Geospatial Analysis of Urban Heat Island Effects and Tree Equity

In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.

Land cover changes in the rural-urban interaction of Xi’an region using Landsat TM/ETM data

Landsat ETM/TM data and an artificial neural network （ANN） were applied to analyse the expansion of the city of Xi＇an and land use/cover change of its surrounding area between 2000 and 2003. Supervised classification and normalized difference barren index （NDBI） were used respectively to retrieve its urban boundary. Results showed that the urban area increased by an annual rate of 12.3%, with area expansion from 253.37 km^2 in 2000 to 358.60 km^2 in 2003. Large areas of farmland in the north and southwest were converted into urban construction land. The land use/cover changes of Xi＇an were mainly caused by fast development of urban economy, population immigration from countryside, great development of infrastructure such as transportation, and huge demands for urban market. In addition, affected by the government policy of “returning farmland to woodland”, some farmland was converted into economic woodland, such as Chinese goosebeerv garden, vineyard etc.

Impact of Urbanisation on Land Use/Land Cover in Puducherry City, India

The change of land use plays a major role in the developmental activity of a developing country. Due to rapid growth of urbanisation and dramatic increasing population, the fertile agricultural land has been converted to built-up area with respect to the demand for housing requirement and to the need for basic infrastructure facilities. The quantum of open space and surface water bodies has also been encroached. There has been a rapid growth of population in Puducherry city from 3.48 million in 1991 to 5.44 million in 2011. Hence the conservation of natural resources becomes one of the major challenges especially in small and medium town. This study was conducted to assess the effect of change on land use in urban agglomeration area of Puducherry city for the duration period from 1997 to 2017. There has been an increase in population in Puducherry city mainly attributed to higher scale of migration from adjoining rural areas and medium town for better education, job opportunities and quality life. Hence, it has been strongly recommended for stringent Development Control Regulations to quantify the urban sprawl and manage the impact of urbanisation of land use/land cover in Puducherry city.

Analysis of Land Use/Cover Dynamics in a Rapidly Urbanizing City: The Case of Gombe Metropolitan Area, Nigeria

The study examines the dynamics of land use/cover in a rapidly urbanizing city of Gombe in Northeast Nigeria. The objective was to apply geospatial techniques in mapping and characterization of the pattern of land use changes in the metropolis that occurred between 1984 and 2015, and assess its’ implications on the socio-economic development of the city. The Landsat satellite images of the area were acquired and classified using maximum likelihood algorithm in identifying the historical trend in the land use changes. The application of Multi-Layer Perception (MLP) neutral network in the prediction of land use changes in the area reveals that Gombe metropolis has witnessed a phenomenal growth in size (133%) between 1991 and 2003. This growth was largely brought by changes in political status of the city that reflected in the socio-economic functions it performs. A 10-year trend in the growth forecast (2015-2055) reveals lack of abatement in the rapidity of this growth pattern. The consequences of this growth include the aggravation of the existing slumps, problems of infrastructure and housing among others. It is recommended that zonal-based planning approach be adopted within the framework of a master plan to tackle the existing and future development needs of the city. The implications of the findings are further discussed.

RS and GIS-based Analysis of Landscape Pattern Changes in Urban-rural Ecotone:A Case Study of Daiyue District,Tai' an City,China

Based on RS data of Daiyue District,Tai'an City in 2000,2005 and 2010,changes of land use types in urban-rural ecotone of Tai'an City from 2000 to 2010 were analyzed.Ecological theories,ArcGIS techniques and landscape structure analysis software Fragstats were applied to select relevant landscape pattern indexes and analyze changes of landscape structure,and compare changes in two durations(2000-2005,2005-2010).The results showed that area of natural landscapes in the study area declined from 2000 to 2010,construction land expanded,land use types were mainly transferred from natural landscapes to man-made landscapes.In terms of landscape level,number of patches(NP),patch density(PD),patch shape index(SHAPE),Shannon's diversity index(SHDI) and Shannon's evenness index(SHEI) increased,the largest patch index(LPI) declined.In terms of type level,arable land were influenced by the most human interventions,large-scale patches turned fragmented,and landscape dominance degraded;woodland landscapes were concentrated in mountainous areas,waterscape indexes showed slight changes.Dominance of regional dominant landscape types degraded,landscape fragmentation and landscape heterogeneity increased,and landscape stability declined.

