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Citation: Ou, B.; Abulizi, A.; Zayiti,
A.; Jiang, J.; Akbar, A.; Yu, T.
Ecological Risk Zoning Control in
Zhundong Economic Development
Zone Based on Landscape Pattern
Changes. Sustainability 2023,15,
15972. https://doi.org/10.3390/
su152215972
Academic Editors: Petra Schneider
and Volker Lüderitz
Received: 15 September 2023
Revised: 3 November 2023
Accepted: 13 November 2023
Published: 15 November 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sustainability
Article
Ecological Risk Zoning Control in Zhundong Economic
Development Zone Based on Landscape Pattern Changes
Bin Ou 1,2, Abudukeyimu Abulizi 1, 2, *, Abudoukeremujiang Zayiti 3, Jiao Jiang 1,2 , Adila Akbar 1,2
and Tingting Yu 1,2
1College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China;
107552101056@stu.xju.edu.cn (B.O.); jiangjiao@stu.xju.edu.cn (J.J.); adilaakbar@stu.xju.edu.cn (A.A.);
107552101053@stu.xju.edu.cn (T.Y.)
2Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
3College of Ecology and Environment, Xinjiang University, Urumqi 830046, China; krimjan411@xju.edu.cn
*Correspondence: keyimabliz@xju.edu.cn; Tel.: +86-135-6587-9831
Abstract:
The Zhundong coalfield in Xinjiang, China, is rich in resources and has great significance to
the development of the Xinjiang region, but its local ecological environment is fragile and its climate
is particularly dry, so mining is very likely to introduce a series of ecological risks; there is an urgent
need for us to provide scientific and feasible guidance for the conservation and development of coal
resources in this region. Therefore, this paper is based on the land-use-type data concerning the
Zhundong Economic and Technological Development Zone from 2000 to 2020, exploring the land
use change characteristics in the Zhundong area during these 20 years and calculating the ecological
risk index of each risky district according to an ecological risk index model. Afterward, this article
uses kriging interpolation to carry out a risk classification analysis to explore changes in ecological
risk in the Zhundong area during the last 20 years and to put forward ecological risk partition and
control measures for areas of different levels of risk. Our research shows the following features:
(1) The land use type in the Zhundong area changed obviously from 2000 to 2020, in which unused
land has always occupied most of the area of the Zhundong coalfield. Grassland was the land use
type with the greatest area transferred, 211,412.35 hm
2
, accounting for 68.11% of the total transferred
area, and it was mainly converted into unused and construction land. (2) In the last 20 years, the
Zhundong coalfield has been dominated by higher-risk and high-risk areas, with obvious changes
in the distribution of ecological risk levels. The low-risk, medium-risk, and higher-risk areas in the
research zone have decreased and then increased; the lower-risk area has declined yearly, and the
high-risk area has increased and then declined. Furthermore, overall, the ecological environment
has transformed toward good condition. (3) High-risk and higher-risk areas still account for most
of the research zone, and there is an urgent need for scientific and feasible programs to carry out
ecological restoration in areas with different ecological risk levels to avoid further deterioration of the
local environment.
Keywords:
land use change; ecological risk index model; ecological risk classification; ecological risk
zoning control
1. Introduction
Coal resources account for about 70% of China’s energy composition [
1
,
2
]. With the
rapid growth in China’s economy, the requirement for coal resources has escalated dra-
matically, and the conflict between domestic supply and demand has become increasingly
prominent. Xinjiang is one of the provinces with the richest coal resources in the country [
3
],
and it is an important resource reserve in China; in its identified mineral reserves, coal
resources rank second in the country, with a reserve of 450.4 billion tons. This research
focuses on the Zhundong coalfield. The Zhundong coalfield is the largest single coalfield
Sustainability 2023,15, 15972. https://doi.org/10.3390/su152215972 https://www.mdpi.com/journal/sustainability
Sustainability 2023,15, 15972 2 of 16
in China; not only is it rich in coal resources, but it also has shallow buried coal seams and
simple hydrogeology [
4
]. As a result, development and mining in the Zhundong coalfield
are relatively easy, the mining potential is very high, and there is great strategic significance.
However, the Zhundong coalfield is situated in the inland dry region of northwest China,
with a fragile ecological environment, and most of the coal mines in this region are open-pit,
the mining of which is very prone to cause irreversible ecological damage [
5
,
6
]. Therefore,
how to develop the Zhundong coalfield carefully and scientifically is an urgent problem
of great practical significance for the economic and social development in the Zhundong
Economic Development Zone and surrounding areas. During the past few years, the
number of investigations concerning the Zhundong coalfield (hereinafter referred to as the
Zhundong area) has increased. He Jing et al. [
7
] conducted a study on the compensation
of ecological development in the Zhundong area based on the ecosystem service value
system. Wu Wei et al. [
8
] evaluated the comprehensive efficiency of different ecological
restoration measures in the Zhundong area based on the data envelopment analysis (DEA)
model. Hao-Chen Yu et al. [
9
] used image-by-image meta-trend analysis to show the spatial
and temporal evolution of remote sensing ecological indices of drought in Zhundong, and
further analyzed the impact mechanism of mining and climate change on land ecosystem
quality in the Gobi mining district by using a multiple regression model and residual
analysis. Fang Liu et al. [
10
] explored variations in the value of ecosystem services based on
land use in the Zhundong coalfield. Yang Chuang et al. [
11
] proposed a green development
direction for the Zhundong coalfield, and Zeng Qiang et al. [12] analyzed the distribution
characteristics of coal resources and the ecological environment in the Xinjiang region.
These scholars have studied various aspects of the Zhundong area.
