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Mountainous areas account for approximately 69% of the land area in China, and these areas are prone to poverty. Thus, analyzing the land use characteristics and conducting simulations and prediction studies of poor cities in mountainous areas are important research topics. The land use change processes and characteristics in Chengde County, Hebei...
Citations
... Lake [9]. The LERI method used the CLUE-S model to study the land type changes' future characteristics and explored the LERI response to land use changes [10]. Jin assessed the regional ecological risk from the spatial pattern perspective, based on the land use changes in Delingha City [11]. ...
To solve grid-scale problems and evaluation indicator selection in landscape ecological risk index (LERI) evaluation, this paper takes the Bailong River Basin in Gansu Province (BLRB) as an example. The LERI evaluation formulae and optimal grid scales were determined by screening landscape indices and area changes in the LERI at different grid scales. The evaluation indices were finally obtained according to the landscape characteristics and the correlation analysis of the landscape index value. Through the statistical analysis of the area of the LERI at the grid scale of 1–6 km, the optimal grid scale was determined to be 5 km. There was little change in land use patterns, with the most significant increases in artificial surfaces at 3.29% and 3.58%, respectively. Cultivated land was the only land use type to decrease by 184.3 km2. The LERI drops with the reduced cultivated land area; the landscape ecological medium risk area and cultivated land keep the same spatial distribution. Due to the limitation of the topography, cultivated land is generally distributed below 2500 m altitude, so 2500 m becomes the turning point in the spatial distribution of the LERI. The medium risk below 2500 m dominates the LERI type. Reduced cultivated land was the leading cause of reduced ecological risk according to an overlay analysis. The study of LERI evaluations provides a theoretical basis for sustainable and ecological environmental protection in the BLRB.
... Land not only provides an important basis of human survival but is also an essential resource for human development [1]. Land use and land cover are two different but closely related concepts. ...
The increasing frequency of human activities has accelerated changes in land use types and consequently affected the atmospheric environment. In this manuscript, we analyze the relationships between the particulate matter concentration and land use changes in the Beijing–Tianjin–Hebei (BTH) region, China, from 2015 to 2018. The experimental results indicate that (1) an improved sine function model can suitably fit the periodic changes in the particulate matter concentration, with the average R2 value increasing to 0.65 from the traditional model value of 0.49, while each model coefficient effectively estimates the change characteristics of each stage. (2) Among all land use types, the particulate matter concentrations in construction land and farmland are high, with a large annual difference between high and low values. The concentration decreases slowly in spring and summer but increases rapidly in autumn and winter. The concentrations in forestland and grassland are the lowest; the difference between high and low values is small for these land use types, and the concentration fluctuation pattern is relatively uniform. Natural sources greatly influence the concentration fluctuations, among which frequent dusty weather conditions in spring impose a greater influence on forestland and grassland than on the other land use types. (3) The landscape pattern of land use exerts a significant influence on the particulate matter concentration. Generally, the lower the aggregation degree of patches is, the higher the fragmentation degree is, the more complex the shape is, the higher the landscape abundance is, and the lower the particulate matter concentration is. The higher the construction land concentration is, the more easily emission sources can be aggregated to increase the particulate matter concentration. However, when forestland areas are suitably connected, this land use type can play a notable role in inhibiting particulate matter concentration aggravation. This conclusion is of great relevance to urban land use planning and sustainable development.
... By combining qualitative analysis with quantitative calculation, this paper makes a comprehensive analysis of various factors of land use change from the perspective of the natural environment, humanities and economy. Principal component analysis (PCA) method is a statistical analysis method used to extract common factors from many variables (Zhai et al. 2018). Variables of the same nature can be grouped into a factor, which then enables reductions in the number of variables, the ability to identify hidden representative factors in many variables, as well as the ability to test the relationship between variables to obtain the important indicators of the different factors. ...
Constant alterations of landscape pattern, triggered by specific natural and human driving forces, have aroused some heated discussions in the field of regional environmental change research especially in mountainous settlements. To explore changes in land use from the microcosmic scale of mountainous settlements enables a clearer, more direct reflection on the relationship between humans and the land they occupy. Firstly, this paper analyzes the land use change of the mountainous settlements in the upper reaches of the Minjiang River from four aspects: land use change amplitude, single land use dynamics, information entropy and land use transfer matrix. Then, we analyzed the variation characteristic of landscape pattern at patches class level and landscape level by choosing the landscape pattern index as analytical indicators. Finally, we used principal component analysis and multi-regression to derive the relation between land use change and influencing factors. The results show that: (1) The study area was dominated by woodland, grassland and dry land. During the studied period of time (1995–2025), the disorder of the land use system increased and the area tended to develop unevenly. (2) The spatial distribution of landscape elements is unbalanced, the proportion of dominant patch type is decreased, and others increased, patch became ever more diffuse. (3) The main natural influencing forces of land use in mountainous settlements are the sunshine hours, relative humidity and evaporation. And the GDP and per capita GDP are the main factors in economic development. The rapid growth of population, the high-speed development of science and technology and the constant adjustment of national policies are also the main factors of land use change. Understanding the characteristics of land use change and influencing factors in mountainous settlements will help the management authority effectively optimize land resources allocation, increase land utilizes efficiency, and protect the ecological environment.