Urban Heat Island Assessment for a Tropical Urban Airshed in India

There has been paucity of field campaigns in India in past few decades on the urban heat island intensities (UHI). Remote sensing observations provide useful information on urban heat island intensities and hotspots as supplement or proxy to in-situ surface based measurements. A case study has been undertaken to assess and compare the UHI and hotspots based on in-situ measurements and remote sensing observations as the later method can be used as a proxy in absence of in-situ measurements both spatially and temporally. Capital of India, megacity Delhi has grown by leaps and bounds during past 2 - 3 decades and strongly represents tropical climatic conditions where such studies and field campaigns are practically non-existent. Thus, a field campaign was undertaken during summer, 2008 named DELHI-I (Delhi Experiments to Learn Heat Island Intensity-I) in this megacity. Urban heat island effects were found to be most dominant in areas of dense built up infrastructure and at commercial centers. The heat island intensity (UHI) was observed to be higher in magnitude both during afternoon hours and night hours (maximum up to 8.3?C) similar to some recent studies. The three high ranking urban heat island locations in the city are within commercial and/or densely populated areas. The results of this field campaign when compared with MODIS-Terra data of land surface temperature revealed that UHI hotspots are comparable only during nighttime. During daytime, similar comparison was less satisfactory. Further, available relationship of maximum UHI with population data is applied for the current measurements and discussed in the context of maximum UHI of various other countries.

Spatio-Temporal Land Cover Analysis and the Impact of Land Cover Variability Indices on Land Surface Temperature in Greater Accra, Ghana Using Multi-Temporal Landsat Data

Urbanization, as a result of anthropogenic activities, reduces the vegetated and green spaces and thereby increases the impervious surfaces in cities. This in turn increases the surface temperature of cities when compared to the rural regions resulting in the formation of urban heat island. Especially, in under-developed countries, it is very crucial to obtain timely and accurate information on the urban trend and its development due to the higher increasing rate of population growth and lack of infrastructural facilities and regulations to mitigate the adverse consequences of urbanization. The current study analyzes the urban development of Greater Accra, Ghana using Landsat 7 dataset acquired in 2002, 2013, and 2020. Further, the influence of urban growth on the land surface temperature (LST) and land cover variability (LCV) indices including NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-Up Index), and NDWI (Normalized Difference Water Index) is identified during the study periods. Results suggest that the area of built-up quadrupled between 2002 and 2020 in the study region. Shannon’s entropy-based analysis suggests that the urban development in the region is heterogeneous or dispersive in nature. Further, the regression analysis highlights a strong positive relation between LST and NDBI (0.755) and a negative relation is found associated between LST and NDVI (0.4417) and LST and NDWI (0.76). Results of the study could be useful to design sustainable urban socio-economic and environmental planning policies in the study region.

基于Landsat数据的城市热岛效应与LUCC关系研究

以Landsat-5和Landsat-8遥感影像数据为基础,通过地表温度反演和支持向量机分类法分别获得研究区城市热岛的空间分布和土地利用/覆盖变化数据,再利用ArcGIS对上述结果进行叠加分析。结果表明:城市热岛范围与强度随着时间变化呈上升趋势;土地利用/覆盖的变化在空间位置上会影响城市热岛效应;其中城市中建设用地与裸土地是导致热岛效应加剧的主要原因,而水系与植被对城市热岛效应有明显的抑制作用。

Assessing Urban Land Use Change in New Braunfels, Texas from 2013 to 2020

Urban cities are the major drivers of economic growth and development. Economic growth and development however results in considerable land cover land use dynamics. This study assessed the dynamics in land cover land use that have occurred in New Braunfels, Texas in the last 7 years (2013-2020) to observe areas in the city that had experienced considerable shifts in land cover and land use. 30-meter resolution Landsat images were used to examine possible changes in land cover land use. New Braunfels was observed to have experienced significant changes in land use especially in developed areas. This change can be attributed to the influx of people into the city, contributing to the need for increased urban development. Analysis of this study shows that about 16% (about 553 hectares) of forest land cover class and 28% (about 1139 hectares) of grassland class in time 1 (August 31, 2013) changed to built-up land use class in time 2 (November 5, 2020). A limitation to this study was that of the spatial resolution of images used. Higher spatial resolution images could impact the producers, users, and overall accuracy assessment. Results from this study can aid in supporting better decision-making for sustainable urban development and climate change mitigation.

