Search

The Jianghan Plain is simultaneously responsible for ecological protection, food security and urbanization, and land use conflicts are prominent. Revealing the driving mechanism of land use/cover change (LUCC) and simulating the land use pattern can help to coordinate the land use conflicts in the future. Utilizing the National Land Survey Data (NLSD) of Jiangling County in Jianghan Plain (2011–2020) and the patch-generating land use simulation (PLUS) model, this paper analyzed the characteristics of land use evolution, applied the random forest classification (RFC) to analyze the driving mechanism, simulated the 2035 land use pattern under three scenarios of natural development, planning guidance and ecological protection through Markov and Cellular Automaton based on multiple random seeds (CARS) models, and proposed several countermeasures. The study found that: 1) From 2011 to 2020, town construction land increased, village construction land, agricultural land and ecological land decreased. 2) The factors driving LUCC were socio-economic factors, spatial factors, and natural factors in descending order. 3) In the three scenarios, the trend of construction land expansion, agricultural land and ecological land encroachment is inevitable by 2035. 4) It is imperative to actively advocate for large-scale mechanization and informatization of agricultural production, encourage the repurposing of idle and inefficiently used construction land, facilitate multi-purpose land utilization, and implement a policy of locally balancing occupation and compensation for cultivated and ecological land. 5) When employing the PLUS model to simulate LUCC, using continuous NLSD yielded more accurate results than remote sensing image interpretation data. This study offers a theoretical basis for the coordinated development of land use in Jianghan Plain, and presents a method to enhance the simulation accuracy of the PLUS model.

Abstract Objective To illustrate the status of all cancer clinical trials and characterize clinical trial enrollment disparities in the most common cancer. Methods Clinical trial data were extracted from ClinicalTrials.gov website. All searched clinical trials were included in the current status analysis of clinical trials on cancer. Among all the clinical trials, only trials addressing single disease sites of breast, prostate, colorectal, or lung (BPCRL) cancer were included in the age disparities analysis. The difference in median age (DMA) between the trial participant median age and the population-based disease-site-specific median age was calculated for each trial. Results A total of 7747 clinical trials were included in the current status analysis of clinical trials on cancer. The number of registered trials had been increasing from 2008 to 2021 (AAPC = 50.60, 95% CI 36.60, 66.00, P

The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan’s new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran’s index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities.