Scenario simulation of land use and land cover change in mining area

Landslide dynamic susceptibility mapping in urban expansion area considering spatiotemporal land use and land cover change

Landslides pose a noteworthy threat in urban settlements globally, especially in areas experiencing extreme climate and rapid engineering. However, researches focusing on the long-term uninterrupted land use and land cover change (LULCC) impacted on landslide susceptibility mapping (LSM) in rapid urban expansion areas remains limited, let alone different temporal scenarios adjacency thresholds. This work aims to refine the temporal LSM considering spatiotemporal land use and land cover (LULC) and to provide decision makers with governing factors in landslides control during urbanization in mountainous areas. Herein, annual LULC data and landslide inventory spanning from 1992 to 2022 were utilized to map dynamic landslide susceptibility in Wanzhou District of the Three Gorges Reservoir Area, China. Initially, the landslide-related factors were filtered as input features of random forest (RF) model before diagnosis via multicollinearity test and Pearson Correlation Coefficient (PCC). The advanced patch-generating land use simulation (PLUS) model was then invited to fuel temporal susceptibility prediction powered by LULCC projections. Finally, the performance of various scenarios was evaluated using Receiver Characteristic Curve (ROC) curves and Shapley Additive exPlanation (SHAP) technique, with discussions on LULCC temporal adjacency thresholds and mutual feedback mechanism between territorial exploitation and landslide occurrences. The results indicate that the precision of LSM is positively correlated with the time horizon, acted by incorporating the latest LULC and LULCC achieving an area under the curve (AUC) of 0.920. The transition of land from forest to cropland and impervious areas should be avoided to minimize the increase in landslide susceptibility. Moreover, a one-year adjacency threshold of LULCC is recommended for optimal model accuracy in future LSM. This dynamic LSM framework can serve as a reference for decision makers in future landslide susceptibility mitigation and land resources utilization in rapid urban expansion areas worldwide.

Geochemical characteristics and migration patterns of rare earth elements in coal mining subsidence lakes under the influence of multiple factors

Mining activities cause surface subsidence and the formation of subsidence lakes, which dynamically change with the continuous coal mining activities. Under the combined influence of various human activities such as agriculture, aquaculture, and floating photovoltaic (FPV), the lake environment undergoes continuous changes, thereby altering the geochemical characteristics of rare earth elements (REEs) in the sediment. This study focused on the subsidence lakes in the Huainan coalfield in eastern China to examine the REEs content in the sediment, elucidated the temporal variations and geochemical characteristics of REEs distribution, explored the main controlling factors of REEs in the sediment, and revealed the migration and transformation behavior of REEs during dynamic subsidence processes. The study revealed that the migration pattern of REEs in the sediment was closely related to the duration of subsidence. The average content of REEs in lake sediments with subsidence duration <5 years increased from 219 μg·g-1 to 248 μg·g-1 compared to the soil, showing an enrichment model primarily driven by rainwater runoff, groundwater input retention, and mineral dissolution. With further subsidence, the processes of reduction dissolution of Fe-Mn oxides/hydroxides, organic colloid adsorption, and hydraulic disturbance gradually replaced the aforementioned enrichment behavior as the main migration pathways, resulting in a decrease in the average REEs content in the sediment to 179 μg·g-1 for subsidence durations exceeding 10 years. There was no strong correlation between REEs fractionation and subsidence duration. Artificial activities, such as FPV, are important factors causing Cerium and Erbium anomalies in some subsidence lake sediments. This study was not only of significant importance for understanding the migration, distribution, and environmental behavior of pollutants in aquatic environments under the interference of human activities but also provided a solid theoretical foundation for the future management of coal mining subsidence lakes.

Multitemporal modeling and simulation of the complex dynamics in urban wetlands: the case of Bogota, Colombia

