Urban Green Spaces: how geospatial information can help identify diversity. A case study from eastern Lesser Poland

Progressing globalisation and suburbanisation are driving dynamic changes in land management, particularly in suburban zones. Green infrastructure and its impact on human quality of life are playing an increasingly important role in appropriate spatial management, because of human activities that are changing the natural environment. Therefore, monitoring and assessing the proportion of green spaces is essential for environmental, urban and social balance. The purpose of the study is to develop a method for measuring and monitoring the diversity of land cover classes, including green spaces as representatives of natural land cover classes. The proposed method describes the current state of land in quantitative and qualitative terms based on spatial data on land cover. The study employs Shannon’s Diversity Index (SHDI) to empirically investigate land cover homogeneity. The intensity of the phenomenon was visualised in space using statistical hot spot analysis. The case study involves two cities in eastern Lesser Poland and districts adjacent to them. The results have demonstrated that the investigated areas have a highly heterogenic land cover. Basic assessment fields have exhibited homogeneity only towards large, green, agricultural, environmentally valuable and, often, protected areas. The results concerning urban green spaces comprise a set of data that constitute a valuable source of information to aid the development of informed urban-planning solutions under the sustainable development paradigm

Doctor of Philosophy

dissertationChina’s retail sector has undertaken tremendous transformation since its opening to foreign investment in 1992. Retail transnational corporations have expanded rapidly in this emerging market. Yet relatively little is known about how they have embedded in the Chinese market and expanded spatially and temporally. China has experienced unprecedented urbanization since the onset of economic reform in 1978. Dramatic land use and land cover (LULC) change and urban expansion have taken place in the past three decades. Detailed time-series analysis of LULC change and urban growth in Chinese cities is still scant. This dissertation focuses on the expansion of foreign hypermarket retailers in China and the urban growth in one Chinese city, Suzhou. This research analyzes the penetration strategy and local embeddedness of foreign hypermarket retailers, examines their spatial inequality and dynamics at different geographical levels, and identifies their location determinants through binary logistic regression models. This study applies random forest classification to multitemporal Landsat Thematic Mapper (TM) images of Suzhou for LULC change analysis, employs landscape metrics and Geographic Information System (GIS) analysis to investigate urban growth patterns, and develops global and local logistic regression models to identify determinants of urban growth. The results indicate that spatiotemporal expansion of foreign hypermarket retailers has been largely dictated by the gradual liberalization policy of the Chinese government. Their local embeddedness has been impacted by both home and host economies. Relative gaps in foreign hypermarkets among three macro regions are narrowing while absolute gaps are widening. Provincial foreign hypermarket distribution has shown significant clustering in the Yangtze River Delta since 2005. Their distribution in Shanghai has changed from dispersion to intensified clustering and shown a clear trend of suburbanization. This study confirms that the random forest algorithm can effectively classify the heterogeneous landscape in Suzhou and LULC change has accelerated from 1986 to 2008. Three urban growth types, edge-expansion, infilling, and leapfrog are identified. Compared with the global model, the geographically weighted logistic regression model has overall better goodness-of-fit and provides more insights to spatial variations of the influence of underlying factors on urban growth

Remote sensing of impervious surface area and its interaction with land surface temperature variability in Pretoria, South Africa

