Landsat TM/OLI-Based Ecological and Environmental Quality Survey of Yellow River Basin, Inner Mongolia Section

Restoration of vegetation in the Yellow River Basin of Inner Mongolia is limited by geographic factors

Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000-2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

Microbial and environmental medium-driven responses to phosphorus fraction changes in the sediments of different lake types during the freezing period

The comparative study of the transformation among sediment phosphorus (P) fractions in different lake types is a global issue in lake ecosystems. However, interactions between sediment P fractions, environmental factors, and microorganisms vary with the nutrient status of lakes. In this study, we combine sequential extraction and metagenomics sequencing to assess the characteristics of P fractions and transformation in sediments from different lake types in the Inner Mongolian section of the Yellow River Basin. We then further explore the response of relevant microbial and environmental drivers to P fraction transformation and bioavailability in sediments. The sediments of all three lakes exhibited strong exogenous pollution input characteristics, and higher nutritional conditions led to enhanced sediment P fraction transformation ability. The transformation capacity of the sediment P fractions also differed among the different lake types at the same latitudes, which is affected by many factors such as lake environmental factors and microorganisms. Different drivers reflected the mutual control of weakly adsorbed phosphorus (WA-P), potential active phosphorus (PA-P), Fe/Al-bound phosphorus (NaOH-P), and Ca-bound phosphorus (HCl-P) with the bio-directly available phosphorus (Bio-P). The transformation of NaOH-P in reducing environments can improve P bioavailability, while HCl-P is not easily bioavailable in weakly alkaline environments. There were significant differences in the bacterial community diversity and composition between the different lake types at the same latitude (p < 0.05), and the role of P fractions was stronger in the sediments of lakes with rich biodiversity than in poor biodiversity. Lake eutrophication recovery was somewhat hindered by the microbial interactions of P cycling and P fractions within the sediment. This study provides data and theoretical support for exploring the commonalities and differences among different lake types in the Inner Mongolian section of the Yellow River Basin. Besides, it is representative and typical for promoting the optimization of ecological security patterns in ecologically fragile watersheds.

Spatiotemporal change in ecological quality and its influencing factors in the Dongjiangyuan region, China

It is of great significance for regional ecological protection and sustainable development to quickly and effectively assess and monitor regional ecological quality and identify the factors that affect ecological quality. This paper constructs the Remote Sensing Ecological Index (RSEI) based on the Google Earth Engine (GEE) platform to analyze the spatial and temporal evolution of ecological quality in the Dongjiangyuan region from 2000 to 2020. An ecological quality trend analysis was conducted through the Theil-Sen median and Mann-Kendall tests, and the influencing factors were analyzed by using a geographically weighted regression (GWR) model. The results show that (1) the RSEI distribution can be divided into the spatiotemporal characteristics of "three highs and two lows," and the proportion of good and excellent RSEIs reached 70.78% in 2020. (2) The area with improved ecological quality covered 17.26% of the study area, while the area of degradation spanned 6.81%. The area with improved ecological quality was larger than that with degraded ecological quality because of the implementation of ecological restoration measures. (3) The global Moran's I index gradually decreased from 0.638 in 2000 to 0.478 in 2020, showing that the spatial aggregation of the RSEI became fragmented in the central and northern regions. (4) Both slope and distance from roads had positive effects on the RSEI, while population density and night-time light had negative effects on the RSEI. Precipitation and temperature had negative effects in most areas, especially in the southeastern study area. The long-term spatiotemporal assessment of ecological quality can not only help the construction and sustainable development of the region but also have reference significance for regional ecological management in China.

The heterogeneous drivers of CO2 emissions in China's two major economic belts: new evidence from spatio-temporal analysis