Notwithstanding these studies, however, at this stage, research on the Zhundong
coalfield is generally in the direction of coal mining technology; there is less research on the
ecological risk in the Zhundong area, and there is still a lack of systematic research on the
ecological restoration of the Northwest Inland Arid Zone. Additionally, existing ecological
risk research in China tends to focus on coastal watersheds [
13
], urban administrative
areas [
14
], ecologically fragile source areas [
15
], and other critical areas [
16
], and systematic
and in-depth research on ecological risk in the Northwest Inland Arid Zone is lacking.
During field visits and inspections carried out in recent years, this study found that the
effect of ecological restoration in the study area at this stage is unsatisfactory, in addition
to other problems; therefore, this study started with the change in land use types in the
Zhundong area, conducted ecological risk research through a 20-year time series, and
analyzed the causes of changes in areas with different risk levels. Lastly, the article suggests
ecological restoration measures for areas with corresponding risk levels.
Ecological risk comprises the threat to ecosystems and their components, reflecting the
adverse ecological effects of ecosystems as a result of anthropogenic activities and variations
in the natural environment [
17
]. Landscape ecological risk assessment is an important
branch of ecological risk assessment at the regional scale, that reflects the integration of
geography and ecology, and pays more attention to the scale effect of ecological risk in
a specific region [
18
,
19
], explaining and predicting the spatial and temporal distribution
and characterization of ecosystem health and potential risk pressures [
20
]. During the
last few years, with the acceleration in urbanization and industrialization, the influence
of changes in land use structure on the ecological environment has become increasingly
more significant [
21
–
23
], and the study of land use ecological risk has gradually become a
leading theme and important issue in the domain of regional ecological risk research by
scholars in China and abroad [24–27].
Land use changes can objectively reveal the degree of effect of land use categories
on ecological comprehensiveness [
28
]. Thus, ecological risk analysis can be carried out
through the structure of land categories and the characteristics of land use shifts. Regarding
the larger scale of the Zhundong coalfield, ecological risk analysis of land use based on
landscape structure can comprehensively assess various types of potential ecological effects
and their cumulative consequences. Results can accurately show the spatial distribution of
Sustainability 2023,15, 15972 3 of 16
various ecological impacts and the characteristics of gradient changes. Therefore, ecological
risk evaluation from the standpoint of land use transformation is one of the effective means
to analyze the ecological restoration measures implemented in the Zhundong coalfield.
However, new developments in the field of landscape ecological risk demand that the
theoretical implications of the ecological effects of land use change need to be further
detailed and defined [
29
], and evaluating how land use change represents ecological risk
effects [
30
]. This is one of the research topics described in this report. In recent years, China
has emphasized the protection of the ecological environment and promulgated a series
of policy measures for pursuing the scientific and orderly promotion of mine ecological
restoration. However, there is a lack of appropriate restoration tools for the ecological
restoration of mining sites in inland drylands. Accordingly, based on available land use
data, this paper calculated the ecological risk index for each region in the Zhundong
coalfield for the period 2000 to 2020. Additionally, the article performed ecological-risk-
level zoning to provide a theoretical basis for proposing corresponding region-specific
ecological restoration measures that can be applied in the Zhundong coalfield.
2. Overview of the Research Zone and Methodology
2.1. Overview of the Research Zone
The Zhundong Coalfield is an important part of China’s 14th largest coal mining area
and is situated in the eastern part of the Junggar Basin [
31
]. The Kalamere Mountains form
the basin’s northern edge [
32
] and the Bogda Mountains border its southern edge. The
terrain, as shown in Figure 1, is high in the northeast and low in the southwest [
33
], and
slopes gently from the north, east, and south margins toward the center, with a general
east-to-west tilt in its shallow disk-shaped basin. The elevation of the southern foothills of
the Kalamere Mountains in the north is 700–1000 m, the elevation of the northern foothills
of the Bogda Mountains in the south is 800–1500 m, and the elevation at the center of
the basin ranges from 700 to 500 m east to the west, decreasing to the west at a slope of
0.5 m km−1
; the terrain is generally relatively flat. The basin experiences a continental arid
desert climate, with large variations in annual and diurnal temperatures [
34
] and an average
annual rainfall of 106 mm, while the average annual evapotranspiration ranges from 1202
to 2380 mm. Hydrographically, the northern part of the Zhundong region is extremely
undeveloped, with no annual flowing surface water; temporary runoff formed by summer
rainfall is discharged southward into the desert, and some of it is collected and evaporated
in low-lying areas. There are a few springs and wells within the basin, but the volume of
water is very small and its quality extremely poor. Thus, it can be seen that the environment
of origin in this area is fragile [
35
,
36
] and highly vulnerable to disturbance caused by
external factors, while open-cast coal mines will inevitably exacerbate the destruction of
the natural environment in the region.
2.2. Data Sources and Processing
For the analysis presented in this article, land use data were obtained from the Institute
of Geographic Sciences and Resources of the Chinese Academy of Sciences (http://www.
resdc.cn/, accessed on 23 March 2023) for China’s land use/land cover remote sensing
monitoring data covering five periods: 2000, 2005, 2010, 2015, and 2020. These data
were supplemented with those gathered for previous years through online searches, field
surveys, and reports of coal mines in the Zhundong Economic Development Zone. Other
socioeconomic-related data were obtained through the same sources. The DEM used in this
article was acquired from the Geospatial Data Cloud Platform (https://www.gscloud.cn/,
accessed on 25 March 2023).
Sustainability 2023,15, 15972 4 of 16
Sustainability 2023, 15, x FOR PEER REVIEW 4 of 16
Figure 1. Map showing the Xingjiang prefecture and topography of the Zhundong coalfield.
