International Journal of Environmental Research and Public Health

Article Spatiotemporal Analysis and Control of Landscape Eco-Security at the Urban Fringe in Shrinking Resource Cities: A Case Study in Daqing, China

Xi Chen 1, Dawei Xu 1,2,*, Safa Fadelelseed 1,3 and Lianying Li 1,4 1 College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China; [email protected] (X.C.); [email protected] (S.F.); [email protected] (L.L.) 2 Key Lab for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province, Harbin 150000, China 3 Ministry of Agriculture, Horticulture Administration Sector, Landscape and Ornamental Plants Department, Elmogran 999129, Sudan 4 College of Art and Design, Harbin University, Harbin 150000, China * Correspondence: [email protected]; Tel.: +86-0451-8219-0984



Received: 17 October 2019; Accepted: 17 November 2019; Published: 21 November 2019


Abstract: As the main bearing area of the ecological crisis in resource-rich cities, it is essential for the urban fringe to enhance regional ecological security during a city’s transformation. This paper takes Daqing City, the largest oilfield in China’s cold land, as an example. Based on remote sensing image data from 1980 to 2017, we use the DPSIR (Driving forces, Pressure, State, Impact, Response) framework and spatial auto-correlation analysis methods to assess and analyze the landscape eco-security change of the study area. From the perspective of time–space, the study area is partitioned, and control strategies are proposed. The results demonstrate that: (1) The landscape eco-security changes are mainly affected by oilfield exploitation and ecological protection policies; the index declined in 1980–2000 and increased in 2000–2017. (2) The landscape eco-security index has obvious spatial clustering characteristics, and the oil field is the main area of warning. (3) The study area determined the protection area of 1692.07 km2, the risk restoration area of 979.64 km2, and proposed partition control strategies. The results are expected to provide new decision-making ideas in order to develop land use management and ecological plans for the management of Daqing and other resource shrinking cities.

Keywords: landscape ecological security; spatial control; urban fringe; resource city; spatiotemporal analysis

1. Introduction Resource cities, especially resource depleted or reduced cities (such as oilfields), are facing enormous challenges to their ecological environment including: abundance industries and oilfields, densification and abandonment, and pollution and built environment legacies [1–4]. As an important reserved land resource and an ecological crisis bearing area, the area on the urban fringe (especially in resource-rich cities) is in a period of continuous transition, with diversified land use patterns and a fragile ecological environment, which seriously threatens regional ecological security [5–8]. Therefore, there is an urgent need to stabilize and enhance the ecological security of the urban fringe in shrinking resource cities. Landscape eco-security assessment based on land use is the basis for ecological security pattern construction [9–12]. Although the establishment of a landscape eco-security assessment system is relatively mature, it is seldom used in the urban fringe, especially in resource cities. Based on geographic

Int. J. Environ. Res. Public Health 2019, 16, 4640; doi:10.3390/ijerph16234640 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2019, 16, 4640 2 of 26 information systems/remote sensing (GIS/RS) technology, using the pressure–state–response (P-S-R) framework to establish an indicator for the assessment of ecological security, and combining popular assessment methods including hierarchical clustering methods, the comprehensive index method, the analytic hierarchy process (AHP) has been recognized and widely applied worldwide [13–16]. Since its founding, the PSR framework has also experienced theoretical and methodological development; the DPSIR (Driving forces, Pressure, State, Impact, Response) framework is the outcome of this development [17–19]. DSPIR is more suitable for the complex situations of resource cities in this study. In recent years, studies on landscape eco-security assessment system are no longer limited to fixed time points. Moreover, the evolution and trends of landscape eco-security have gradually received attention. An analysis of the causes of changes can provide a strong basis for future policy-making [20–22]. The spatial warning and control of landscape eco-security are a direct and effective way to enhance regional ecological security. In recent years, space partitions are becoming more and more detailed, but they are still based on the current situation [23,24], which ignores the dynamics and stability of landscape eco-security. Therefore, in this study, space partitions should consider the spatial and temporal changes of landscape eco-security. The spatial partitioning method is the key to space control. There are two main spatial partitioning methods: One is an overlay method that emphasizes the vertical process between the natural environment, human activities, and land use changes in the landscape unit [25]. The other is a method of using model partitioning to emphasize the landscape level process represented by the minimum cumulative resistance model (MCR). Both methods have a different emphasis and should be given comprehensive consideration in this study [26,27]. At present, there are 262 resource cities in China, while 88% of cities are experiencing or are about to experience recession and transition [28]. This paper takes the urban fringe of Daqing City in Heilongjiang Province as an example. Daqing is a famous petroleum city; however, the peak period of oil production in this city has passed, and the city is about to enter a new period of transformation and development. Therefore, we use Daqing as a forward-looking and representative example for enhancing the landscape eco-security of the urban fringe in a resource city. In order to enhance the landscape eco-security of the urban fringe in Daqing, based on the 1980–2017 landscape eco-security assessment, this paper analyzes the trends of and reasons behind landscape eco-security changes, identifying the spatial control scope and proposing spatial control strategies. This paper’s significance is as follows: (1) We use the DPSIR framework to construct an assessment model and analyze its temporal and spatial variation characteristics, making up for the lack of basic research on the urban fringe of resource cities. (2) Based on time and space analyses, we combine the MCR model and the overlay methods for space partitions, which provides a new partition idea for the space control of resource cities. (3) We analyze the influencing factors of landscape eco-security changes and a proposal for space control strategies to provide support for ecological security construction in the urban fringe of Daqing.

2. Materials and Methods

2.1. Study Area

The city of Daqing, Heilongjiang Province (123◦450 E–125◦470 E, 45◦230 N–47◦290 N) is located in the hinterland of Songnen Plain, with flat terrain and a relatively concentrated distribution of farmland, grassland, and woodland. Daqing Oilfield, once the largest oilfield in China, is also a world famous super large continental oilfield. Its unique oil resources led to the city’s rise from a pasture with a population of less than 20,000 to a petrochemical city with a population of millions. The study area is located inside the main urban area of Daqing City, outside the central city, and is jointly managed by the oilfield and the administration, with a total area of 2695 km2 (Figure1). According to the administrative division, this area is managed by the Ranghulu District, Saertu District, Longfeng District, and Honggang District. The oilfield mainly includes the second, third, fourth, fifth, and sixth Oil Production Plants of Daqing. The oilfield area is large and distributed in a strip shape. Except for Int. J. Environ. Res. Public Health 2019, 16, 4640 3 of 26 Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 3 of 27 the necessaryExcept for recourse the necessary exploitation recourse demand, exploitation the oilfielddemand, is hardlythe oilfield affected is hardly by other affected construction by other land. construction land. At present, most of the oil wells are still in service. However, with the exploitation At present, most of the oil wells are still in service. However, with the exploitation of resources and the of resources and the development of cities, a large amount of abandoned land will be produced in development of cities, a large amount of abandoned land will be produced in the study area. the study area.

FigureFigure 1. 1. LocationLocation of of the the study study area. area.

