Search

Urban agglomerations play a leading role in China's economic development and social governance, and the study of carbon emissions from land-use in urban agglomerations is helpful to the regional coordinate emission reduction. In this study, the carbon emission coefficient method to measure the land-use carbon emissions of the urban agglomeration around Poyang Lake during 2000-2020 was adopted, the standard deviation ellipse was used to further explore the migration trajectory of the land use carbon emissions, and finally the Markov-PLUS model and the gray BP neural network were applied to the multi-scenario prediction of the land- use carbon emissions in 2030. The finding of the study indicated that during the years 2000-2020, the farmland was an important source of rapid expansion of urban agglomerations, land-use carbon emissions showing an upward trend with an average annual increase of 1.880 million tons, while the construction land and forest land were the main contributors of carbon sources and sinks, respectively. As a whole, main part of the carbon emission tended to the change from southwest-ward migration to northeast-ward migration, with a cumulative migrated distance of 37.39 km and 38.50 km, respectively; and the prediction results showed that the urban agglomeration around Poyang Lake will have the highest carbon emission (58.826 3 million tons) in the scenario of adequate farmland protection in 2030, followed by the natural development and ecological priority scenarios, with respective 58.764 8 million tons, 58 669 4 milliontons. The results drawn from this study could provide the reference basis for the urban agglomeration around Poyang Lake to increase carbon sinks, and to reduce carbon sources, thus realizing the sustainable development of the city. [ABSTRACT FROM AUTHOR]

In order to explore the spatial distribution, spatial pattern evolution and spatial aggregation of the coupling and coordination of water resources utilization, low-carbon emission and green development of the Upper and Middle Yellow River, coupling coordination degree model, standard deviation ellipse and spatial autocorrelation analysis method were used to analyze the spatial heterogeneity of the coupling and coordination of water resources utilization, low-carbon emission and green development in 54 cities of the Upper and Middle Yellow River from 2010 to 2020. The results show that a) the comprehensive evaluation index of the three subsystems has been improved to varying degrees and the degree of coupling and coordination of each city is different. The proportion of primary coordination cities has increased from 55 % in 2010 to 74 % in 2020, and there are fewer intermediate coordination cities. b) The main migration direction of the center of gravity of the coupling coordination degree of the three subsystems is southwest, and the direction of the long axis of the standard deviation ellipse is north- west-southeast. The standard deviation of the long axis and the short axis is reduced by 2.21 km and 0.59 km, respectively, and there is a gathering trend of migration to the southwest. c) The coupling coordination degree of the three subsystems has a significant positive correlation in space. The high-high aggregation is mainly distributed in the south and west of the middle reaches of the Yellow River, the high-low aggregation is mainly distributed in Lanzhou City, and the low-low aggregation is mainly distributed in the west of the upper reaches of the Yellow River. Although the coupling coordination degree of the three subsystems of the Upper and Middle Yellow River has been increased year by year, the spatial heterogeneity is obvious. [ABSTRACT FROM AUTHOR]

Using the land use data set from 2000 to 2020 as the data source, GIS technology was used to explore the characteristics of land use change in Zhaotong city from three aspects: land use transfer matrix, standard deviation ellipse and center of gravity transfer model, and landscape pattern index was used to analyze the landscape pattern evolution from the landscape level and landscape type level. The results show that: (1) The main land types in Zhaotong are forest land, cultivated land and grassland, the growth rate of construction land is the largest, the standard deviation ellipse of grassland is the least obvious, and the distribution of center of gravity of cultivated land, forest land and grassland is relatively stable. (2) From the landscape level, the number of patches increased, the degree of connectivity decreased, the largest patch distribution dominance weakened, the degree of fragmentation increased, the connectivity decreased, the cohesion decreased and the complexity increased. (3) From the landscape type level, the landscape type with the largest patch number, patch density and edge density is cultivated land, the landscape type with the largest patch index and aggregation index is woodland, the landscape type with the largest mean patch fractal dimension is construction land, and the landscape type with the largest interspersion & juxtaposition index is water. [ABSTRACT FROM AUTHOR]