CO2 emissions have become increasingly prominent in China, and the primary emitters are economic belts that are spread throughout China. Two major economic belts, i.e., the Yangtze River Economic Belt (YTREB) and the Yellow River Economic Belt (YREB). Combined with stochastic impacts by regression on population, affluence and technology model, the spatial Durbin model under the space-and-time fixed effect and the Geographical and Time-Weighted Regression are employed to explore the spatio-temporal distribution characteristics and heterogeneous drivers of CO2 emissions in the two economic belts. The results are as follows. First, CO2 emissions exhibit obvious spatial correlation features in the YREB, but no such obvious spatial correlation is found in the YRETB. Second, in the YREB, the magnitude of the total influencing factors on CO2 emissions follows an order where affluence (A) is the biggest driver, followed by energy intensity (EI), technology (TEC) and openness (OP), while the biggest driver in the YRETB is industrial structure supererogation (ISS), followed by population (P), energy intensity (EI), and affluence (A). Both direct and spatial spillover effects of the drivers are observed in the two economic belts. Third, the CO2 emissions show a notable temporal lag effect in the YREB, but not in the YRETB. Fourth, the effects of the CO2 emission drivers illustrate significant spatio-temporal heterogeneity in the two economic belts.

Exploring the spatiotemporal variations in regional rainwater harvesting potential resilience and actual available rainwater using a proposed method framework

Rainwater harvesting potential provides a basis for alleviating regional drought and water shortages. The resilience of rainwater harvesting potential is directly related to the sustainable level of actual available rainwater. Thus, SWAT model was combined with the proposed rainwater harvesting potential evaluation model to quantify rainwater harvesting potential, its resilience and actual available rainwater in the study area. The results showed that: (1) restoration of forest and grass increased the rainwater resource potential in the study area by 12.41 %, especially in the northeast, central and southwest of the study area. Although the surface runoff increased slightly in the past 20 years, it remained stable at 28.62 % of rainwater harvesting potential, which was benefited from the rainwater harvesting potential resilience to maintain the component stability; (2) rainwater harvesting potential resilience in the study area increased from class II to class III, which was closely related to the 17.93 % increase in the resilience intensity of the study area to resist external interference; and (3) surface runoff and net soil moisture content were the main components affecting the spatiotemporal variation of actual available rainwater, and lateral flow was also the main component affecting the spatial variation of actual available rainwater. In the past 20 years, the actual available rainwater has been increasing, and its conversion rate exceeded 89 %. The high level of actual available rainwater has been expanding to the western region with dense grassland coverage. This study provides a scientific basis for clarifying the sustainable utilization level of rainwater.

Evaluation and Strategic Response of Sustainable Livelihood Level of Farmers in Ecological Resettlement Area of the Upper Yellow River-A Case Study of Liujiaxia Reservoir Area, Gansu Province

The level of sustainable livelihoods, as a yardstick for measuring the social development of migrants, is of great importance to the sustainable development of the region. Based on the analysis of the policy logic of ecological protection and high-quality development in the Yellow River basin, this paper constructs a "ternary" system model and evaluation index system for sustainable livelihoods of farm households in the ecological resettlement areas of the upper Yellow River, and proposes that the harmonious relationship between the three basic dimensions of economy, society and environment is the key to evaluate the sustainable livelihood level of farm households in ecological resettlement areas. Based on the comprehensive evaluation index to assess the comprehensive development level of ecological resettlement areas, we introduced the coupling coordination degree and constructed the coordinated development degree model of "economic-social-environmental" system to characterize the sustainable livelihood level. Through the data of 1116 questionnaires and in-depth interviews in the ecological migrant resettlement area of Liujiaxia reservoir in the upper reaches of the Yellow River basin, the sustainable livelihood status and spatial distribution differences of farm households in 14 townships in the region were evaluated, and the validity of the indicator system was empirically tested. Finally, sustainable livelihood strategies for farm households in the ecological resettlement areas of the upper Yellow River are proposed for the economic, social and environmental dimensions, and the indicator system is further revised. The evaluation system can not only advance the research paradigm of sustainable livelihood assessment for farmers in ecological migrant resettlement areas but can also be widely guided and applied to the sustainable development of ecological migrant practices in China.