DaqingDaqing was was established established due due to to the the exploration exploration an andd development development of ofoil oil fields, fields, so the so development the development of the study area is closely related to the exploitation of oil resources. The area’s oil-derived properties of the study area is closely related to the exploitation of oil resources. The area’s oil-derived properties make it unique in its natural resources and land space compared to other cold oil fields in China. make it unique in its natural resources and land space compared to other cold oil fields in China. With the development of oil and the growth of the local economy, the city’s development has obvious Withphases the development of development, of oil which and thecan growthbe divided of theinto local three economy, stages: budding, the city’s development, development andhas decline obvious phasesand of transformation development, (Figure which can2). Before be divided 1960, intoDaqi threeng was stages: a pasture. budding, After development, 1960, because and of the decline and transformationdiscovery of oil, (Figurethe city2 began). Before to develop. 1960, Daqing Since was1979, a the pasture. city officially After 1960, started because construction. of the discoveryAfter of oil,2000, the due city to began the reduction to develop. of oil Since production 1979, the and city the offi impactcially startedof national construction. environmental After protection 2000, due to the reductionpolicies, Daqing of oil productionhas started to and formulate the impact a series of nationalof ecological environmental environmental protection protection policies, policies. Daqing In has startedthe approval to formulate of construction a series projects, of ecological laws and regu environmentallations, such as protection the environmental policies. protection In the approval law of construction projects, laws and regulations, such as the environmental protection law and the Environmental Impact Assessment Law, have been strictly observed. In terms of pollution control, these laws control the total amount and increment of pollution discharge. Emergency plans for heavy Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 4 of 27 Int. J. Environ. Res. Public Health 2019, 16, 4640 4 of 26 and the Environmental Impact Assessment Law, have been strictly observed. In terms of pollution control, these laws control the total amount and increment of pollution discharge. Emergency plans pollutionfor heavy weather pollution in Daqingweather City,in Daqing as well City, as an as implementation well as an implementation plan for strengthening plan for strengthening water and soilwater pollution and soil control pollution in Daqing control City, in Daqing have been City, issued. have been In terms issued. of In natural terms protection, of natural protection, the project ofthe returningproject of grazing returning land grazing to grassland, land rotationalto grassland, grazing, rotational the “Weathered, grazing, the Sandy “Weathered, and Salinized” Sandy land and renovation,Salinized” land and renovation, afforestation and have afforestation been carried have out. been Wetland carried protectionout. Wetland has protection also been has promoted, also been naturepromoted, reserve nature management reserve management and protection and have protection been strengthened, have been strengthened, several reservoirs several in Daqing reservoirs have in beenDaqing expanded have been and expanded protected, and and protected, the project and of controlling the project a of hundred controlling ponds a hundred have been ponds implemented have been sinceimplemented 2000. The since ecological 2000. spatialThe ecological pattern ofspatial “landscape, pattern forest, of “landscape, farmland, forest, and water” farmland, is thus and becoming water” is clearer.thus becoming In oilfield clearer. construction, In oilfield “green construction, environmental “green protection” environmental has been protection” consistent has throughout been consistent the processthroughout of oil the field process operations of oil andfield has operations gradually and attached has gradually importance attached to developing importance the to developing ecological environmentthe ecological of theenvironment oil field. Inof 2016, the oil a 40 field. km2 oilIn field2016, ecologicala 40 km2construction oil field ecological demonstration construction area wasdemonstration built. area was built.

FigureFigure 2. 2.Urban Urban development development context context of of the the study study area. area.

2.2.2.2. Data Data and and Land Land Use Use Classification Classification Criteria Criteria TheThe remote remote sensing sensing image image data data in this in studythis study were were taken taken from thefrom United the United States Geological States Geological Survey (USGS).Survey According(USGS). According to Figure 1to, theFigure MSS, 1, TM,the MSS, ETM TM,+, and ETM+, OLI-TIRS and OLI-TIRS images taken images by Landsattaken by satellite Landsat insatellite 1980, 1990, in 1980, 2000, 1990, 2010, 2000, and 2017 2010, were and selected 2017 were (Table selected1). Other (Table auxiliary 1). Other materials auxiliary were materials from Daqing were Generalfrom Daqing Planning, General the Daqing Planning, Statistical the Daqing Yearbook, Statistical the Daqing Yearbook, Oilfield Statisticalthe Daqing Yearbook, Oilfield theStatistical China StatisticalYearbook, Yearbook, the China and Statistical the China Yearbook, Agricultural and the Product China PriceAgricultural Survey YearbookProduct Price (Table Survey2). Yearbook (Table 2). Table 1. Remote sensing information at different times.

SatelliteTable Date 1. Remote Data sensing Type information Band at Resolution different times. Cloud Kappa SatelliteLANDSAT1–3 Date 1980.07 Data MSS Type Band 4 30Resolution M 0Cloud 83.3% Kappa LANDSAT1–3LANDSAT4–5 1980.07 1990.07 MSS TM 7 4 30 M 30 M 00 85.4% 83.3% LANDSAT7 2000.07 ETM+ 7 30 M 0.01 86.8% LANDSAT4–5LANDSAT8 1990.07 2010.07 OLI–TIRS TM 11 7 30 M 30 M 00 87.1% 85.4% LANDSAT7LANDSAT8 2000.07 2017.07 OLI–TIRS ETM+ 11 7 30 M 30 M 0.01 0.01 87.8% 86.8% LANDSAT8 2010.07 OLI–TIRS 11 30 M 0 87.1% LANDSAT8 2017.07Table 2. SocioeconomicOLI–TIRS information11 1980–2017. 30 M 0.01 87.8%

NameTable 2. Socioeconomic information 1980–2017. Contents The boundary of the urban fringe; the specific content of the Daqing Urban Planning Name plan (especially in ecologicalContents environment construction) The boundary of the urban fringe; the specific content of the plan Daqing Urban Planning Oilfield production; population; GDP; pollution Daqing Statistical Yearbook (especiallyconsumption; in ecological the environment primary, secondary, construction) and tertiary output Oilfield production;value; environmental population; protection GDP; pollution investment; consumption; population; the Daqing Oilfield Statistical Statistical Yearbook Yearbook primary, secondary, Oilfield scope; and oilfield tertiary ecological output constructionvalue; environmental plan; protection GDP;investment; mineral population; production (especially oilfield); pollution China Statistical Yearbook Daqing Oilfield Statistical consumption; population; Oilfield scope; oilfield ecological construction plan; HeilongjiangYearbook Agricultural Product Price Planting area of grain crops in Daqing; total output value of Survey Yearbook grain crops in Daqing;

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The land use types in the study area are divided into eight types (Table3): woodland, high coverage grassland, medium coverage grassland, low coverage grassland, water area, farmland, construction land, saline-alkali land and others (Figure A1). This classification system is based on multi-source land use data, referring to the “Classification of Land Use Status of the People’s Republic of China” (GB/21010–2007), the “China Resources and Environment Database” land use remote sensing classification system of the Chinese Academy of Sciences, and combining remote sensing images with the regional characteristics of the study area.

Table 3. Classification system of land use in the study area.

I II Description Woodland Forest land; shrub land; open forest land; High coverage grassland Grassland coverage >50%; Ecological land Medium coverage grassland Grassland coverage ranges from 20% to 50%; Low coverage grassland Grassland coverage ranges from 5% to 20%; Water Reservoirs; ponds; lakes; marshes; Farmland Dry land; paddy field; Non-ecological land Construction land Rural; Urban; industrial and transportation land; Saline-alkali land and others Saline-alkali land; other unused land;

2.3. Methods

2.3.1. A Landscape Eco-Security Assessment System Based on the DPSIR Framework (1) Establishment of the assessment system and the determination of weight In this study, the DPSIR framework was used to assess landscape eco-security. In the DPSIR assessment model, “Driving forces” refers to the fundamental driving force and the potential incentive for environmental change, mainly due to the changes brought about by economic and urban development. “Pressure” is the direct cause of the changes in the ecological environment of the research area, which mainly refers to the impact of human activities on the natural environment, such as the exploitation of oil resources and the discharge of waste. “State” is the actual situation of ecological environment under pressure, which is mainly reflected by the proportion and change of grassland coverage and non-ecological land. “Impact” refers to the impact of the state on the ecological environment, which is specifically reflected by the ecological risk, ecosystem service value, and ecological resilience. “Response” refers to policies formulated by human beings to promote sustainable development, such as increasing investment to improve resource utilization efficiency and reducing pollution (Figure3). According to the specific characteristics and study purpose of the research area, combined with a study of the relevant literature, the assessment system is designed using five dimensions (driving forces, pressure, state, impact, and response), and seven indicators. On the basis of the analytic hierarchy process (AHP) and the suggestions of 15 experts (including those from the fields of urban planning, landscape architecture, ecology, environmental science, and petroleum engineering), the weight of the index layer and the value of the index were obtained (Table4). In addition, the units and ranges of the selected indicators in the P-S-R framework were different, and the linear normalization function was used to standardize each indicator. The equation is as follows:

x min y = g(x) = − max min − where y is a range from 0 to 1, and x is the normalized value; Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 6 of 27

and the linear normalization function was used to standardize each indicator. The equation is as follows: x − min y = g(x)= max − min Int. J. Environ. Res. Public Health 2019, 16, 4640 6 of 26 where y is a range from 0 to 1, and x is the normalized value;

FigureFigure 3. 3.DPSIR DPSIR modelmodel ofof ecologicalecological environment quality quality evolution evolution in in the the study study area. area.

TableTable 4. 4.Landscape Landscape ecologicalecological securitysecurity assessment system of of the the urban urban fringe fringe in in Daqing. Daqing.

Dimension Weight Sub-DimensionSub- Indicator Weight ( ) Dimension Weight Indicator Weight ±(±) Dimension D1—Urbanization growth D—Driving forces 0.05 Urbanization 0.5 (+) intensityD1—Urbanization (UGI) growth D—Driving forces 0.05 Urbanization 0.5 (+) Economy; D2—Perintensity capita (UGI) GDP 0.5 (+) — Economy; P1—ResourceD2 Per capita Curse GDP 0.5 (+) P—Pressure of Oil production 0.5 (+) 0.2 CoeP1—Resourcefficient (ES ) Curse landscape change Oil production i 0.5 (+) P—Pressure of P2—EnvironmentalCoefficient (ESi) 0.2 Environment 0.5 (+) landscape change performanceP2—Environmental index (EPI) Environment 0.5 (+) S1—Grassland degradation performance index (EPI) 0.25 ( ) Ecological land intensity (K ) − S—State of land use 0.2 S1—Grasslandi1 degradation S2—Grassland restoration 0.25 (−) intensity (Ki1) 0.25 (+) Ecological landintensity (Ki2) Non-ecological S3—ProportionS2—Grassland of restoration S—State of land use 0.2 0.50.25 ( (+)) land non-ecologicalintensity (K landi2) (Ui) − Non-ecologicalI1—Ecological S3—Proportion risk index of non- I—Impact of the Risk 0.50.5 ( ()−) land (ERIecologicalk) land (Ui) − landscape ecological 0.5 I2—Ecological resilience system Resilience I1—Ecological risk index 0.25 (+) Risk (ECOres) 0.5 (−) (ERIk) I—Impact of the I3—Ecosystem service value Service I2—Ecological resilience 0.25 (+) landscape ecological 0.5 Resilience (ESV) 0.25 (+) R1—Intensity(ECOres) of input R—Humansystem response 0.05 Human 1 (+) ecologicalI3—Ecosystem construction service (IEC) Service 0.25 (+) value (ESV) R1—Intensity of input (2) Index computing method R—Human response 0.05 Human ecological construction 1 (+) Combining expert opinions with the relevant references(IEC) [29–33], the specific index calculation methods are shown in Table5.

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Table 5. Index computing method for landscape ecological security assessment.

Indicator Equation Description

Ubd is the urbanization index of the study city d in year-b, Uad is

Ubd Uad urbanization index of the study city d in year-a, Ub is the national D1 UGI = U −U b− a urbanization index in year-b, and Ua is the national urbanization index in year-a.

Pn Ei/ i=1 Ei Ei is the resource production in region i, SIi is the output value of P1 ESi = Pn SIi/ i=1 SIi secondary industry in region i, and n is the number of regions.

xi is the total consumption of urban i or pollutant i of the study city xi/gd P2 EPI = d; Xi is the total consumption of urban i or pollutant i in China; gd is Xi/G the GDP of the study city d; and G is the national GDP.

∆Sit1 is the area of grassland transferred to lower coverage S1 K = ∆Sit1 1 grassland, construction land, saline–alkali land, and others. S is the i1 Sit ∆t it × area of grassland at the start of the study, and ∆t is the time interval.

∆Sit2 is the area of grassland transferred to higher coverage S2 K = ∆Sit2 1 grassland, water, and woodland. S is the area of grassland at the i2 Sit ∆t it × start of the study, and ∆t is the time interval. S is the area of non-construction land. A is the total area of S3 Ui = Si i A sampling block i.

Aki is the area of land use type i in study area k, Ak is the area of n P Aki ( ) study area k, Ei is the interference index of land use type i I1 ERIk = A Ei Fi i=1 k × (Table A1), Fi is the vulnerability index of land use type i (Table A2), and n is the number of land use types.

n Ai is the area of land use type i in study area, Pi is the elastic score of P  A P  I2 ECO = i× i land use type i, and n is the number of land use types. C is the res Ci i i=1 landscape fragmentation index of land use type i (Table A3). A is the area of land use type i in study area, VC is the total value Pn i i I3 ESV = A VC coefficient of ecological function per unit area of land use type i i × i i=1 (Table A4), and n is the number of land use types.

EId is the amount of investment in ecological construction of the R1 IECd = EId/gd study city d, and gd is the GDP of the study city d.

(3) The assessment unit determination Because the research area is under the jurisdiction of different administrative regions and oilfields, it needs clear analytical units to reflect the specific spatial differences at an objective level. In this paper, the grid and quadrant are two levels of evaluation units (Figure4). Because there is no uniform standard for the selection of the assessment grid unit [34–36], this paper selects a 1 1 km grid as the × basic unit based on the test of the satellite, the land use classification, and the study area (especially the density of well in oilfield). Taking the center of the study area as the starting point, the area is divided into eight quadrants: north, north-east, east, south-east, south, south-west, west, and north-west. Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 8 of 27

(especially the density of well in oilfield). Taking the center of the study area as the starting point, the Int.area J. Environ.is divided Res. Publicinto Healtheight 2019quadrant, 16, 4640s: north, north-east, east, south-east, south, south-west, west, 8 ofand 26 north-west.

(a) (b)

FigureFigure 4. 4.Determination Determination ofof thethe areaarea of of analysis analysis ( a(a);); 1 1 × 11 kmkm assessmentassessment unitunit ((bb);); quadrantquadrant division division of of × thethe study study area. area.

2.3.2.2.3.2. SpatialSpatial Auto-CorrelationAuto-Correlation AnalysisAnalysis (1)(1) GlobalGlobal auto-correlation auto-correlation analysis analysis TheThe global global spatial spatial auto-correlation auto-correlation describes describes the spatial the spatial aggregation aggregation characteristics characteristics of the attribute of the valuesattribute in values the whole in the study whole area. study Global area. Global Moran’s Mo Iran’s is the I is most the most commonly commo usednly used analysis analysis index index at presentat present [37 ].[37]. It canIt can measure measure the the aggregation aggregation or or dispersion dispersion degree degree of of the the spatial spatial distribution distribution of of thethe landscapelandscape eco-security eco-security index index in in the the study study area. area. The The equation equation is is as as follows: follows:

n m Pn Pm    (  ) WijxWi ij− xxi ()xxj −xj x x n n i=1 j=1 − − 1 Xn 2 1 X n MoranisI==1 =j 1 ,S22 = 1 (x x)2, x = 1x Moran`sI = 0 n m S = ()ixi − x ,x = i xi n 2 Pm P n  − n  2 S Wij ni=i 1=1 i=1n i =1 S i=1 jW=ij1 i==1 j 1 , where Xi is the observation value of the i-th region, n is the number of the raster, and Wij is a binary adjacent-spacewhere Xi is the weightobservation matrix, value indicating of the i-th the regi adjacenton, n is relationship the number of of the the spatial raster, objects.and Wij Theis a binary value rangeadjacent-space of Moran’s weight I index matrix, is between indicating1 and the 1.adjacent Under relationship the premise of athe Z-score spatial significance objects. The test, value if − Moran’srange of IMoran’s> 0, the I attribute index is valuesbetween are − positively1 and 1. Under correlated the premise in space, of anda Z-score the larger significance the index, test, the if denserMoran’s the I spatial> 0, the distribution. attribute values If Moran’s are positively I < 0, the co attributerrelated values in space, arenegatively and the larger correlated the index, in space, the anddenser the the smaller spatial the distribution. index, the moreIf Moran’s discrete I < 0, the the spatial attribute distribution. values are Ifnegatively Moran’s Icorrelated= 0, the attribute in space, valuesand the are smaller randomly the distributedindex, the more in space. discrete the spatial distribution. If Moran’s I = 0, the attribute values are randomly distributed in space. (2) Local Spatial Auto-Correlation Analysis (2) Local Spatial Auto-Correlation Analysis A global spatial auto-correlation analysis can reveal the overall spatial dependence, but for the spatialA auto-correlation global spatial auto-correlation analysis of larger analysis regions, can it is reveal insuffi thecient overall to analyze spatial the dependence, whole area. but Therefore, for the inspatial order auto-correlation to study the possible analysis local of spatial larger aggregationregions, it relationship,is insufficient the to hot-spotanalyze analysisthe whole method area. andTherefore, hot-spot in optimization order to study analysis the possible (local spatiallocal spat auto-correlationial aggregation analysis relationship, method) the are hot-spot introduced analysis to exploremethod the and spatial hot-spot aggregation optimization degree analysis of the landscape (local spatial eco-security auto-correlation index distribution analysis ofmethod) individual are evaluationintroduced units. to explore the spatial aggregation degree of the landscape eco-security index distribution of individualHot-spot analysisevaluation calculates units. the Z scores between patches based on the Getis–Ord Gi* statistical indexHot-spot in the GIS analysis platform, calculates which canthe directlyZ scores reflect between the patches agglomeration based on of the a high Getis–Ord value area Gi* (hot-spotstatistical index in the GIS platform, which can directly reflect the agglomeration of a high value area (hot-spot

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area) and a low value area (cold point area) in space [38]. The higher the Z value, the more obvious area)the agglomeration and a low value of areathe hot-spot (cold point area. area) The in equation space [38 is]. as The follows: higher the Z value, the more obvious the agglomeration of the hot-spot area. The equationn is as follows:n wijxj − X wij n n * jP==1 Pj 1 Gi = wijxj X wij j=1 − j=1 2 n  n  Gi∗ =   tv  2  2  n  Pnwij − Pn wij  n w 2   w   = ij   =ij   j 1j=1 − j=1j 1  S S nn==1 1 where Xj is the attribute value of the plaque j; wij is the spatial weight matrix between the plaque i and where Xj is the attribute value of the plaque j; wij is the spatial weight matrix between the plaque i the plaque j; and n is the total plaque number. and the plaque j; and n is the total plaque number. Hot spot optimization analysis is based on the Optimized Hot Spot Analysis tool (Arcgis 10.5). Hot spot optimization analysis is based on the Optimized Hot Spot Analysis tool (Arcgis 10.5). This tool can interrogate data to automatically select parameter settings that will optimize the hot-spot This tool can interrogate data to automatically select parameter settings that will optimize the hot- results. It will aggregate incident data, select an appropriate scale of analysis, and adjust the results spot results. It will aggregate incident data, select an appropriate scale of analysis, and adjust the forresults multiple for multiple testing andtesting spatial and dependence.spatial dependence. In this In paper, this paper, this tool this is tool used is to used predict to predict the trend the trend of the spatialof the aggregationspatial aggregation of landscape of landscape eco-security eco-security and identify and identify risk warning risk warning areas. areas. 2.3.3. Space Partition Methods 3.3.3. Space Partition Methods (1) Overlay analysis (1) Overlay analysis The space of the study area was partitioned from the perspective of time–space, considering The space of the study area was partitioned from the perspective of time–space, considering the the past, present, and future landscape eco-security changes of the study area for comprehensive past, present, and future landscape eco-security changes of the study area for comprehensive identificationidentification andand partitioning.partitioning. TheThe 20102010 and 2017 hotspot analysis and and 2017 2017 hotspot hotspot optimization optimization analysisanalysis results results were were overlaid overlaid to identifyto identify the the ideal id protectioneal protection area, area, the core the protectioncore protection area, thearea, bottom the linebottom protection line protection area, the ecologicalarea, the potentialecological area, potent theial risk area, supervisory the risk area, supervisory the risk preventionarea, the risk area, theprevention key restoration area, the area, key and restoration the core area, restoration and the area core (Figure restoration5). area (Figure 5).

FigureFigure 5.5. Partitioning standards.

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(2) Resistance analysis The resistance surface reflects the trend of the spatial expansion of the ecological flow [39]. This paper uses the minimum cumulative resistance (MCR) model to determine the extent of the protected area. The core protection area, the bottom line area, and the ecological potential area were selected as the ecological source. Based on the hotspot analysis superposition results and the classification of land status, the resistance index system was constructed, whose weight was determined based on 15 experts’ suggestions (Table6). We calculated the resistance surface using the MCR model and considered the ideal protection area to identity the scope of the protection area. In the protection area, the construction land and farmland were determined as ecological conflict areas, and the spaces that do not overlap with the ecological source were determined as the protection buffer area. The MCR equation is as follows: iX=m MCR = fmin D R ij × i j=n where f is the unknown negative function, indicating the negative correlation between the minimum cumulative resistance and ecological suitability; min represents the minimum value of the cumulative resistance of a landscape unit to the source; Dij is the spatial distance from source j to landscape unit i; and R is the resistance coefficient of the landscape unit i to the motion process. D R is used to i ij × i measure the relative accessibility of a path from its source to a point in space.

Table 6. Establishment of the resistance surface.

Dimension Weight Indicator Resistance Value Water 1 Woodland 2 High coverage grassland 3 Medium coverage grassland 4 Land use 0.5 Low coverage grassland 5 Farmland 6 Saline–alkali land and others 7 Construction land 8 Core protection area (including Bottom line 1 protection area) Ecological potential area 2 Ideal protection area 3 Overlying 0.5 Other area 4 result Risk supervisory area 5 Risk prevention area 6 Key restoration area 7 Core restoration area 8

3. Results

3.1. Trend of the Landscape Eco-Security Index The landscape eco-security index of the study area showed a fluctuating downward trend, in which the index declined in 1980–2000 and increased in 2000–2017 (Figure6). Among these dates, 1980–1990 is the maximum range of decline, and 2000–2010 is the maximum range of increase. The trend of the impact index is consistent with the trend of the landscape eco-security index. The impact index changes of the different quadrants in the study area show that (Figure7) the main change period within the oilfields dominated by the north–south direction is 1980–1990. During this period, the index of the north mainly increased due to an increase in the ESV, the index of south mainly declined due to the increase in the index of ERI, and the index of ECO declined. The main change areas on the outside of the oilfields are north-west, west, and south-west. The main change years are 1980–1990 Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 11 of 27 Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 11 of 27 Int.declined J. Environ. due Res. to Public the increase Health 2019 in, 16 the, 4640 index of ERI, and the index of ECO declined. The main change 11 of 26 declinedareas on thedue outside to the increaseof the oilfields in the areindex north-west of ERI, and, west, the and index south-west. of ECO declined. The main The change main years change are areas1980–1990 on the and outside 2000–2010. of the oilfieldsDue to the are increase north-west in the, west, index and of south-west. ERI, the landscape The main eco-security change years index are and 2000–2010. Due to the increase in the index of ERI, the landscape eco-security index of the study 1980–1990of the study and area 2000–2010. showed a Duedownward to the increase trend in in1980–1990. the index Influenced of ERI, the by landscape the decline eco-security of the ERI index area showed a downward trend in 1980–1990. Influenced by the decline of the ERI index in the ofin the studysouth-west area showed and north-west a downward and the trend rise in of 1980–1990. the ESV index Influenced in the west, by the the decline landscape of the eco-security ERI index south-west and north-west and the rise of the ESV index in the west, the landscape eco-security index inindex the south-westshowed an andupward north-west trend in and 2000–2010. the rise of the ESV index in the west, the landscape eco-security indexshowed showed an upward an upward trend intrend 2000–2010. in 2000–2010.