Copyright of Resources Development & Market is the property of Sichuan Resource Development & Market Magazine Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantifying green transformation level of 26 mountainous counties is crucial for the construction of a demonstration zone for common prosperity in Zhejiang. Based on the perspective of "green ecology-green production-green life" three-dimensional space, a green transformation indicator system was constructed; the temporal and spatial differentiation characteristics and driving factors of green transformation in 26 mountainous counties of Zhejiang from 2010 to 2021 were studied using vertical and horizontal pull-off grade method, gravity center-standard deviation ellipse, and geographically and temporally weighted regression (GTWR) model. The results show that from 2010 to 2021, the overall green transformation of 26 mountainous counties showes an increasing trend, with an average annual increase of 2. 428%, indicating that there is still considerable room for improvement; the variation coefficient of green transformation decreases year by year, and the characteristic of the regional differences gradually changes from "large gap and low level" to "small gap and high level". From 2010 to 2021, green transformation of 26 mountainous counties gradually showes a spatial distribution pattern with "Yongjia-Jinyun-Qingtian" as the core; the gravity center of green transformation gradually expands to the north, and the northern region of 26 mountainous counties have a significant improvement in green transformation during the study period; the spatial distribution of green transformation in 26 mountainous counties generally follows a northwest-southeast trend, and the distribution pattern is relatively stable; the distribution range of the standard deviation ellipse gradually narrows, and the spatial agglomeration continues to increase, indicating that the problem of regional development imbalance has improved. Each influencing factor shows strong temporal and spatial heterogeneity. Economic development, urbanization, government regulation and human capital quality have always been the main driving factors for green transformation of 26 mountainous counties; the driving forces of financial development, scientific, technological level and openness to the outside world have gradually increased; the driving effect of industrial structure is still unstable, and the driving ability for green transformation of 26 mountainous counties is limited. [ABSTRACT FROM AUTHOR]

Copyright of Resources Development & Market is the property of Sichuan Resource Development & Market Magazine Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] The utilization efficiency of land and water resources in the Huaihe River basin was evaluated to clarify the degree of coupling and coordination between the two and their spatial differentiation characteristics, in order to provide a theoretical reference for improving the utilization efficiency of land and water resources and promoting the benign and coordinated development of land and water resources in the basin. [Methods] The Super-SBM model was used to measure the land and water resource utilization efficiencies of 30 cities in the Huaihe River basin. The coupling coordination degree model was constructed to discuss the coordinated development of the two. The standard deviation ellipse and the Dagum Gini coefficient method were used to analyze the spatial deviation degree and spatial differentiation source of the coupled coordination degree. [Results] ① During the study period, the utilization efficiency of land and water resources in the Huaihe River basin showed a fluctuating upward trend, and the spatial heterogeneity was significant. ② From 2011 to 2014, the degree of coupling and coordination between the two factors was in the barely coordinated stage. From 2015 to 2020, the degree of coupling and coordination was basically in the primary coordination and intermediate coordination stage, both of which were dominated by the lag of water resource utilization efficiency. A spatial pattern of “higher in the east and west, and lower in the middle” was gradually presented. ③ The coupling and coordination degree of land and water resource utilization efficiency in the northwest and southeast cities of the Huaihe River basin increased rapidly, and there was a phenomenon of strong and weak alternation. ④ The overall difference of the coupling coordination degree between the two showed a downward trend, and the spatial differentiation mainly came from the hypervariable density, followed by regional differentiation. [Conclusion] The utilization efficiencies of urban land resources and water resources in the Huaihe River basin were not high, and the coupling coordination degree was also low. Cities should strengthen the efficient and intensive use of water and land resources, improve the coupling coordination degree between the two, and provide a decision-making basis for the implementation of differentiated resource development strategies in various regions.

