Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands

Introduction

This book is a selection of the best papers presented at the CUPUM conference at Aalto University, Helsinki, Finland in June 2021. CUPUM stands for Computational Urban Planning and Urban Management and is a once every two years conference, held somewhere in the world. This chapter is the introductory chapter to this book. It introduces the title and central theme of the book: ‘Urban Informatics and Future Cities’. Therein, three cross cutting themes can be identified: big data, disasters and resiliance, and walkability and tourism. Besides, the chapter provides an overview of the content of the volume by presenting briefly each of its consituting chapters, their titles and authors and their main content. In total 30 chapters have been included in this volume

Smart Governance and COVID-19 Control in Wuhan, China

In dealing with the global COVID-19 pandemic, China has achieved reasonable success in governing COVID-19 within two months with the help of technologies. This study specifically focuses on how these massive technologies have been implemented to facilitate the smart governance of COVID-19 in Wuhan, China. By discursively analyzing existing data from multiple sources, the results obtained in this chapter show that the real ‘smartness’ of the smart governance of COVID-19 in Wuhan is the innovative use of technologies to develop different types of governance approaches to control COVID-19 in an effective and targeted way. As the pandemic continues to evolve worldwide, lessons learned from Wuhan, China can be beneficial to other countries in different institutional contexts to build their own, context-specific governance for controlling the pandemic

Smart Governance and COVID-19 Control in Wuhan, China

In dealing with the global COVID-19 pandemic, China has achieved reasonable success in governing COVID-19 within two months with the help of technologies. This study specifically focuses on how these massive technologies have been implemented to facilitate the smart governance of COVID-19 in Wuhan, China. By discursively analyzing existing data from multiple sources, the results obtained in this chapter show that the real ‘smartness’ of the smart governance of COVID-19 in Wuhan is the innovative use of technologies to develop different types of governance approaches to control COVID-19 in an effective and targeted way. As the pandemic continues to evolve worldwide, lessons learned from Wuhan, China can be beneficial to other countries in different institutional contexts to build their own, context-specific governance for controlling the pandemic

Introduction

This book is a selection of the best papers presented at the CUPUM conference at Aalto University, Helsinki, Finland in June 2021. CUPUM stands for Computational Urban Planning and Urban Management and is a once every two years conference, held somewhere in the world. This chapter is the introductory chapter to this book. It introduces the title and central theme of the book: ‘Urban Informatics and Future Cities’. Therein, three cross cutting themes can be identified: big data, disasters and resiliance, and walkability and tourism. Besides, the chapter provides an overview of the content of the volume by presenting briefly each of its consituting chapters, their titles and authors and their main content. In total 30 chapters have been included in this volume