1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 1980 1990 2000 2010 2017 1980Drving forces 1990Pressure 2000 2010State 2017 Drving forces Pressure State Impact Response Landscape eco-security Impact Response Landscape eco-security

Figure 6. Changing trend of the landscape eco-security index in the study area. Figure 6. ChangingChanging trend trend of the landscape eco- eco-securitysecurity index in the study area.

North North 0.8 0.35 North North Northwest 0.750.8 Northeast 1980 Northwest 0.350.3 Northeast 1980 0.7 0.25 Northwest 0.75 Northeast 1980 Northwest 0.3 Northeast 1980 0.650.7 1990 0.250.2 1990 0.650.6 1990 0.150.2 1990 West 0.550.6 East 2000 West 0.150.1 East 2000 West 0.55 East 2000 West 0.1 East 2000 2010 2010 2010 2010 Southwest Southeast 2017 Southwest Southeast 2017 Southwest Southeast Southwest Southeast South 2017 South 2017 South South

(a) (b) (a) (b)

North North 0.85 0.35 North North Northwest 0.850.75 Northeast 1980 Northwest 0.350.3 Northeast 1980 0.65 0.25 Northwest 0.750.55 Northeast 1980 Northwest 0.3 Northeast 1980 0.65 1990 0.250.2 1990 0.550.45 0.35 1990 0.150.2 1990 West 0.45 East West East 0.350.25 2000 0.150.1 2000 West 0.25 East 2000 West 0.1 East 2000 2010 2010 2010 2010 Southwest Southeast 2017 Southwest Southeast 2017 Southwest Southeast Southwest Southeast South 2017 South 2017 South South

(c) (d) (c) (d) Figure 7. Landscape impact layer index changes in 8 directions ( a). Trend Trend of the impact index in 8 Figuredirections 7. Landscape (b).). Trend ofimpact the ERI layer index index in 8 changesdirections directions in ( c8). directions Trend Trend of the the(a). ECO ECO Trend index index of thein in different di impactfferent indexquadrants in 8 directions(d).). Trend ( ofofb). thethe Trend ESVESV of indexindex the ERI inin 8 8index directions.directions. in 8 directions (c). Trend of the ECO index in different quadrants (d). Trend of the ESV index in 8 directions.

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3.2. Spatial Auto-Correlation Trend

3.2.1. Global Auto-Correlation Analysis From 1980 to 2017, the Moran’s I index > 0 and p-value < 0.01. This indicates that the landscape eco-security distribution of the Daqing urban fringe has a significant spatial positive correlation (Table7). Therefore, the landscape eco-security index in the study area has obvious spatial clustering characteristics.

Table 7. Results of the global auto-correlation analysis in the study area.

Global Auto-Correlation Index 1980 1990 2000 2010 2017 Moran’s Index 0.473113 0.509808 0.493504 0.473886 0.502602 Expected Index 0.000427 0.000427 0.000427 0.000428 0.000428 − − − − − Variance 0.000234 0.000241 0.000234 0.000235 0.000234 Z-score 30.932970 32.874252 32.260210 30.921220 32.884483 P-value 0.000000 0.000000 0.000000 0.000000 0.000000

3.2.2. Local Spatial Autocorrelation Analysis Hotspot analysis shows (Figure8), using the method of the spatial fracture point, the spatial aggregation degree (Giz-score) of the study area is divided into seven grades: cold spots-high, cold spots-middle, cold spots-low, not significant, hot spots-high, hot spots-middle, and hot spots-low. The proportion of the hot-spot area was larger than that of the cold spot in 1980–2017 (Figure9). The hotspot areas decreased year by year, and the cold spot areas continued to rise. This indicates that although the landscape eco-security increased with fluctuations, the low index aggregation areas continue to increase. The main changes occurred in 1980–1990 and 2000–2010. Therefore, we should control the area of low aggregation’s degree in the future to prevent an increase of its area. The hot-spot optimization analysis shows that there is a large coupling between the cold-spot gathering location and the oilfield location (Figure 10), which is the future risk warning area. According to the quadrant analysis (Figure 11), the cold-spot proportion is mainly concentrated in the south, south-east, north, and north-east. Among these areas, cold spots-high are mainly distributed in north and south. The hotspots distribution is opposite that of the cold spots. Hotspots are mainly concentrated in the west, south-west, north-west, and east. Among these areas, the hot spots-high proportion is high in the west and northwest. The change of aggregation is mainly concentrated in the south, south-west, west, east, north-east, and south-east. North of the cold-spot proportion continues to increase, while the hot spot continues to decrease where the oilfield is located. West of the hot-spot proportion increased, while the cold-spot proportion decreased in 1980–1990. West of the hot-spot proportion decreased in 2000–2010. The south-west trend is opposite to that of the west. Both the area north-east of the cold-spot proportion and the hot-spot degree increased in 1980–1990; the 2000–2010 change of the north east is opposite to that of 1980–1990. The area south-east of the cold-spot proportion decreased, while the hot spot increased in 1980–1990. The area south-east of the cold-spot proportion increased, while the hot-spot proportion decreased in 1990–2017. The area east of the cold-spot proportion increased, while the hot-spot proportion decreased in 1980–1990.

3.3. Space Partition Based on the 2010–2017 hot-spot analysis and the hot-spot optimization analysis in 2017, we identified a risk warning area of 979.64 km2, of which the core restoration area is 46.54 km2, the key restoration area is 241.98 km2, the risk prevention area is 106.39 km2, the risk supervision area is 357.13 km2, and the ecological potential area is 227.59 km2. We identified the bottom line protection area as 106.29 km2, while the core protection area is 222.85 km2, and the ideal protection area is 296.76 km2 (Figure 12). The bottom line protection area and the core protection area are identified as ecological sources, and the ecological potential area is identified as a potential ecological source. Int.Int. J. Environ. J. Environ. Res. Res. Public Public Health Health2019 2019,,16 16,, 4640x FOR PEER REVIEW 13 of 13 27 of 26

theInt. resistance J. Environ. Res. analysis Public Health result 2019 , and16, x FORthe PEER ideal REVIEW prot ection scope, the areas around the core 13 ofsource 27 According to the resistance analysis result and the ideal protection scope, the areas around the core resistance of <30,000 and the potential source resistance of <14,000 identified the protection area the resistance analysis result and the ideal protection scope, the areas around the core source source(1692.07 resistance km2), of of which<30,000 the andecological the potential buffer area source is 1135.34 resistance km2, of and<14,000 the ecological identified conflict the protection area is resistance of2 <30,000 and the potential source resistance of <14,0002 identified the protection area area (1692.072 km ), of which the ecological buffer area is 1135.34 km , and the ecological conflict area is 496.52(1692.07 km km(Figure2), of 13).which the ecological buffer area is 1135.34 km2, and the ecological conflict area is 496.52 km2 (Figure 13). 496.52 km2 (Figure 13).

Figure 8. Local spatial autocorrelation analysis in the study area. FigureFigure 8. 8.Local Local spatialspatial autocorrelationautocorrelation analysis analysis in in the the study study area. area.

2017 2017

2010 2010

2000 2000

1990 1990

1980 1980 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0%Cold 10%spots-High 20% 30%Cold spots-Middle 40% 50%Cold 60% spots-Low 70% 80%Not significant 90% 100%

ColdHot spots-High spots-Low ColdHot spots-Middle HotCold spots-Hign spots-Low Not significant

Hot spots-Low Hot spots-Middle Hot spots-Hign

Figure 9. Change in the proportion of spatial agglomeration in the study area. Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 14 of 27

Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 14 of 27 Figure 9. Change in the proportion of spatial agglomeration in the study area.

Int. J. Environ. Res.Figure Public Health 9. Change2019, 16 in, 4640the proportion of spatial agglomeration in the study area. 14 of 26

Figure 10. Hot-spot optimization analysis. Figure 10. Hot-spot optimization analysis. Figure 10. Hot-spot optimization analysis.