... Therefore, scenario simulation is gradually changing from using single model to multiple integrated models [14][15][16][17][18][19][20][21][22][23][24][25][26] . Previous studies have suggested that logistic regression model can better reveal the main driving forces and interaction mechanisms of LULC change 11,[26][27][28][29] . Binary logistic regression model (BLRM) is good for binary dependent variables, while multinomial logistic regression model is more suitable for multivariate dependent variables. ...
... www.nature.com/scientificreports/ regression model is often used for driving factors analysis of LULC change in ecologically fragile areas such as reservoir area 11,26 , mountainous area 29 , etc. And it is also mainly used for driving factors analysis of urban land use change 27,28 . ...
... Considering the accessibility, usability of the data and the actual conditions in the study area, seven driving factors were selected based on the land use map of Weishan County in 2005 and the DEM data 5,10,11,13,26,[28][29][30] . The driving factors included: (1) terrain factors, including elevation and slope factors; (2) five accessibility factors, including the nearest distance between each grid pixel and the main roads, the major rivers, the residential area, the major mines, and the ditches. ...
In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and the related 7 driving factors at a resolution of 60 m. Using the CLUE-S model, combined with Markov model, the simulation of LULC under three scenarios—namely, natural development scenario, ecological protection scenario and farmland protection scenario—were explored. Firstly, using LULC map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual LULC map in 2016 with the simulated map in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the spatial distribution pattern of LULC in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for LULC changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.
... Scholars at home and abroad mostly use models to study future land use structure and spatial distribution. Trend extrapolation method, Markov model and system dynamics model are commonly used models for land use structure prediction (Mishra and Rai 2016;Naboureh et al. 2017;Wu et al. 2017;Zhai et al. 2018;Zhao et al. 2016). Trend extrapolation method is a kind of extrapolation prediction that realized by finding a suitable function to reflect the trend of change according to the rising or falling trend of the predicted object with no situation of sudden change (Huang and Zhao 2011). ...
... According to the actual situation of the research area and the comprehensiveness, accuracy, availability and quantifiable description of driving factors, this paper selected 10 driving factors from the aspects of natural conditions and social economy: topographic factors (slope and altitude); distance factors (the closest distances from main road, town, village and water area to the abandoned mine land), the main roads includes railways, national roads, provincial roads, county roads and township roads, and the distance factor adopts Euclidean distance; socio-economic factors (urbanization level, population density and regional per capita GDP calculated by dividing township administrative regions into units); soil factor (soil fertility grade). ROC curve is usually used to evaluate and test the effect of driving force explanatory ability Mohammady et al. 2018;Zhai et al. 2018). The larger the ROC value is, the better the regression analysis result is and the higher the accuracy is. ...
The mountainous abandoned mine land is often distributed in the form of fragmented patches. Therefore, it can greatly promote the reuse value of abandoned mine land and relieve the pressure of land demand to realize the rational reuse of abandoned mine land based on the future land use structure and spatial layout of mountainous area. In this paper, optimization of the spatial structure of mountainous abandoned mine land reuse is realized through the system dynamics model and CLUE-S model. Mentougou district, Beijing, China is selected as the research area. System dynamics model with feedback functions is constructed to simulate land use structure from 2011 to 2025, which is taken as the quantitative constraint on spatial structure optimization. CLUE-S model with neighborhood analysis function is applied to simulate future land use spatial structure. The simulation result layer is superimposed with the abandoned mine land distribution layer and the optimized spatial structure of abandoned mine land reuse then is determined, checked by reuse suitability evaluation. The result shows that abandoned mine land can be fully optimized as other land use types according to demand, and the reuse directions are water conservancy facilities land, urban land, rural residential land, tourism land, garden land, woodland and grassland. The trend of abandoned mine land reuse tend to be consistent with land use types of neighboring patches. This study can provide theoretical reference for the practices of mountainous abandoned mine land reuse.
This literature review focuses on land quality evaluation (LQE) and its effects on sustainable development through quantitative analysis and value-added information. In contrast to the traditional perspective, a structured review based on bibliometric indicators and social network analysis allows identifying hidden evidence for answering the following research questions: (i) What: What is the application of LQE? (ii) Which: Which sustainable development goals does the application contribute to? (iii) Why and how: What are the main applications and methods of each topic? (iv) Where: Where is the hotspot of the problem? What is the future research orientation of the topic? (v) How and when: How has the topic grown since 2000? Data investigation explores 4029 articles in 2000–2019 from four publishers. With the support of VOSviewer software, six clusters corresponding to six main applications of LQE are classified. Overlapping keywords in several clusters are resolved by the binary term frequency counter for the cluster preference determination. After conducting the data verification and editing process, a structured review is performed again with systematic research questions. This research offers a synthesis of traditional and novel quantitative analysis for literature review, which is comprehensive, accurate, and reliable.
Air is an indispensable natural resource for all human activities. As an essential trace gas in the atmosphere, high NO2 and SO2 will affect the natural environment and human health. Based on the Ozone Monitoring Instrument's data, the temporal and spatial distribution of NO2 and SO2 concentrations in the Beijing-Tianjin-Hebei region from 2005 to 2017 was analyzed. Results showed that, on the annual scale, the concentration increased at first and then decreased. On the monthly scale, both of the two had regular fluctuations with annual cycles. The spatial distribution of pollutants was high in the southeast and low in the northwest. By analyzing the influencing factors of pollutants, it was found that environmental conditions are more the
periodic fluctuations and spatial distribution differences of image density, and policy-oriented conditions are the main reason for the concentration trend decline in the later period.
