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Journal of Resources and Ecology >

2022 , Vol. 13 >Issue 6: 977 - 985

DOI: https://doi.org/10.5814/j.issn.1674-764x.2022.06.003

Resource Use and Resource Economy

Ecosystem Service Value Evolution and Security Pattern Optimization in Huaihai Economic Zone

  • CAO Yuhong , 1, 3 ,
  • CAO Yuandan 1 ,
  • CHEN Zhiyu 2 ,
  • YU Dailiang 1
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  • 1. School of Ecology and Environment, Anhui Normal University, Wuhu, Anhui 241002, China
  • 2. School of Geography and Tourism, Anhui Normal University, Wuhu, Anhui 241002, China
  • 3. Collaborative Innovation Center for Restoration and Reconstruction of Degradated Ecosystem in Wanjiang River Basin, Wuhu, Anhui 241002, China

CAO Yuhong, E-mail:

Received date: 2021-12-20

  Accepted date: 2022-03-10

  Online published: 2022-10-12

Supported by

The National Natural Science Foundation of China(41971175)

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Abstract

The ecological and environmental effects caused by land use change have attracted global attention. Huaihai Economic Zone, as the core of the Huaihe River ecological economic belt, has experienced a reciprocal evolution of land use, ecological security and regional economic development. Based on multi-stage land use data extracted by Google Earth Engine (GEE), the spatio-temporal differentiation characteristics of ecosystem service value (ESV) evolution in Huaihai Economic Zone from 1998 to 2018 were analyzed with the help of ESV assessment and a minimum accumulated resistance model (MCR), and the regional ecological security pattern (ESP) was optimized. The results show that ESV intensity has obvious spatial differentiation, which is higher in northeastern China and lower in southwestern China. The median ESV area accounted for the largest proportion, while the high and low ESV areas accounted for a small proportion. The characteristics of EVS temporal and spatial differentiation show decreasing and increasing grades. From the perspective of development period, the ESV grade changes show a positive trend. In the optimization of the ecological security pattern, 26 important ecological sources, 22 main landscape ecological corridors, and 65 ecological strategic nodes were optimized and identified, and the middle-level ecological security zone accounted for the largest proportion. The main reasons for the changes in the ESV and ESP are closely related to the changes in local natural resources and the changes and adjustments in government protection policies. These research results can provide a reference for inter-provincial territorial space protection and the formulation of a sustainable development strategy.

Key words： land use change; ecosystem service value; optimization of ecological security pattern; Huaihai Economic Zone

Cite this article

CAO Yuhong , CAO Yuandan , CHEN Zhiyu , YU Dailiang . Ecosystem Service Value Evolution and Security Pattern Optimization in Huaihai Economic Zone[J]. Journal of Resources and Ecology, 2022 , 13(6) : 977 -985 . DOI: 10.5814/j.issn.1674-764x.2022.06.003