2.2. Data Sources and Processing
For the analysis presented in this article, land use data were obtained from the Insti-
tute of Geographic Sciences and Resources of the Chinese Academy of Sciences
(hp://www.resdc.cn/, accessed on 23 March 2023) for China’s land use/land cover remote
sensing monitoring data covering five periods: 2000, 2005, 2010, 2015, and 2020. These data
were supplemented with those gathered for previous years through online searches, field
surveys, and reports of coal mines in the Zhundong Economic Development Zone. Other
socioeconomic-related data were obtained through the same sources. The DEM used in
this article was acquired from the Geospatial Data Cloud Platform
(hps://www.gscloud.cn/, accessed on 25 March 2023).
Combining the actual situation of the Zhundong coalfield, local landscape character-
istics, and the relevant literature relating to the Zhundong coalfield and other elements,
this analysis selected six broad landscape types: cultivated land, meadow land, forest
land, waters, construction land, and unused land according to the frontier of the research
zone. ArcGIS 10.2 software was used to crop and reclassify land use data, and the soft-
ware’s spatial analysis function was used to convert the data into a raster format. After-
ward, this study applied the software’s Create Fishnet and Segmentation tools to the land-
use-type data in the project area for grid segmentation, dividing the area into risky neigh-
borhoods. This paper also used Fragstats 4.2 and Excel software 2007 tools to calculate the
results of the processing, resulting in the ecological risk index of the risky neighborhoods.
Next, this study imported the resulting ecological risk index into the ArcGIS 10.2 software
package to carry out kriging interpolation analysis, which provided the ecological risk
class classification for the research zone. Once the ecological risk classification was com-
plete, the landscape paern was analyzed and supplemented with field research data, sta-
tistical yearbook data, Zhundong coalfield report data, and other data, which ultimately
provided support for the remediation of different levels of ecological risk in the research
zone.
2.3. Research Methodology
Ecological Risk Modeling
To best construct the ecological risk model, this study queried a large number of re-
lated reports in the literature to select the most appropriate model cell size, which was
Figure 1. Map showing the Xingjiang prefecture and topography of the Zhundong coalfield.
Combining the actual situation of the Zhundong coalfield, local landscape character-
istics, and the relevant literature relating to the Zhundong coalfield and other elements,
this analysis selected six broad landscape types: cultivated land, meadow land, forest land,
waters, construction land, and unused land according to the frontier of the research zone.
ArcGIS 10.2 software was used to crop and reclassify land use data, and the software’s
spatial analysis function was used to convert the data into a raster format. Afterward, this
study applied the software’s Create Fishnet and Segmentation tools to the land-use-type
data in the project area for grid segmentation, dividing the area into risky neighborhoods.
This paper also used Fragstats 4.2 and Excel software 2007 tools to calculate the results
of the processing, resulting in the ecological risk index of the risky neighborhoods. Next,
this study imported the resulting ecological risk index into the ArcGIS 10.2 software pack-
age to carry out kriging interpolation analysis, which provided the ecological risk class
classification for the research zone. Once the ecological risk classification was complete,
the landscape pattern was analyzed and supplemented with field research data, statistical
yearbook data, Zhundong coalfield report data, and other data, which ultimately provided
support for the remediation of different levels of ecological risk in the research zone.
2.3. Research Methodology
Ecological Risk Modeling
To best construct the ecological risk model, this study queried a large number of related
reports in the literature to select the most appropriate model cell size, which was found to
be 2–5 times the average patch area [37]. The final choice for the Zhundong research zone
was to create a grid consisting of 2000 m
×
2000 m square cells, thus segmenting the region
into a total of 4054 risk plots.
The ecological environment around an open-pit coal mine is fragile, and the study
coalfield is situated in the inland dry zone of northwest China, where the landscape changes
caused by human activities are obvious. Therefore, based on studying a large amount of
the literature, and with reference to ecological risk evaluation studies and the features of
the landscape pattern in the research zone, this study selected the following three factors
to construct a calculation model for the index of landscape interference (U
i
): index of
landscape fragmentation (C
i
), separation (S
i
), and dominance (K
i
) [
38
,
39
]. Ran et al.’s [
29
]
study based on this modeling framework is widely recognized. The formula is as follows:
Ui=aCi+bSi+cKi(1)
Sustainability 2023,15, 15972 5 of 16
where the landscape fragmentation index Ciis:
Ci=ni
Ai
(2)
and n
i
is the number of patches of landscape type iand A
i
is the total area of landscape
category i.
The landscape separation index Siis:
Si=A
2Airni
A(3)
where Ais the total landscape area.
The degree of landscape dominance Kiis:
Ki=1
4ni
N+mi
M+Ai
2A(4)
By reviewing the corresponding literature and based on the actual conditions in the
project area, variables a,b, and cin Equation (1) were assigned the values 0.5, 0.3, and
0.2 [
40
,
41
], respectively. The meaning of each parameter is the degree of influence that each
index has on the value of landscape ecological services, and a+b+c= 1.
In addition, with the help of the landscape ecology method, the degree of landscape
disturbance (U
i
), the degree of vulnerability (E
i
), and the index of loss (R
i
) were selected as
the risk evaluation indexes [19,42,43]:
Ri=Ei×Ui(5)
where degree of vulnerability (E
i
) refers to the fragility of ecosystems caused by strong
human disturbances. When the fragility is smaller, the risk to ecosystems is also smaller,
vulnerability (E
i
) was obtained through the examination of the previous literature [
44
].
Combined with the actual conditions in the Zhundong coalfield, the values for construction
land, forest land, meadow land, cultivated land, waters, and unused land were assigned as
1–6, respectively, and normalized to derive the fragility index for each landscape category.
The landscape ecological risk index (ERI) was constructed based on each index [45]:
ERIi=∑N
i=1
Aki
Ak
Ri(6)
where A
ki
denotes the area of landscape type iin the kth risk plot, A
k
is the area of the kth
risk plot, and Ridenotes the lossiness index of landscape type i.