An Integrated Remote Sensing and GIS in Monitoring Landuse and Land Cover Change in Egbeda Local Government Area, Oyo State, Nigeria

Effective planning relies on accurate and up-to-date information on existing land use and land cover. The timely detection of trends in land use and land cover change and a quantification of such trends are of specific interest to planners and decision makers. The aim of this research is to use remote sensing and GIS to monitor landuse and land cover change in Egbeda Local Government Area, Oyo State with a view to determining how useful such information can be to planners and decision makers for effective urban management. The research was conducted using remote sensing and Geographical information System at determining the trend and extent of land use and land cover change and its driving force in Egbeda Local Government Area, Oyo State. The methods used include: digitization, digital image processing and spatial analysis using an inverse distance weighted (IDW) technique, Maximum likelihood supervised classification and post classification change detection techniques were applied to Landsat imageries acquired in 1984, 2006 and 2018. Imageries were classified into built-up area, vegetation, bare surface, cultivation and water body. The results of the analysis obtained showed drastic change in built-up area which rose to 32.8% from 25.4% between 1984 and 2018 periods. To reduce the effect of land use expansion in the study areas, policy measures were recommended which include proper inventory of land use and land cover, regular monitoring of urban areas spread of development and regional development programs. These will enable the government, stakeholders, policy makers and planners to make informed decisions provided by these technologies to attain and sustain future urban development.

Land Use and Land Cover Change Detection in the Saudi Arabian Desert Cities of Makkah and Al-Taif Using Satellite Data

Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Saudi Arabia has undergone significant change in land use and land cover since the government embarked on a course of intense national development 30 years ago, as a result of huge national oil revenues. This study evaluates LULC change in Makkah and Al-Taif, Saudi Arabia from 1986 to 2013 using Landsat images. Maximum likelihood and object-oriented classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. The results indicated that urban areas have increased over the period by approximately 174% in Makkah and 113% in Al-Taif. Analysis of vegetation cover over the study area showed a variable distribution from year to year due to changing average precipitation in this environment. Object-based classification provided slightly greater accuracy than maximum likelihood classification. Information provided by satellite remote sensing can play an important role in quantifying and understanding the relationship between population growth and LULC changes, which can assist future planning and potential environmental impacts of expanding urban areas.

Drivers of Land Cover Dynamics for Pugu and Kazimuzumbwi Forest Reserves in Kisarawe, Tanzania

Forests that are close to growing urban centres have been subject to constant deforestation and degradation from various factors. This study assesses the drivers of land cover dynamics in Pugu and Kazimzumbwi forest reserves in the context of urban and peri-urban expansion of Dar es Salaam for the past three decades. The study adopted review of relevant literature and household survey from three settlements surrounding the forest reserves. One hundred and fifty (150) households were collected from Buyuni, Chanika and Masaki in Ilala and Kisarawe and administered with semi-structured questionnaire to collect information on migration, use of forest products by communities and perception on climate change and variability. SPSS computer program was used to analyse the questionnaire data while tables and graphs were adopted for presentation of the results. Rural-urban and internal urban migration in Dar es Salaam was identified as one of the primary drivers of land cover dynamics in peri-urban areas and adjoining environments. The migration was intensified by push drivers which include urban growth, market of land and reliance on forest product among community members as source of their livelihoods. The increased rainfall variability accompanied with high temperature has contributed to frequent droughts which compromises rainfed agriculture. Thus, the successful conservation of the forest will require strengthened enforcement of protection measures supported with introduction of alternative livelihood strategies for majority of poor community members.

Dynamics of Land Use/Cover Change in Manikganj District, Bangladesh: A Case Study of Manikganj Sadar Upazila

This study revealed land use/cover change of Manikganj Sadar Upazila concerning with urbanization of Dhaka city. The study area also offers better residential opportunity and food support for Dhaka city. The major focus of this study is to find out the spatial and temporal changes of land use/cover and its effects on urbanization while Dhaka city is an independent variable. For analyzing land use/cover change GIS and remote sensing technique were used. The maps showed that, between 1989 and 2009 built-up areas increased approximately +12%, while agricultural land decreased -7%, water bodies decreased about -2% and bare land decreased about -2%. The significant change in agriculture land use is observed in the south-eastern and north eastern site of the city because of nearest distance and better transportation facilities with Dhaka city. This study will contribute to the both the development of sustainable urban land use planning decisions and also for forecasting possible future changes in growth patterns.

