Linking thermal variability and change to urban growth in Harare Metropolitan City using remotely sensed data.

Doctor of Philosophy in Environmental Science. University of KwaZulu-Natal. Pietermaritzburg, 2017.Urban growth, which involves Land Use and Land Cover Changes (LULCC), alters land surface thermal properties. Within the framework of rapid urban growth and global warming, land surface temperature (LST) and its elevation have potential significant socio-economic and environmental implications. Hence the main objectives of this study were to (i) map urban growth, (ii) link urban growth with indoor and outdoor thermal conditions and (iii) estimate implications of thermal trends on household energy consumption as well as predict future urban growth and temperature patterns in Harare Metropolitan, Zimbabwe. To achieve these objectives, broadband multi-spectral Landsat 5, 7 and 8, in-situ LULC observations, air temperature (Ta) and humidity data were integrated. LULC maps were obtained from multi-spectral remote sensing data and derived indices using the Support Vector Machine Algorithm, while LST were derived by applying single channel and split window algorithms. To improve remote sensing based urban growth mapping, a method of combining multi-spectral reflective data with thermal data and vegetation indices was tested. Vegetation indices were also combined with socio-demographic data to map the spatial distribution of heat vulnerability in Harare. Changes in outdoor human thermal discomfort in response to seasonal LULCC were evaluated, using the Discomfort Index (DI) derived parsimoniously from LST retrieved from Landsat 8 data. Responses of LST to long term urban growth were analysed for the period from 1984 to 2015. The implications of urban growth induced temperature changes on household air-conditioning energy demand were analysed using Landsat derived land surface temperature based Degree Days. Finally, the Cellular Automata Markov Chain (CAMC) analysis was used to predict future landscape transformation at 10-year time steps from 2015 to 2045. Results showed high overall accuracy of 89.33% and kappa index above 0.86 obtained, using Landsat 8 bands and indices. Similar results were observed when indices were used as stand-alone dataset (above 80%). Landsat 8 derived bio-physical surface properties and socio-demographic factors, showed that heat vulnerability was high in over 40% in densely built-up areas with low-income when compared to “leafy” suburbs. A strong spatial correlation (α = 0.61) between heat vulnerability and surface temperatures in the hot season was obtained, implying that LST is a good indicator of heat vulnerability in the area. LST based discomfort assessment approach retrieved DI with high accuracy as indicated by mean percentage error of less than 20% for each sub-season. Outdoor thermal discomfort was high in hot dry season (mean DI of 31oC), while the post rainy season was the most comfortable (mean DI of 19.9oC). During the hot season, thermal discomfort was very low in low density residential areas, which are characterised by forests and well maintained parks (DI ≤27oC). Long term changes results showed that high density residential areas increased by 92% between 1984 and 2016 at the expense of cooler green-spaces, which decreased by 75.5%, translating to a 1.98oC mean surface temperature increase. Due to surface alterations from urban growth between 1984 and 2015, LST increased by an average of 2.26oC and 4.10oC in the cool and hot season, respectively. This decreased potential indoor heating energy needed in the cool season by 1 degree day and increased indoor cooling energy during the hot season by 3 degree days. Spatial analysis showed that during the hot season, actual energy consumption was low in high temperature zones. This coincided with areas occupied by low income strata indicating that they do not afford as much energy and air conditioning facilities as expected. Besides quantifying and strongly relating with energy requirement, degree days provided a quantitative measure of heat vulnerability in Harare. Testing vegetation indices for predictive power showed that the Urban Index (UI) was comparatively the best predictor of future urban surface temperature (r = 0.98). The mean absolute percentage error of the UI derived temperature was 5.27% when tested against temperature derived from thermal band in October 2015. Using UI as predictor variable in CAMC analysis, we predicted that the low surface temperature class (18-28oC) will decrease in coverage, while the high temperature category (36-45oC) will increase in proportion covered from 42.5 to 58% of city, indicating further warming as the city continues to grow between 2015 and 2040. Overall, the findings of this study showed that LST, human thermal comfort and air-conditioning energy demand are strongly affected by seasonal and urban growth induced land cover changes. It can be observed that urban greenery and wetlands play a significant role of reducing LST and heat transfer between the surface and lower atmosphere and LST may continue unless effective mitigation strategies, such as effective vegetation cover spatial configuration are adopted. Limitations to the study included inadequate spatial and low temporal resolution of Landsat data, few in-situ observations of temperature and LULC classification which was area specific thus difficult for global comparison. Recommendations for future studies included data merging to improve spatial and temporal representation of remote sensing data, resource mobilization to increase urban weather station density and image classification into local climate zones which are of easy global interpretation and comparison

Diurnal variation of amplified canopy urban heat island in Beijing megacity during heat wave periods: Roles of mountain-valley circulation and urban morphology

In the context of global warming and rapid urbanization, heat waves (HW) are becoming more frequent, which is amplifying canopy urban heat island (CUHI) via various driving mechanisms. While the roles of local circulation and urban morphology remain unclear in the synergistic interaction between HW and CUHI. By utilizing the data from high-density automatic weather stations in the Beijing megacity, this article explored spatiotemporal patterns of the interactions between HW and CUHI. The average daily CUHII during HW periods exhibited a significant increase of 59.33 % compared to the non-heat wave (NHW) periods. Mountain-valley breeze significantly modulated the spatiotemporal patterns of CUHI intensity (CUHII). In particular, on an urban scale, the turning mountain-valley breeze caused horizontal transport of heat inner-city, resulting in the north-south asymmetric pattern of urban excess warming during HW periods. On a street scale, the amplified CHUII was closely associated with urban morphology in the inner city, especially for the vertical characteristics of buildings. During the mountain breeze phase, the amplification of CUHII in the high-rise street zone was significantly stronger than that in the low-rise street zone. During the valley breeze phase, the amplification of CUHII in high-rise street zones exhibits weaker effects in the afternoon compared to the low-rise street areas, while demonstrating stronger amplification during the nighttime. Our findings provide scientific insight to understand the driving mechanisms of urban excess warming and mitigating the escalating risks associated with extreme high-temperature events over megacities in the transitional zone of mountains and plains

Impacts, strategies and tools to mitigate UHI

The impacts of climate changes to cities, which are home to over half of the world´s population, are already being felt. In many cases, the intensive speed with which urban centres have been growing means that little attention has been paid to the role played by climatic factors in maintaining the quality of life. Among the negative consequences of rapid city growth is the expansion of the problems posed by urban heat islands, defined as areas in a city that are much warmer than in other sites, especially in comparison with rural areas. This paper analyses the consistency of the UHI related literature in three stages: first it outlines its characteristics and impacts in a wide variety of cities around the world, which poses pressures to public health in many different countries. Then it introduces strategies which may be employed in order to reduce its effects, and finally, it analyses available tools to systematize the initial high-level assessment of the phenomenon for multidisciplinary teams involved in the urban planning process. The analysis of the literature on the characteristics, impacts, strategies and digital tools to assess on the UHI, reveals the wide variety of parameters, methods, tools and strategies analysed and suggested in the different studies, which does not always allow to compare or standardize the diagnosis or solutions

Characterization of the UHI in Zaragoza (Spain) using a quality-controlled hourly sensor-based urban climate network

The study of the urban heat island (UHI) is of great importance in the context of climate change, where increasingly frequent and intense extreme thermal events will generate lethal effects in cities. In this work, we characterize the UHI of the urban area of Zaragoza (Spain) using a thermohygrometric network of hourly observatories composed of 21 sensors, from March 2015 to February 2021. Due to the diversity of urban spaces and the high volume of information (˜ 995, 000 observations), we performed an exhaustive quality control. Incorporating a synoptic analysis to better identify atmospheric situations not recorded by sensors. The results indicate that 1.6% of observations are removed, mainly due to outliers and hourly variability. We demonstrate that the UHI displays the classical center-periphery pattern with intensity values around 2 °C, but with variations due to the urban structure. We also observe seasonal UHI variations that intensify, especially in winter and autumn nights. Finally, this characterization confirms the differences in UHI intensity are due to their structural and climatic characteristics, which can ultimately guide the logical urban planning design of Zaragoza, and other Mediterranean-like cities with a similar urban environment