Using ArcGIS 10.2 and Fragstats 4.2 software, the value for each risk plot during the
period 2000 to 2020 was exported for the land use types, and the Excel software package
was used to calculate each risk plot. The results of the calculations were then interpolated to
the ERI of each risk plot using kriging interpolation in the ArcGIS software package, and the
interpolation results were graded according to the natural breakpoint method [
46
]. Based
on multiple references in the literature [
39
,
47
] and the actual conditions in the study area,
five ecological risk class zones were delineated: lower-risk (0–0.071), low-risk (0.071–0.093),
medium-risk (0.093–0.115), high-risk (0.115–0.145), and higher-risk (ERI > 0.145).
3. Results and Analysis
3.1. Analysis of Land Use Change
After reclassifying the land use data for each year in the Zhundong coalfield, as can
be seen in Table 1, there are significant changes in the area of each land use type between
2000 and 2020. By 2020, the area of unused land was 1,424,536.02 hm
2
, accounting for
92.25% of the total area of the Zhundong coalfield. As the land is relatively barren and
the land use categories are fairly narrow, the local ecological environment is fragile. Over
Sustainability 2023,15, 15972 6 of 16
the past 20 years, the areas of cultivated land, water, construction land, and unused land
have all been increasing (Table 2), with construction land and unused land increasing
significantly, by 23,874.44 and 109,997.56 hm
2
, respectively, while the areas of arable land
and water have increased to a lesser extent, by only 22.54 and 578.7 hm
2
. In contrast, the
area of forest land and meadow land decreased significantly, with forest land decreasing
by 829.55 hm
2
and meadow land decreasing by 133,643.7 hm
2
. After 2005, with further
construction and development in the Zhundong coalfield, the area of unused land grew
dramatically, and the area of meadow land and forest land decreased sharply, especially
after 2010. The Zhundong coalfield has experienced continuous ecological degradation:
the already fragile ecological environment of the local area has further deteriorated, with
the ecological risk rising and many ecological issues occurring, which seriously restricts
economic and social development in the local area. Thus, there is a great need for sci-
entific and feasible conservation programs to achieve sustainable development in the
Zhundong coalfield.
Table 1. Variation in the area of each land category in the Zhundong coalfield, 2000–2020 (hm2).
Year
Cultivated Forest Meadow Waters Construction Land Unused Land
Area (hm2) Area (hm2) Area (hm2) Area (hm2) Area (hm2) Area (hm2)
2000 44.6 892.01 230,627.16 0 539.05 1,314,511.61
2005 58.1 894.41 230,630.72 0 538.82 1,314,491.83
2010 55.89 61.74 118,498.23 0 12,956.85 1,415,046.6
2015 67.32 61.74 116,465.76 524.34 19,813.32 1,409,686.83
2020 67.23 62.46 96,959.34 578.7 24,413.49 1,424,536.02
Table 2. Land-type transfer matrix for the Zhundong coalfield, 2000–2020 hm2.
Cultivated Forest Meadow Waters Construction
Land
Unused
Land
Total
Transfers
Cultivated - - 0 0 0 0 10.14 10.14
Forest 3.86 - - 594.83 0 0 261.03 859.72
Meadow 28.81 30.18 - - 314.49 3763.69 207,275.18 211,412.35
Waters 0 0 0 - - 0 0 0
Construction
land 0 0 0 0 - - 273.44 273.44
Unused land 0 0 77,173.83 264.21 20,384.19 - - 97,822.22
Total
transferred 32.68 30.18 77,768.65 578.7 24,147.88 207,819.79 - -
Total net
transfers 22.54 −829.55 −133,643.7 578.7 23,874.44 109,997.56 - -
Using ArcGIS software package, the intersection analysis of five-phase images from
2000 to 2020 was carried out to obtain the land-type transfer matrix across 20 years, and the
land-type transfer map of the coalfield was made according to the results (Figure 2). As
can be seen in Table 2and Figures 2and 3, meadowland is the land type with the largest
transferred area, with a transfer out of 211,412.35 hm
2
, accounting for 68.11% of the total
transfer-out area. The transferred area is dominated by unused land and construction
land, with areas of 207,275.18 and 3763.69 hm
2
, accounting for 98.04% and 1.78% of the
transferred area of meadow land, respectively, and the transferred areas for cultivated land,
forest land, and water are 28.81, 30.18, and 314.49 hm
2
, respectively. Area conversions of
varying sizes also occurred among other land types, but the magnitude of the increase or
decrease was relatively small.
Sustainability 2023,15, 15972 7 of 16
Sustainability 2023, 15, x FOR PEER REVIEW 7 of 16
transferred area, with a transfer out of 211,412.35 hm2, accounting for 68.11% of the total
transfer-out area. The transferred area is dominated by unused land and construction
land, with areas of 207,275.18 and 3763.69 hm2, accounting for 98.04% and 1.78% of the
transferred area of meadow land, respectively, and the transferred areas for cultivated
land, forest land, and water are 28.81, 30.18, and 314.49 hm2, respectively. Area conver-
sions of varying sizes also occurred among other land types, but the magnitude of the
increase or decrease was relatively small.
Figure 2. Distribution of land-type transfer in the Zhundong coalfield, 2000–2020.
Figure 2. Distribution of land-type transfer in the Zhundong coalfield, 2000–2020.
Sustainability 2023, 15, x FOR PEER REVIEW 7 of 16
transferred area, with a transfer out of 211,412.35 hm2, accounting for 68.11% of the total
transfer-out area. The transferred area is dominated by unused land and construction
land, with areas of 207,275.18 and 3763.69 hm2, accounting for 98.04% and 1.78% of the
transferred area of meadow land, respectively, and the transferred areas for cultivated
land, forest land, and water are 28.81, 30.18, and 314.49 hm2, respectively. Area conver-
sions of varying sizes also occurred among other land types, but the magnitude of the
increase or decrease was relatively small.
Figure 2. Distribution of land-type transfer in the Zhundong coalfield, 2000–2020.