Urban wetlands are essential to the longstanding health and well-being of cities. Acknowledged as rich in biodiversity and highly productive ecosystems, they provide ecosystem services represented in aspects such as air purification, urban climate regulation, physical and mental health, recreation, and contemplation, among a wide variety of other goods and services on which the quality of life of the inhabitants of large cities such as Bogota depends largely. We used cellular automata to model and simulate urban wetland changes in Bogota, Colombia. The study applied the coupled Markov-Future Land Use Simulation (FLUS) model to simulate and analyze land use/land cover (LULC) change over 20 years. First, we used an orthomosaic (1998) and two WorldView-2 satellite images (2004 and 2010), to detect land cover changes. Then, using the artificial neural network FLUS module, we calculated the relationships between land classes and associated drivers and estimated the probability of occurrence of each land class. Finally, we applied Intensity Analysis to examine the observed and projected LULC change (1998-2034). Results indicate that gains in areas of crops and pastures are at the expense of wetlands. In addition, simulation outputs show that wetlands will likely represent less than 2% of the total study area in 2034, representing a 14% decrease in 24 years. The importance of this project lies in its potential contribution to the decision-making process within the city and as an instrument of natural resource management. Additionally, the results of this study could contribute to the United Nations Sustainable Development Goal 6, "Clean water and sanitation," and climate change mitigation.

The Evolution of Landscape Patterns and Its Ecological Effects of Open-Pit Mining: A Case Study in the Heidaigou Mining Area, China

This paper investigates the impact of land use/cover type changes in the Haideigou open-pit coal mine on the evolution of the landscape patterns and ecological and environmental quality in the mine area, based on medium- and high-resolution remote sensing images in 2006, 2011, 2016, and 2021 using ArcGIS 10.5, Fragstats 4.2, and the Google Earth Engine platform. The results show that: (1) From 2006 to 2021, the area of cropland and waste dumps in the Heidaigou mining area changed significantly, the land use shifted in a single direction, and the overall land use change was unbalanced. (2) Through the analysis of landscape indicators, it was shown that the diversity of the landscape patches in the study area increased, connectivity decreased, and the patches became more fragmented. (3) Based on the changes in the mean value of the RSEI over the past 15 years, the ecological environment quality of the mining area deteriorated first and then improved. The quality of the ecological environment in the mining area was significantly affected by human activities. This study provides an important basis for achieving the sustainability and stability of ecological environmental development in mining areas.

Spatial Modelling and Prediction with the Spatio-Temporal Matrix: A Study on Predicting Future Settlement Growth

In the past decades, various Earth observation-based time series products have emerged, which have enabled studies and analysis of global change processes. Besides their contribution to understanding past processes, time series datasets hold enormous potential for predictive modeling and thereby meet the demands of decision makers on future scenarios. In order to further exploit these data, a novel pixel-based approach has been introduced, which is the spatio-temporal matrix (STM). The approach integrates the historical characteristics of a specific land cover at a high temporal frequency in order to interpret the spatial and temporal information for the neighborhood of a given target pixel. The provided information can be exploited with common predictive models and algorithms. In this study, this approach was utilized and evaluated for the prediction of future urban/built-settlement growth. Random forest and multi-layer perceptron were employed for the prediction. The tests have been carried out with training strategies based on a one-year and a ten-year time span for the urban agglomerations of Surat (India), Ho-Chi-Minh City (Vietnam), and Abidjan (Ivory Coast). The slope, land use, exclusion, urban, transportation, hillshade (SLEUTH) model was selected as a baseline indicator for the performance evaluation. The statistical results from the receiver operating characteristic curve (ROC) demonstrate a good ability of the STM to facilitate the prediction of future settlement growth and its transferability to different cities, with area under the curve (AUC) values greater than 0.85. Compared with SLEUTH, the STM-based model achieved higher AUC in all of the test cases, while being independent of the additional datasets for the restricted and the preferential development areas.

Scenario-Based Predictions of Urban Dynamics in Île-de-France Region: A New Combinatory Methodologic Approach of Variance Analysis and Frequency Ratio

Modelling land use dynamics is a critical scientific issue. Despite a diversity of models coming from the fields of remote sensing, geography, and economics, including multicriteria decision analysis and machine-learning models, taking into account the external driving factors of urbanization is still a main challenge. This study aims at simulating various land use development scenarios with global and local parameters. Thus, the developed approach is able to estimate and simulate the dynamic evolution of land use classes, the evolution of urban attractivity, both of which depend on several driving factors. The proposed scenarios incorporate anticipated global changes, such as an increase in oil prices and a decrease in wealth, and local spatial changes such as the provision of new rail lines and the development of new activity zones. The results of simulations, for the study area covering a great part of the Île-de-France region, show for the year 2050 an 18% increase in urban areas and a 25% decrease in bare soils, compared to the year 2018. Moreover, the increase of global prices and the reduction of income levels would increase the attractivity of public transport modes and drive urbanization around stations, reduce the accessible distances to public transport systems by 8.5%, reduce the dependency on private vehicles, and increase the concentrated saturation of urban development. These scenarios will serve as a basis for the deployment of nature-based solutions and renewable energy production.

