Introduction
Urban and rural planning studies and work are not only important components of China's modernization and sustainable development, but also related to the daily lives of hundreds of millions of urban and rural residents. UPSC has been presenting major problems and difficulties in the planning field, which is not only necessary for promoting the further scientific development of planning work but also one of the basic tasks to be learned.
Last year, at the plenary session of the 2022/2023 China Urban Planning Annual Conference, the list of major problems and difficulties in the planning field in 2023 organized by UPSC was released. It is hoped that this list will provide support for relevant decision-making departments to assess future trends in planning science and to plan and layout research fields in advance. This will guide planning units, research institutions, universities, and planning technology workers to strengthen research on related issues, enhance scientific collaboration, and promote the application of research results to improve the level of urban planning, construction, and governance.
How to summarize and deduce the formation and development laws of the human habitat environment in a systematically and intelligently way?
Problem Type: Cutting-edge Scientific Issues
Recommended by: Zhou Lan, Vice-president of UPSC, Director of Jiangsu Provincial Department of Housing and Urban-Rural Development; Jiangsu Planning and Design Group Co., Ltd.
Authors:
Mei Yaolin, Executive Director of UPSC, General Manager and Senior Engineer of Jiangsu Planning and Design Group Co., Ltd.
Chen Jun, Member of the Planning Informatization Committee of UPSC, Deputy Director of Data Information Center of Jiangsu Planning and Design Group Co., Ltd., Professor-level Senior Engineer.
Xu Yunyi, Engineer at Data Information Center of Jiangsu Planning and Design Group Co., Ltd.
Jiang Jinliang, Senior Engineer at Data Information Center of Jiangsu Planning and Design Group Co., Ltd.
Description
In 1977, the United Nations Human Settlements Program was established. The formation, construction, development, and renewal of human settlements has been an important topic in the academia. In 1993, Wu Liangyong delivered an academic report titled "Today and Tomorrow of China's Architectural Industry: Prospects for Human Settlement Environment," focusing on addressing the primary contradictions in China's urban and rural development, in which formally introduced the concept of "human settlement environment studies" for the first time. At the Human Settlement Environment Research Center's establishment conference in 1995, the study of human settlement environment construction issues was further defined as "human settlement environment science," aiming to "understand and master the objective laws of human settlement occurrence and development, and better construct settlement environments that align with human thoughts."
Over the past forty years, theories in urban and rural planning, geography, sociology, ecology, and other disciplines have attempted to describe the regularities of human settlement formation and development. Advanced technologies such as remote sensing, geographic information systems, and big data have been applied to explore these patterns and deduce future trends. The theoretical and methodological systems of human settlement environment science are continually being refined. Intelligent analysis, induction, and deduction of urban space have become current research hotspots. However, there has yet to be a technology framework that integrates theories of complex mega-systems, forming an intelligent analysis, induction, and deduction framework.
Therefore, it’s urgent for an intelligent and systematic approach to induce the laws of human settlement environment formation and development while utilizing emerging large-scale intelligent models within complex mega-systems to deduce future human settlement environment planning and construction. The construction of Digital China requires the development of a systematic engineering framework. This framework should combine various sources of spatiotemporal big data, deep learning, artificial intelligence, and other digital ways to induce and deduce the laws of human settlement environment formation and development. It should dissociate time and space, forming regular models with Chinese characteristics and promoting their application.
Background
Currently, the concept and theory of "human settlement environment science" have been widely applied in major mega-projects and expanded to integrated research on human settlement environments connected to globalization, urbanization, modernization, and digitization. Internationally, the United Nations awards the "UN Annual Human Settlements Award" each year. In China, the State Council designated the improvement of rural living environments as a key task in the rural revitalization strategy in 2021. Human settlement environment research emphasizes holistic thinking and is based on the study of open complex mega-systems. It should extract frameworks from the urban studies and systems engineering proposed by Mr. Qian Xuesen, draw upon the ideas crystallized by Mr. Wu Liangyong, and integrate the cutting-edge technological methods proposed by experts in smart city construction and urban computational science for systematic and intelligent exploration.
In the context of smart city construction, experts such as Academician Wu Zhiqiang proposed that the key to high-quality development in urban and rural planning and construction in China lies in "urban computing and urban governance through data." While the physical world is fragmented, the spatial aspect of the digital world can unfold along the timeline, allowing for both retrospective induction and deductive inference. The mapping between the physical and digital worlds is highly consistent with the construction of Digital China. By using digital twin technology to map the physical human settlement environment to digital virtual space, and thus support Digital China construction, we need to propose systematic research paths for the formation mechanism, development laws, construction logic, and renewal methods of human settlement environments. Through a combination of qualitative and quantitative methods, and utilizing informatization methods, attempts should be made to propose inducible and deducible regular models.