1 Introduction

Ecosystem service functions refer to the natural environment conditions and utility that human beings depend on for survival that are formed and maintained by ecosystems and ecological processes (Ouyang et al., 1999). The changes in ecosystem service value (ESV) are known to show obvious regional differences (Zeng et al., 2014). Land pattern changes affect ecological processes, and thus affect ecosystem services (Fu, 2019). Ecosystem services are closely related to human well-being, and the land use changes caused by human activities are one of the main driving forces of ecosystem service changes (Xu et al., 2019a). At the same time, ecosystem service value is of great significance for the evaluation of regional ecological sustainable development (Lou et al., 2019). Therefore, it is of great significance to explore the impact of land use change on ecosystem service value for both regional ecological environment protection and the formulation of a social and economic development strategy (Liu et al., 2021; Zhang et al., 2022). Recently, many scholars at home and abroad have conducted a large number of empirical studies on the impact of land use changes at different scales on ecosystem service value. At the beginning of the 21st century, the research objects of LUCC around the world mainly focused on hot spot regions and land use change processes, while in the present stage, scholars mainly study land use change and sustainability, as well as its impact on ESV (Zhu and Meng, 2009).
In order to evaluate the impact of land use change on ESV, scholars at home and abroad have conducted qualitative and quantitative studies using a variety of methods, such as grey prediction model (Wang et al., 2015), multi-scale spatial cell and spatial autocorrelation analysis (Wu et al., 2015) and the ESV model (Sheng et al., 2018). These methods and models have been widely used in practical applications in recent years because of their strong synthesis capabilities. For example, some quantitative estimates of ESV around Beijing and Tianjin, the Yangtze River Economic Belt and the ecological research area were conducted from a time series perspective to judge their overall development trends (Li et al., 2015; Li, 2019; Zhu and Zhong, 2019). Some studies have analyzed various kinds of land use changes in a study area through the interpretation of remote sensing images, and they provide a new research framework for studying the impact of land use change on ESV from a spatial perspective (Chen et al., 2018; Guo et al., 2019a; Lv et al., 2019; Zhang et al., 2019). On the other hand, the grey GM(1,1) model was used to predict the ESV in 2018 and 2022 in each zone (Li et al., 2016). Some studies have established evaluation indexes and evaluation models of ESV based on local economic and population data in order to analyze local land use and ecological security (Gao and Sun, 2017; Wang and Jia, 2018). Some have used the CLUE-S model to predict the land use data in the source region of Wujiang River in 2030 and to analyze the impact on ESV (Han et al., 2018). Foreign scholars have also carried out relevant studies, such as analyzing the causes of land use change and forest degradation (Verburg et al., 2006; Lambin and Meyfroidt, 2010). From the perspective of economics, one study divided the ESV of ecosystem services into 17 categories, and determined that ecosystem services are the direct or indirect benefits that human beings can obtain from the ecosystem (Costanza et al., 1997).
Ecological security is based on the ecosystem services provided by the ecosystem for human beings, and the construction of the ecological security pattern (ESP) is an effective measure for maintaining the normal operation of the ecosystem (Wang and Pan, 2019; Cao et al., 2020). ESP is based on the relationship between ecological processes and services and can be used to form a spatial allocation plan to ensure the structural and functional integrity of the ecosystem (Xu et al., 2019b). The construction of ESP is also a comprehensive method to protect regional ecological sustainability (Peng et al., 2018a). In general, ESP consists of two parts: ecological source and ecological corridor (Peng et al., 2018b). For example, one study reported the development of land resources in transition zones based on the ecological security model (Peng and Zhou, 2019), and used the resistance threshold method for ecological security zoning. Finally, the minimum cumulative resistance model (MCR) was used to determine the ecological corridors, so as to construct the ecological security pattern comprehensively (Hao et al., 2019). Taking the Harbin-Changchun urban agglomeration as an example, the ESP of urban agglomeration was established and optimized based on ecosystem function evaluation (Guo et al., 2019b). The habitat quality analysis module of the invest model and Circuitscape 4.0 were used to screen ecological source areas and ecological corridors, and then the Linkage Mapper was used to evaluate the importance and connectivity of relevant ecological elements to establish the ecological security pattern and delineate priority areas for ecological restoration (Li et al., 2021). The least resistance model (MCR) was applied to extract the ecological corridor network in order to construct the regional ESP (Huang et al., 2019; Zhu et al., 2019; Xu et al., 2021). As the focus and hotspot of landscape ecology, the identification and construction of ESP plays an important role in maintaining regional ecological security and realizing regional sustainable development (Hao et al., 2019). Therefore, the goal of this study was to explore the impact of land use changes on ESV and formulate corresponding strategic measures according to regional ecological environment quality and socio-economic development, using Huaihai Economic Zone as the study area.

2 Data and methods

2.1 Data source and processing

The research data were mainly obtained from Landsat TM5 (1998, 2008) and Landsat TM8 (2018) remote sensing images through the Google Earth Engine (GEE) cloud platform. The Random forest (RF) classifier was used to classify the land use types in the study area into six primary types: forest land, grassland, water area, cultivated land, construction land and bare land, with a spatial resolution of 30 m and an overall accuracy of more than 75% (Table 1). The DEM data came from the geospatial data cloud of Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (http://www.gscloud.cn). Road network data were from the Open Street Map (https://www.openstreetmap.org). The data of grain production (rice, corn and wheat) used to calculate the service value of each ecosystem per unit area in the Huaihai Economic Zone were obtained from the Statistical Yearbooks of Anhui, Jiangsu, Henan and Shandong provinces from 1998 to 2018.
Table 1 Testing the accuracy of land use type data for the study area
Year Sample Training set Test set Kappa Overall accuracy (%)
1998 582 75562 115275 0.89 92.62
2008 596 72698 91276 0.88 91.81
2018 636 39266 34076 0.83 87.88

2.2 Research method

In this study, the land use data interpreted by remote sensing were mainly used to calculate the ESV and construct the ESP. The specific model formulas are shown in Table 2.
Table 2 Research model formula
Model name Model formula Meaning of variables
Ecosystem Services Value $ESV=\underset{i=1}{\overset{n}{\mathop \sum }}\,\left( {{A}_{i}}\times V{{C}_{i}} \right)$ (1) ESV: ecosystem service value, yuan; i: land-use type; Ai: area of class ‘i' land use type, ha; VCi: ecosystem service value per unit area of type i land use type, yuan ha‒1
$V{{C}_{i}}=\underset{j=1}{\overset{k}{\mathop \sum }}\,\left( E{{C}_{ij}}\times {{E}_{a}} \right)$ (2) j: type of ecosystem services; ECij: value equivalent of item j of ecosystem services of the i-th land use type; Ea: ecosystem economic value per unit, yuan ha‒1
${{E}_{a}}=\frac{1}{7}\underset{r=1}{\overset{n}{\mathop \sum }}\,\frac{{{m}_{r}}{{p}_{r}}{{q}_{r}}}{M}$ (3) r: type of food crops; mr: national average price of the r type of food crops, yuan kg‒1; pr: yield per unit area of the r-type grain, kg ha‒1; qr: sown area of the r-type grain crop, ha; M: sown area of grain crops, ha
Ecosystem Service Value Intensity ${{E}_{k}}=\underset{i=1}{\overset{n}{\mathop \sum }}\,\left( \frac{{{A}_{ki}}}{{{A}_{k}}}\times V{{C}_{i}} \right)$ (4) Ek: intensity of ecosystem service value of the k-th grid; Aki: area of the i-th land use type of the k-th grid, ha; Ak: area of the k-th grid, ha
Minimum Cumulative Resistance $MCR={{f}_{\text{min}}}\underset{i=1}{\overset{m}{\mathop \sum }}\,\underset{j=1}{\overset{n}{\mathop \sum }}\,\left( {{D}_{ij}}\times {{R}_{i}} \right)$ (5) MCR: minimum cumulative resistance value; f: positive correlation between minimum cumulative resistance and ecological process; min: the evaluated plaques were evaluated with minimum cumulative resistance to different sources; Dij: distance from source ‘j' to land unit ‘i'; Ri: drag coefficient
Minimum Cumulative Resistance difference $MC{{R}_{d}}=MC{{R}_{s}}-MC{{R}_{c}}$ (6) MCRd: minimum cumulative resistance difference between ecological and urban land expansion; MCRs: minimum cumulative resistance value of ecological land expansion; MCRc: minimum cumulative resistance value of urban land expansion
Firstly, the ESV evaluation model of grid units was established by referring to Xie's (2015) China Ecosystem Services Value Scale (2015) and this was combined with the grid divisions under the GIS platform to measure the temporal and spatial evolution of ESV in the study area. The second step was to use the MCR model, which simulates the resistance of various ecological processes, to calculate the resistance that needs to be overcome in the process from “source” to any unit, in order to construct the spatial pattern of the ecological security network. The minimum cumulative resistance difference was obtained by subtracting the calculated minimum cumulative resistance values of urban land and ecological land for the two expansion sources. Considering the regional ecological environment and the impact of human activities, MCR in the model selection of resistance factors ultimately selected the high correlation between ecology and urban expansion and a total of eight factors. The resistance factor was divided into four grades, i.e., 1, 2, 3, 4, based on the resistance factor and the size of the influence degree, and the expert scoring method was used to determine the respective weights (Cao, 2018). The results are shown in Table 3. When the difference in the MCR value is greater than 0, it indicates that the resistance of ecological expansion is relatively greater, which is suitable for urban expansion. When the difference in the MCR value is less than 0, it means that the resistance of urban expansion is relatively greater, which is more suitable for ecological expansion. When the difference of the MCR value is equal to 0, it represents the dividing line between suitable ecological land and suitable urban land.
