Impacts of mining on vegetation phenology and sensitivity assessment of spectral vegetation indices to mining activities in arid/semi-arid areas.

Measuring the impact of mining activities on vegetation phenology and assessing the sensitivity of vegetation indices (VIs) to it are crucial for understanding land degradation in mining areas and enhancing the carbon sink capacity following the ecological restoration of mines. To this end, we have developed a novel technical framework to quantify the impact of mining activities on vegetation, and applied it to the Bainaimiao copper mining area in Inner Mongolia. Phenological indices are extracted based on the VI time series data of Sentinel-2, and changes in phenological differences in various directions are used to quantify the impact of mining activities on vegetation. Finally, indicators such as mean difference, standard deviation, index value distribution interval, and concentration of index value distribution were selected to assess the sensitivity of the Enhanced Vegetation Index (EVI), Green Chlorophyll Index (GCI), Global Environmental Monitoring Index (GEMI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI), Red-Edge Chlorophyll Index (RECI), and Soil-Adjusted Vegetation Index (SAVI) to mining activities. The results of the study show that the impact of mining activities on surrounding vegetation extends to an area three times larger than the actual mining activity area. When compared with the reference and unaffected areas, the affected area experienced a delay of approximately 10 days in seasonal vegetation development. Environmental pollution caused by the tailings pond was identified as the primary factor influencing this delay. Significant variations in the sensitivity of each VI to assess mining activities in arid/semi-arid areas were observed. Notably, GCI, GNDVI and RDVI displayed relatively high sensitivity to discrepancies in the spectral attributes of vegetation within the affected area, while SAVI reflected the overall spectral stability of the vegetation in the affected area. The research findings have the potential to provide valuable technical guidance for holistic environmental management in mining areas and hold great significance in preventing further land degradation and supporting ecological restoration in mining areas.

Study on coupling coordination degree of urbanization and ecological environment in Chengdu-Chongqing economic circle from 2002 to 2018.

Under the western development strategy of China, the urbanization process of Chengdu-Chongqing economic circle (CCEC) develops rapidly, but also brings a series of ecological and environmental problems. Understanding the coordination mechanism that links urbanization and the ecological environment (UE) is crucial for promoting environmental conservation and sustainable development. Using the comprehensive nighttime light index (CNLI) and the remote sensing ecological index (RSEI), this study objectively evaluated the urbanization level and ecological environment quality and used the modified coupling coordination degree model to quantify the coupling coordination of UE for the two indexes. The results show that (1) the urbanization level of each city in the CCEC presents an increasing trend year by year, showing a circle distribution pattern with the twin cities as the core. (2) The overall eco-environmental quality presents a fluctuating upward trend, and in recent years, it has been significantly improved, showing a spatial pattern of higher in the surrounding areas and lower in the middle. (3) The overall coupling coordination of the study area is developing, and the upward trend is larger in recent years. The spatial distribution is centered on the "double nucleus," and the distribution of circles is characterized by a gradual decrease from the inside to the outside; the coupling coordination of cities in the northwest and east of the CCEC is decreasing, and that of cities in the northeast and southwest is increasing. During the study period, a total of 5 cities have reached the level of coordinated development, while most other cities are in the stage of uncoordinated development, mainly due to the lagging development of urbanization. CCEC still needs to strengthen the construction of urbanization, in order to improve the degree of coordination between economic development and ecological environment.

Spatiotemporal Relationship between Ecosystem Service Value and Ecological Risk in Disaster-Prone Mountainous Areas: Taking the Upper Reaches of the Minjiang River as an Example.

Mountainous areas are susceptible to disasters; the frequent occurrence of disasters drives the changes in ecosystem service value (ESV) and also brings certain ecological risk, which further increases the incidence of disasters. However, few scholars have investigated the spatiotemporal correlation between the ESV of disaster-prone mountainous areas and ecological risk index (ERI) with basin as the unit. This paper aims to clarify the spatial relationship between ESV and ERI under the changes of land use. Taking the upper reaches of the Minjiang River as the study area, the authors collected the land use data of 2000-2020, estimated ESV by the value equivalent factor per unit area method, and constructed the ERI. On this basis, the relationship between ESV and ERI was investigated in details. The results show the following: (1) From 2000 to 2020, the total ESV exhibited a fluctuating upward trend. The spatial distribution of ESV was greatly affected by slope and altitude; an important reason for the rising ESV in the study area is the increase of forest area and water area. (2) The upper reaches of the Minjiang River had a generally low ERI and relatively good overall ecoenvironment. After 2010, however, the ecological risk continued to rise. Most of the strongly high risk areas are areas with frequent human activities, such as low-altitude areas and river banks. (3) There is a spatial correlation and coupling between ESV and ERI in the study area; i.e., the strongly high ESV areas generally had a low ecological risk. The correlation intensified with the elapse of time. The changes in the service value of regional ecosystems driven by unreasonable land use will have a great impact on the ecoenvironment. By clarifying the spatiotemporal relationship between ESV and ERI, this research provides theoretical basis and data support to the formulation of ecoenvironmental restoration and protection plans for the upper reaches of the Minjiang River and to the coordinated development between society, economy, and ecoenvironment in the region.