Figure 3. Land use classification of the Zhundong coalfield, 2000–2020 (a–e).
3.2. Calculation of the Ecological Risk Index for the Research Zone
Based on the ecological risk index model, the ERI for each ecological risk plot was
calculated, and the calculated ERI was imported into ArcGIS software package for kriging
interpolation analysis. Applying the natural breakpoint method to the analysis results for
ecological risk grading, the study obtained a map showing the distribution of the ecological
risk level for the Zhundong coalfield (Figure 4), and calculated (Table 3) based on the
grading results. As shown in the figure and table, it can be seen that in the past 20 years,
the Zhundong coalfield has been dominated by higher-risk areas and high-risk areas, and
Sustainability 2023,15, 15972 8 of 16
the distribution of its ecological risk levels has changed significantly. The area of low-risk,
medium-risk, and higher-risk zones in the research zone decreased and then increased,
the area of lower-risk zones decreased from year to year, and the area of higher-risk zones
increased and then decreased. From the extended 20-year time series, the area of low-risk,
medium-risk, and higher-risk zones increased by 17,974.59, 6790.40, and 218,091.74 hm
2
,
respectively; the area of the lower-risk zone and the higher-risk zone decreased by 68,303.46
and 174,553.28 hm2, respectively.
Sustainability 2023, 15, x FOR PEER REVIEW 8 of 16
Figure 3. Land use classification of the Zhundong coalfield, 2000–2020 (a–e).
3.2. Calculation of the Ecological Risk Index for the Research Zone
Based on the ecological risk index model, the ERI for each ecological risk plot was
calculated, and the calculated ERI was imported into ArcGIS software package for kriging
interpolation analysis. Applying the natural breakpoint method to the analysis results for
ecological risk grading, the study obtained a map showing the distribution of the ecolog-
ical risk level for the Zhundong coalfield (Figure 4), and calculated (Table 3) based on the
grading results. As shown in the figure and table, it can be seen that in the past 20 years,
the Zhundong coalfield has been dominated by higher-risk areas and high-risk areas, and
the distribution of its ecological risk levels has changed significantly. The area of low-risk,
medium-risk, and higher-risk zones in the research zone decreased and then increased,
the area of lower-risk zones decreased from year to year, and the area of higher-risk zones
increased and then decreased. From the extended 20-year time series, the area of low-risk,
medium-risk, and higher-risk zones increased by 17,974.59, 6790.40, and 218,091.74 hm2,
respectively; the area of the lower-risk zone and the higher-risk zone decreased by
68,303.46 and 174,553.28 hm2, respectively.
Figure 4. Transfer matrix of ecological risk levels in the Zhundong coalfield, 2000–2020.
Table 3. Changes in the size of areas with different ecological risk levels (hm2).
Year Low Risk Lower Risk Medium Risk Higher Risk High Risk
2000 15,577.98 129,816.51 61,113.62 132,213.13 1,207,892.73
2005 15,182.47 129,450.51 61,129.41 136,642.21 1,204,209.38
2010 13,580.80 86,278.05 40,742.41 76,691.60 1,329,321.10
2015 30,756.53 72,697.25 67,105.15 205,309.81 1,170,745.23
2020 33,552.58 61,513.06 67,904.02 350,304.87 1,033,339.45
As the Zhundong coalfield is situated in the easternmost part of the Junggar Basin in
the Gobi Desert area, with inconvenient transportation, the Zhundong coalfield experi-
enced a low degree of investigation in the last century, and has not been exploited on a
Figure 4. Transfer matrix of ecological risk levels in the Zhundong coalfield, 2000–2020.
Table 3. Changes in the size of areas with different ecological risk levels (hm2).
Year Low Risk Lower Risk Medium Risk Higher Risk High Risk
2000 15,577.98 129,816.51 61,113.62 132,213.13 1,207,892.73
2005 15,182.47 129,450.51 61,129.41 136,642.21 1,204,209.38
2010 13,580.80 86,278.05 40,742.41 76,691.60 1,329,321.10
2015 30,756.53 72,697.25 67,105.15 205,309.81 1,170,745.23
2020 33,552.58 61,513.06 67,904.02 350,304.87 1,033,339.45
As the Zhundong coalfield is situated in the easternmost part of the Junggar Basin in
the Gobi Desert area, with inconvenient transportation, the Zhundong coalfield experienced
a low degree of investigation in the last century, and has not been exploited on a large scale
across a wide range [
48
], with an annual output of less than 30,000 tons of coal before 2005
and a very small amount of mining. Basically, the entire coalfield has yet to be exploited.
From Figure 5, it can be seen that the regional ecological risk in the Zhundong coalfield
basically remained unchanged between 2000 and 2005, and the ecological environment was
less affected by human activities.
Sustainability 2023,15, 15972 9 of 16
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large scale across a wide range [48], with an annual output of less than 30,000 tons of coal
before 2005 and a very small amount of mining. Basically, the entire coalfield has yet to be
exploited. From Figure 5, it can be seen that the regional ecological risk in the Zhundong
coalfield basically remained unchanged between 2000 and 2005, and the ecological envi-
ronment was less affected by human activities.
Figure 5. Distribution of ecological risk levels in the Zhundong coalfield between 2000 and 2020
(a)–(e).
During the period 2005–2010, due to coal mine consolidation in 2007 and the expan-
sion of mining in Zhundong coalfield, the ecological risk index increased in most parts of
the coalfield region as a whole, and the area of high-risk zones grew dramatically, with
serious damage to the ecological environment occurring. Nonetheless, the ecological risk
index decreased and the ecological environment improved in some areas in the central
and eastern parts of the coalfield.
Between 2010 and 2015, although a safety accident occurred in 2008 at the Laojun-
miao mine in the Zhundong coalfield and all coal mines were forced to shut down, the
ecological environment was not restored quickly due to a lag in ecological restoration [9].