Table 3 Classification of different ESV grades
Classification The lower ESV Low ESV Middle ESV High ESV The higher ESV
Scope (yuan km‒2) Ek < 994200 994200 ≤ Ek < 1121600 1121600≤ Ek < 1946700 1946700 ≤ Ek < 2891700 Ek ≥ 2891700
Huaihai Economic Zone includes some cities in four different provinces (Anhui, Jiangsu, Henan and Shandong). According to the statistical yearbook of each province, the grain output per unit area was compared with the national output in the same period to determine the modification coefficients of ESV: Anhui 1.17, Jiangsu 1.74, Shandong 1.39 and Henan 1.38, which means that 1 unit of the ecological system in Anhui Province economic value is 1553.63 yuan ha‒1, in Jiangsu it is 2145.87 yuan ha‒1, in Shandong it is 1851.31 yuan ha‒1, and in Henan it is 2173.54 yuan ha‒1.
The area of the grid for calculating the intensity of ESV was 5 km×5 km, and the Huaihai Economic Zone was divided into 4055 grids. Formula (4) was used to calculate the ESV intensity (Ek) of each grid (Table 2). The natural discontinuous point classification method was used to divide the region into five grades (Table 3).
In the construction of ESP, the identification of “source” is the basis of ESP construction. The areas with woodland area greater than 10 km2, water patch area greater than 10 km2 and elevation greater than 200 m were selected as ecological protection sources, and areas with construction land area greater than 5 km2 were selected as urban expansion sources. These criteria identified 26 ecological sources and 138 urban expansion sources (Fig. 1). Using the cost distance and grid calculator tools in ArcGIS, the minimum cumulative resistance surface of ecological expansion and the minimum cumulative resistance surface of urban expansion were then calculated according to the resistance factor values, weights and formula (5) in Table 2. The difference in the minimum cumulative resistance surface values of the two was further calculated according to formula (6). When the minimum cumulative resistance difference value is less than 0, the area is suitable for ecological expansion, and when the minimum cumulative resistance difference value is greater than 0, the area is suitable for urban expansion. In order to better classify the types of ecological security zones, the natural discontinuous point classification method was used to identify the mutation points through the relationship of the change between the minimum cumulative resistance difference and the grid area. The results show that when the minimum cumulative resistance is less than 0, the slope changes suddenly at the MCR difference value of -49485.05. When the minimum cumulative resistance is greater than 0, the slope changes suddenly at the MCR difference value of 165689.23, and the land around the mutation point changes significantly. Therefore, MCR difference values of -49485.05, 0 and 165689.23 were finally adopted as the partition points, and the regional regulation of ecological security improvement in Huaihai Economic Zone was divided into four types: high-level ecological security area, medium-level ecological security area, low-level ecological security area and other areas.
Fig. 1 Distribution of ecological protection sources and urban expansion sources
In the MCR model, the ecological corridor is based on the surface of least resistance to ecological expansion as described above. A reasonable threshold value for a large patch of ecological source area was then selected to further identify the ecological source points, and each ecological source point was taken as the center and the remaining source points were taken as the target point group. The least-resistance path between ecological sources was extracted through the cost distance and cost path tools in ArcGIS 10.2, which fully considered the factors such as river traffic and roads in Huaihai Economic Zone, and the spatial distribution of the main ecological corridors was finally obtained. The ecological strategy point is based on the minimum cumulative resistance surface of ecological expansion. The hydrological analysis tool in ArcGIS 10.2 was used to extract the ridge line of the minimum accumulation surface, namely the maximum resistance path, and the intersection of the ecological corridors and the path of maximum resistance was regarded as the ecological strategic points.