Includes summary for chapter 1-5Pretoria, City of Tshwane (COT), Gauteng Province, South Africa is one of the cities that continues to experience rapid urban sprawl as a result of population growth and various land use, leading to the change of natural vegetation lands into impervious surface area (ISA). These are associated with transportation (paved roads, streets, highways, parking lots and sidewalks) and cemented buildings and rooftops, made of completely or partly impermeable artificial materials (e.g., asphalt, concrete, and brick). These landscapes influence the micro-climate (e.g., land surface temperature, LST) of Pretoria City as evidenced by the recent heat waves characterized by high temperature. Therefore, understanding ISA changes will provide information for city planning and environmental management. Conventionally, deriving ISA information has been dependent on field surveys and manual digitizing from hard copy maps, which is laborious and time-consuming. Remote sensing provides an avenue for deriving spatially explicit and timely ISA information. Numerous methods have been developed to estimate and retrieve ISA and LST from satellite imagery. There are limited studies focusing on the extraction of ISA and its relationship with LST variability across major cities in Africa. The objectives of the study were: (i) to explore suitable spectral indices to improve the delineation of built-up impervious surface areas from very high resolution multispectral data (e.g., WorldView-2), (ii) to examine exposed rooftop impervious surface area based on different colours, and their interplay with surface temperature variability, (iii) to determine if the spatio-temporal built-up ISA distribution pattern in relation to elevation influences urban heat island (UHI) extent using an optimal analytical scale and (iv) to assess the spatio-temporal change characteristics of ISA expansion using the corresponding surface temperature (LST) at selected administrative subplace units (i.e., local region scale). The study objectives were investigated using remote sensing data such as WorldView-2 (a very high-resolution multispectral sensor), medium resolution Landsat-5 Thematic Mapper (TM) and Landsat-8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) at multiple scales. The ISA mapping methods used in this study can be grouped into two major categories: (i) the classification-based approach consisting of an object-based multi-class classification with overall accuracy ~90.4% and a multitemporal pixel-based binary classification. The latter yielded an area under the receiver operating characteristic curve (AUROC) = 0.8572 for 1995, AUROC = 0.8709 for 2005, AUROC = 0.8949 for 2015. (ii) the spectral index-based approach such as a new built-up extraction index (NBEI) derived in this study which yielded a high AUROC = ~0.82 compared to Built-up Area Index (BAI) (AUROC = ~0.73), Built-up spectral index (BSI) (AUROC = ~0.78), Red edge / Green Index (RGI) (AUROC = ~0.71) and WorldView-Built-up Index (WV-BI) (AUROC = ~0.67). The multitemporal built-up Index (BUI) also estimated with AUROC = 0.8487 for 1993, AUROC = 0.8302 for 2003, AUROC = 0.8790 for 2013. This indicates that all these methods employed, mapped ISA with high predictive accuracy from remote sensing data. Furthermore, the single-channel algorithm (SCA) was employed to retrieve LST from the thermal infrared (TIR) band of the Landsat images. The LST overall retrieval error for the entire study generally was quite low (overall root mean square RMSE ≤ ~1.48OC), which signifies that the Landsat TIR used provided good results for further analysis. In conclusion, the study showed the potential of multispectral remote sensing data to quantify ISA and evaluate its interaction with surface temperature variability despite the complex urban landscape in Pretoria. Also, using impervious surface LST as a complementary metric in this research helped to reveal urban heat island distribution and improve understanding of the spatio-temporal developing trend of urban expansion at a local spatial scale.Rapid urbanization because of population growth has led to the conversion of natural lands into large man-made landscapes which affects the micro-climate. Rooftop reflectivity, material, colour, slope, height, aspect, elevation are factors that potentially contribute to temperature variability. Therefore, strategically designed rooftop impervious surfaces have the potential to translate into significant energy, long-term cost savings, and health benefits. In this experimental study, we used the semi-automated Environment for Visualizing Images (ENVI) Feature Extraction that uses an object-based image analysis approach to classify rooftop based on colours from WorldView-2 (WV-2) image with overall accuracy ~90.4% and kappa coefficient ~0.87 respectively. The daytime retrieved surface temperatures were derived from 15m pan-sharpened Landsat 8 TIRS with a range of ~14.6OC to ~65OC (retrieval error = 0.38OC) for the same month covering Lynwood Ridge a residential area in Pretoria. Thereafter, the relationship between the rooftops and surface temperature (LST) were examined using multivariate statistical analysis. The results of this research reveal that the interaction between the applicable rooftop explanatory features (i.e., reflectance, texture measures and topographical properties) can explain over 22.10% of the variation in daytime rooftop surface temperatures. Furthermore, analysis of