中部高四周低的变化趋势,高温区面积约占总面积的41%,低温区面积约占总面积的23%;时间上,伊犁河谷平均地表温度的年际波动较大,以2013年、2006年、2007年和2008年尤为突出;地表温度的年内变化呈现出单峰型分布,地表温度高值集中在3-8月,最高值出现在7月;（3）不同土地利用/覆盖类型下年均地表温度分布的总体特征为建设用地最高,稀疏草地、旱地等次之,冰川/积雪最低;（4）伊犁河谷地表温度变化趋势呈严重减少、基本不变和轻微增加区域面积分别占5%、37%和26%,以基本不变和轻微增加为主。伊犁河谷地表温度时空变化不仅受大尺度气候变化影响,还受土地类型差异影响,两者共同构成了不同地理区域及景观的温场格局,绿色植被对地表温度时空分布具有重要的调节作用。     

中国城市扩展对气温观测的影响及其高估程度(英文)

Since the implementation of the reform and opening up policy in China in the late 1970s, some meteorological stations ’entered’ cities passively due to urban expansion. Changes in the surface and built environment around the stations have influenced observations of air temperature. When the observational data from urban stations are applied in the interpolation of national or regional scale air temperature dataset, they could lead to overestimation of regional air temperature and inaccurate assessment of warming. In this study, the underlying surface surrounding 756 meteorological stations across China was identified based on remote sensing images over a number of time intervals to distinguish the rural stations that ’entered’ into cities. Then, after removing the observational data from these stations which have been influenced by urban expansion, a dataset of background air temperatures was generated by interpolating the observational data from the remaining rural stations. The mean urban heat island effect intensity since 1970 was estimated by comparing the original observational records from urban stations with the background air temperature interpolated. The result shows that urban heat island effect does occur due to urban expansion, with a higher intensity in winter than in other seasons. Then the overestimation of regional air temperature is evaluated by comparing the two kinds of grid datasets of air temperature which are respectively interpolated by all stations’ and rural stations’ observational data. Spatially, the overestimation is relatively higher in eastern China than in the central part of China; however, both areas exhibit a much higher effect than is observed in western China. We concluded that in the last 40 years the mean temperature in China increased by about 1.58℃, of which about 0.01℃ was attributed to urban expansion, with a contribution of up to 0.09℃ in the core areas from the overestimation of air temperature.