A novel landslide susceptibility optimization framework to assess landslide occurrence probability at the regional scale for environmental management.

Landslide is a hazard that has drastic repercussions on population and the environment worldwide. Landslide susceptibility mapping (LSM) is vital for landslide disaster management and formulating mitigation strategies. In this study, with the support of geographic information system and remote sensing, a new LSM hybrid framework is developed based on random forest (RF) and cusp catastrophe model (CCM). Under the framework, 15 conditioning factors and 2082 historical landslides are selected to test and compare its performance in a landslide-prone area in Liangshan, Southwest China. The results depicted a better performance of the new LSM hybrid framework (RF-CCM) than those of RF or traditional application mode of catastrophe model (Catastrophe fuzzy membership functions, CFMFs) only. The RF-CCM achieved the highest accuracy (0.901), the narrowest confidence interval (0.895-0.907), and the smallest standard error (0.004) among all the models. Notably, RF-CCM successfully decreased the uncertainty of CFMFs in determining the relative importance of conditioning factors, overcame the dependence of the CFMFs on independence among the conditioning factors, and had a higher stability level than RF. Moreover, distance to human engineering activities and slope had the greatest impact on LSM in the modeling process. The study result can provide insights for developing reliable predictive models for other landslide-prone areas with similar geo-environmental conditions.

Spatiotemporal Variation and Driving Forces Analysis of Eco-System Service Values: A Case Study of Sichuan Province, China.

Sichuan Province is an important ecological barrier in the upper reaches of the Yangtze River. Therefore, it is critical to investigate the temporal and spatial changes, as well as the driving factors, of ecosystem service values (ESVs) in Sichuan Province. This paper used land use data from 2000, 2005, 2010, 2015, and 2020 to quantify the spatiotemporal changes in the ESVs in Sichuan Province. Correlation coefficients and bivariate spatial autocorrelation methods were used to analyze the trade-offs and synergies of ESVs in the city (autonomous prefecture) and grid scales. At the same time, we used a Geographical Detector model (GDM) to explore the synergies between nine factors and ESVs. The results revealed that: (1) In Sichuan Province, the ESVs increased by 0.77% from 729.26 × 109 CNY in 2000 to 741.69 × 109 CNY in 2020 (unit: CNY = Chinese Yuan). Furthermore, ecosystem services had a dynamic degree of 0.13%. Among them, the ESVs of forestland were the highest, accounting for about 60.59% of the total value. Among the individual ecosystem services, only food production, environmental purification, and soil conservation decreased in value, while the values of other ecosystem services increased. (2) The ESVs increased with elevation, showing a spatial distribution pattern of first rising and then decreasing. The high-value areas of ESVs per unit area were primarily distributed in the forestland of the transition area between the basin and plateau; The low-value areas were distributed in the northwest, or the urban areas with frequent human activities in the Sichuan Basin. (3) The tradeoffs and synergies between multi-scale ecosystems showed that ecosystem services were synergies-dominated. As the scale of research increased, the tradeoffs between ecosystems gradually transformed into synergies. (4) The main driving factors for the spatial differentiation of ESVs in Sichuan Province were average annual precipitation, average annual temperature, and gross domestic product (GDP); the interaction between normalized difference vegetation index (NDVI) and GDP had the strongest driving effect on ESVs, generally up to 30%. As a result, the distribution of ESVs in Sichuan Province was influenced by both the natural environment and the social economy. The present study not only identified the temporal and spatial variation characteristics and driving factors of ESVs in Sichuan Province, but also provided a reference for the establishment of land use planning and ecological environmental protection mechanisms in this region.

Study on Spatiotemporal Variation Pattern of Vegetation Coverage on Qinghai-Tibet Plateau and the Analysis of Its Climate Driving Factors.

As one of the most sensitive areas to global environmental change, especially global climate change, the Qinghai-Tibet Plateau is an ideal area for studying global climate change and ecosystems. There are few studies on the analysis of the vegetation's driving factors on the Qinghai-Tibet Plateau based on large-scale and high-resolution data due to the incompetence of satellite sensors. In order to study the long-term vegetation spatiotemporal pattern and its driving factors, this study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to improve the spatial resolution of the GIMMS NDVI3g (8 km) data of the Qinghai-Tibet Plateau in 1990 and 1995 based on the MODIS NDVI (500 m) data. The research on the spatiotemporal pattern and driving factors of vegetation on the Qinghai-Tibet Plateau from 1990 to 2015 was carried out afterward, with combined data including topographic factors, annual average temperature, and annual precipitation. The results showed that there was a strong correlation between the actual MODIS NDVI image and the fused GIMMS NDVI3g image, which means that the accuracy of the fused GIMMS NDVI3g image is reliable and can provide basic data for the accurate evaluation of the spatial and temporal patterns of vegetation on the Qinghai-Tibet Plateau. From 1990 to 2015, the overall vegetation coverage of the Qinghai-Tibet Plateau showed a degrading trend at a rate of -0.41%, and the degradation trend of vegetation coverage was the weakest when the slope was ≥25°. Due to the influence of the policy of returning farmland to forests, the overall degradation trend has gradually weakened. The significant changes in vegetation in 2010 can be attributed to the difference in the spatial distribution of climatic factors such as temperature and precipitation. The area with reduced vegetation in the west was larger than the area with increased vegetation in the east. The effects of temperature and precipitation on the distribution, direction, and degradation level of vegetation coverage were varied by the areal differentiation in different zones.

