Based on the analysis of the existing land use change simulation model, combined with macroland use change driving factors and microlocal land use competition, and through the application of Python language integrated technical approaches such as CA, GIS, AHP, and Markov, a multitarget land use change simulation model based on cellular automata(CA) is established. This model was applied to conduct scenario simulation of land use/cover change of the Jinzhou New District, based on 1:10000 map scale land use, planning, topography, statistics, and other data collected in the year of 1988, 2003, and 2012. The simulation results indicate the following: (1) this model can simulate the mutual transformation of multiple land use types in a relatively satisfactory way; it takes land use system as a whole and simultaneously takes the land use demand in the macrolevel and the land use suitability in the local scale into account; and (2) the simulation accuracy of the model reaches 72%, presenting higher creditability. The model is capable of providing auxiliary decision-making support for coastal regions with the analysis of the land use change driving mechanism, prediction of land use change tendencies, and establishment of land resource sustainable utilization policies.
With the ultrahigh-speed, large-scale development of tourism and the increasing frequency, intensity, and scope of extreme natural hazards in the context of climate warming, tourism has entered a high-risk era. Based on the central urban area within the outer ring of Shanghai as the research area and the tourism attraction as the research object, this paper takes the flood scenario simulation combined with GIS network analysis to evaluate the spatial accessibility of the emergency response of urban key public service departments (120) under current and future river flood scenarios in different return periods. The results of the study show that, (1) under the current and future flood scenarios, the submergence range is mainly distributed within 2 ∼ 3 km along the banks of the Huangpu River, and it tends to increase from north to south; (2) there are 6, 9, and 21 tourism attractions in the emergency blind area under the once-in-a-century floods in 2010, 2030, and 2050 and 98, 105, and 112 tourism attractions in the emergency blind area under the once-in-a-millennium floods in 2010, 2030, and 2050, respectively; (3) in the flood scene, local road traffic in the inundation area is interrupted by water, and 120 first aid cannot get or be delayed to some tourist attraction (blind area); and (4) in 2030, under the normal and flooding scenarios, 120 first aid in the downtown area of Shanghai has the fastest route to tourism attractions according to the speed of S1, S2, S3, and S4. The flooding intensity (range and water depth), road traffic conditions (vehicle flow speed), and the number and location of key public service departments jointly determine the service scope and response time of medical emergency in urban floods. Since the flood control area of the central city in Shanghai is mainly distributed in the 2 ∼ 3 km area on both banks of the Huangpu River, the impact of flood on the emergency medical service in the entire central city is limited, mainly in some hospitals in the riverside area, where 120 emergency vehicles are unable or delayed to reach some tourism attractions. The research indicates that the quantitative assessment method of spatial accessibility of the emergency response under flood scenario simulation has important scientific value and practical significance, which can provide decision-making basis for emergency management of tourism in China’s urban flood disaster.
Abstract: Eliminating poverty and upgrading the industrial structure are major challenges faced by contiguous poverty-stricken areas in the three-year campaign against poverty. Since the national strategy of targeted poverty alleviation was put forward, the tourism industry has become one of the crucial avenues through which residents increase their income, optimize the industrial structure, promote economic development, and escape the poverty trap. It is therefore urgent to study the coupling coordination relationship between industrial structure transformation and upgrade and tourism poverty alleviation efficiency. Taking the 42 national poverty-stricken counties in the Wuling Mountain Area as examples, the SBM model and improved entropy method are applied to measure the tourism poverty alleviation efficiency and industrial structure transformation and upgrading index, respectively. The coupling coordination model is then employed to describe the spatio-temporal evolution characteristics of the coupling coordination relationship between industrial structure transformation and upgrade and tourism poverty alleviation efficiency in the Wuling Mountain Area. The results are as follows. (1) The industrial structure transformation and upgrading index of the study area as a whole and each sub-area shows irregular changes, and the future development trend is not obvious. Tourism poverty alleviation efficiency declined slightly at the end of the sample period in Hunan and Guizhou subareas, while Hubei and Chongqing subareas showed a significant upward trend. (2) The uncoupled and uncoordinated county units of industrial structure transformation and upgrade and tourism poverty alleviation efficiency are concentrated in the central part of Wuling Mountain Area, and the number of units decreased annually. The number of counties that achieved coupling and coordination increased significantly and presented an agglomeration trend to the edge zone. (3) The transition from uncoupling disorder (type 1) to coupling coordination (type 2) is the core transformation path, which leads to the fact that the number of type 2 regions increased significantly, and gradually formed a band distribution at the edges of the study area. Finally, based on the above research results, it is suggested that the poverty-stricken areas should actively strengthen the integrated development of tourism industry and other industries, and give full play to the two-way radiation effect of industrial structure transformation and upgrade and tourism poverty alleviation efficiency. This would reconstruct and optimize the coupling path and spatial distribution pattern of the two, which enables the coordinated development of industrial structure changes and poverty alleviation through tourism. In turn, this realizes the optimization and adjustment of the industrial structure in poor areas and allows for smooth poverty alleviation.
Ecological risk assessment is an important part of the sustainable development of World Heritage. The Ming Great Wall Heritage (MGWH) plays an important role in World Heritage conservation as a representative of large linear heritage, yet its ecological risks have not received much attention. This study assessed the ecological risk of MGWH based on simultaneous consideration of spatial heterogeneity and autocorrelation of geographic factors, and four protection zones were further identified from the perspective of preservation status and risk by using GeoDetector, principal component analysis and bivariate autocorrelation. The results showed that there were statistically significant differences in the preservation status of MGWH at different elevations. Based on this assessed ecological risk, it was found that 63.49% of MGWH grids were in the low to medium risk, while the highest risk areas (16.61%) were mainly concentrated in lower (200–500 m) and medium (500–1000 m) elevation. As elevation increased, the dominant factor of ecological risk shifted from human factors to natural factors and the main ecological risk showed a trend of increasing and then decreasing with increasing elevation. In addition, four types of risk protection zones (i.e., Protection—Restricted, Restoration—Moderate exploited, Restoration—Restricted and Protection—Moderate exploited) and policy suggestions were identified in this study from the perspectives of conservation, restoration and development, respectively. Future ecological protection of the MGWH should be based on the principle of “cultural heritage protection first”, with restricted development and use (e.g., tourism and education) and enhanced ecological restoration and environmental management of the surrounding area. This study provides references for the risk assessment of the cultural heritage at a large spatial scale, which is conducive to the maintenance and improvement of heritage value.
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