spatial distribution between mean daytime surface temperature and the residential rooftop indicated that the red, brown and green roof surfaces show lower LST values due to high reflectivity, high emissivity and low heat capacity during the daytime. The study concludes that in any study related to the spatial distribution of rooftop impervious surface area surface temperature, effect of various explanatory variables must be considered. The results of this experimental study serve as a useful approach for further application in urban planning and sustainable development.Evaluating changes in built-up impervious surface area (ISA) to understand the urban heat island (UHI) extent is valuable for governments in major cities in developing countries experiencing rapid urbanization and industrialization. This work aims at assessing built-up ISA spatio-temporal and influence on land surface temperature (LST) variability in the context of urban sprawl. Landsat-5 Thematic Mapper (TM) and Landsat-8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) were used to quantify ISA using built-up Index (BUI) and spatio-temporal dynamics from 1993-2013. Thereafter using a suitable analytical sampling scale that represents the estimated ISA-LST, we examined its distribution in relation to elevation using the Shuttle Radar Topography Mission (SRTM) and also create Getis-Ord Gi* statistics hotspot maps to display the UHI extent. The BUI ISA extraction results show a high predictive accuracy with area under the receiver operating characteristic curve, AUROC = 0.8487 for 1993, AUROC = 0.8302 for 2003, AUROC = 0.8790 for 2013. The ISA spatio-temporal changes within ten years interval time frame results revealed a 14% total growth rate during the study year. Based on a suitable analytical scale (90x90) for the hexagon polygon grid, the majority of ISA distribution across the years was at an elevation range of between >1200m – 1600m. Also, Getis-Ord Gi* statistics hotspot maps revealed that hotspot regions expanded through time with a total growth rate of 19% and coldspot regions decreased by 3%. Our findings can represent useful information for policymakers by providing a scientific basis for sustainable urban planning and management.Over the years, rapid urban growth has led to the conversion of natural lands into large man-made landscapes due to enhanced political and economic growth. This study assessed the spatio-temporal change characteristics of impervious surface area (ISA) expansion using its surface temperature (LST) at selected administrative subplace units (i.e., local region scale). ISA was estimated for 1995, 2005 and 2015 from Landsat-5 Thematic Mapper (TM) and Landsat-8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) images using a Random Forest (RF) algorithm. The spatio-temporal trends of ISA were assessed using an optimal analytical scale to aggregate ISA LST coupled with weighted standard deviational ellipse (SDE) method. The ISA was quantified with high predictive accuracy (i.e., AUROC = 0.8572 for 1995, AUROC = 0.8709 for 2005, AUROC = 0.8949 for 2015) using RF classifier. More than 70% of the selected administrative subplaces in Pretoria experienced an increase in growth rate (415.59%) between 1995 and 2015. LST computations from the Landsat TIRS bands yielded good results (RMSE = ~1.44OC, 1.40OC, ~0.86OC) for 1995, 2005 and 2015 respectively. Based on the hexagon polygon grid (90x90), the aggregated ISA surface temperature weighted SDE analysis results indicated ISA expansion in different directions at the selected administrative subplace units. Our findings can represent useful information for policymakers in evaluating urban development trends in Pretoria, City of Tshwane (COT).Globally, the unprecedented increase in population in many cities has led to rapid changes in urban landscape, which requires timely assessments and monitoring. Accurate determination of built-up information is vital for urban planning and environmental management. Often, the determination of the built-up area information has been dependent on field surveys, which is laborious and time-consuming. Remote sensing data is the only option for deriving spatially explicit and timely built-up area information. There are few spectral indices for built-up areas and often not accurate as they are specific to impervious material, age, colour, and thickness, especially using higher resolution images. The objective of this study is to test the utility of a new built-up extraction index (NBEI) using WorldView-2 to improve built-up material mapping irrespective of material type, age and colour. The new index was derived from spectral bands such as Green, Red edge, NIR1 and NIR2 bands that profoundly explain the variation in built-up areas on WorldView-2 image (WV-2). The result showed that NBEI improves the extraction of built-up areas with high accuracy (area under the receiver operating characteristic curve, AUROC = ~0.82) compared to the existing indices such as Built-up Area Index (BAI) (AUROC = ~0.73), Built-up spectral index (BSI) (AUROC = ~0.78 ), Red edge / Green Index (RGI) (AUROC = ~0.71) and WorldView-Built-up Index (WV-BI) (AUROC = ~0.67). The study demonstrated that the new built-up index could extract built-up areas using high-resolution images. The performance of NBEI could be attributed to the fact that it is not material specific, and would be necessary for urban area mapping.Environmental SciencesD. Phil. (Environmental Sciences