Monitoring canopy quality and improving equitable outcomes of urban tree planting using LiDAR and machine learning

Urban tree canopies are fundamental to mitigating the impacts of climate change within cities as well as providing a range of other important ecosystem, health, and amenity benefits. However, urban tree planting initiatives do not typically utilize data about both the horizontal and vertical dimensions of the tree canopy, despite height being a critical determinant of the quality and value of urban canopy cover. We present a novel pipeline that uses airborne LiDAR data to train a multi-task machine learning model to generate estimates of both canopy cover and height in urban areas. We apply this to multi-source multi-spectral imagery for the case study of Chicago, USA. Our results indicate that a multi-task UNet convolutional neural network can be used to generate reliable estimates of canopy cover and height from aerial and satellite imagery. We then use these canopy estimates to allocate 75,000 trees from Chicago's recent green initiative under four scenarios, minimizing the urban heat island effect and then optimizing for an equitable canopy distribution, comparing results when only canopy cover is used, and when both canopy cover and height are considered. Through the introduction of this novel pipeline, we show that including canopy height within decision-making processes allows the distribution of new trees to be optimised to further reduce the urban heat island effect in localities where trees have the highest cooling potential and allows trees to be more equitably distributed to communities with lower quality canopies

Urban and regional heat island adaptation measures in the Netherlands

The urban planner´s role should be adapted to the current globalised and overspecialised economic and environmental context, envisioning a balance at the regional scale, apprehending not only new technologies, but also new mapping principles, that allow obtaining multidisciplinary integral overviews since the preliminary stages of the design process. The urban heat Island (UHI) is one of the main phenomena affecting the urban climate. In the Netherlands, during the heat wave of 2006, more than 1,000 extra deaths were registered. UHI-related parameters are an example of new elements that should be taken into consideration since the early phases of the design process. PROBLEM STATEMENT Thus, the development of urban design guidelines to reduce the heat islands in Dutch cities and regions requires first an overall reflection on the heat island phenomenom (relevance of the large scale assessment, existing tools, instruments) and proposal of integrative and catalysing mapping strategies and then a specific assessment of the phenomenom at the selected locations in The Netherlands (testing those principles). MAIN RESEARCH QUESTION Could the use of satellite imagery help analyse the UHI in the Netherlands and contribute to suggest catalysing mitigation acions actions implementable in the existing urban context of the cities, regions and provinces assessed? METHOD The development of urban design principles that aim at reaching a physical balance at the regional scale is critical to ensure a reduction of the UHI effect. Landsat and Modis satellite imagery can be analysed and processed using ATCOR 2/3, ENVI 4.7 and GIS, allowing not only a neighbourhood, city and regional scale assessment, but also generating holistic catalysing mapping typologies: game-board, rhizome, layering and drift, which are critical to ensure the integration of all parameters. The scientific inputs need to be combined not only with other disciplines but often also with existing urban plans. The connection between scientific research and existing agreed visions is critical to ensure the integration of new aspects into the plans. RESULTS At the neighbourhood level the areas that have a greater heat concentration in the cities of Delft, Leiden, Gouda, Utrecht and Den Bosch are the city centres characterised