North North 1 1 1980 1980 Northwest 0.8 Northeast Northwest 0.8 Northeast 0.6North 0.6North 1 1 0.4 19901980 0.4 19901980 Northwest 0.20.8 Northeast Northwest 0.20.8 Northeast West 0.60 East 2000 West 0.60 East 2000 0.4 1990 0.4 1990 0.2 0.2 West 0 East 20102000 West 0 East 20102000 Southwest Southeast Southwest Southeast 20172010 20172010 Southwest South Southeast Southwest South Southeast 2017 2017 South South (a) (b) (a) Figure 11. Cont. (b)

Int.Int. J. J. Environ. Environ. Res. Res. Public Public Health Health 20192019, ,1616, ,x 4640 FOR PEER REVIEW 15 15 of of 27 26

North North 15% 30% 25% Northwest 12% Northeast 1980 Northwest Northeast 1980 9% 20% 15% 6% 1990 10% 1990 3% 5% West 0% East 2000 West 0% East 2000 2010 2010 Southwest Southeast 2017 Southwest Southeast 2017 South South

(c) (d)

North North 25% 60% Northwest 20% Northeast 1980 Northwest 50% Northeast 1980 15% 40% 30% 10% 1990 20% 1990 5% 10% West 0% East 2000 West 0% East 2000 2010 2010 Southwest Southeast 2017 Southwest Southeast 2017 South South

(e) (f)

North North 30% 50% 25% 1980 1980 Northwest 20% Northeast Northwest 40% Northeast 15% 30% 10% 1990 20% 1990 5% 10% West 0% East 2000 West 0% East 2000 2010 2010 Southwest Southeast Southwest Southeast 2017 2017 South South

(g) (h)

Figure 11. 11. ChangeChange of of spatial spatial diversity diversity in in8 directions 8 directions (a). (a Proportion). Proportion of the of thehotspot hotspot in 8 indirections 8 directions (b). Proportion(b). Proportion of the of cold the coldspots spots in 8 in directions 8 directions (c). (Proportionc). Proportion of the of thehot hot spot-high spot-high area area change change in in8 directions8 directions (d ().d Proportion). Proportion of the of the cold cold spot-hig spot-highh area’s area’s change change in 8 in directions 8 directions (e). (Proportione). Proportion of the of hot the spot-middlehot spot-middle area’s area’s change change in 8 indirections 8 directions (f). (Proportionf). Proportion of the of the cold cold spot-middle spot-middle area area change change in in8 directions8 directions (g ().g ).Proportion Proportion of of the the hot hot spot-low spot-low ar areaea change change in in different different quadrants quadrants ( (hh)) Proportion Proportion of of the the coldcold spot-low area change in 8 directions.

Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 16 of 27 Int. J. Environ. Res. Public Health 2019, 16, 4640 16 of 26 Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 16 of 27

Figure 12. Time–space overlay analysis. FigureFigure 12.12. Time–space overlay overlay analysis. analysis.

(a) (b) FigureFigure 13. 13.Protection Protection(a) area area analysis:analysis: (a) resistance analysis; analysis; (b (b) )protection protection(b) area area partition. partition.

Figure 13. Protection area analysis: (a) resistance analysis; (b) protection area partition.

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According to an analysis of land use type (Figure 14), the main land use type in the core restoration According to an analysis of land use type (Figure 14), the main land use type in the core area is saline-alkali land, which is identified as the main risk source. The key restoration area is restoration area is saline-alkali land, which is identified as the main risk source. The key restoration mainly composed of saline-alkali land and farmland, which is concentrated at the edge of the core area is mainly composed of saline-alkali land and farmland, which is concentrated at the edge of the restorationcore restoration area in area the southin the of south the oilfield. of the Theoilfield. risk preventionThe risk prevention area is mainly area composed is mainly of composed saline-alkali of land,saline-alkali farmland, land, and farmland, medium-coverage and medium-coverage grassland. The grassland. farmland The is farmland concentrated is concentrated at the edge ofat thethe saline-alkaliedge of the saline-alkali land in the land southern in the area southern of the area oilfield, of the and oilfield, its risk and is relativelyits risk is high.relatively The high. medium The coveragemedium coverage grassland grassland is located is atlocated the edge at the of edge the saline-alkali of the saline-alkali land in land the in north the north of the of oilfield. the oilfield. The grasslandThe grassland is easily is degradedeasily degraded and converted and converted into saline-alkali into saline-alkali land. The saline-alkaliland. The saline-alkali land is concentrated land is atconcentrated the edge of at the the key edge restoration of the key area, restoration whose scope area, is whose small scope and interlaced is small and with interlaced other land. with The other risk supervisionland. The risk area supervision is mainly composedarea is mainly of farmland, composed which of farmland, is located which around is thelocated risk preventionaround the arearisk andprevention plays a buareaffering and role.plays The a buffering ecological potentialrole. The areaecological is mainly potential composed area of is farmland mainly andcomposed grassland of andfarmland is located and grassland in the south and of is thelocated oilfield. in the The south bottom of the line oilfield. protection The bottom area is line mainly protection composed area ofis watermainly in composed the north-east of water of the in study the north-east area. The coreof the protection study area. area The is dispersedcore protection outside area the is oilfield dispersed area. Theoutside main the land oilfield use area. type isThe high-coverage main land use grassland. type is high-coverage The ecological grassland. potential The area ecological is located potential inside thearea oilfield, is located and inside its main the landoilfield, use and types its aremain medium-coverage land use types are grassland medium-coverage and farmland. grassland The ideal and protectionfarmland. areaThe andideal the protection protection area buff ander connect the protection the core protectionbuffer connect area inthe series. core Theprotection main land area use in typesseries. are The farmland main land and use high types coverage are farmland grassland. and high coverage grassland.

100% 4 90% 3.5 80% 3 70% 60% 2.5 50% 2 40% 1.5 30% 1 20% Square kilometer 10% 0.5 0% 0

Farmland Woodland High-coverage grassland

Medium-coverage grassland Low-coverage grassland Water

Construction land Unused land Total area

Figure 14. Space partition and land use type.

4. Discussion

4.1. The Main Reasons for Landscapelandscape eco-security Eco-Security Change Change According to the curve fittingsfittings (Figure(Figure 1515))[ [40–440–422],], thethe changeschanges ofof thethe landscapelandscape eco-securityeco-security indexindex in the study area are affected affected by the socio-ec socio-economiconomic indicators (GDP, ecological investment, oil production),production), thethe landscapelandscape patches number, andand thethe landland useuse types (saline-alkali(saline-alkali land, high coverage grassland, and water). At present, we can only collect the overall cons constructiontruction and environmental environmental data data for for Daqing Daqing City, City, whilewhile thethe specificspecific data data for for the the Daqing Daqing urban urban fringe fringe area area and eachand each plant plant area arearea deficient, are deficient, which makeswhich itmakes impossible it impossible to carry to out carry a detailed out a analysis.detailed analysis. Therefore, Therefore, the analysis the ofanalysis the reasons of the for reasons the landscape for the eco-securitylandscape eco-security changes in eachchanges quadrant in each is quadrant mainly based is mainly on the based impact on layer the impact index, thelayer hot-spot index, analysisthe hot- andspot landanalysis use and transfer land(Figure use transfer 16). These(Figure changes 16). These reflect changes four phenomena:reflect four phenomena: (1) A lack of (1) protection A lack of controlprotection of thecontrol study of area the hasstudy caused area has the landscape’scaused the landscape’s eco-security eco-security to be destroyed. to be destroyed. Due to the lackDue ofto farmlandthe lack of control, farmland disorderly control, reclamation disorderly destroyed reclamation a large destroyed number a oflarge high-coverage number of grassland high-coverage areas grassland areas and increased the fragmentation of green land, thereby decreasing the 1980–1990 impact indices of the west and south-west, while the north-west increased the 1980–1990 cold-spot