Toponym, as the spiritual memory shared by the residents, carries rich cultural connotation and is of great significance to the continuation and development of the excellent traditional Chinese context. This paper analyzes the spatial distribution characteristics of the toponyms in Hehuang Valley by means of the research methods of classification statistics, kernel density estimation and standard deviation ellipse. The results show：（1） geographical names of Hehuang Valley can be divided into three categories（natural landscape, human landscape and others）.（2）The names of Hehuang Valley show a directional trend of the divergence of Huangshui River, Yellow River, Datong River and other water systems with Xining as the center.（3）The toponyms of natural landscape fully embodies the ancestors'wisdom in living near the rivers and trying to avoid the disadvantages of the landscapes for their residence in Hehuang Valley, and reflects the rough natural environment.（4）The toponyms of human landscape show the historical facts of the integration and development of multi-ethnic groups, and the characteristics of the military and communication areas in the Hehuang Valley. This paper can provide some useful information of the toponyms for the study of multi-ethnic integration, population migration, and cultural inheritance in Hehuang Valley. [ABSTRACT FROM AUTHOR]

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to accurately grasp the temporal and spatial characteristics of the development of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin, taking 356 water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin as the research object, comprehensively using spatial autocorrelation analysis, kernel density analysis, standard deviation ellipse and geographic detector to analyze the spatial and temporal differentiation characteristics and influencing factors of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin. The results show that from 2001 to 2021, the number of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin shows a rapid growth trend, and the spatial distribution has experienced a process of evolution from low-value areas to middle-value areas and high-value areas. The water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin have a positive correlation in space, showing a significant spatial distribution pattern of agglomeration, and the degree of agglomeration continues to increase. The nuclear density is characterized by a “Xing”-shaped distribution, showing a spatial evolution pattern with the middle and lower reaches of the Yellow River as the core agglomeration area, and the agglomeration difference gradually expands from the middle reaches to the lower reaches. The distribution pattern of the cold and hot spots is “cold in the west and hot in the east”, which shows a trend of continuous expansion of the cold spot area and stable change of the hot spot area. The distribution direction is in the spatial trend of “east (slightly north) -west (slightly south) ”.The spatial differentiation of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin is the result of the combined action of multiple factors. The economic level is the dominant factor, the traffic condition is the key factor, and the natural condition is the relevant factor. [ABSTRACT FROM AUTHOR]

Agriculture comprises a complex greenhouse gas source and sink system. Different regions and planting and breeding conditions lead to two types of carbon sources or sinks in the agricultural systems. Identifying the characteristics of carbon emissions in agricultural systems and influencing factors is of great significance to achieve green agricultural development, which will also provide a data basis to promote the realization of “carbon peak” and “carbon neutrality” goals. Taking the Hexi Corridor as an example, we calculated and analyzed the spatial and temporal characteristics of agricultural carbon emissions and influencing factors in 20 counties in the Hexi region from 2000 to 2020. The following results were obtained：from 2000 to 2020, agricultural carbon emissions in Hexi showed a slow increase. The regions with the largest agricultural carbon emissions were Liangzhou District and Ganzhou District, accounting for 31.74% of the total agricultural carbon emissions in Hexi. From the perspective of planting and stockbreeding, the planting industry in the Hexi region was determined to be a carbon sink, with carbon absorption of 1.41×108 t, and stockbreeding was considered a carbon source, with carbon emissions reaching 4.17×107 t. From 2000 to 2020, the net carbon emissions of agriculture in Hexi showed fluctuations, but the overall trend was decreasing, and the agricultural system changed to carbon sinks. In the planting industry, the factor with the greatest impact on agricultural carbon emission was determined to be planting scale, and in regions with stable scale development, the factor with the greatest impact was found to be the mechanization degree. The main influencing factors for smaller regions were the rural electricity consumption. In the agricultural area with a large scale and high proportion of stockbreeding industry, the most influential factor was the stockbreeding scale, and the correlation degree was greater than 0.9. From 2000 to 2020, the agricultural carbon emission intensity in the Hexi region showed a process of random distribution to significant aggregation, and the center of agricultural carbon emission shifted slowly to the southeast, but only in Zhangye City. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Science & Technology (10036504) is the property of Editorial Board of Environmental Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of South China Fisheries Science is the property of South China Fisheries Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Scientific evaluation of urbanization quality is of great significance to measure the level of urban development and promote sustainable urban development. Based on the two dimensions of urban development and urban environmental quality, an evaluation index system of urbanization quality in Liaoning province was constructed, and methods including entropy weight, standard deviation ellipse and geographic detector were comprehensively used to explore the urbanization quality and its spatial distribution, spatial evolution trend and influencing factors in Liaoning province. The results show that, from 2005 to 2019,the overall urbanization quality index increased from 2.74 to 4.74,of which the quality of economic urbanization subsystem had the largest increase, the quality of social urbanization and environmental governance subsystem had an obvious upward trend, and the quality of environmental state and environmental pressure subsystem was relatively stable. For the spatial distribution of urbanization quality, the index ranged from 0.087 to 0.740 for Liaoning’s cities, with Shenyang as the “big core” and Dalian as the “small core” of regional agglomeration. The center of gravity ellipse of urbanization quality standard deviation fell on Liaoyang, and the deflection trajectory was along southeast-northwest-southwest from 2005 to 2019,with annual increasing distance and speed of the center of gravity ellipse of standard deviation. Among all the subsystems, economic urbanization, social urbanization and environmental management posed more influence on urbanization quality in Liaoning province; specifically, main influencing indexes included urbanization area, fixed assets investment, number of people participating in primary pension insurance, number of college students per ten thousand people, and capacity of domestic garbage removal and urban sewage treatment, which played growing influence on urbanization quality. [ABSTRACT FROM AUTHOR]