Dynamic monitoring and analysis of factors influencing ecological environment quality in northern Anhui, China, based on the Google Earth Engine

Monitoring the ecological environment quality is an important task that is often connected to achieving sustainable development. Timely and accurate monitoring can provide a scientific basis for regional land use planning and environmental protection. Based on the Google Earth Engine platform coupled with the greenness, humidity, heat, and dryness identified in remote sensing imagery, this paper constructed a remote sensing ecological index (RSEI) covering northern Anhui and quantitatively analyzed the characteristics of the spatiotemporal changes in the ecological environment quality from 2001 to 2020. Geodetector software was used to explore the mechanism driving the characteristics of spatial differentiation in the ecological environment quality. The main conclusions were as follows. First, the ecological environment quality in northern Anhui declined rapidly from 2001 to 2005, but the rate of decline slowed from 2005 to 2020 and a trend of improvement gradually emerged. The ecological environment quality of Huainan from 2001 to 2020 was better and more stable compared with other regional cities. Bengbu and Suzhou showed a trend of initially declining and then improving. Huaibei, Fuyang, and Bozhou demonstrated a trend of a fluctuating decline over time. Second, vegetation coverage was the main influencing factor of the RSEI, while rainfall was a secondary factor in northern Anhui from 2001 to 2020. Finally, interactions were observed between the factors, and the explanatory power of these factors increased significantly after the interaction. The most apparent interaction was between vegetation coverage and rainfall (q = 0.404). In addition, we found that vegetation abundance had a positive impact on ecological environment quality, while population density and urbanization had negative impacts, and the ecological environment quality of wetlands was the highest. Our research will provide a theoretical basis for environmental protection and support the high-quality development of northern Anhui.

Evaluation of the Ecological Environment Quality of the Kuye River Source Basin Using the Remote Sensing Ecological Index

Landsat remote sensing images obtained from 2000, 2005, 2010, 2015, and 2020 were analyzed. The normalized vegetation index (NDVI), moisture index (WET), land surface temperature (LST), and normalized building-soil index (NDBSI) were extracted based on the four aspects of greenness, humidity, heat, and dryness. The Remote Sensing Ecological Index (RSEI) was calculated using principal component analysis to quantitatively analyze and dynamically monitor and evaluate the ecological environment changes in the Kuye River Basin over the past 20 years. From the perspective of spatial and temporal distribution, the ecological and environmental quality of Kuye River Basin had a downward trend from 2000 to 2020. The overall RSEI grade was medium or poor, and the average RSEI decreased. The proportion of excellent and good grade watershed areas decreased, whereas that of medium, low, and poor grade watershed areas increased over the study period. Spatially, RSEI decreased gradually from southeast to northwest. The degraded areas were mainly distributed in urban areas with frequent human activities. Conversely, the superior eco-environmental quality areas were mainly distributed in eastern sections of the watershed. Compared with 2000, the eco-environmental quality of the Yulin urban area and Shenmu County in the southern section of the watershed are worsening.

Evaluation of Remote Sensing Ecological Index Based on Soil and Water Conservation on the Effectiveness of Management of Abandoned Mine Landscaping Transformation

Abandoned mines are typical areas of soil erosion. Landscape transformation of abandoned mines is an important means to balance the dual objectives of regional ecological restoration and industrial heritage protection, but the secondary development and construction process of mining relics require long-term monitoring with objective scientific indicators and effective assessment of their management effectiveness. This paper takes Tongluo Mountain Mining Park in Chongqing as an example and uses a remote sensing ecological index (RSEI) based on Landsat-8 image data to assess the spatial and temporal differences in the dynamic changes in the ecological and environmental quality of tertiary relic reserves with different degrees of development and protection in the park. Results showed that: ① The effect of vegetation cover, which can significantly improve soil and water conservation capacity. ② The RSEI is applicable to the evaluation of the effectiveness of ecological management of mines with a large amount of bare soil areas. ③ The mean value of the RSEI in the region as a whole increased by 0.090, and the mean values of the RSEI in the primary, secondary and tertiary relic reserves increased by 0.121, 0.112 and 0.006, respectively. ④ The increase in the RSEI in the study area is mainly related to the significant decrease in the dryness index (NDBSI) and the increase in the humidity index (WET). The remote sensing ecological index can objectively reflect the difference in the spatial and temporal dynamics of the ecological environment in tertiary relic protection, and this study provides a theoretical reference for the ecological assessment of secondary development-based management under difficult site conditions.