3 Results and analysis

3.1 Spatio-temporal changes in the value of ecosystem services

The spatial distribution of ESV in the study area is shown in Fig. 2. From 1998 to 2018, the ESV had roughly the same spatial layout, with values that were low in urban areas, high in rural areas, high in Shandong and Jiangsu in the east, and low in Anhui and Henan in the west. There are obvious spatial differences in ESV intensity, and the approximate dividing line of high and low ESV is a line between the northeastern point of Jining-Heze junction and the southwestern point of Suqian-Suzhou junction. The high ESV region is to the east of the dividing line, and the low ESV region is to the west of the dividing line. According to the statistics of the different grade zones, the proportion of middle ESV area is relatively large, which is between 56.32%-56.39% in the three periods, and basically does not change with time, indicating that its distribution is relatively extensive. The low ESV area decreased at first and then increased. It decreased from 17.77% in 1998 to 9.77% in 2008, however, the grids of the low ESV region began to decrease again in 2018, and the change was mainly in the southern region, with the proportion rising to 18.59%. The proportion of the lower ESV areas increased in 2018 compared with 1998 and 2008, and the main supplementation came from the low ESV areas. The higher and high ESV areas accounted for less than 20% of the total area, and during the period of 1998-2018, they both decreased at first and then increased.
Fig. 2 Distribution of ecosystem service value grades in Huaihai Economic Zone from 1998 to 2018
In terms of the overall change in ESV ratings, the area of the declining zone was 620.52 km2 larger than that of the rising zone during 1998-2018, and its proportion was 0.65% higher than that of the rising zone. From 1998 to 2008, the area of constant ESV grade was the largest, accounting for 49.93%. There were more areas of decline, accounting for 26.85% of the total area, while the area of rising grade was the smallest, accounting for 6.56%, and the area of falling grade accounted for 20.29 percentage points more than that of the rising grade. From 2008 to 2018, the area of constant ESV grade decreased by 16.66 percentage points compared with the previous period, and the area of increasing ESV grade grew by 25.73 percentage points. During this period, the proportion of the declining area of ESV grade decreased by 9.07% compared with the previous period. It can be seen from the periods of development that the change in the ESV level from 2008 to 2018 showed a better trend than that from 1998 to 2008, and the ecological environment was improved.
In terms of the spatial distribution of ESV grade changes, the different grids showed both increasing and decreasing spatial and temporal differentiation patterns (Fig. 2). The decline of ESV is usually concentrated in some interface locations. One is the provincial interface, such as the interface between Shangqiu in Henan Province and Suzhou and Huaibei in Anhui Province, as well as the interface between Xuzhou in Jiangsu Province and Zaozhuang and Jining in Shandong Province. The second type of interface is the landscape ecological interlaced interface, such as the ecological ecotone between mountains, hills and plains in Linyi City, the land and water ecotone between Nansi Lake and its surrounding areas, and the land and sea ecotone in Lianyungang City. The interface results from human social economic activities and ecological landscape in temporal-spatial contact channels, and it plays an important role in energy and material exchange and other ecological processes. At the same time, it produces all kinds of contradictions and ecological environment problems, because in the face of effective interests the best interests of all parties are pursued with the minimum of spending. Therefore, in order to curb the declining trend of ESV, it is necessary to comprehensively master the activity rules of the different systems in the interface and carry out effective management to coordinate the interface conflicts, improve the ESV and maintain the ecological security.