Due to the expansion of artificial oases in these areas, scientific assessment of the carbon emission and eco-environment effects caused by changes in agriculture, towns, and ecological space is of great significance in grasping the carbon emission characteristics of various land use types, formulating land use emission reduction strategies, promoting the construction of ecological civilization, and optimizing the spatial pattern of the national territory. Based on land use data and socio-economic data, taking the inland river basin of the arid zone of the Xinjiang-Aksu River Basin as the research object, the carbon emission coefficient method was used to measure land-use carbon emissions, and spatial autocorrelation analysis and standard deviation ellipse were used to analyze the spatial evolution characteristics of carbon emissions from agriculture-town-ecological space in the Aksu River Basin. Based on the eco-environment quality index and ecological contribution rate, the impact of the agriculture-town-ecological space transformation on the eco-environment effects in the Aksu River Basin was explored. The results showed that： ① The scale of agricultural space and town space continued to rise, while the overall scale of ecological space was shrinking. The carbon source provided by agricultural space and town space showed a continuous upward trend, while the carbon sink provided by ecological space showed a trend of first increasing and then decreasing, with an overall downward trend. ② There was a positive spatial correlation between the net carbon emissions and the carbon emissions provided by the agriculture-town-ecological space. The center of gravity of carbon emissions in the basin generally moved to the southwest except for the ecological space, whereas the other space and net carbon emissions moved to the southeast. ③ The eco-environment quality index in the basin increased first and then decreased and generally showed a downward trend. From 1990 to 2000, the ecological environment quality improved overall； from 2000 to 2010, it deteriorated severely； and from 2010 to 2020, it deteriorated slowly.

Compound floods and derived landslide disasters are frequent in estuaries under the influence of high-intensity localized heavy rainfalls and tidal level top support.This paper proposes a comprehensive method for risk assessment and spatial migration patterns of compound flood and derived landslide disasters.Meanwhile,taking Guangzhou as the study area,it constructs the index system for risk assessment of compound floods and derived landslide disasters in the city.Additionally,the weighted comprehensive evaluation method is adopted to assess the risk of multi-source compound disasters,and the spatial risk distribution pattern of the above-mentioned three types of disasters and the migration law of the disaster risk are explored based on the standard deviation ellipse method.The results are as follows:① 52.81% areas of Guangzhou are medium-high risk and high-risk ones,and the risk of composite floods and derived landslide disasters as a whole presents the characteristics of high risk in the northeast and low risk in the southwest,among which the risk of Conghua District and Zengcheng District is higher.Thus,disaster prevention and mitigation measures should be taken to reduce the disaster risks in the above areas.② The center of gravity of the risk of heavy rainfall flooding-composite flooding-composite flooding and derived landslide hazards first moves to the southwest and then to the northeast,and the disaster risk shows a southwest-northeast distribution pattern,with the first enhanced and then gradually weakened aggregation effect of disaster risks.The results can provide a scientific basis for the risk decision-making of compound disasters and disaster prevention planning.

