Future urban development towards green smart cities: opportunities and challenges
Urban greenspaces play a prime role in making city liable and natural. They are a vital part of the city on the way to achieve sustainable development. They have great values in offering ecosystem services, improving environmental quality and maintaining biodiversity. Smart allocation of greenspaces in the cities will optimize their values to enhance the adaptive capacity in the context of the climate change and anthropogenic processes. Due to competition for space in the urban region, the urban forests and urban greenspaces are vulnerable to the encroachments associated with the growth of the city and the damages linking to extreme weather.
This session aims to gather original viewpoints and bring up discussions concerning various opportunities and challenges in different areas of science of earth observations, environmental health in association with vegetation health, economy and industrialization, in particular, liking to urban greenspaces. innovative techniques and approaches are encouraged to be introduced to foster applications of remote sensing and GIS in contemporary practice. Urban greenspaces are expected to be assessed, monitored and managed by the means of remote sensing and GIS technologies and benchmark models. It is also encouraged to present and discuss the green indices, conceptual frameworks, implemented approaches, models and innovative techniques to make city smarter in greening. Outcomes of the comprehensive studies are essential to make the cities more adaptive in the context of climate change.
Typhoon is one of the most severe natural hazards. It can cause great damages to the people, properties, and greenspace infrastructure. Greenspaces include parks, gardens, play grounds, plants, etc. In urban areas, greenspaces are highly prone to be affected by typhoons resulting dangers to humans, infrastructure, and transportation. This study introduces a vulnerable assessment framework of urban greenspaces (UGSs) to typhoons by using remote sensing data and GIS techniques. The key purpose is to mitigate potential damages of urban greenspace and other related risks associated with typhoons. Firstly, we analyze the typhoon characteristics; identify the impacts of typhoons on the UGSs in Taiwan; and derive the UGSs information (biological and physical features) from multi-sensor satellite images to build GIS database for the UGS server for further assessment. Secondly, we derive the soil characteristics from the soil map and remote sensing data; propose an vulnerable assessment framework to evaluate the vulnerability of the UGSs to typhoon in major cities in Taiwan. Thirdly, we improve and test the R3GIS platform after integrating with new tools of assessing vulnerability of UGSs to typhoons for demonstration of its benefits to UGS management in Taiwan. The outcomes will be expected to support warning system to serve the related authorities for mitigating the damages of typhoons on UGSs and communities. The vulnerability of UGS in Taiwan to typhoon winds can be assessed via three domains: (i) typhoon characteristics; (ii) UGSs features; and (iii) soil composition. These components will be captured via multi-sub indicators that reveal the possibility whether trees in the UGS will fail during the threat of typhoons and related risks. Thus, the combination of all mentioned domains/indicators in the vulnerability assessment framework thas a potential to provide a warning to related authorities with possible solutions for lesseing the damages of both UGS and public properties. In EGU meeting we are going to introduce an overall concept of the research work and the first phase results of the study such as typhoon characteristics and features of urban greenspaces in Taiwan, and the conceptual UGS vulnerability assessment framework.
How to cite:
Nguyen, K.-A. and Liou, Y.-A.: GIS and remote sensing-based framework for urban greenspaces management: assessment of vulnerability to typhoons in Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-243, https://doi.org/10.5194/egusphere-egu2020-243, 2020.
The smart and sustainable city idea gained momentum in recent years in order to cope with population growth in urban areas and to make the city live. Cities are projected to consume 70% of the world's resources and 66% of the world population by 2050. Most of tier-3 and tier-2 cities will convert to tier-1 city, and we need to identify and protect the urban green spaces. Urban green areas have many esthetic advantages, including environmental benefits such as a fall in city temperature in the summer and absorption of rainwater. Social advantages are such as feelings of happiness and peace. Objective quantification of greenery on its neighbourhood spatial distribution may help identify essential and potential areas. Heterogeneous land uses describe urban areas. Urban heat island (UHI), with high Land surface temperatures (LST), is distinguished by its city development pattern, socioeconomic and anthropogenic activities. The LST is rising rapidly not only in cities but also in tier-3 & tier-2 cities. Urban green areas, including parks, playgrounds, gardens and areas, such as ponds, pools, lakes and rivers, will contribute to the control of land temperatures in and around the city. Such spaces also lead to the formation of the Urban Cooling Island (UCI), where temperatures are comparatively cooler than surrounding temperatures, because of their shade of the trees and their evapotranspiration. This cooling island formation is referred to as the Park Cooling Island (PCI) impact. The present work aims to describe the effect of urban green and urban blue spaces on LST using a range of data sources with geospatial technologies. Udupi town, which comes under Udupi district, Karnataka, India is a tier-3 city, selected for the present research work. The data used in the study include Landsat 8 temporal satellite images and secondary data, such as field data from various government and semi-government organisations. LST has been measured using the emissivity reference channel algorithm from Landsat 8 thermal bands. Different indices such as Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index NDWI, Land Shape Index (LSI) are determined from images from Landsat 8. The results show that LST exists with high spatial variability and urban green, blue spaces have a stronger influence on LST.