Int. J. Environ. Res. Public Health 2019, 16, 4640 18 of 26

Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 18 of 27 and increased the fragmentation of green land, thereby decreasing the 1980–1990 impact indices of theproportions west and of south-west, the south-west, while theeast, north-west and north-east increased and thethe 1980–19902000–2010 cold-spot cold-spot proportions proportion ofof thethe south-west,west. Due to east, the andlack north-eastof construction and the land 2000–2010 control, cold-spotthe expansion proportion of construction of the west. land Due destroyed to the lack the oforiginal construction green space, land control, and the the cold-spot expansion proportion of construction of the south land and destroyed south-east the continued original green to increase space, andafter the 1990. cold-spot (2) Oilfield proportion exploitation of the is south mainly and manifested south-east through continued two to trends. increase On after the one 1990. hand, (2) Oilfield oilfield exploitationexploitation iscauses mainly surf manifestedace subsidence. through Wetlands two trends. and On potholes the one hand,were formed oilfield exploitationin and around causes the surfaceoilfield, subsidence. which increased Wetlands the impact and potholes indices wereof the formed north and in and the aroundhot-spot the proportion oilfield, whichof the north-east increased thein 1980–1990. impact indices On the of theother north hand, and the the exploration hot-spot proportionand expansion of the of north-eastthe oilfield indestroyed 1980–1990. the Onsurface the othervegetation, hand, thewhich exploration eventually and degraded expansion into of saline the oilfield-alkali destroyedland, and thethe surfacecoverage vegetation, of the grassland which eventuallyaround the degraded saline-alkali into saline-alkaliland continued land, to and decrea the coveragese due to of a the lack grassland of protection around and the saline-alkalirenovation. landTherefore, continued the exploitation to decrease dueof oilfields to a lack has of protectionformed a large-scale and renovation. risk warning Therefore, area, the which exploitation decreased of oilfieldsthe impact has indices formed of a large-scalethe south in risk 1980–1990 warning and area, increased which decreased the cold-spot the impact proportion indices of ofthe the south south in in1980–2017. 1980–1990 (3) and Environmental increased the protection cold-spot policies, proportion such of as the rotational south in 1980–2017.grazing, returning (3) Environmental farmland to protectiongreen land, policies, and water such restoration, as rotational have grazing, improved returning the grassland farmland coverage, to green land, the blue–green and water restoration,space area, haveand coherence, improved which the grassland greatly improved coverage, the the landscape blue–green eco-security space area, of the and external coherence, oilfield. which The greatly impact improvedindices of thethe landscapesouth-west, eco-security west, and north-west, of the external as we oilfield.ll as the The hot-spot impact proportion indices of of the the south-west, south-west west,and north-east, and north-west, increased as well in 2010–2017. as the hot-spot Therefore, proportion in the of future the south-west construction and of north-east, the urban increased fringe of inDaqing, 2010–2017. to implement Therefore, inexisting the future environmental construction protection of the urban policies, fringe of it Daqing, will be to necessary implement to existing strictly environmentalcontrol the risk protection warning area policies, and itthe will protection be necessary area. to strictly control the risk warning area and the protectionTherefore, area. in the future, we should reduce the risk warning area and the landscape patches number;Therefore, increase in the the ecological future, we pr shouldotection reduce areas; theand risk develop warning ecolog areaical and industries the landscape to increase patches GDP number;and ecological increase investment. the ecological protection areas; and develop ecological industries to increase GDP and ecological investment.

(a) (b)

(c) (d)

Figure 15. Cont.

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(e) (f)

FigureFigure 15. 15.The The relationship relationship between between landscape landscape eco-security eco-security index andindex the indicators:and the indicators: (a) GDP indicators; (a) GDP (indicators;b) oil production (b) oil indictors;production (c )indictors; protection (c) investment protection indicators;investment (indicators;d) landscape (d) patches landscape indicators; patches (indicators;e) water and (e) high water coverage and high grassland coverage area grassland indicators; area (indicators;f) saline-alkali (f) saline-alkali land area indicators. land area indicators.

4.2.4.2. RiskRisk WarningWarning AreaArea ControlControl StrategiesStrategies TheThe controlcontrol strategy strategy for for the the risk risk warning warning area area should should focus focus on on the the restoration restoration and and prevention prevention of the of riskthe sourcerisk source (saline-alkali (saline-alkali land, whichland, iswhich mainly is formedmainly byformed the oilfield by the exploitation oilfield exploitation without ecological without control).ecological For control). the core For restoration the core restoration area and the area key and restoration the key restoration area, since area, the saline-alkalisince the saline-alkali land has beenland lefthasfor been many left years,for many its degree years, of its salinization degree of issalinization serious, so is it serious, is difficult so andit is time-consumingdifficult and time- to reuseconsuming it. In future to reuse development, it. In future this development, land should this be mainlyland should used forbe mainly construction. used for If necessary,construction. after If detectingnecessary, the after salinity detecting of the the area, salinity a traditional of the treatmentarea, a traditional method (physical treatment and method chemical (physical treatment) and ischemical used for treatment) the classification is used for treatment the classification [43]. The risktreatment prevention [43]. The area risk should prevention focus on area controlling should focus the furtheron controlling degradation the further of land. degradation The control of strategyland. The for control farmland strategy is as for follows farmland [44]: is (1) as Reducefollows the[44]: use (1) ofReduce chemical the fertilizersuse of chemical to prevent fertilizers land to salinization prevent land and salinization advocate the and use advocate of farmyard the use manure, of farmyard such asmanure, straw returningsuch as straw and livestockreturning manure, and livestock to improve manure, soil to organic improve matter soil content.organic matter (2) Under content. certain (2) conditions,Under certain the conditions, fallow and the returning fallow and farmland returning will fa promotermland thewill recovery promote ratethe recovery of soil fertility, rate of and soil farmersfertility, who and takefarmers turns who to fallowtake turns farmland to fallow resources farmland should resources be subsidized should be to subsidized promote the to recoverypromote ofthe soil recovery fertility. of Optimized soil fertility. use Optimized after returning use after the farmlandreturning isthe mainly farmland concentrated is mainlyon concentrated returning the on farmlandreturning to the forests farmland and grasslands.to forests and (3) grasslands. Integrate the (3 farmland) Integrate to the reduce farmland the landscape to reduce fragmentation. the landscape Integratefragmentation. the farmland Integrate into the blocks, farmland gather into the farmlandblocks, gather together the and farmland improve together connectivity and betweenimprove theconnectivity farmland, therebybetween enhancing the farmland, its landscape thereby eco-security. enhancing Theits controllandscape strategy eco-security. for medium The coverage control grasslandstrategy for is asmedium follows coverage [45]. (1) If grassland it is discontinuous is as follows grassland [45]. (1) with If it a is small discontinuous area, it should grassland be developed with a intosmall farmland, area, it whichshould will be reducedeveloped the fragmentationinto farmland, of which the farmland. will reduce (2) For the large-scale fragmentation continuous of the grassland,farmland. human(2) For damage,large-scale such continuous as grazing, grasslan shouldd, behuman strictly damage, restricted. such As as an grazing, important should area tobe reducestrictly the restricted. regional As landscape’s an important ecological area to risk reduce and the protect regional the landscape’s landscape’s ecological ecological environment, risk and protect the riskthe supervisionlandscape’s areaecological should environment, focus on maintaining the risk supervision the stability ofarea the should landscape, focus such on maintaining as planting saltthe tolerantstability crops of the or landscape, developing such improved as planting rice planting, salt tolerant to improve crops or economic developing benefits improved while achieving rice planting, risk supervisionto improve economic [46]. The ecologicalbenefits while potential achieving area hasrisk bothsupervision a potential [46]. salinization The ecological risk potential and resistance area has to salinization.both a potential The salinization landscape in risk this and area resistance is relatively to sa stablelinization. and has The high landscape ecological in this potential. area is Therefore, relatively itstable is important and has to high focus ecological on its protection potential. and Therefore, utilization. it Appropriateis important developmentto focus on its should protection be carried and oututilization. while exerting Appropriate the ecological development potential should of the be land, carried so as out to while optimize exerting the allocation the ecological of land potential resources. of Usingthe land, the so ecological as to optimize potential the area allocation to establish of land a blue resources. ecological Using network the ecological can reduce potential the total area soil to salinityestablish in a the blue study ecological area [47 network]. can reduce the total soil salinity in the study area [47].

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Figure 16. DistributionDistribution of of land land use use transfer. transfer.

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4.3. Ecological Protection Area Control Strategies The control strategy for the protection area should focus on restricting the ecological conflict area to protect the ecological source (Table8). For the ecological protection core area, in principle, any construction projects are prohibited from entering—that is, all ecological resources in the area are protected, including enclosure restoration, and all activities that may damage the ecological environment are prohibited [48]. For the water bottom line protection area, except for the ecological protection core area control strategies, the demarcation and isolation protection of drinking water should be carried out at the same time, and control measures, such as habitat restoration, proliferation, and release of the key habitats of aquatic organisms, should be implemented [49]. The ideal protection area has the potential to develop into a core protection area. Therefore, priority should be given to protecting ecology, strictly controlling the development and construction of projects that destroy ecological functions, and encouraging the establishment of green infrastructure, such as ecological green corridors, country parks, and rural landscapes, thus returning farmland to green and demolishing non-ecological buildings (only retaining single-story ecological buildings as green infrastructure housing) [50]. For the ecological potential area, in addition to the restrictions of the ideal protection area, the potential value of ecosystem services can be appropriately exerted to develop the farmland for ecological farm projects [51]. As a transitional area between ecological space and non-ecological space, the ecological buffer zone is less restricted (retain low-rise buildings). In addition to the construction that can be carried out by ecological potential areas, the ecological agriculture project, and the necessary rural living and supporting service facilities, production infrastructure for cultivation, eco-tourism, and leisure facilities are also encouraged to be built [52].

Table 8. Ecological conflict area control strategies.

The Protection Area Farmland Construction Land Development Proposals Core protection area; Returning farmland to a No construction, only for scientific Dismantle Bottom line area green–blue space research and education green infrastructures, such as Retain and convert to Retain single-story ecological greenways, country parks, Potential ecological area ecological farmland ecological buildings and country landscapes The ecological agriculture project, Returning farmland to a Retain single-story Ideal protection area Construction of green infrastructures green–blue space ecological buildings The ecological agriculture project; Retain and convert to necessary rural living service facilities; Ecological buffer Retain low-rise buildings ecological farmland cultivation production infrastructure; eco-tourism; leisure facilities

5. Conclusions Through the application of remote sensing and GIS technologies, and using the DPSIR framework to build an assessment model, this paper analyses the trends of and reasons behind landscape eco-security changes in the urban fringe of Daqing from 1980 to 2017, thereby determining the area’s spatial partition scope and control strategies. The landscape ecological security index shows a downward trend. In order to enhance the landscape eco-security of the study area, two types of control strategies are proposed: controlling the expansion of risk sources (the risk warning area) and protecting the ecological space (the protection area). Conclusions were drawn and are presented as follows. The landscape eco-security index of the study area was bounded by the year 2000. From 1980 to 2000, the index of the study area decreased (especially the oilfield); from 2000 to 2017, the index of the external oilfield increased. The landscape eco-security index in the study area has obvious spatial clustering characteristics. The proportion of cold spots increased and formed a risk warning area. The changes of the landscape eco-security index in the study area is affected by the socio-economic Int. J. Environ. Res. Public Health 2019, 16, 4640 22 of 26 indicators (GDP, ecological investment, and oil production), the landscape patches number, and the land use types (saline-alkali land, high coverage grassland, and water). Based on the result of the time and space analysis, we identified a risk warning area of 979.64 km2 (mainly in the oilfield), including an ecological potential area, a risk supervisory area, a risk prevention area, a key restoration area, and a core restoration area. The protection area of 1692.07 km2, includes the bottom line protection area, core protection area, ideal protection area, ecological buffer area, and conflict area. Risk warning area strategies focus on controlling and renovating saline-alkali land (the risk source) to prevent further expansion. Ecological protection area strategies focus on controlling the disorderly expansion of construction land and farmland, increasing the coherence and area of the blue–green space, and improving grassland coverage.

Author Contributions: Conceptualization, X.C.; methodology, X.C.; software, X.C.; validation, D.X., S.F. and L.L.; formal analysis, X.C.; investigation, L.L.; resources, D.X.; data curation, S.F.; writing—original draft preparation, X.C.; writing—review and editing, X.C., D.X., S.F. and L.L.; visualization, X.C.; supervision, D.X.; funding acquisition, Northeast Forestry University. Funding: This research was funded by the Fundamental Research Funds for the Central Universities, Northeast Forestry University, Grant Number: 2572018CP06 Acknowledgments: We thank the reviewers and the assistant editor for their constructive suggestions for improving the manuscript. Conflicts of Interest: The authors declare no conflict of interest.

Appendix A

Table A1. Calculation Method of Landscape Ecological Risk Index.

Indicator Formula Parameter Meaning N is the number of patches of Landscape i C = n /A landscape type i, A is the total area Fragmentation Index (C ) i i i of the landscape (a plot)

q Di is the distance index of Landscape Separation 1 ni A Si = Di/Pi = landscape type i, Pi is the area Index (N ) 2 A Ai i × × index of landscape type i

DEi is the number of plaques in Landscape Dominance the unit type i/the total number of DOi = (1 + DEi + Pi)/3 = (1 + ni/N + Ai/A) Index (Di) plaques in the unit, Pi is the area i in the unit/the total area of the unit a, b, and c are the weights of each landscape index, and the three are added to 1. This paper assigns three indices to 0.502, 0.301, and Landscape Interference Ei = aCi + bSi + cDOi 0.197 respectively. After Index (Ei) calculating the Ci,Si, and DOi indicators according to the above formula, normalization is required due to different dimensions. E is the i-type land use Ecological Risk Loss i R = E F interference index, F is the Index (R ) i i × i i i corresponding vulnerability index.

Table A2. Ecological vulnerability index of different land use types.

Land High Medium Low Saline- Construction Use Farmland Woodland Coverage Coverage Coverage Water Alkali Land Type Grassland Grassland Grassland Land Level 5 2 3 4 7 8 6 1 Index 0.8743 0.7048 0.7952 0.8440 0.9097 0.9208 0.8949 0.5 Int. J. Environ. Res. Public Health 2019, 16, 4640 23 of 26

Table A3. Eco-resilience score of different land use types.

Classification Land Use Type Score Ecological Value

I Woodland 9.0 They have control and decisive significance in maintaining (8–10) High coverage 8.5 ecosystem elasticity. grassland Medium coverage They play an important role in maintaining oasis stability and II 7.0 grassland maintaining oasis regulation capacity, also can increase (6–8) Farmland 6.0 humidity and improve microbial cycle in local climate. III Water 4.0 It is necessary to strengthen management, effective maintenance, (2–4) Low coverage and careful use, if not well utilized, can easily reduce the 2.0 grassland elasticity of regional ecosystems. They are the focus of ecological management and adjustment, IV Saline-alkali land 1.0 but saline-alkali land is relatively stable, so the score is higher (0–2) Construction land 0.0 than desert.

Table A4. Value of ecosystem services of different land use types.

High Medium Low Saline- Land Use Construction Farmland Woodland Coverage Coverage Coverage Water Alkali Type Land Grassland Grassland Grassland Land Equivalent 8.76 21.19 7.02 5.36 3.75 52.67 0.83 0.41 factor ESV (km2) 7995.45 19,334.00 6406.81 4893.50 3424.56 48,067.77 761.01 371.66 Int. J. Environ. Res. Public Health 2019, 16, x FOR PEER REVIEW 24 of 27

Figure A1. Classification of Land Use and Land Cover from 1980 to 2017. Figure A1. Classification of Land Use and Land Cover from 1980 to 2017. References

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