Objectives: With the rapid advancement of urbanization, the study of urban space expansion has become a hot spot in urban development research. Methods: Based on statistical yearbook data, land use status remote sensing monitoring data, and DMSP(defense meteorological satellite program)/OLS(operational linescan system) night light data, we can extract the urban construction land and calculate the change of area. In order to obtain the expansion types and expansion direction of Urumqi from 2000 to 2018, we use the method of convex shell to recognise the expansion types, and use the methods of centroid shift and the standard deviation ellipse to judgment the direction of Urumqi's expansion. Results: The results show that Urumqi is middle speed expansion mode from 2000 to 2006, highspeed expansion mode from 2007 to 2013, and fast expansion mode from 2014 to 2018. The recognition results of the method of convex shell show that the expansion types of Urumqi from 2000 to 2018 are all filled. The direction of Urumqis expansion judged by the method of centroid shift is that Urumqis center of mass shifted to the southwest from 2000 to 2006, the center of mass continued to shift toward the southwest from 2007 to 2013, the center of mass shifte toward the northeast from 2014 to 2018.The verification results by the method of standard deviation ellipse show that Urumqi expand along the northwestsoutheast direction from 2000 to 2006, expand along the southwestnortheast direction from 2007 to 2013, continued to expand along the southwestnortheast direction from 2014 to 2018. The direction expands between methods of centroid shift and standard deviation ellipse is substantially the same. Conclusions: The driving mechanism of Urumqi's urban expansion is subject to many factors. The interaction of multiple factors, while promoting urban development, also causes the spatial and temporal differentiation of urban expansion. [ABSTRACT FROM AUTHOR]

The secondary industry is the pillar industry in China. It is an important mean to grasp the trend of industrial development by studying its spatial agglomeration. Currently, studies on spatial agglomeration were mainly based on the aggregated statistical data, and discussion regarding the fine-grained spatial data in national scale is inadequate. This paper filled the gap by using registration data of industrial and commercial enterprises in China in year 2001, 2006 and 2012 to analyze the four industrial categories of secondary industry. This study proposed a concept of the most significant agglomeration scale to analyze industrial agglomeration intensity. Experiment results show that the spatial distribution of the secondary industry in China is mainly located on the southeast of China. The agglomeration gravity centers are wandering in the junction of Hubei Anhui, and Henan provinces. The intensity of spatial distribution of secondary industry increased gradually. During 2001 and 2012, the differences of the agglomeration intensity on both sides of Hu’s line in mining industry and power industry were gradually narrowed. While the differences of that in manufacturing industry and construction industry were gradually increased. On the southeast of Hu’s line, the differences of the most significant agglomeration scale in four industries are obvious, while the differences of that are relatively small on the northwest side. To a certain extent, these phenomena reflects that industries in the southeast of China develop well and present distinct spatial characteristics. In the meantime, industries in the northeast of China needs to be intensified the development to create the distinct characteristics. [ABSTRACT FROM AUTHOR]

By using the per capita GDP from 2001~2012 of the counties in Hubei province and comprehensively using the methods such as Nich, Theil, Weighted coefficient of variation, Moran's I and Getis-Ord Gi index and Standard Deviation Ellipse (SDE), this paper analyzes and forecasts the evolution of the county economy of Hubei province on ArcGIS 9. 3. The following four conclusions have been drawn from the analysis: 1) the absolute differences of the economic development among the counties were extremely significant and the county economic development was of various zonality, while the relative differences of the economic development among the counties have gradually decreased; 2) there was a strong spatial autocorrelation among the economic development of the counties and the autocorrelation have enhanced over time, indicating that the differences of the economic development among the counties have converged; 3) the county economy of Hubei province shows a spatial pattern of "low in west and high in east" and "high in middle and low in surrounding", with the hotspots concentrating a-round Wuhan city in east of Hubei province and having a trend of moving to the west of Hubei province and increasing over time, while the cold areas distributing in the marginal areas such as the northwest, southwest, northeast and southeast areas of Hubei province and decreasing over time, reflecting that the county economy of Hubei province is getting better; 4) the spatial distribution of the county economy presents a "northwest-southeast" pattern, with the distance of the economic gravity center moving from east to west greater than that from north to south in the twelve years, and the moving distance from 2005-2008 being the larger than that of other years. [ABSTRACT FROM AUTHOR]