by their red ceramic roof tiles, brick street paving, and canals. Several mitigation strategies could be implemented to improve the UHI effect in those areas; however, since the city centres are consolidated and listed urban areas, the mitigation measures that would be easier to implement would consist in improving the roof albedo. A consistent implementation of albedo improvement measures (improving the thermal behaviour not only of flat roofs, but also of tiled pitched roofs) of all roofs included in the identified hotspots (with an average storage heat flux greater than 90 W/m2) would help reduce the temperatures between 1.4°C and 3°C. Pre-war and post-war compact and ground-based neighbourhoods present similar thermal behaviour of the surface cover, and green neighbourhoods and small urban centres also present similar thermal behaviour. At the city scale the analysis of 21 medium-size cities in the province of North Brabant, which belongs to the South region of the county -in relative terms the most affected by the UHI phenomenon during the heat wave of 2006-, reveals that albedo and normalised difference vegetation index (NDVI) are the most relevant parameters influencing the average nightime land surface temperature (LST). Thus, imperviousness, distance to the nearest town and the area of the cities do not seem to play a significant role in the LST night values for the medium-size cities analysed in the region of North Brabant, which do not exceed 7,700 ha in any case. The future growth of most medium-size cities of the regions will not per se aggravate the UHI phenomenon; in turn it will be the design of the new neighbourhoods that will impact the formation of urban heat in the province. The average day LST of provincial parks in South Holland varies depending on the land use. The analysis of the average night LST varies depending of the land use of the patches. The following surfaces are arranged from the lowest to the highest temperatures: water surfaces, forests, cropland, and greenhouse areas. For each of these land uses, NDVI, imperviousness and landscape shape index (LSI) shape index influence the thermal behaviour of the patches differently. NDVI is inversely correlated to day LST for all categories, imperviousness is correlated to day LST for all areas which do not comprise a significant presence of greenhouses (grassland and built patches) and inversely correlated to LST for areas with a high presence of greenhouses (cropland and warehouses). Greenhouse surfaces have highly reflective roofs, which contribute to the reduction of day LST. Finally, landscape shape index varies depending on the nature of the surrounding patches, especially for small patches (built areas, forests and greenhouse areas). When the patches analysed are surrounded by warmer land uses, slender and scattered patches are warmer, more compact and large ones are cooler. In turn, when they are surrounded by cooler patches it is the opposite: slenderer and scattered patches are cooler and more compact and larger ones are warmer. In Midden-Delfland (1 of the 6 South Holland provincial parks), most of the hotspots surrounding the park are adjacent to grassland patches. The measure to increase the cooling capacity of those patches would consist in a change of land use and/or an increase of NDVI of the existing grassland patches. CONCLUSIONS Satellite imagery can be used not only to analyse the heat island phenomenom in Dutch neighbourhoods, cities and regions (identify neighbourhoods with highest surface temperature, identify impact of city size and morphology in surface temperature, calcuate average surface temperature for different land uses…), but also to suggest mitigation actions for the areas assessed. Moreover, satellite imagery is here used to generate catalysing mapping typologies: game-board, rhizome, layering and drift, ensuring that the measures proposed remain accurate enough to actualy be efficient and open enough to be compatible with the rest of urban planning priorities