Spectral Features for the Detection of Land Cover Changes

Derivation of more sensitive spectral features from the satellite data is immensely important for better retrieving land cover information and change monitoring, such as changes in snow covered area, forests, and barren lands as some examples from local to the global scale. The major objectives of this paper are to present the potential of water-resistant snow index (WSI) for the detection of snow cover changes in the Himalayas, extant two composite images, biophysical image composite (BIC) and forest cover composite (FCC) for the detection of changes in barren lands and forested areas respectively, and two newly designed composite images, water cover composite (WCC) and urban cover composite (UCC) for the detection of changes in water and urban areas respectively. This research implemented the image compositing technique for the detection and visualization of land cover changes (water, forest, barren, and urban) with respect to local administrative areas where a significant land cover change occurred from 2001 to 2016. A case study was also conducted in the Himalayan region to identify snow cover changes from 2001 to 2015 using the WSI. Analysis of the annual variation of the snow cover in the Himalayas indicated a decreasing trend of the snow cover. Consequently, the downstream areas are more likely to suffer from snow related hazards such as glacial outbursts, avalanches, landslides and floods. The changes in snow cover in the Himalayas may bring significant hydrophysical and livelihood changes in the downstream area including the Mekong Delta. Therefore, the countries sharing the Himalayan region should focus on adapting the severe impacts of snow cover changes. The image compositing approach presented in the research demonstrated promising performance for the detection and visualization of other land cover changes as well.

海南岛沿海城镇化对海风锋推进影响的数值模拟

本文利用中尺度模式WRF-ARW(Weather Research and Forecasting Model-Advanced Research WRF)(Version 4.0)对海南岛不同天气条件下的典型海风锋个例进行了高分辨率数值模拟,通过设计局地城镇化的敏感性试验,重点分析了海南岛沿海城镇化对海风锋推进的影响及其可能机制。研究结果表明:海南岛沿海城镇化造成的海风锋结构差异是热力作用和动力作用共同影响的结果;城镇下垫面的摩擦效应与城市热岛的增强阻碍海风向内陆推进,减弱了海风锋途经地区的降温增湿效应,造成海风锋位置相对滞后;而城镇化所引起的高海陆热力差异增强了海风风速及海风辐合,同时导致海风锋前的垂直上升气流和海风环流厚度也明显增强。海风锋发展不同时期,城镇化对海风锋的推进影响有所不同。海风锋发展初期,海陆热力差异引起的推动作用与摩擦效应的阻碍作用相抵消,导致海风锋的推进无明显影响;海风锋发展强盛阶段,城镇化条件下内陆城市与非城市之间的热力差异有所增强,阻碍了海风锋向内陆推进,导致海风锋内陆渗透距离减小。不同天气条件下城市化对海风锋推进的影响有所不同,相比于晴空天气,多云天气下城市与非城市的热力差异稍强,加强了城市热岛效应对海风推进的阻碍作用,导致海风锋滞后距离稍远。此外,当土地利用类型更换为城镇后,净辐射与陆气间交换能量减少,导致其潜热通量显著减小,感热通量值变大,从而升高了下垫面温度,增强了海风的垂直上升运动,进而造成边界层高度的升高。

Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing,China

Land surface temperature （LST）, which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis. This study examined the effect impervious surfaces （IS） spatial patterns have on LST in Beijing, China. A classification and regression tree model （CART） was adopted to estimate IS as a continuous variable using Landsat images from two seasons combined with QuickBird. LST was retrieved from the Landsat Thematic Mapper （TM） image to examine the relationships between IS and LST. The results revealed that CART was capable of consistently predicting LST with acceptable accuracy （correlation coefficient of 0.94 and the average error of 8.59%）. Spatial patterns of IS exhibited changing gradients across the various urban-rural transects, with LST values showing a concentric shape that increased as you moved from the outskirts towards the downtown areas. Transect analysis also indicated that the changes in both IS and LST patterns were similar at various resolution levels, which suggests a distinct linear relationship between them. Results of correlation analysis further showed that IS tended to be positively correlated with LST, and that the correlation coefficients increased from 0.807 to 0.925 with increases in IS pixel size. The findings identified in this study provide a theoretical basis for improving urban planning efforts to lessen urban temperatures and thus dampen urban heat island effects.