Wetlands play an important role in maintaining ecosystem functions. Wetlands in China have suffered intensive human disturbance, especially before 2000, resulting in great losses and degradation. Therefore, two national wetland resource surveys were carried out by the Chinese government during 1998-2003 and 2008-2013 to determine the status of wetlands, understand their dynamics, and provide substantial data that can aid scientific wetland conservation. Based on the survey data, the spatial pattern and spatial autocorrelation were explored using the standard deviation ellipse as well as global and local spatial autocorrelation statistics. GIS mapping was employed to display the results via the visualization of the spatial patterns and relationships. Results indicate that:① Changes in the wetlands of China are significant and exhibit obvious regional differences. The center of the ellipse of the total wetlands has moved to the west, and the degree of spatial differentiation between natural wetlands and artificial wetlands is increasing. There is no significant spatial autocorrelation for changes in artificial wetlands. ② The changes in natural wetlands are significantly spatially autocorrelated and clustered, which are identified by global Moran's I and local Moran's I . The hotspots of natural wetland change are concentrated primarily in Qinghai, Tibet, and Sichuan. The individual hotspot is in Inner Mongolia and the cold spot is in Henan. The difference in spatial autocorrelation between natural and artificial wetland changes indicates that natural wetland changes have shown spatial continuity, while artificial wetland changes have shown strong spatial randomness. ③ Some useful spatial associations are used to delineate wetland conservation effects. Then, three major or five minor effective protection management regions are identified. Wetland conservation efforts should be continuously strengthened and improved, especially in the middle-lower Yangtze River region of central China. The use of Moran statistics helps to reveal spatial autocorrelation and identify the conservation effects in wetland changes, which can provide a basis for decision-making in regional wetland conservation and management systems.

We use 3487 surface soil samples, 35 soil profile samples, and 93 agricultural products and root soil samples obtained from the southeastern Tarim basin, Xinjiang, northwestern China (Ruoqiang County and Qiemo County, Bayingguo Mongolia Autonomous Prefecture, and Minfeng County and Yutian County, Hetian Prefecture) to assess As contamination. Multivariate statistical analysis, geostatistics, and global information system (GIS) techniques are used to study:the spatial distribution characteristics of soil As, the effects of various agricultural products on As enrichment, and to compare the characteristics of the As content of agricultural products and root soils in spatially significantly and non-significantly autocorrelated regions. The As content of soil samples were relatively low, and the average As contents determined for agricultural land and non-agricultural land were 9.81 mg·kg -1 and 7.94 mg·kg -1 , respectively. We found that 568 surface soil samples (16.3% of all samples) had an As content that exceeded Xinjiang soil background values (11.2 mg·kg -1 ) and that five samples exceeded the risk screening values (25 mg·kg -1 ). The Moran's indexes of spatial autocorrelation were>0, and the main aggregation types of spatial autocorrelation of soil As were high-high and low-low types, with the zone of the high-high type being mainly located in the agricultural land of each county. A GIS spatial distribution map showed that the high value area of soil As content presented a flaky or island-like scattered distribution. The standard deviation ellipses showed that the trend direction of soil As content in:Ruoqiang County was from north to south, Qiemo County and Minfeng County were both from southwest to northeast, and Yutian County was from northwest to southeast. The As content of the vertical profiles of the agricultural land in Ruoqiang County fluctuated from the surface to depth, whereas those of other counties were relatively stable. The As enrichment ability of crops was ranked as:root vegetables > walnuts > wheat > corn > red dates. The As contents of corn and red dates showed a significant positive correlation with that of the root soil. There was no significant difference in the As content of agricultural products between significant autocorrelation zones and non-significant autocorrelation zones, whereas there was a significant difference in the As content of root soils.