Urban and regional heat island adaptation measures in the Netherlands

The urban planner´s role should be adapted to the current globalised and overspecialised economic and environmental context, envisioning a balance at the regional scale, apprehending not only new technologies, but also new mapping principles, that allow obtaining multidisciplinary integral overviews since the preliminary stages of the design process. The urban heat Island (UHI) is one of the main phenomena affecting the urban climate. In the Netherlands, during the heat wave of 2006, more than 1,000 extra deaths were registered. UHI-related parameters are an example of new elements that should be taken into consideration since the early phases of the design process. Problem statement Thus, the development of urban design guidelines to reduce the heat islands in Dutch cities and regions requires first an overall reflection on the heat island phenomenom (relevance of the large scale assessment, existing tools, instruments) and proposal of integrative and catalysing mapping strategies and then a specific assessment of the phenomenom at the selected locations in The Netherlands (testing those principles). Main research question Could the use of satellite imagery help analyse the UHI in the Netherlands and contribute to suggest catalysing mitigation acions actions implementable in the existing urban context of the cities, regions and provinces assessed? Method The development of urban design principles that aim at reaching a physical balance at the regional scale is critical to ensure a reduction of the UHI effect. Landsat and Modis satellite imagery can be analysed and processed using ATCOR 2/3, ENVI 4.7 and GIS, allowing not only a neighbourhood, city and regional scale assessment, but also generating holistic catalysing mapping typologies: game-board, rhizome, layering and drift, which are critical to ensure the integration of all parameters. The scientific inputs need to be combined not only with other disciplines but often also with existing urban plans. The connection between scientific research and existing agreed visions is critical to ensure the integration of new aspects into the plans. Results At the neighbourhood level the areas that have a greater heat concentration in the cities of Delft, Leiden, Gouda, Utrecht and Den Bosch are the city centres characterised by their red ceramic roof tiles, brick street paving, and canals. Several mitigation strategies could be implemented to improve the UHI effect in those areas; however, since the city centres are consolidated and listed urban areas, the mitigation measures that would be easier to implement would consist in improving the roof albedo. A consistent implementation of albedo improvement measures (improving the thermal behaviour not only of flat roofs, but also of tiled pitched roofs) of all roofs included in the identified hotspots (with an average storage heat flux greater than 90 W/m2) would help reduce the temperatures between 1.4°C and 3°C. Pre-war and post-war compact and ground-based neighbourhoods present similar thermal behaviour of the surface cover, and green neighbourhoods and small urban centres also present similar thermal behaviour. At the city scale the analysis of 21 medium-size cities in the province of North Brabant, which belongs to the South region of the county -in relative terms the most affected by the UHI phenomenon during the heat wave of 2006-, reveals that albedo and normalised difference vegetation index (NDVI) are the most relevant parameters influencing the average nightime land surface temperature (LST). Thus, imperviousness, distance to the nearest town and the area of the cities do not seem to play a significant role in the LST night values for the medium-size cities analysed in the region of North Brabant, which do not exceed 7,700 ha in any case. The future growth of most medium-size cities of the regions will not per se aggravate the UHI phenomenon; in turn it will be the design of the new neighbourhoods that will impact the formation of urban heat in the province. The average day LST of provincial parks in South Holland varies depending on the land use. The analysis of the average night LST varies depending of the land use of the patches. The following surfaces are arranged from the lowest to the highest temperatures: water surfaces, forests, cropland, and greenhouse areas. For each of these land uses, NDVI, imperviousness and landscape shape index (LSI) shape index influence the thermal behaviour of the patches differently. NDVI is inversely correlated to day LST for all categories, imperviousness is correlated to day LST for all areas which do not comprise a significant presence of greenhouses (grassland and built patches) and inversely correlated to LST for areas with a high presence of greenhouses (cropland and warehouses). Greenhouse surfaces have highly reflective roofs, which contribute to the reduction of day LST. Finally, landscape shape index varies depending on the nature of the surrounding patches, especially for small patches (built areas, forests and greenhouse areas). When the patches analysed are surrounded by warmer land uses, slender and scattered patches are warmer, more compact and large ones are cooler. In turn, when they are surrounded by cooler patches it is the opposite: slenderer and scattered patches are cooler and more compact and larger ones are warmer. In Midden-Delfland (1 of the 6 South Holland provincial parks), most of the hotspots surrounding the park are adjacent to grassland patches. The measure to increase the cooling capacity of those patches would consist in a change of land use and/or an increase of NDVI of the existing grassland patches. Conclusions Satellite imagery can be used not only to analyse the heat island phenomenom in Dutch neighbourhoods, cities and regions (identify neighbourhoods with highest surface temperature, identify impact of city size and morphology in surface temperature, calcuate average surface temperature for different land uses…), but also to suggest mitigation actions for the areas assessed. Moreover, satellite imagery is here used to generate catalysing mapping typologies: game-board, rhizome, layering and drift, ensuring that the measures proposed remain accurate enough to actualy be efficient and open enough to be compatible with the rest of urban planning priorities

Proceedings of International Virtual Conference 2020 on Spatial Planning and Sustainable Development: Lockdown Urbanism

The ongoing pandemic has led to more than 100 million of confirmed cases and 2.16 million deaths of people globally (up to late January 2021). A variety of health and well-being issues resulting from the largest scale lockdown in the 21st century have addressed emerging global challenges for urban sustainability and smart city development: how to creatively design local neighbourhood and home in response to changing lifestyles? How to smartly design digital and social infrastructure to support individual adaption to changed life-styles? How urban governance and smart city deal with a variety of social, spatial and information inequalities? The multi-disciplinary and international discussion and debates on these timely questions help rethink the planning and governance of healthy city in the uncertain contexts