The quality and scale of urbanization development are the two main aspects in China’s current urbanization process. By measuring and analyzing the level differences in these two aspects, the healthy development of China’s urbanization and urban–rural integration will be promoted. Based on the quality of urbanization and the scale of urbanization, this paper constructs an evaluation index system for urbanization coordination level. On this basis, this paper analyzes the spatial correlation, spatial difference, and spatial pattern evolution characteristics of urbanization coordination level in 286 sample cities nationwide from 2005 to 2015. Then, by introducing the spatial econometric regression model, this paper discusses the driving mechanism of the spatial and temporal evolution of urbanization coordination level. The results show that: (1) The level of coordination between urbanization quality and urbanization scale shows a strong spatial correlation in space, which is consistent with the actual development status; (2) the level of urbanization coordination shows a trend of evolution from northeast to southwest in the evolution of spatial pattern, but the extent of change is small; and (3) the spatial and temporal pattern of urbanization coordination level is affected by different driving forces, of which internal source is the primary impact factor, followed by administrative level and investment level. In addition, the level of urbanization coordination has a positive spillover effect on the level of urbanization coordination in adjacent areas.

With advancements in urbanization, natural lands are constantly being encroached upon by artificial impervious surfaces, leading to serious ecosystem damage. Calls for Green Infrastructure to address urban environmental issues and resource reallocation are growing. How to optimize Green Infrastructure networks are becoming increasingly important under rapid urbanization. In this study, we used the main city zone in Hangzhou as the study area, and we extracted 2000, 2010 and 2020 land-use data. We used morphological spatial pattern analysis to identify Green Infrastructure landscape types and further extract Green Infrastructure elements. We identified the spatial priority of Green Infrastructure network elements through landscape connectivity evaluation according to ecological importance and development vulnerability. After the construction of a Green Infrastructure network, we analyzed its spatio-temporal characteristics to determine the Green Infrastructure network’s spatial priority. Through spatial prioritization, the gradual construction and optimization of Green Infrastructure networks will help to improve urban green spaces in stages. Smartly coordinating urban growth and ecological protection based on Green Infrastructure spatial prioritization may help improve urban living environments and enhance sustainable urban development capabilities. In conclusion, sources dominate corridors and codes are changing. If sources are fragmented, the integration degree decreases and the first-level source advantage is weakened. The corridor morphology continuously develops, and the corridor structure stabilizes. Second-level corridors gradually replace third-level corridors to guide Green Infrastructure network structure development. Codes present a scatter distribution and tend to average, closely following corridor change.

The urban thermal environment has become a challenging issue. Streets, as an essential public space in cities, can be laid out in such a way to effectively alleviate a problematic urban thermal environment. In this study, we calculated the layout characteristics of various types of streets in the study area based on network big data combined with field research. We used ENVI-met thermal environment numerical simulation technology to simulate the thermal environment, with a multiple linear regression model to explore the internal relationship between the street-level thermal environment of each land use type and its layout factors. The results indicate that streets in the study area are primarily oriented north–south and east–west, with distinct layout differences among various street types. Additionally, the daily variation trend of thermal comfort PMV of all street types is similar, though north–south streets show a larger daily variation than east–west streets. Lastly, the optimal thermal environment layout differs for each type of street; the relationship between street form and thermal comfort PMV also varies across different street types. This study provides scientific evidence to better understand the relationship between a street’s layout and its thermal environment, offering a theoretical basis for street layout planning aimed at mitigating the urban thermal environment.

The accurate quantification of biomass helps to understand forest productivity and carbon cycling dynamics. Research on uncertainty during pretreatment is still lacking despite it being one of the major sources of uncertainty and an essential step in biomass estimation. In this study, we investigated pretreatment uncertainty and conducted a comparative study on the uncertainty of three optical imagery preprocessing stages (radiometric calibration, atmospheric and terrain correction) in biomass estimation. A combination of statistical models (random forest) and multisource data (Landsat enhanced thematic mapper plus (ETM+), Landsat operational land imager (OLI), national forest inventory (NFI)) was used to estimate forest biomass. Particularly, mean absolute error (MAE) and relative error (RE) were used to assess and quantify the uncertainty of each pretreatment, while the coefficient of determination (R²) was employed to evaluate the accuracy of the model. The results obtained show that random forest (RF) and 10-fold cross validation algorithms provided reliable accuracy for biomass estimation to better understand the uncertainty in pretreatments. In this study, there was a considerable uncertainty in biomass estimation using original OLI and ETM+ images from. Uncertainty was lower after data processing, emphasizing the importance of pretreatments for improving accuracy in biomass estimation. Further, the effects of three pretreatments on uncertainty of biomass estimation were objectively quantified. In this study (results of test sample), a 33.70% uncertainty was found in biomass estimation using original images from the OLI, and a 34.28% uncertainty in ETM+. Radiometric calibration slightly increased the uncertainty of biomass estimation (OLI increased by 1.38%, ETM+ increased by 2.08%). Moreover, atmospheric correction (5.56% for OLI, 4.41% for ETM+) and terrain correction (1.00% for OLI, 1.67% for ETM+) significantly reduced uncertainty for OLI and ETM+, respectively. This is an important development in the field of improving the accuracy of biomass estimation by remote sensing. Notably, the three pretreatments presented the same trend in uncertainty during biomass estimation using OLI and ETM+. This may exhibit the same effects in other optical images. This article aims to quantify uncertainty in pretreatment and to analyze the resultant effects to provide a theoretical basis for improving the accuracy of biomass estimation.

Coordinating the interrelationships among economic growth, land resource utilization, and carbon emissions is critical for promoting high-quality economic growth and achieving sustainable urban progress. According to the gravity model and the Tapio decoupling model, this study examined the decoupling relationships of economic growth with land expansion and carbon emissions in Zhejiang Province during the period of 2002–2017. We found that (1) The economic gravity center and the built-up area gravity center generally shifted towards the northwest; however, the carbon emission gravity center initially shifted towards the northwest and then towards the southwest. The spatial coupling between the economic gravity center and the built-up area gravity center exhibited a tendency of ‘first weakening, then strengthening, and last weakening’, whereas the spatial coupling between the economic gravity center and the carbon emission gravity center displayed a tendency of ‘first strengthening and then weakening’. (2) The decoupling of economic growth and land expansion is weak at every stage with effective controls on land expansion. However, in recent years, the phenomenon of ‘expansive negative decoupling’ has become prevalent in counties and cities surrounding the central city. The decoupling of economic growth and carbon emissions steadily increased at each stage, first ‘expansive coupling and expansive negative decoupling’, then ‘weak decoupling’, and finally ‘strong decoupling’. The urban low-carbon transformation effect is remarkable. (3) Zhejiang Province should prioritize addressing the regional imbalance and state instability in the decoupling relationships. It is crucial to comprehensively consider the natural resource endowment, macro-policy factors, and urban development orientation of counties and cities while implementing differentiated planning and control strategies, which will promote regional coordination and comprehensive, high-quality development in all areas.