Thus, after 2010, the overall regional ecological risk index of the Zhundong coalfield de-
creased as a whole. Although a series of developments were carried out in the coalfield
after 2010, overall, the quality of the ecosystem improved in 2015 compared to 2010.
Between 2015 and 2020, the change in ecological risk level was relatively small, with
the main change being that the area of the high-risk zone became smaller. This occurred
because China has aached great importance to the ecological environment in recent
years, enacted a string of policies and measures for the conservation of the ecological en-
vironment, and given increasingly more consideration to ecological environmental pro-
tection for the production activities of the mines. As a result, the deterioration of the fragile
ecological environment has been significantly mitigated, and the ecological environment
has become less vulnerable. A large number of lower-risk areas in the northeastern part
of the region, however, have been transformed into higher-risk and high-risk areas, and
the quality of the ecological environment has been degraded and reduced on a large scale.
3.3. Spatial Autocorrelation Analysis of Landscape Ecological Risk
(1) Ecological risk global autocorrelation analysis
The calculated ecological risk indices for each risk plot for the years 2000–2020 were
imported into GeoDa software 1.8 to obtain Moran’s I scaer plots (global autocorrelation
Figure 5.
Distribution of ecological risk levels in the Zhundong coalfield between 2000 and
2020 (a)–(e).
During the period 2005–2010, due to coal mine consolidation in 2007 and the expansion
of mining in Zhundong coalfield, the ecological risk index increased in most parts of the
coalfield region as a whole, and the area of high-risk zones grew dramatically, with serious
damage to the ecological environment occurring. Nonetheless, the ecological risk index
decreased and the ecological environment improved in some areas in the central and
eastern parts of the coalfield.
Between 2010 and 2015, although a safety accident occurred in 2008 at the Laojunmiao
mine in the Zhundong coalfield and all coal mines were forced to shut down, the ecological
environment was not restored quickly due to a lag in ecological restoration [
9
]. Thus, after
2010, the overall regional ecological risk index of the Zhundong coalfield decreased as
a whole. Although a series of developments were carried out in the coalfield after 2010,
overall, the quality of the ecosystem improved in 2015 compared to 2010.
Between 2015 and 2020, the change in ecological risk level was relatively small, with
the main change being that the area of the high-risk zone became smaller. This occurred
because China has attached great importance to the ecological environment in recent years,
enacted a string of policies and measures for the conservation of the ecological environment,
and given increasingly more consideration to ecological environmental protection for the
production activities of the mines. As a result, the deterioration of the fragile ecological
environment has been significantly mitigated, and the ecological environment has become
less vulnerable. A large number of lower-risk areas in the northeastern part of the region,
however, have been transformed into higher-risk and high-risk areas, and the quality of
the ecological environment has been degraded and reduced on a large scale.
3.3. Spatial Autocorrelation Analysis of Landscape Ecological Risk
(1)
Ecological risk global autocorrelation analysis
The calculated ecological risk indices for each risk plot for the years 2000–2020 were
imported into GeoDa software 1.8 to obtain Moran’s I scatter plots (global autocorrelation
analysis). As shown in Figure 6, Moran’s I index is greater than 0 in each year and shows
an increasing trend, indicating that the distribution of landscape ecological risk levels in the
Zhundong coalfield during the period from 2000 to 2020 has a spatial positive correlation,
and there is a clustering effect. Areas with high ecological risk values in the coalfield region
have similarly high ecological risk values in neighboring areas, and districts with lower
ecological risk values have lower ecological risk values in neighboring areas.
Sustainability 2023,15, 15972 10 of 16
Sustainability 2023, 15, x FOR PEER REVIEW 10 of 16
analysis). As shown in Figure 6, Moran’s I index is greater than 0 in each year and shows
an increasing trend, indicating that the distribution of landscape ecological risk levels in
the Zhundong coalfield during the period from 2000 to 2020 has a spatial positive corre-
lation, and there is a clustering effect. Areas with high ecological risk values in the coal-
field region have similarly high ecological risk values in neighboring areas, and districts
with lower ecological risk values have lower ecological risk values in neighboring areas.
Figure 6. Scaer plots showing ecological-risk Moran indices for the Zhundong coalfield during the
period 2000 to 2020.
(2) Local correlation analysis of ecological risks
Further local autocorrelation analysis of the ecological risk of the Zhundong coalfield
was carried out using the GeoDa software package, and the LISA aggregation map of the
research zone was obtained (Figure 7). In Figure 7, the spatial distribution of the ecological
risk index at each year (2000, 2005, 2010, 2015, 2020) is primarily dominated by the high–
high aggregation area and the low–low aggregation area, and both regions have a high
degree of consistency with the spatial distribution paern of ecological risk, with the low–
low aggregation area more centralized in its distribution. From 2000 to 2005, ecological
risk was primarily in the southwestern and northeastern regions; after 2005, the spatial
distribution of ecological risks changed, and the low–low aggregation area changed to be
mainly distributed in the west central and northeastern regions, which is related in recent
years to the ecological restoration measures at the Wucaiwan and Jiangjunmiao mines in
the west central region, such as the construction of reservoirs and ecological establishment
of forests, among others. In addition, the high–high aggregation area is primarily located
in the area where construction sites are concentrated and there are more human activities,
causing greater anthropogenic interference in poorly stabilized ecosystems. Thus, the de-
gree of loss in regional landscapes is also relatively higher.
Figure 6.
Scatter plots showing ecological-risk Moran indices for the Zhundong coalfield during the
period 2000 to 2020.