How to cite:
Shetty, P. and g s, D.: Examining the Effects of Heat Mitigation on the Physical Properties of Urban Green Space and Urban Blue Space: A Case Study, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-760, https://doi.org/10.5194/egusphere-egu2020-760, 2020.
The scale of urbanization in China during the past 30 years is unprecedented in human history along with its fast economic growth, presenting profound impacts on socioeconomics, human well-being, and the environment. We quantified spatial patterns and temporal courses of urban land expansion for 32 major cities across China from the late 1970s to 2010 using multitemporal Landsat data of 1978, 1990, 1995, 2000, 2005, and 2010, and further explored the effects of urbanization on climate (i.e., urban heat islands), and vegetation phenology and growth in these 32 cities, together with MODIS Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) products.
We found that rapid urban expansion was observed in these 32 major cities from 1978 to 2010, with an overall annual expansion rate of 6.8 ± 2.5 %. Chinese urban expansion does not fit urban expansion theory consistently over time and has transitioned from contradicting to conforming to Gibrat’s law, which states that the growth rate is independent of city size. The surface urban heat island intensity (SUHII) differed substantially between day and night and varied greatly with season. Spatial variability of the SUHII is ultimately controlled by background climate. The growing season started 11.9 days earlier and ended 5.4 days later in urban zones compared to rural counterparts. The phenological sensitivity to temperature were 9-11 days SOS advance and 6-10 days EOS delay per 1 °C increase of LST. For the first time, we developed a general conceptual framework for quantifying the impacts of urbanization on vegetation growth and applied it in 32 Chinese cities. Results indicated prevalent vegetation growth enhancement in urban environment and vegetation growth was enhanced at 85% of the places along the intensity gradient. This growth enhancement offset about 40% of direct loss of vegetation productivity caused by replacing productive vegetated surfaces with non-productive impervious surfaces. The urban environments, considered as the "harbingers" of global environmental change and "natural laboratories" for global change studies, shed new insights and approaches into global change science, and the urban-rural gradient provides an excellent experimental manipulations for global change studies.
How to cite:
Zhao, S.: Contemporary Urban Expansion in China and its diverse effects, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2136, https://doi.org/10.5194/egusphere-egu2020-2136, 2020.
Yanzhe Yin, Andrew Grundstein, Deepak Mishra, Navid Hashemi, and Lakshmish Lakshmish
High-quality temperature data at a finer spatial-temporal scale is critical for analyzing the risk of heat hazards in urban environments. The variability of urban landscapes makes cities a challenging landscape for quantifying heat exposure. Most of the existing heat hazard studies have inherent limitations on two fronts: the spatial-temporal granularities are too coarse and the ability to track the actual ambient air temperature instead of land surface temperature. Overcoming these limitations requires radically different research approaches, both the paradigms for collecting the temperature data and developing models for high-resolution heat mapping. We present a comprehensive approach for studying urban heat hazards by harnessing a high-quality hyperlocal temperature dataset from a network of mobile sensors and using it to refine the satellite-based temperature products. We mounted vehicle-borne mobile sensors on thirty city buses to collect high-frequency (5 sec) temperature data from June 2018 to Nov 2019. The vehicle-borne data clearly show significant temperature differences across the city, with the largest differences of up to 10℃ and morning-afternoon diurnal changes at a magnitude around 20℃. Then we developed a machine learning approach to derive a hyperlocal ambient air temperature (AAT) product by combining the mobile-sensor temperature data, satellite LST data, and other influential biophysical parameters to map the variability of heat hazard over areas not covered by the buses. The machine learning model output highlighted the high spatio-temporal granularity in AAT within an urban heat island. The seasonal AAT maps derived from the model show a well-defined hyperlocal variability of heat hazards which are not evident from other research approaches. The findings from this study will be beneficial for understanding the heat exposure vulnerabilities for individual communities. It may also create a pathway for policymakers to devise targeted hazard mitigation efforts such as increasing green space and developing better heat-safety policies for workers.
How to cite:
Yin, Y., Grundstein, A., Mishra, D., Hashemi, N., and Lakshmish, L.: A mobile sensor-based Approach for Analyzing and Mitigating Urban Heat Hazards, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12446, https://doi.org/10.5194/egusphere-egu2020-12446, 2020.
Francesco Busca, Francesca Vigliocco, and Roberto Revelli
This paper is part of the panorama of studies on climate changes in an urban context. Starting from the concept of Ecosystem Services, we aim to underline the importance of rebalancing equally what is demanded in an urban ecosystem and what it provides people with, focusing on pollutants quantity, carbon sequestration and runoff reduction. Ecosystem services (ES) can be defined as the components of natural capital that provide direct products (food, drinking water, etc) and benefits (like biological variability and soil creation) to people. Our goal is to determinate and to quantify ES related to urban greenspaces in terms of both economic and environmental point of view.