A Remote-Sensing Ecological Index Approach for Restoration Assessment of Rare-Earth Elements Mining

In order to meet the requirements for comprehensive and multidimensional generalization of ecological management effectiveness evaluation indexes in the context of ecological restoration advocating comprehensive management by multiple means, this paper explores the rationality of using RSEI as an ecological management effectiveness evaluation index to adapt to the systematic transformation of the management goal of abandoned mine restoration from ecological restoration to regional socioeconomic sustainable development. Based on Landsat-8 image data, the remote sensing ecological index (RSEI) was used to evaluate the dynamic changes and spatial and temporal differences of the ecological environment in the study area under the long-term multimeans comprehensive management. The RSEI is suitable for evaluating the effectiveness of comprehensive ecological management in mining areas with a large amount of bare soil. The regional RSEI mean value increased by 0.029 in the early stage and 0.051 in the later stage by fragmentation management, indicating a better effect of multimeans comprehensive management. The remote sensing ecological index can objectively reflect the difference of spatial distribution characteristics of ecological environment in the four “Ecological+” governance regions. It can both objectively reflect the ecological status of the study area and reflect the differentiated spatial distribution characteristics of the ecological environment in different treatment areas, which is of long-term practical significance to the ecological construction of the study area. This study provides a theoretical reference for ecological assessment of complex situation under difficult site conditions.

Land Use and Climate Change Altered the Ecological Quality in the Luanhe River Basin

Monitoring and assessing ecological quality (EQ) can help to understand the status and dynamics of the local ecosystem. Moreover, land use and climate change increase uncertainty in the ecosystem. The Luanhe River Basin (LHRB) is critical to the ecological security of the Beijing–Tianjin–Hebei region. To support ecosystem protection in the LHRB, we evaluated the EQ from 2001 to 2020 based on the Remote Sensing Ecological Index (RSEI) with the Google Earth Engine (GEE). Then, we introduced the coefficient of variation, Theil–Sen analysis, and Mann–Kendall test to quantify the variation and trend of the EQ. The results showed that the EQ in LHRB was relatively good, with 61.08% of the basin rated as ‘good’ or ‘excellent’. The spatial distribution of EQ was low in the north and high in the middle, with strong improvement in the north and serious degradation in the south. The average EQ ranged from 0.58 to 0.64, showing a significant increasing trend. Furthermore, we found that the expansion of construction land has caused degradation of the EQ, whereas climate change likely improved the EQ in the upper and middle reaches of the LHRB. The results could help in understanding the state and trend of the eco-environment in the LHRB and support decision-making in land-use management and climate change.

Spatiotemporal and Multiscale Analysis of the Coupling Coordination Degree between Economic Development Equality and Eco-Environmental Quality in China from 2001 to 2020

Evaluating and exploring regional eco-environmental quality (EEQ), economic development equality (EDE) and the coupling coordination degree (CCD) at multiple scales is important for realizing regional sustainable development goals. The CCD can reflect both the development level and the interaction relationship of two or more systems. However, relevant previous studies have ignored non-statistical data, lacked multiscale analyses, misused the coupling coordination degree model or have not sufficiently considered economic development equality. In response to these problems, this study integrated multisource remote sensing datasets to calculate and analyse the remote sensing ecological index (RSEI) and then used nighttime light data and population density data to calculate the proposed nighttime difference index (NTDI). Next, a modified coupling coordination degree (MCCD) index was proposed to analyse the MCCD between EEQ and EDE. Then, spatiotemporal and multiscale analyses at the county, city, province, urban agglomeration and country levels were performed. Global and local spatial autocorrelation and trend analyses were performed to evaluate the spatial aggregation degree and change trends from 2001 to 2020. The main conclusions are as follows: (1) The EEQ of China displayed a fluctuating upwards trend (0.0048 a−1), with average RSEI values of 0.5950, 0.6277, 0.6164, 0.6311 and 0.6173; the EDE of China showed an upwards trend (0.0298 a−1), with average NTDI values of 0.1271, 0.1635, 0.1642, 0.2181 and 0.2490; and China’s MCCD indicated an upwards trend (0.0220 a−1), with values of 0.4614, 0.5027, 0.4978, 0.5401 and 0.5525. (2) The highest global Moran’s I of NTDI and MCCD was achieved at the city scale, while the highest RSEI was achieved at the county scale. From 2001 to 2020, the spatial agglomeration effect of the RSEI decreased, while that of the NTDI and MCCD increased. (3) A power function relationship occurred between NTDI and MCCD at different scales. Furthermore, the NTDI had a higher contribution to improving the MCCD than the RSEI and the R2 of the fitted curve at different scales ranged from 0.8183 to 0.9915.