(2)
Local correlation analysis of ecological risks
Further local autocorrelation analysis of the ecological risk of the Zhundong coalfield
was carried out using the GeoDa software package, and the LISA aggregation map of
the research zone was obtained (Figure 7). In Figure 7, the spatial distribution of the
ecological risk index at each year (2000, 2005, 2010, 2015, 2020) is primarily dominated by
the high–high aggregation area and the low–low aggregation area, and both regions have a
high degree of consistency with the spatial distribution pattern of ecological risk, with the
low–low aggregation area more centralized in its distribution. From 2000 to 2005, ecological
risk was primarily in the southwestern and northeastern regions; after 2005, the spatial
distribution of ecological risks changed, and the low–low aggregation area changed to be
mainly distributed in the west central and northeastern regions, which is related in recent
years to the ecological restoration measures at the Wucaiwan and Jiangjunmiao mines in
the west central region, such as the construction of reservoirs and ecological establishment
of forests, among others. In addition, the high–high aggregation area is primarily located
in the area where construction sites are concentrated and there are more human activities,
causing greater anthropogenic interference in poorly stabilized ecosystems. Thus, the
degree of loss in regional landscapes is also relatively higher.
Sustainability 2023,15, 15972 11 of 16
Sustainability 2023, 15, x FOR PEER REVIEW 11 of 16
Figure 7. Distribution of local indicators of spatial autocorrelation (LISA) of ecological risks in the
Zhundong coalfield during 2000–2020.
4. Discussion
In recent years, China’s economic and social development has led to an increased
demand for coal. The development and utilization of coal resources in the Zhundong coal-
field is imminent, which is of great significance to the development of the Zhundong dis-
trict [49]. Land use and ecosystems are closely related to the changes caused by coal min-
ing and certainly cause changes in land types. Land use changes in mining areas are
closely related to the policies implemented by China’s government [50], which continues
to give aention to ecological environment, security, and protection. While there are fewer
studies on ecological risk assessment in the inland arid zones of northwest China, after
2005, there has been large-scale development of coal resources in the Zhundong region
and a lack of corresponding theoretical basis for ecological risk research in the same pe-
riod, with earlier approaches such as the ecological risk assessment model [51] being un-
able to cope with the increasing compound risks in the mining area. During this same
period, coal mining has caused high levels of damage to the ecological environment that
have not been thoroughly researched. Although the local mining areas have responded
positively to government policy and have vigorously promoted ecological restoration
measures, there are remaining problems with the ecological restoration measures imple-
mented in small areas. The effects of ecological restoration have been affected, so it is im-
portant to improve the efficiency of ecological risk assessment for the sustainable devel-
opment of ecosystems in arid zones [52]. Therefore, the paper analyzed the ecological risk
level in each region of the Zhundong coalfield by calculating the changes in the regional
ecological risk index based on the changes in land type during the period of 2000–2020.
This method has been adopted in many, study areas today and has proven to be advanta-
geous in mining areas [43,53] as well as in areas that are ecologically [54], and although
the limitations of the method in terms of assessment have been noted [55], it is still the
most suitable method for ecologically fragile areas in need of ecological restoration theo-
retical guidance at this stage [29]. The recommended ecological restoration measures are
as follows:
(1) For low-risk and lower-risk zones, the study found that the transition to high-risk
and high-risk zones should be controlled. The low-risk and lower-risk areas in the
Figure 7.
Distribution of local indicators of spatial autocorrelation (LISA) of ecological risks in the
Zhundong coalfield during 2000–2020.
4. Discussion
In recent years, China’s economic and social development has led to an increased
demand for coal. The development and utilization of coal resources in the Zhundong
coalfield is imminent, which is of great significance to the development of the Zhundong
district [
49
]. Land use and ecosystems are closely related to the changes caused by coal
mining and certainly cause changes in land types. Land use changes in mining areas are
closely related to the policies implemented by China’s government [
50
], which continues
to give attention to ecological environment, security, and protection. While there are fewer
studies on ecological risk assessment in the inland arid zones of northwest China, after
2005, there has been large-scale development of coal resources in the Zhundong region and
a lack of corresponding theoretical basis for ecological risk research in the same period,
with earlier approaches such as the ecological risk assessment model [
51
] being unable
to cope with the increasing compound risks in the mining area. During this same period,
coal mining has caused high levels of damage to the ecological environment that have not
been thoroughly researched. Although the local mining areas have responded positively to
government policy and have vigorously promoted ecological restoration measures, there
are remaining problems with the ecological restoration measures implemented in small
areas. The effects of ecological restoration have been affected, so it is important to improve
the efficiency of ecological risk assessment for the sustainable development of ecosystems in
arid zones [
52
]. Therefore, the paper analyzed the ecological risk level in each region of the
Zhundong coalfield by calculating the changes in the regional ecological risk index based
on the changes in land type during the period of 2000–2020. This method has been adopted
in many, study areas today and has proven to be advantageous in mining areas [
43
,
53
] as
well as in areas that are ecologically [
54
], and although the limitations of the method in
terms of assessment have been noted [
55
], it is still the most suitable method for ecologically
fragile areas in need of ecological restoration theoretical guidance at this stage [
29
]. The
recommended ecological restoration measures are as follows:
(1)
For low-risk and lower-risk zones, the study found that the transition to high-risk
and high-risk zones should be controlled. The low-risk and lower-risk areas in the
research zone are mainly the original local meadow land, forest land, and subsequent
ecological restoration forest and grassland areas. Precipitation is relatively scarce in
the research zone and must be supplemented by scientifically feasible methods to
Sustainability 2023,15, 15972 12 of 16
artificially restore tree plantations and grasses, such as a selection of local drought-,
saline-, and cold-resistant adaptive plants in the planting of forests and grass to take
advantage of the recent years of aridity in northwest China, the “green” trend [
56
],
and the promotion of local ecosystems and sustainable socioeconomic development.