3.2 Improved ecological security pattern

The ESP is designed to improve and restore the natural ecosystem, including ecological security zoning and the construction of ecological security networks (Fig. 3).
Fig. 3 Landscape ecological security regulation pattern

3.2.1 Ecological security partition

In total, the ecological security area in Huaihai Economic Zone covers 88014.83 km2, accounting for 92.22% of the total area of the study area. The high-level ecological safety zone covers an area of 1762.93 km2, accounting for 1.85% of the total area, and it tends to be small and scattered on the spatial distribution range. Mainly distributed in the Yimeng mountain area of the northern and southern hilly region, it has the MCR minimum value difference, so it is the most suitable for the planning of ecological land. In the future, the relevant policy should be based on “three line a single”, so it can be divided into a forbidden zone, stick to the ecological red line, set up the ecological safety consciousness, prohibit any form of urban development and construction activities, and since the region has been destroyed, ecological restoration work should be carried out in time to ensure the ecological security of the region. The area of the medium-level ecological security zone is 20788.15 km2, accounting for 21.78% of the total area, and it is mainly distributed spatially in the northern and central regions of the Huaihai Economic Zone. Its regional ecological condition is superior. In the future, it should be divided into restricted development zones in order to strengthen the management of the regional ecology, taking steps to limit urban land expansion and adjusting measures to the local conditions for active protection. The low-level ecological security area covers 65463.75 km2, accounting for 68.59% of the total area, and it is widely distributed spatially. This area is a transitional area of ecological protection, agricultural production and urban construction land. In the future, reasonable and efficient urban and rural construction and intensive utilization can be carried out to a certain extent, but at the same time, attention should be paid to the active improvement and management of the ecological environment. The “other area” type covers 7421.03 km2, accounting for 7.78% of the total area. It is mainly distributed in the western part of the study area, particularly the northwestern marginal zone which belongs to the southwest plain of the Yellow River south bank, and human activity here has been strong since ancient times. In the future, development efforts should focus on strengthening the heterogeneous ecological landscape and multifunctional complex ecological network construction, in order to improve the ecological environment.
From the perspective of administrative regions, the high-level ecological security areas are mainly distributed in the three cities of Linyi, Jining and Suqian. Among them, Linyi City has a higher-level ecological security area of up to 1236.27 km2, accounting for 70.13%. The medium-level ecological security areas are mainly distributed in Linyi, Jining, Zaozhuang, Xuzhou, Suqian, Suzhou and Lianyungang, among which Linyi has the largest area of 7566.71 km2, accounting for 36.40%. Meanwhile, Huaibei, Shangqiu and Heze have small areas of the middle-level ecological security area, of which the area in Huaibei is the least at only 127.52 km2, accounting for 0.61%. The low-level ecological safety areas are mainly distributed in Xuzhou, Suzhou, Linyi and Heze, among which Xuzhou has the largest area of 9360.86 km2, accounting for 14.30%. Huaibei and Zaozhuang have smaller areas of low-level ecological security area, among which Zaozhuang has the smallest medium-level ecological security area at only 2475.02 km2, accounting for 3.78%. The other regions are mainly distributed in Heze, Shangqiu and Jining, among which Shangqiu occupies 3106.57 km2 in the other regions, accounting for 41.86%.

3.2.2 Ecological security network

The ecological security network mainly connects different ecosystems through ecological corridors, and plays the role of facilitating material, information and energy transfers in the ecosystem. There are 22 major ecological corridors based on ecological expansion in the Huaihai Economic Zone, with a total length of about 1557.06 km (Fig. 3). These corridors are low-resistance channels between adjacent ecological sources, which serve as important channels for habitat, migration and diffusion of various organisms, and they play a variety of positive roles in protecting biological diversity and purifying the ecological environment.
Ecological strategic points are also important nodes among ecological sources, which profoundly affect the transfer of materials, information and energy in regional ecosystems. There are 65 common ecological strategic points in the research area, which are mainly distributed in Linyi, Zaozhuang and Jining. They are relatively fragile areas in the ecological corridor, their ecological environment can be easily damaged, and they are the key areas for ecological protection and environmental governance. In the future, these ecological strategic nodes should be optimized and regulated to further improve the spatial pattern of the ecological security network.