Climate Change and Environmental Sustainability-Volume 4

Anthropogenic activities are significant drivers of climate change and environmental degradation. Such activities are particularly influential in the context of the land system that is an important medium connecting earth surface, atmospheric dynamics, ecological systems, and human activities. Assessment of land use land cover changes and associated environmental, economic, and social consequences is essential to provide references for enhancing climate resilience and improving environmental sustainability. On the one hand, this book touches on various environmental topics, including soil erosion, crop yield, bioclimatic variation, carbon emission, natural vegetation dynamics, ecosystem and biodiversity degradation, and habitat quality caused by both climate change and earth surface modifications. On the other hand, it explores a series of socioeconomic facts, such as education equity, population migration, economic growth, sustainable development, and urban structure transformation, along with urbanization. The results of this book are of significance in terms of revealing the impact of land use land cover changes and generating policy recommendations for land management. More broadly, this book is important for understanding the interrelationships among life on land, good health and wellbeing, quality education, climate actions, economic growth, sustainable cities and communities, and responsible consumption and production according to the United Nations Sustainable Development Goals. We expect the book to benefit decision makers, practitioners, and researchers in different fields, such as climate governance, crop science and agricultural engineering, forest ecosystem, land management, urban planning and design, urban governance, and institutional operation.Prof. Bao-Jie He acknowledges the Project NO. 2021CDJQY-004 supported by the Fundamental Research Funds for the Central Universities and the Project NO. 2022ZA01 supported by the State Key Laboratory of Subtropical Building Science, South China University of Technology, China. We appreciate the assistance of Mr. Lifeng Xiong, Mr. Wei Wang, Ms. Xueke Chen, and Ms. Anxian Chen at School of Architecture and Urban Planning, Chongqing University, China

The use of satellite data, meteorology and land use data to define high resolution temperature exposure for the estimation of health effects in Italy

Introduction. Despite the mounting evidence on heat-related health risks, there is limited evidence in suburban and rural areas. The limited spatial resolution of temperature data also hinders the evidence of the differential heat effect within cities due to individual and area-based characteristics. Methods. Satellite land surface temperature (LST), observed meteorological and spatial and spatio-temporal land use data were combined in mixed-effects regression models to estimate daily mean air temperature with a 1x1km resolution for the period 2000-2010. For each day, random intercepts and slopes for LST were estimated to capture the day-to-day temporal variability of the Ta–LST relationship. The models were also nested by climate zones to better capture local climates and daily weather patterns across Italy. The daily exposure data was used to estimate the effects and impacts of heat on cause-specific mortality and hospital admissions in the Lazio region at municipal level in a time series framework. Furthermore, to address the differential effect of heat within an urban area and account for potential effect modifiers a case cross-over study was conducted in Rome. Mean temperature was attributed at the individual level to the Rome Population Cohort and the urban heat island (UHI) intensity using air temperature data was calculated for Rome. Results. Exposure model performance was very good: in the stage 1 model (only on grid cells with both LST and observed data) a mean R2 value of 0.96 and RMSPE of 1.1°C and R2 of 0.89 and 0.97 for the spatial and temporal domains respectively. The model was also validated with regional weather forecasting model data and gave excellent results (R2=0.95 RMSPE=1.8°C. The time series study showed significant effects and impacts on cause-specific mortality in suburban and rural areas of the Lazio region, with risk estimates comparable to those found in urban areas. High temperatures also had an effect on respiratory hospital admissions. Age, gender, pre-existing cardiovascular disease, marital status, education and occupation were found to be effect modifiers of the temperature-mortality association. No risk gradient was found by socio-economic position (SEP) in Rome. Considering the urban heat island (UHI) and SEP combined, differential effects of heat were observed by UHI among same SEP groupings. Impervious surfaces and high urban development were also effect modifiers of the heat-related mortality risk. Finally, the study found that high resolution gridded data provided more accurate effect estimates especially for extreme temperature intervals. Conclusions. Results will help improve heat adaptation and response measures and can be used predict the future heat-related burden under different climate change scenarios.Open Acces

中国陝西省南部における伝統的な住宅の冬の省エネルギー設計に関する研究

The combination of solar energy and buildings can greatly save energy, and a great deal of practical and theoretical research has been conducted on solar buildings around the world. Rural areas in southern Shaanxi, China, have wet and cold winters. The average room temperature is 4°C and below 2°C at night, which greatly exceeds the range of thermal comfort that the human body can tolerate. In response to a series of problems such as backward heating methods and low heating efficiency in southern Shaanxi, two fully passive heating methods are proposed for traditional houses in the region. They are rooftop solar heating storage systems and thermal storage wall heating systems (TSWHS), respectively. These two systems have been compared with the status quo heating system to confirm the practicality of the new system and to provide an idea for heating and energy saving in traditional houses in rural areas.北九州市立大