Spatial-temporal pattern evolution and driving force analysis of ecological environment vulnerability in Panzhihua City.

Panzhihua City, a typical eco-fragile region for agro-sylvo-pastoral industry in China, is located in the dry-hot valley of the Jinsha River, characterized by its big landform undulation, great elevation difference, uneven hydrothermal conditions, and complex geological structure. As a crucial ecological barrier in upper reaches of the Yangtze River, this area is abundant in water resources and mineral resources, such as vanadium and titanium. However, due to its over-development for nonnatural urban economy in the mining industry, agriculture, and animal husbandry, ecological problems are getting worse. Such problems as soil erosion and groundwater pollution have led obvious ecological degeneration in Panzhihua city. Therefore, for protecting the eco-environment and planning construction, it is significant to scientifically recognize that how eco-environment changes based on spatial-temporal, and how the driving mechanism affects Panzhihua city. Nowadays, there are some theories and methods that study eco-environmental protection and city construction in Panzhihua, but they are not comprehensive enough to study its spatial-temporal evolution and driving-force system. This study takes Panzhihua City as the research area of which evaluation factors, for example, topography, soil, vegetation, and meteorological factors, are chosen to construct an evaluation system suitable for the ecological environment vulnerability of Panzhihua City. These factors are selected in three aspects, which are ecological sensitivity, ecological recovery, and ecological pressure from 2005 to 2015 in this area. Then, spatial principal component analysis method, CA-Markov model, and dynamic degree model are applied to analyze the spatial-temporal evolution for ecological vulnerability based on three periods from 2005 to 2015 in Panzhihua City. Besides, GeoDetector is used to quantitatively analyze how spatial-temporal disparities change and what drives them to change. The results show that (1) during these 10 years, the overall ecological fragility of Panzhihua City is steadily increasing from northwest to southeast. The overall ecological quality is moderate, and regional differences are obvious. Places of moderate vulnerability or above are distributed in central and eastern regions of frequent human activities; places of mild vulnerability or below are distributed in the regions of Yanbian County and Miyi County. (2) The comparison of the changing rates based on vulnerability levels is severe > potential > moderate > mild > slight. The overall vulnerability changes within a small trend, showing a balanced two-way transition state between adjacent vulnerability levels. The comprehensive index for overall ecological vulnerability decreases period by period. (3) The interactions between each two factors toward spatial differentiation and explanatory power by ecological vulnerability show a two-factor-enhanced relation, indicating that multiple factors form the ecological vulnerability of Panzhihua City.

[Responses of vegetation changes to climatic variations in Panxi area based on the MODIS multispectral data].

It is an important research area to quantitatively studying the relationship between global climatic change and vegetation change based on the remote sensing technology. Panxi area is the ecological barrier of the upper reaches of the Yangtze River, and it is essential for the stability of the ecological environment of Sichuan as well as that of the whole China. The present article analyzes the vegetation change in 2001-2008 and the relationship between vegetation change and climatic variations of Panxi area, based on MODIS multispectral data and meteorological data. The results indicate that NDVI is positively correlated with temperature and precipitation. The precipitation is the major factor that affects the change of vegetation in the Panxi region and the trend of NDVI is similar with autumn precipitation; while at the same time the influence of climate has a one-month-time-lag.

[Land use/cover change during lately 50 years in Three Gorges Reservoir Area].

Based on the topographic maps (1:50,000) in 1955, MSS images in 1972, and TM images in 1986 and 2000, the dynamic changes of land use during lately 50 years in Three Gorges Reservoir Area were quantitatively analyzed, with their driving forces discussed. The results showed that during lately 50 years, the structure of land use in the study area changed obviously, with a decrease of woodland, water area and unused land, and an increase of cultivated land, grassland and construction land. During the periods of 1955-1972, 1972-1986 and 1986-2000, woodland had a persistent and gradual decrease, grassland and cultivated land underwent a process of increase-decrease-increase and of increase-increase-decrease, respectively, construction land increased continually, while water area and unused land kept decreasing. Policy, economic development, and population growth were the main driving factors of the land use change in the study area.