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Under economic globalization, synergy among cities has been actively promoted. Establishing inter–city networks and joint regional development could catalyze economic growth. The mode and pace of urban growth could be gauged by construction land expansion and human–land coordination. This study adopted the dynamic change, the center of gravity, and coordination analyses to comprehensively portray spatial patterns and changes amongst 13 oasis town groups in Xinjiang, China, from 2000 to 2018. The results identified that 2010 was the turning point of acceleration in construction land expansion, demonstrating notable spatial differentiations among town groups. Northern Xinjiang experienced faster urban growth than southern Xinjiang. The Urumqi–Changji–Shihezi (UCS) town group on the northern slope of the Tianshan Mountains constituted the crucial urban core with the fastest construction land expansion. Although the towns in southern Xinjiang were small and beset by inherent limitations in the early period, some town groups acquired new impetus and vitality and became the fastest–developing areas in Xinjiang in recent years. The growth was driven by China’s western development program, economic assistance, and Silk Road Economic Belt. Eastern Xinjiang had convenient transportation, but its small urban entities needed population supplementation to invigorate urban expansion. In the far north, the Altay and Tacheng–Emin (TE) town groups were situated too far from development cores. They lacked the collateral benefits of nearby strong–growth loci, resulting in sluggish growth. A north–south dual–hub strategy was proposed to spearhead the dissemination of urban growth by fostering core–periphery linkages pump–primed by improved road connections.

The eco-environment of the arid area is constantly fragile global-wide. The study on the spatial and temporal variation of its landscape pattern can quickly identify the driving factors, which is an effective analysis method of ecological conservation in the arid area. In this study, Jinghe County, Xinjiang, in Northwestern China, is chosen as a case study of understanding the major driving force of the oasis landscape. Landsat satellite images of 1994, 2007, and 2017 are used as the basic data sources for analysis. The moving window method, transition matrix, and factor analysis are selected as the main technical means for this paper to reveal the temporal and spatial variation of landscape pattern in Jinghe County, and to quantitatively describe its driving factors. The results of the analysis show that: (1) The landscape pattern of Jinghe County has changed dramatically, especially the construction land and farmland. Both show an increase of 351.29% and 269.01% respectively between 1994 and 2017. Farmland increased the most, with the proportion of 6.45% in Jinghe County, and expanded along with the “triangle” three sides. The area of forest land increased slightly, the area of grassland and unused land decreased, and the area of water did not change significantly. (2) The dominant obvious regional differences of landscape types in Jinghe County are mainly manifested in farmland and forest land. Taking the unused land as the boundary, the biodiversity of farmland decreased, and the aggregation degree deepened, while the fragmentation degree of forest land increased. (3) The spatial–temporal variation of landscape patterns in Jinghe County is the result of the combination of natural and human factors, but the correlation between human factors and the change of landscape area is significantly greater than that of natural factors. Thus, human factors are the main driving force of landscape pattern change in Jinghe County. The scientific management and planning of the intensity of human activities in Jinghe County should be the focus of ecological environment restoration and protection.

This study aims to analyze the pollution characteristics and sources of heavy metal elements for the first time in the Zhundong mining area in Xinjiang using the linear regression model. Additionaly, the health risks with their probability and infleuencing factors on different groups of people's were also evaluated using Monte Carlo (MC) simulation approach. The results shows that 89.28% of Hg was from coal combustion, 40.28% of Pb was from transportation, and 19.54% of As was from atmospheric dust. The main source of Cu and Cr was coal dust, Hg has the greatest impact on potential ecological risks. which accounted for 60.2% and 81.46% of the Cu and Cr content in soil, respectively. The all samples taken from Pb have been Extremely polluted (100%). 93.3% samples taken from As have been Extremely polluted. The overall potential ecological risk was moderate. Adults experienced higher non-carcinogenic risks of heavy metals from their diets than children. Interestingly, body weight was the main factor affecting the adult's health risks. This research provides more comprehensive information for better soil management, soil remediation, and soil pollution control in the Xinjiang mining areas.