Housing quality and lost (public) space in Croatia

IN ENGLISH: In the post-socialist period and within the current social transition context, urban and rural Croatia has, just like other transition countries, experienced many changes in the social structure and space. One example is the housing quality which is a replica of the situation in the Croatian society and has also undergone some major changes. Socially oriented housing construction co-financed by the state and the cities is in an unfavourable position compared to private housing construction. In the last twenty years the amount of the social housing construction has been only a minor part of the total contruction work in the country. For instance, out of nine newly planned residential housing developments in Zagreb, the capital city, only three have been completed and the work on the rest of them has stopped and is unlikely to continue. Private construction work prevails especially on the edge of the city and is characterised by high density housing. This type of housing construction doesn't benefit the majority of citizens in search of accommodation (price per square meter is too high, low-quality building). There is also a big problem of the community facilities (primary and secondary infrastructure, schools, kindergartens, playgrounds, green areas, sidewalks, public transport etc.). The existing globalisation-transition circumstances of the Croatian society corroborate the fact which experts of various profiles often point out: ignoring the process of (urban) planning will irreparably damage the space. The city transformation shows the absence of comprehensive urban planning which results in an ever increasing number of random buildings which do not fit in the surroundings. This leads up to yet another important issue – the shrinking and, in some cases, disappearance of public space which becomes the “lost space“. In recent years there has been a lot of building in the city core and on the edge which does not quite fit in the existing urban structure, image or the skyline of the city. The current situation in the process of planning can be characterized as a conflict and imbalance between the powerful actors (mostly political and economic) and less powerful actors (mostly professional and civil). The actors who have the political power and influence and the ones who possess the capital are forming an “alliance” between two important layers of the social structure. The lack of civil and professional actors, “lost spatial actors”, and therefore of civic aggregation is also present and that is also the cause of public space “disappearance” and undermined process of public participation. --------------- IN CROATIAN: U postsocijalističkom razdoblju i trenutnom tranzicijskom kontekstu urbana i ruralna Hrvatska su, kao i ostale tranzicijske zemlje, doživjele mnoge promjene u društvenoj strukturi i samom prostoru. Na primjeru kvalitete stanovanja kao replike stanja u hrvatskom društvu mogu se vidjeti značajne promjene. Društveno usmjerena stambena izgradnja sufinancirana od strane države i gradova je stoga rjeđa i u nepovoljnijoj je situaciji prema privatnoj stanogradnji. Zadnjih dvadeset godina udjel socijalne stambene gradnje je zanemariv u ukupnoj izgradnji na razini zemlje. Primjerice, od devet planiranih stambenih naselja izgrađenih po modelu POS-a u Zagrebu samo su tri i završena. Na ostalima je proces gradnje zastao i ne čini se da će se privesti kraju. Privatna je gradnje prisutnija, posebno na rubovima grada, a obilježava je visoka gustoća gradnje. Ovakav tip gradnje ne odgovara većini stanovnika koji su u procesu potražnje stambene nekretnine (visoka cijena kvadratnog metra, a slaba kvaliteta gradnje). Postoji također i problem nedostatne opremljenosti susjedstva (primarna i sekundarna infrastruktura, škole, vrtići, igrališta, zelene površine, pješačke staze, javni transport itd.). Navedene globalizacijsko-tranzicijske okolnosti hrvatskog društva potvrđuju ono što eksperti različitih profila ističu, a to je da će ignoriranje procesa (urbanog) planiranja nepovratno uništiti prostor gradova. Ovakve transformacije pokazuju nedostatak sustavnog urbanog planiranja što rezultira sve većim brojem zgrada koje se ne uklapaju u neposrednu okolinu. To nadalje dovodi do drugog važnog aspekta – smanjivanja i u nekim slučajevima, nestanka javnog prostora koji postaje „izgubljeni prostor“. Posljednjih je godina izgrađen velik broj zgrada, i u središtu i na rubovima grada, koje se ne uklapaju u postojeću urbanu strukturu, izgled ili vizuru grada. Ovakvu situaciju obilježavaju sukob i neravnoteža između moćnijih društvenih aktera (većinom političkih i ekonomskih) i onih manje moćnih (većinom profesionalnih i civilnih). Politički i ekonomski akteri se često povezuju u „savez“ dvaju najjačih u društvenoj strukturi. S druge strane nedostatak utjecaja civilnih i profesionalnih aktera kao „izgubljenih prostornih aktera“ dovodi do „nestanka“ javnih prostora te smanjenja važnosti procesa participacije (sudjelovanja javnosti)