基于Landsat ETM+数据的福州市土地利用/覆被与城市热岛的关系研究

在利用Landsat ETM+遥感数据提取的4种信息指数的基础上,采用决策树方法,对福州市土地利用/覆被进行分类,并运用辐射传输方程算法反演了地表温度,进而对研究区城市热岛的空间分布特征及其与土地利用/覆盖类型的关系进行定量研究.结果表明,福州市存在热岛效应,热岛空间分布与城市建成区轮廓基本一致;城市建筑用地和裸地对地表温度的贡献最大,是城市热岛的主要贡献因素,而水体和林草地具有较好的降温作用;不同土地利用/覆盖类型的地表温度存在较大差异,并且地表温度与反映土地利用/覆盖类型的4种指数在一定范围内具有明显的相关性.

基于Landsat卫星资料的苏州城市热岛效应遥感分析

为了对苏州市快速城市化进程中的热岛效应进行研究,采用三个时期的Landsat/TM遥感影像资料来反映地表热辐射信息。基于CART决策树分类得到每个时期的土地覆盖分类图,然后通过单通道算法反演得到地表温度,并对2个时期的地表温度进行标准化分级处理,计算得到采取本文定义,1986,1995及2004年的热岛面积指数分别为4.87%,11.10%和37.87%。研究了城市化过程中城市热岛强度和空间分布变化,分析了土地覆盖变化对热岛效应的影响。结果表明,苏州市存在比较明显的城市热岛效应,并且在20多年中随着城市化过程热岛范围进一步扩展。

Urban Planning Based on Nature—A Nature-Based Solution

After an international contest announced by the City of Abu Dhabi “Cool Abu Dhabi Challenge”1 and the article published as a digest of a paper titled A Nature-based Solution [1], the decision has been made to take part in improving thermal comfort in public spaces by mitigating the impact of the effect of Urban Heat Islands (UHI)2 in the city of the Belgrade. The basic research aims at achieving the balance between the conflicting impacts when the buildings with their infrastructure and water-green surrounding area are in such correlation that it fulfils acceptable living and heating standards and reduces the use of fossil fuels for cooling the urban areas (buildings). By implementing the remote detection it is possible to analyze and quantify the impact of over-building on the temperature rise in urban areas as well as the disturbance of the heating comfort and the increased demand for additional cooling. Now it is possible to create virtual models that will incorporate this newly-added urban vegetation into urban plans, depending on the evaporation potential that will affect the microclimate of the urban area. Such natural cooling can be measured and adapted and hence aimed at a potential decrease in areas with UHI emissions [2]. Suitable greenery in the summer season can be a useful improvement which concurrently enables and complements several cooling mechanisms—evaporative cooling and evapotranspiration, i.e. natural cooling systems. The remote detection shall establish and map the “healthy” and “unhealthy” greenery zones—that is the vegetation zones with the highest evaporative potential with the “cooling by evaporation” effect and also, by implementing the urban prediction model, it shall propose green infrastructure corridors aimed at a potential decrease in the Urban Heat Island Emission.

基于Landsat-8影像的芜湖市城市热岛与土地利用/覆盖的关系

利用2013年8月11日Landsat-8OLI/TIRS影像数据,以安徽省芜湖市的鸠江区、镜湖区、弋江区和三山区为研究区,使用ENVI 5.1遥感图像处理软件,对Landsat-8影像的TIRS 10波段使用单窗算法进行地表亮度温度反演,再使用神经网络法对OLI多光谱影像进行土地利用/覆盖分类,并利用GIS空间分析和数理统计方法对芜湖市城市热岛效应与土地利用/覆盖的关系进行定量研究分析.研究结果表明:芜湖市城市中心区地表亮度温度明显高于市郊,强热岛区与热岛区面积共18.79km2,占研究区总面积的1.69%,城市热岛效应存在但不显著;土地利用/覆盖类型不同,地表亮度温度差异明显;建设用地表面温度相对较高,是城市热岛效应强度增加的主要影响因素,而林地和水体面积的增加能有效缓解城市热岛效应的强度.