Effortless Economic Elevation: Canadian Style – Evidence from combining data from multiple sources on the relationship between specific anthropogenic urban environments and urban viability in Shenzhen
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Effortless Economic Elevation: Canadian Style
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Degree of coordination between environmental quality and urban development in Chengdu-Chongqing Economic Circle based on Google Earth Engine
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Jiajie Zhang Jiajie Zhang Scilit Preprints.org Google Scholar View Publications and Tinggang Zhou Tinggang Zhou Scilit Preprints.org Google Scholar View Publications *
Received: February 2, 2023 / Revised: February 23, 2023 / Accepted: February 26, 2023 / Published: March 1, 2023
Rapid urbanization often puts enormous pressure on the resources on which the ecological environment depends. It is necessary to quickly assess the interaction and interaction between regional urbanization and the ecological environment. This paper uses the Google Earth Engine (GEE) platform, combines MODIS and remote sensing night illumination datasets, and calculates the Remote Sensing Environmental Index (RSEI) and Communication Coordination Degree (CCD) to measure communication coordination and analyze spatio-temporal changes. in the Chengdu-Chongqing Economic Circle (CCEC) for 2010, 2015 and 2020. Our results demonstrate four main findings. First, the CCD varies spatially; it peaks in the plains of Chengdu and West Chongqing, decreases on the mountains, and the lowest degree of coupling in the central, southern, and northern borders of the CCEC. In addition, it demonstrated a tendency to first remain constant and then increase, mainly in response to political decisions. Second, the changes between different levels of connectivity were almost stable and occurred mainly between adjacent levels. Third, the level of urban connectivity spreads from the center of Chengdu to Chongqing and has a general tendency to increase over time. Fourth, in the last year, the types of connections show a distribution pattern of a developmental axis connected to two peaks. In particular, the backward types of houses in the environmental system in Chengdu, Chongqing and surrounding areas as well as the rest are mainly backward types of houses in the economic system. High internal connection types are also mostly found at high and low connection levels. In this context, constructive proposals were presented to optimize the development of the studied area.
Environmental index based on remote sensing; nighttime remote sensing data; degree of clutch coordination; Google Earth engine; Chengdu-Chongqing Economic Circle
Assessing Demographic And Economic Vulnerabilities To Sea Level Rise In Bangladesh Via A Nighttime Light Based Cellular Automata Model
Urban expansion is the most important human social change in the world [1]. Today, the main pattern of urbanization has shifted from the expansion of individual cities to the overall construction of urban agglomerations [2]. However, urbanized areas and living beings face great environmental and ecological pressure due to the release of polluted waste from intensive human activities [3]. In fact, this is a problem not only for developing countries, but also for developing countries. To address these global issues, there are many valuable works on the study and evaluation of urban sustainability [4]. Moreno et al. believes that “city 15 minutes” is an effective and advanced approach to planning in the context of the global crisis [5]. It looks like a compact city where densification strategies are implemented in the project. With the gradual maturation of Internet of Things (IoT) technology, Beli et al. argued that smart and sustainable cities based on Io can improve city management and government decisions [6]. Communication coordination is one of the most important aspects of sustainable development, generally exploring the interconnection and dynamic development of relationships between the social economy, the ecological environment and urban land use. Tso et al. presented a cloud model to build an indicator system and evaluate, both quantitatively and qualitatively, the construction status of ecological civilization in China [7]. Ariken et al. created a comprehensive basis for the assessment of CCD on the Silk Road Economic Belt from demographic, economic, social and spatial aspects [8]. Among the studies in this field, the degree of communication coordination model can intuitively explain the degree of interaction between two or more systems [9] and is widely used in research on modern urbanization, precision agriculture and economic diversification [10, 11, 12] . However, in previous research on the development of environmental coordination, few studies have applied remote sensing technology, and most existing studies evaluate urban connectivity only using statistical data from the government or relevant agencies. To make the results more reliable, collecting and processing data requires a lot of time and effort. However, due to the difference in knowledge and objectives, the existing methods are highly dependent on subjective factors. The achievements of different thematic structures also lack comparison and generality. Fortunately, the advent of remote sensing technology has dramatically improved the cost-benefit balance, providing powerful support to experts in related disciplines.
In recent years, remote sensing technology has developed significantly. The advantages of its wide spatial coverage, fast measurement time and rich information that can be recorded means that it has made the research of urban remote sensing environment more practical. Compared with the previous single indicators such as NDVI, LAI, EVI, etc., the current indicators are more comprehensive, complex and systematized. Firozjaei et al. proposed a new land surface ecological state composition index (LSESCI) to distinguish the status of different types of land use and land cover [13]. Wu et al. proposed a new Remote Sensing Environmental Vulnerability Index (RSEVI) to assess environmental vulnerability [14]. Xu Hanqiu [15] proposed the Remote Sensing Environmental Index (RSEI) model. The model is entirely based on data collected through remote sensing technology, which is easily accessible, objective and reliable. The RSEI and its refinements have been widely used in contemporary environmental quality assessment and analysis: Tang et al. assessed environmental degradation in typical mountainous regions based on RSEI and found that RSEI can better represent environmental quality than landscape indicators [ 16 ]. Yuan et al. studied the detection of spatio-temporal changes by RSEI in Lake Donting Basin and analyzed the relationship between RSEI and potential influencing factors [17]. Zheng et al. given that the discrete standard deviation of the RSEI partially solves the problem of instability in time series and interregional measurements [18].
In addition, studies have confirmed that nighttime lighting data is highly correlated with urbanization, such as Andreano et al., who estimated the relationship between lighting and poverty indicators. The results showed that the use of light helps in measuring and mapping poverty [19]. Melander et al. studied the relationship between night light and economic activity, collecting samples from residential and industrial facilities in Sweden. They found that night light may be the best proxy for urbanization [20]. Wang et al. quantified the level of urbanization on the Tibetan Plateau using nighttime light data from Luojia 1-01 (LJ1-01). The results showed that Lj1-01 has the potential to effectively estimate the level of urbanization around the world, especially for less developed regions [21]. Therefore, it is possible to use night lighting data to characterize the level of urban development.
In addition, the growth of cloud-based systems such as Google Earth Engine (GEE) provides free access to EO datasets around the world. GEE, like other cloud computing platforms, is very popular because it provides efficient methods of storing, accessing, and analyzing data on high-performance servers. GEE was launched by Google in 2010 and made remote sensing data freely accessible through Python web application programming interfaces (APIs) and a web-based JavaScript interactive development environment (IDE) [ 22 ]. For this, recent studies have applied GHG to various environmental problems, such as erosion monitoring [23], forest fire mapping [24], land cover change [25], etc.
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In 2021, China proposed the CCEC construction guidelines, which emphasized the promotion of quality development, making it an important growth center in China’s southwest region. Therefore, it is necessary to explore the path of evolution to ensure quality development.
In order to inform an ecologically constrained economy and guide agglomeration construction, this paper proposes a framework that makes full use of remote sensing data to assess communication coordination in CCEC.
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