4 Discussion

ESV and ESP are closely related to local natural resources and government conservation policies. In 2004, the national Forest City Assessment process was launched with the aim of bringing forests into the cities and having the cities embrace the forests. As the national government attaches great importance to environmental protection, the Huaihai Economic Zone will adhere to the concepts of ecological priority, green development, restoration and governance, and actively promote the gradual improvement of the quality and stability of the ecosystem. At the same time, with the developments in science and technology, the city economy of Huaihai Economic Zone has been greatly improved. Under the dual effect of economic support and policy protection, the ecosystem service value and ecological security pattern of Huaihai Economic Zone have been markedly improved.
The evaluation of ESV and the study of ESP are the current and future hotspots of research on ecological economics and resources economics. This study starts from the perspective of landscape changes, and discusses the changes of ESV in the trans-provincial regional economy of Huaihai Economic Zone from 1998 to 2018. It provides a theoretical basis and reference for territorial spatial planning, orderly protection and restoration, and the formulation of a sustainable development strategy. However, this paper also has some shortcomings. 1) In the processing of the landscape data, due to the fact that unused land and meadows are easily confused with farmhouses and farmland in the 30 m Landsat images, they are difficult to identify. Therefore, to reduce this source of error, a small number of unused land samples were reduced during the process; however, this may contribute to the uncertainty of the unused land type. 2) Huaihai Economic Zone is composed of four different provinces. As a result, there are certain deviations in terms of ESV equivalents and 1 unit of ecosystem economic value, which are difficult to unify, and this makes data processing quite complicated. Therefore, the theoretical construction, research methods and the ability to solve practical problems need to be further improved and perfected in future research.

5 Conclusions

This paper analyzed the changes of ESV from 1998 to 2018 in the Huaihai Economic Zone, and constructed the ecological security pattern based on the GEE cloud platform image and the land use data generated by RF classifier. The results indicate four key features of this system.
(1) From 1998 to 2018, the ESV in the study area showed a spatial distribution pattern of high in the east and low in the west, and a temporal trend of decreasing at first and then increasing. The middle ESV area accounted for the largest proportion, while the high and low ESV areas accounted for a small proportion. The overall grid is dominated by intermediate horizontal grids, with less prominent high and low horizontal grids. The areas of constant ESV rating always occupy a large proportion, and there are more areas of declining ESV rating from 1998 to 2008, but more areas of rising ESV rating from 2008 to 2018. Therefore, the overall trend of ESV development in the study area is good.
(2) The low-resistance value distribution in the Huaihai Economic Zone is relatively concentrated and mainly distributed in grasslands, mountains, woodland and other areas with a good ecological environment. The high-level, medium-level and low-level ecological security zones account for 1.85%, 21.78% and 68.59% of the total area, respectively, and other areas account for 7.78%. The high-level ecological security areas are mainly distributed in Linyi and Suqian. From the perspective of low-level ecological security areas, they are the most widely distributed and account for the highest proportion, so the government needs to make greater efforts to improve their safety level.
(3) According to the important ecological sources of the Huaihai Economic Zone, 22 landscape ecological corridors with a total length of about 1557.06 km and 65 important ecological strategic nodes were identified through the consensus of ArcGIS 10.2 tools, superimposed Huaihai Economic Zone nature reserves, ecological sources, and the different levels of ecological safety areas and other areas. Finally, the ESP of Huaihai Economic Zone was generated, which will contribute to the dislocation development of regional economic growth and ecological environmental protection, in order to realize the harmonious coexistence between man and nature.
(4) The ecosystem service value and ecological security pattern largely depend on local natural resources and government protection policies. With the national government's emphasis on environmental protection, the Huaihai Economic Zone pays attention to the protection and restoration of the ecological environment while pursuing development, and actively promotes the gradual improvement in the quality and stability of the ecological system.

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