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Urbanization is a dominant driver of landscape transformation across the world, with cities representing centers of economic and socio-cultural development. Today, more than 4.2 billion people live in urban areas, which represent ~3% of the Earth’s land area. By 2050, it is predicted this number will increase to 6.6 billion people (~70% of the predicted global population). As the human population grows, cities around the globe will continue to expand, increasing the demand for food and services. Within cities, urban forests provide multiple nature-based solutions, as well as other environmental services and socio-economic benefits, such as heat mitigation and social integration. Urban forests are also important for coping with psychological stress during events, such as the COVID-19 pandemic. Therefore, urban forests are a priority for basic and applied forest research because they are intimately connected with people’s physical, cultural, and economic well-being in the urban environment, and can also be important reservoirs of biodiversity. To promote a better understanding of urban forests and landscape ecology, this book in “Urban Forests and Landscape Ecology” compiled research set in urban forests and focused on some spatially explicit processes. Studies presented in this book are highly interdisciplinary and use a wide range of research approaches. This book present nine scientific publications from global urban forests demonstrating that these forests, as a nature-based solution, provide multiple environmental services and are crucial to improve urban livability and thereby the wellbeing of city dwellers.

Research & information: general --- Biology, life sciences --- aesthetics --- causal effects --- crown form --- foliage form --- urban forests --- urban forest --- NATURA 2000 area --- soundscape --- birds --- biological diversity --- ecosystem disservices --- Mediterranean region --- green infrastructure --- urban forest types --- indicators --- microclimate --- human thermal comfort --- outdoor thermal environment --- public health --- ecological services --- urban green space --- remote sensing --- deep learning --- convolutional neural network --- residual structure --- attention mechanism --- urban biodiversity --- urban habitat quality --- InVEST model --- land surface temperature --- Moran's I --- Zhengzhou --- social media data --- spatiotemporal utilization --- Shanghai --- ecological function --- landscape structure --- GIS --- air pollution alleviation --- accumulation on leaves --- PM2.5 --- encapsulated particles --- urban trees --- aesthetics --- causal effects --- crown form --- foliage form --- urban forests --- urban forest --- NATURA 2000 area --- soundscape --- birds --- biological diversity --- ecosystem disservices --- Mediterranean region --- green infrastructure --- urban forest types --- indicators --- microclimate --- human thermal comfort --- outdoor thermal environment --- public health --- ecological services --- urban green space --- remote sensing --- deep learning --- convolutional neural network --- residual structure --- attention mechanism --- urban biodiversity --- urban habitat quality --- InVEST model --- land surface temperature --- Moran's I --- Zhengzhou --- social media data --- spatiotemporal utilization --- Shanghai --- ecological function --- landscape structure --- GIS --- air pollution alleviation --- accumulation on leaves --- PM2.5 --- encapsulated particles --- urban trees

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Over the last two decades, many researchers have focused on developing countries' urbanization patterns and processes. In this context, the scarcity of spatial data has been an obstacle to studying urbanization quantitatively, especially in Asian and African cities. The use of remote sensing data and geographical information systems (GIS) techniques can overcome the above limitations. Data on land use and land cover, land surface temperature, population density, and energy consumption can be extracted based on remote sensing at various spatial and temporal resolutions. GIS techniques can be used to analyze urbanization patterns and predict future patterns. Thus, the link between urbanization and sustainable urban development has increasingly become a principal issue in designing and developing sustainable cities at the local, regional, and global levels. This volume shows the spatiotemporal analysis of urbanization using GIS and remote sensing in developing countries, with a special emphasis on future urban sustainability in Asia and Africa. Capturing the spatial-temporal variation of urbanization patterns will help introduce proper sustainable urban planning in developing countries, especially for Asian and African cities.

Research & information: general --- Geography --- LST --- urban-rural gradient --- sub-Saharan region --- Addis Ababa --- Ethiopia --- cellular automata --- spatial layout --- transportation infrastructure --- LUCC --- spatial patterns --- spatial differences --- DMSP-OLS --- China --- India --- landscape pattern --- industrial rural area --- rural landscape --- landscape ecology --- southern Jiangsu --- land use and cover --- land surface temperature --- built-up land --- agricultural land --- gradient analysis --- Nuwara Eliya --- Sri Lanka --- urban public space --- environment --- check-in data --- social media platform --- point of interest --- urbanization --- GIS --- urban development zones --- urban sustainability --- regression analysis --- GWR --- fragmentation --- non-agricultural conversion of rural land --- urban green space --- RSEI --- remote sensing --- ecological status --- dynamic motoring --- Pingtan Island --- urban land expansion --- spatial pattern --- driving forces --- Pearl River Delta --- urban agglomeration --- urban heat island --- impervious surface area --- biophysical composition index --- coastal city --- Xiamen --- surface urban heat island --- MODIS --- land cover --- habitat quality --- spatiotemporal analysis --- Yangtze River Delta Urban Agglomeration --- urban planning --- LULC change --- transition matrix --- systematic transition --- Blantyre city --- life quality index (LQI) --- Kandy city --- AHP --- MCDM --- COVID-19 pandemic --- environmental quality --- PM10 concentration --- LST --- urban-rural gradient --- sub-Saharan region --- Addis Ababa --- Ethiopia --- cellular automata --- spatial layout --- transportation infrastructure --- LUCC --- spatial patterns --- spatial differences --- DMSP-OLS --- China --- India --- landscape pattern --- industrial rural area --- rural landscape --- landscape ecology --- southern Jiangsu --- land use and cover --- land surface temperature --- built-up land --- agricultural land --- gradient analysis --- Nuwara Eliya --- Sri Lanka --- urban public space --- environment --- check-in data --- social media platform --- point of interest --- urbanization --- GIS --- urban development zones --- urban sustainability --- regression analysis --- GWR --- fragmentation --- non-agricultural conversion of rural land --- urban green space --- RSEI --- remote sensing --- ecological status --- dynamic motoring --- Pingtan Island --- urban land expansion --- spatial pattern --- driving forces --- Pearl River Delta --- urban agglomeration --- urban heat island --- impervious surface area --- biophysical composition index --- coastal city --- Xiamen --- surface urban heat island --- MODIS --- land cover --- habitat quality --- spatiotemporal analysis --- Yangtze River Delta Urban Agglomeration --- urban planning --- LULC change --- transition matrix --- systematic transition --- Blantyre city --- life quality index (LQI) --- Kandy city --- AHP --- MCDM --- COVID-19 pandemic --- environmental quality --- PM10 concentration