Specifically, the study has been developed through the use of i-Tree, a suite developed in the US context, that shows on both small and large scale the economic, environmental and water-related benefits provided by a green area. Its applicability has been tested for an Italian context on a newly built park, located in “Revello Street – Turin”, with the collaboration of the Municipality of Turin, comparing past, present and future scenarios.
Eco, Hydro and Canopy tools were used for that urban greenspace, providing useful information on software usage and justifying the creation and/or the expansion of new urban green areas through economic and environmental outputs. Results show how the transition from a past residential area to an almost totally green area has led to air quality improvement, with a consequent increase in carbon storage and pollutants reduction, while in view of future improvement works in the park (intensification of arboreal and shrubby presence), the results economically justify the intervention by showing a significant water runoff reduction with consequent reduction of flood events risk.
This work aims to deepen advantages and disadvantages of i-Tree and to insert the software as an effective and innovative tool, not widely known in a European context, for the monitoring and development of methodologies to make urban spaces increasingly sustainable, within a view of smart cities.
How to cite:
Busca, F., Vigliocco, F., and Revelli, R.: Ecosystem services determination on an Italian urban greenspace , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14632, https://doi.org/10.5194/egusphere-egu2020-14632, 2020.
Paolo Viskanic, Alice Pasquinelli, Alessio Fini, and Piotr Wezyk
Climate change is a serious and cross-cutting issue: urban areas are particularly sensitive to climate impacts, especially to heatwaves, floods and droughts. Typically, urban phenomena (such as the ‘urban heat island effect’ – where the urban area is significantly warmer than the surrounding rural areas) and the impacts of extreme weather events demonstrate the high vulnerability of cities.
Specific urban adaptation strategies are therefore needed to make cities more resilient. In this context, green areas and green infrastructures are seen among the most widely applicable, economically viable and effective tools to combat the impacts of climate change and help people adapt to or mitigate adverse effects of this change.
LIFE URBANGREEN is a European Funded project dealing with climate adaptation through the maximisation of ecosystem services provided by urban green areas maintained in an innovative way. The main expected result is a smart, integrated, geospatial management system, to monitor and govern all activities related to urban green areas, maximizing ecological benefits.
Five innovative modules are being developed within the project, aimed at:
providing irrigation to trees only when and where actually needed
reducing the carbon footprint of maintenance activities through a more efficient job planning
quantifying ecosystem services provided by green areas
monitoring health conditions of trees using remote sensing data
increasing citizen participation in urban green management
The project involves 5 Italian and Polish partners:
R3 GIS (GIS software company and project coordinator, Bolzano, Italy)
University of Milano (scientific coordinator, Milano, Italy)
ZZM (manager of urban green areas in Krakow, Poland)
Anthea (manager of urban green areas in Rimini, Italy)
Also, the National Central University (NCU) in Taiwan, under the coordination of Prof Yuei-An Liou, supports the project and participates as external partner and will test some innovations of the LIFE URBANGREEN Project in Taiwan.
During the EGU conference, results obtained during the first two years of the project will be presented. More information on the project is available at www.lifeurbangreen.eu
How to cite:
Viskanic, P., Pasquinelli, A., Fini, A., and Wezyk, P.: LIFE URBANGREEN: Innovative technological platform to improve management of green areas for better climate adaptation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20662, https://doi.org/10.5194/egusphere-egu2020-20662, 2020.
KEYWORDS: Urbanisation, Remote sensing, Comprehensive environmental quality, Bhopal, India
A tremendous increase in the global human population has become a major threat to the environment mainly these situations are existing in developing nations. A higher population poses higher demands as well as pressure on the environment directly or indirectly, which is an issue for the sustainable development of the country. Most of the Indian cities are facing challenges in environmental sustainability. Bhopal the capital city of Madhya Pradesh, India is presently going through rapid urbanization and industrialization which leads to environmental degradation of the city. The study aims at analyzing the environmental sustainability of the city. The study is performed using satellite-based remote sensing data integrated with the census data. Initially, Landsat TM satellite data of the years 2001 and 2011 are utilized for extracting the land use land cover (LULC) transformations. Further, MODIS data products at 1 km resolution are used for estimating the biophysical indicators (BI) which are normalized difference vegetation index (NDVI) and land surface temperature (LST). A comprehensive environmental quality index (CEQI) is obtained by integrating BI with census data and transformations in CEQI are studied for the urban environment. The results depicted an increase in urban built-up with a phenomenal decay in the greenness of the city. The results from CEQI reveals significant changes in the different zones of the city which are highly affected due to change in urbanization and greenness pattern of the city. The study highlights the critical zones of the city and suggests measures to improve the environmental quality for the critical zones which can help the policy-makers in sustainable planning of the city.
How to cite:
Singh, S. and Jain, K.: Comprehensive urban environment quality assessment using remote sensing satellite data for Bhopal city, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21201, https://doi.org/10.5194/egusphere-egu2020-21201, 2020.