For effective monitoring and protection, researchers need to analyze the trends and causes of landscape pattern change in wetlands. The present study used Geographic Information System and remote sensing technology to analyze temporal and spatial dynamics of landscape pattern and related driving forces in the Ebinur Lake Wetland National Nature Reserve (ELWNNR) in China. We used Landsat images from 1972, 1998, 2007 and 2013, and classified the landscape into six types of land cover: water body, wetland, vegetation, salinized land, desert, and other objects (i.e., Gobi and Mountain). Landscape transition matrices and change pattern analysis were used understand wetland dynamics. Our results showed that land cover had changed dramatically during 1972–2013. The spatial extent of much of the wetland areas in the ELWNNR had reduced gradually from 1972 to 2007, and wetland loss occurred more rapidly after 2007. From 1972 to 2013, 415.8 km2 of wetland area had been lost and only 250.1 km2 wetland area had expanded, which represents a 22% decrease in wetland area in the ELWNNR. At the same time, the landscape pattern experienced diverse changes in the Nature Reserve. The high-density human population of the region has an intensive effect on the region. Wetlands in the nature reserve have also changed with recent rapid development in the region. This study may provide scientific information for developing effective and sustainable conservation plans for the ELWNNR.

Rapid urbanization in China in recent decades has given rise to increasingly serious ecological and environmental problems. Specifically, the provinces along the Silk Road Economic Belt (SREB) in China have experienced rapid urbanization, and need to take pro-active action in balancing urbanization development with eco-environment conservation. This paper aims to develop comprehensive urbanization and eco-environment (UAEE) evaluation models to explore UAEE development of SREB in China from 2004 to 2018. In terms of methodology, these evaluation models are subsequently combined with CCDM (Coupling coordination degree model) and GTWR (Geographically and Temporally Weighted Regression) models to measure and analyze coupling degree and spatio-temporal heterogeneity of UAEE. The results show that: Firstly, from 2004 to 2018 in all regions of the SREB, the urbanization showed a gradual upward trend. Among them, comprehensive urbanization index (CUI) of Guangxi increased by 3.067%. Secondly, the comprehensive eco-environment index (CEI) of Chongqing, Sichuan, Guangxi, Shaanxi and Gansu has improved; while the eco-environment quality of Yunnan, Qinghai, Ningxia and Xinjiang has deteriorated during this period, with the rate of decrease in Xinjiang reaching a significant 2%; Thirdly, in 2018, Chongqing, Sichuan, Guangxi, Shaanxi and Gansu are in a state of high coordination level with the eco-environment under the rapid urbanization process, while Yunnan, Qinghai, Ningxia and Xinjiang are at a moderate coordination level. Since 2011, these areas are in a state of lagging development of the eco-environment. Finally, the interactive relationship between UAEE tends to converge. There is heterogeneity in time and space among SREB regions. The negative interaction effect of UAEE is mainly focused on the northwest regions. In conclusion, this research will provide a basis of scientific evaluation for the coordinated degree of UAEE, promote regional urbanization vis-a-vis the improvement in environmental policy making.

Abstract Soil salinity is a common global environmental problem that severely restricts industrial, agricultural and human development. In Northwest China, soil salinity is a problem affecting the Lake Ebinur area and needs to be monitored and addressed. The use of optical remote sensing technology to for timely and accurate soil salinity monitoring has great potentials and can be crucial for industrial and agricultural development. Optical remote sensing technology is an important data source for monitoring of soil salinization because of its rich spectral information and high-resolution. Based on the HJ-1/HSI data of fractional derivative transformation, this paper calculated the parameters, such as the difference index (DI), normalized difference index (NDI), ratio index (RI) and salt index (SI), that can invert the spatial distribution of salinization and then calculates a particle swarm optimization support vector machine (PSO-SVM). These index parameters were used to invert the spatial distribution information of salinized soil to explore the influence of fractional derivatives on the estimation accuracy of the spatial distribution of salinized soil. The results showed the following: (1) The optimal model based on different fractional derivatives and exponential transformations was the DI transformation under the fractional derivative of 1.2-order. R2, RMSE and RPD were 0.66, 13.81 g/kg and 2.59, respectively. These data show that the model had a good prediction effect. (2) The application of fractional derivatives in the processing of hyperspectral images could highlight the spectral details of the images and enrich their pretreatment methods, which is of great significance for the inversion of the distribution of salinized soil by hyperspectral images. (3) In the lakeside area of Lake Ebinur, the soil is mainly saline to severely saline. In the northern mountainous region of Lake Ebinur, the soil is mainly non-saline soil to mildly saline soil. Finally, in the Kuitun riverbank area in the southeast of Lake Ebinur, the soils are mainly non-saline soils to mildly saline soils. The results of this study demonstrate the potential of spectral index optimization and prediction models to monitor soil salinization based on fractional derivatives. This technique highlights the spectral detail information and enriches the preprocessing methods of hyperspectral imagery, resulting in the mapping of the spatial distribution of the degree of soil salinization. This has practical importance for the prevention and control of soil salinization and its spatial extent in arid and semi-arid regions.