However, improvements in ecosystem quality cannot be judged by the amount of
vegetation planted alone. After fieldwork in some areas of the Zhundong coalfield
during 2021 and 2022, this study found that the ecological restoration measures of
vegetation planting in the mining area also brought about a range of problems, such as
soil erosion and salinization. Therefore, the search for locally appropriate vegetation
planting methods requires a certain amount of scientific practice and should not be
considered as a temporary “greening”. As for the original forests and grasslands in
the local area, local government departments should try to avoid these areas when
planning for development and construction, and formulate good protection measures
to minimize the ecological damage caused by human activity.
(2)
For the higher and high-risk areas, the study concluded that the existing favorable
situation should be maintained. The higher and high-risk areas in the research zone
mainly refer to the original ecological fragility of the area and the extent of human
activity on the land, for which local government departments and corporations can
introduce advanced mining technology and the corresponding mining protection
measures, such as ecological restoration of the gangue landfill area of the mining
district. These sectors and businesses can also minimize the damage to the area around
the mining activity by optimizing the spatial layout of the mine. The mining area
is in an extremely arid zone, where groundwater is the primary source of water for
production and domestic use, and production and development should ensure water
resource conservation and prevent the further expansion into high- and higher-risk
zones areas, rather than focusing on the economic value brought by exploitation.
For the original ecologically fragile areas, it is possible to reduce the construction of
mining roads, control heavy metal pollution from mining and minimize damage to
sites outside construction and production areas.
(3)
The medium-risk areas in the research zone are mainly low- and high-risk interface
areas, which are ecological buffer zones. For the medium-risk zone, the transformation
to high-risk zones should be reduced and such transformation and the transformation
of low-risk zones to medium-risk zones can be prevented through relevant ecological
protection measures, such as planting suitable vegetation and constructing grass-
planting squares to stabilize sand with vegetation and prevent sand erosion, which
would be helpful in curbing further expansion of high-risk zones and subsequent
ecological degradation in the research zone.
There are several shortcomings in our analysis. For example, the land use category
of construction land does not distinguish between residential and mining construction
land, and therefore, the categories may not be sufficiently fine. In addition, for the selec-
tion of data, only five periods of data for a long time series (20 years) were chosen, and
the analysis of some specific years was not sufficiently detailed, such as not analyzing
the specific changes for each year in the study area during 2010–2015, but instead only
researching and analyzing based on changes in two-year images and fieldwork data, which
likely have some errors. Additionally, although land use change is closely related to the
ecosystem, this study did not take into account the effect of local elevation, climate, and
other natural sources of risk. As this study mainly refers to the impact of anthropogenic
activity factors, it still lacks decisiveness. Our approach needs to be more refined in further
research in order to seek a more in-depth and scientific analysis of changes in the spatial
pattern of ecological risk in the Zhundong coalfield region, and to put forward specific and
feasible ecological restoration and control measures for large-scale open-cast coal mines in
arid zones.
Sustainability 2023,15, 15972 13 of 16
5. Conclusions
This article analyzes the spatial changes in ecological risk in the Zhundong coalfield
region from 2000 to 2020, providing a scientific theoretical basis for the conservation of the
ecological environment in the research zone. In recent years, there have been few studies
that evaluate ecological risk in arid areas, and there is a lack of corresponding theoretical
foundations for the restoration of mines in the inland arid areas of northwest China. The
present study, however, is a useful exploration of the ecological restoration measures that
can be applied in the surface coal mines in northwest China, which is based on correlating
ecological risk and land use.
The study investigated the landscape pattern changes and ecological risk-level changes in
the Zhundong coalfield using five periods of land use data, arriving at the following conclusions:
(1) Most of the research zone is unused land. Between 2000 and 2020, the area of cultivated
land, water area, construction land, and unused land increased, while the area of
meadow land and forest land decreased. In particular, meadow land was transformed
into other types of land, which is closely related to the continuous development in the
area during the last few years, such as an increase in population, increasing need for
land, and expansion in the mining area.
(2) The ecological risk pattern of the research zone is clearly distributed, with the high-risk
and higher-risk areas consistently accounting for most of the total area of the research
zone during the 20-year period, with the area of the higher-risk zones decreasing
and then increasing, and the area of the high-risk zones continuing to decline. From
the general viewpoint of the Zhundong coalfield, the ecological risk index has been
reduced during the last 20 years, and the ecological environment quality is on an
improving trend, but most of the areas remain ecologically fragile. Changes in risk
level have a greater impact on the surrounding environment, and as shown from the
field visits, the medium-risk areas around the mine face a series of problems such as
water shortage and soil salinization. Scientific and feasible protection measures are
needed to protect the ecological environment from further deterioration.
(3)
During the 20-year period, the spatial distribution of the overall ecological risk in the
Zhundong coalfield has a positive correlation, with a high degree of aggregation, and
the spatial pattern of landscape ecological risk is more consistent with the variations
in the actual ecological risk index.
Author Contributions:
Investigation, T.Y., J.J. and A.A. (Adila Akbar); supervision, A.Z. writing—original
draft, B.O.; writing—review and editing, B.O. and A.A. (Abudukeyimu Abulizi). All authors have read
and agreed to the published version of the manuscript.
Funding:
This research was funded by the Key Project of Joint Funds of the National Natural Science
Foundation of China, “The coal resources of protective exploitation and environmental effects in
Xinjiang” (Grant No.U1903209) and the National Natural Science Foundation of China, “Assessment
and source identification of heavy metal exposures of wild animals in Xinjiang Kalamaili Mountain
Nature Reserve” (No. 42167058).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
The data used to support the findings of this study are available
upon request.
Acknowledgments:
We thank the Key Project of Joint Funds of the National Natural Science Foun-
dation of China and the National Natural Science Foundation of China, “Assessment and source
identification of heavy metal exposures of wild animals in Xinjiang Kalamaili Mountain Nature
Reserve”, for their support of this research.
Conflicts of Interest: The authors declare no conflict of interest.
Sustainability 2023,15, 15972 14 of 16
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