An integrated approach of logistic-MCE-CA-Markov to predict the land use structure and their micro-spatial characteristics analysis in Wuhan metropolitan area, Central China

As human interference with the natural environment accelerates, land use has undergone great changes. However, to realize rational land development in the rural-urban ecotone, the micro-spatial (MS) unit is the best scale for the management and planning of sustainable land use. Taking Wuhan metropolitan area as research area, the integrated logistic-multi-criteria evaluation (MCE)-cellular automata (CA)-Markov model was used to simulate land use pattern for 2025. In addition, the 1 km×1 km, 2 km×2 km, 3 km×3 km, and 4 km×4 km and typical sample belt were built to reveal the spatial microcosmic expression of land use structure. The results showed that the kappa coefficient and figure of merit (FoM) were 88.01% and 26.86%, respectively, indicating the integration model has high prediction accuracy. In 2005-2025, the diversification of land use in the Wuhan metropolitan area will be generally above the medium level, and the types of land combinations will be relatively abundant. As human activities increase, the land use degree will show increases continuously, it will expand outward from Wuhan, and there is a positive correlation between cultivated land-rural residential land and urban land-cultivated land. The spatial distribution of land use structure presents regional scale characteristics, and different regions have micro-spatial scale dependence. The selection of MS scales based on local conditions can be a good way to reflect land use internal structure and provide a better reference for the compilation of regional land use optimization.

Evaluation of Land-Use Changes as a Result of Underground Coal Mining—A Case Study on the Upper Nitra Basin, West Slovakia

Mining activity has one of the most fundamental influences on the landscape (in terms of both aesthetics and use). Its activity and manifestations, even when mining takes place underground, have visual manifestations on the surface. The impact of subsurface mining has a synergistic effect on the elements of the landscape structure. This manifestation is continuous in the context of mining intensity. Using the Earth remote sensing method, we identified several fundamental changes. The most significant of these was the creation of wetlands and the modification of watercourse lines. In the area in which there was no permanent water sources, several water areas with a total area of more than 30 ha were created. We also found that the length of watercourses has halved, the area of grassland has doubled, and urban area has decreased. It was the creation of water areas that supported not only better ecological stability of the landscape, but also the growth of biodiversity. Wetlands can be a dynamic element of future development. Understanding the development of land-cover changes is necessary for the purpose of planning nature and landscape conservation, as well as to identify areas of conflict with economic use.

Simulation and Optimization of Supply and Demand Pattern of Multiobjective Ecosystem Services—A Case Study of the Beijing-Tianjin-Hebei Region

Assessing and predicting the impact of land use/cover changes on ecosystem service supply and demand are crucial to formulating effective sustainable land use policies. In this study, we use the ecosystem service (ES) score matrix, ES supply rate, and ES supply/demand ratio to analyze the supply/demand pattern of ecosystem services based on land use/cover changes in the Beijing-Tianjin-Hebei region from 1990 to 2020. The Conversion of Land Use and Its Effects-Simulation (CLUE-S) model is used to simulate the spatiotemporal patterns of land use change in three scenarios of natural development, ecological priority development, and economic priority development and to predict and simulate the evolution of the ES supply and demand patterns in these different scenarios from 2030 to 2050. It was found that the main land use types are farmland and woodland in the Beijing-Tianjin-Hebei region, accounting for more than 67% from 1990 to 2020, the proportion of farmland decreased from 51.79% to 46.11%, and the proportion of woodland increased from 20.99% to 21.34%; the land use transformation was mainly from farmland to construction land from 1990 to 2020. The supply of ES in the Beijing-Tianjin-Hebei region was at a high level, the supply rate of ES increased from 0.78 to 0.81, the supply/demand ratio of ES decreased from 0.33 to 0.16 from 1990 to 2020, and the supply and demand of ES in the northern and western parts of the Beijing-Tianjin-Hebei region were in surplus. In the natural development scenario, the ES in the Beijing-Tianjin-Hebei region would remain in a high supply state from 2030 to 2050, but the pressure would be greater than before. The deficit, centered on urban construction, would widen, and the ecological situation would deteriorate. In the ecological priority development scenario, the pressure on the ES would be relieved, and the rate of deficit expansion would be reduced. In the economic development priority scenario, the pressure on the ES would increase sharply, and the deficit area would expand rapidly.