Remote sensing technology can objectively and quantitatively evaluate spatial-temporal change of ecological environmental quality. This paper uses images from Landsat5 Thematic Mapper (TM) in 2007 and Landsat8 operational land imager (OLI) in 2013 and 2016 to extract indicators such as greenness, wetness, heat, and dryness that reflect the ecological environment quality of arid area. The principal component analysis (PCA) used the evaluating ecological environment quality of the Ebinur Lake Wetland National Nature Reserve to explore the characteristics of spatial differentiation for ecological quality in environment as indicated in the remote sensing ecological index (RSEI). The results showed that the greenness and wetness have positive effects on the ecological environment while the heat and dryness have negative effects. Wetness has a greater impact on the ecological environment than the other three indicators. The proportion of RSEI of degeneration, invariability, and improvement were 20.57%, 42.98%, 36.44%. Thus, the ecological environment had improved. The improved area in 2016 was once located in bad level in 2007. The ecological environment had degraded in the southern part of the lake. The value of Moran's I showed an increased trend first and then decreased. The value of Moran's I increased in 2013, in comparison with 2007, indicating a strong positive correlation and certain internal connection between the ecological environment qualities in the study area. The spatial distribution was clustered rather than random. In comparison with 2013, the auto-correlation in 2016 was relatively weak, an indication that the spatial distribution was random and disperse. The area of High-High (HH) mostly reached to the significant level of 0.05 in 2007 and then to 0.01 in 2013 and 2016. This study offered important results and information for ecological environment protection and region planning.

Land-cover and land-use change (LCLUC) alters landscape patterns and affects regional ecosystems. The objective of this study was to examine LCLUC and landscape patterns in Ebinur Lake Wetland National Nature Reserve (ELWNNR) and Ganjia Lake Haloxylon Forest National Nature Reserve (GLHFNNR), two biodiversity-rich national nature reserves in the Ebinur Lake Watershed (ELW), Xinjiang, China. Landsat satellite images from 1972, 1998, 2007 and 2013 were used to calculate the dynamics of a land-cover and land-use (LCLU) transition matrix and landscape pattern index using ENVI 5.1 and FRAGSTATS 3.3. The results showed drastic land use modifications have occurred in ELWNNR during the past four decades. Between 1972 and 1998, 1998 and 2007, and 2007 and 2013, approximately 251.50 km2 (7.93%), 122.70 km2 (3.87%), and 195.40 km2 (6.16%) of wetland were turned into salinized land. In GLHFNNR both low and medium density Haloxylon forest area declined while high density Haloxylon forest area increased. This contribution presents a method for characterizing LCLUC using one or more cross-tabulation matrices based on Sankey diagrams, demonstrating the depiction of flows of energy or materials through ecosystem network. The ecological landscape index displayed that a unique landscape patches have shrunk in size, scattered, and fragmented. It becomes a more diverse landscape. Human activities like farming were negatively correlated with the landscape diversity of wetlands. Furthermore, evidence of degraded wetlands caused by air temperature and annual precipitation, was also observed. We conclude that national and regional policies related to agriculture and water use have significantly contributed to the extensive changes; the ELWNNR and GLHFNNR are highly susceptible to LCLUC in the surrounding Ebinur Lake Watershed.

The Ebinur Lake is a closed inland lake located within the arid region of the Xinjiang Autonomous Region in the northwestern part of China, near the Kazakhstan border. The shrinkage of the lake area is believed to be caused by ecological environmental deterioration and has become an important restraining factor for the social development of the local population. Of all the lakes in the Xinjiang Autonomous Region, the Ebinur Lake is the most severely impacted water body. The lake has undergone change in size naturally for over thousands of years due to natural causes. However, the authors observed the dramatic changes in the freshwater resources of this region from the aerial images from 1972 to 2013. Thus, this paper traces and analyzes the change in the Ebinur Lake surface area in the past 41 years. A set of six satellite images acquired between 1972 and 2013 was employed to map the change in the surface area of the Ebinur Lake using the water index approach. The authors applied the traditional normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) to quantify the change in the water body area of the Ebinur Lake during the study period. The results indicate that the lake area has experienced a dramatic decrease of 31.4% from 1972 to 2013. The paper also examines the natural processes and human activities that may have contributed to the decrease in the lake area. The results show that the decrease in total lake area appears to coincide with periods of rapid land reclamation in the study area. Moreover, the uncontrolled land reclamation activities, such as irrigation, can increase the sedimentation in the Ebinur Lake thereby reducing the lake size. Reduction of the lake area has a negative ecological impact on the environment and on human life and property. The lake area is the most important factor to ensure the environment of the watershed and the key index to measure the environment balance.

A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management.