Currently, the practical application of existing scientific and technological accumulations still faces many challenges in summarizing such laws. For example, the methods of data collection need to be improved, and there is a lack of solutions for how to reconcile structured and unstructured data. The process of law induction lacks advanced algorithms and characteristic frameworks as intermediate carriers. The models generated from laws lack comprehensive deductive frameworks and can only be inferred in limited environments. There are also difficulties in robustness and regularity tests on the results of induction and deduction. Therefore, it’s necessary to utilize a systematic engineering framework combined with digital methods to attempt to induce and deduce the laws of human settlement environment formation and development.
Latest Updates
Research on this scientific problem nowadays mainly faces four major challenges: data collection methods applied to inductive analysis, normalization of data structures, methods for constructing analysis carriers, and mapping methods for digital twin spaces.
Data collection methods applied to inductive analysis include integrated collection of public information, aerial photography, oblique photography, and input from various sensors. While the collection of multi-source spatiotemporal big data is generally convenient, there are still difficulties in obtaining certain data, such as data for fine-grained city modeling and focusing on the interactive effects between individual buildings and the overall city. Currently, the more advanced method involves using laser scanning to generate point cloud data for contours and structures. However, issues such as low scanning efficiency and the need for repeated corrections in the scanning process persist. For data with high precision requirements and significant necessity, there often lacks technics and collection methods.
Normalizing data structures is an exploratory method to address the problem of carrying out intelligent analysis from the source. Currently, the cutting-edge method is the unified framework and collaborative expression method developed by the National Satellite Mapping Application Center. This method constructs an integrated processing technology system for multi-source data through a land big data correlation and aggregation model oriented towards the human-land relationship complex. It also includes corresponding platforms to optimize spatial patterns, thereby meeting the demand for carrying multi-source data and conducting intelligent analysis. However, overall, widely accepted normalization methods and systems are still in the exploratory stage.
Data analysis and induction require carrier intermediaries, with complex network topology methods currently representing the forefront. After scholars optimize these methods in conjunction with the analysis objects, they assess the current and future states of urban and rural complex mega-systems. For instance, utilizing vector autoregression models to conduct complex network analysis of the forms of PM2.5, PM10, SO2, CO, NO2, and O3 pollutants on social networks has explored the dynamic correlations and causes of haze pollution in human settlement environments. Although such results have been fruitful over the years, the achievements made by the optimization schemes mentioned above are based on hierarchical extraction from complex mega-systems and are not universally applicable. They cannot fulfill the function of induction and deduction for the types of multi-factor interventions in complex mega-systems, and their robustness and efficiency need further verification.
Research on digital space mapping methods is currently in the stage of summarizing and promoting existing technological methods, focusing on aspects such as visualization capacity building and intelligent management. For example, analyzing the connotations and four characteristics of the data loop empowerment system in digital twin cities and proposing a construction method for digital twin cities based on stereoscopic perception for visualization and intelligent management. Additionally, regarding how to utilize digital twin technology to optimize digital and smart city construction, the application aspects of existing technologies have been summarized. The above research focuses on the practical application of digital twin technology in smart city construction, lacking exploration of mapping and deduction methods, ultimately leading to the absence of the deduction of human settlement environment laws in digital twin spaces.
Significancy
Studying the regularities of human settlement environment formation and development can greatly accelerate the construction progress of Digital China and smart urban and rural areas. The inductive models derived from these regularities can dissociate time and space in the virtual world, comprehensively retracing the experiential regularities of human settlement environment formation and development. The future human settlement environments deduced by these models can maximize the value of digital twin technology, providing an intuitive understanding of the representation and essence of future human settlement environment spatiotemporal scenarios across multiple contexts. This will enable China to become a benchmark in the field of global human settlement environment construction. The regularities induced by China will form the "Chinese model," which will be widely promoted worldwide. At the same time, research on this issue can foster breakthroughs in a wide range of related technologies and methods, which will have positive implications for overcoming bottlenecks currently faced in various research fields in China. Overall, this scientific problem involves multiple dimensions and levels, and the related research outcomes can serve as important support for various directions in China's "14th Five-Year Plan" construction.
Source: <https://mp.weixin.qq.com/s/n4ASZqm6UvXvFaAxpWdD9w>
Translated by He Huiling
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