1. Introduction
With the rapid development of social economy and the continuous improvement of living standards, the problem of the destruction of the ecological environment is becoming increasingly serious. Now, with improving environmental awareness, ecological assessment has received global attention, and in our country in particular [
1]. Ecological security is an indispensable part of the national and social stability, and it is also a key factor in maintaining sustainable socioeconomic development [
2]. The current state of ecological conditions and the knowledge of various sources influencing these conditions are important in evaluating future scenarios and their better management.
In recent years, efforts have been made to evaluate the ecological environment of almost every country in numerous ecological setups, for example, cities, lands, coastal areas, and river basins. Liao et al. [
3] proposed an evaluation index system of karst-mountain ecological security from three resource aspects and ecological environmental pressure, resources, and ecological environmental qualities, as well as the capacity for environmental protection and ecological construction. Zhang et al. [
4] have discussed the dynamic changes in the landscape pattern and ecological security of the Ebinur Lake basin in the past 10 years. Dong et al. [
5] constructed the ecological safety assessment system of Shuifeng Lake from the four aspects of socioeconomic impact, water ecological health, ecological service functions, and regulatory management based on the Driving-Force-Pressure-State-Impact-Response (DPSIR) model.
Combined remote-sensing and GIS technologies are being widely used in the monitoring, mapping, and better managament of ecological environments. Zuo et al. [
6] proposed a method of ecological safety assessment from a pixel scale to a small watershed or county scale using remote-sensing data and related models. Shao et al. [
7] carried out a comprehensive evaluation of the ecoenvironmental quality of the resource-based city of Panzhihua from five aspects, biological abundance, vegetation coverage, water density, land degradation, and pollution load based on multisource remote-sensing data, statistical data, and GIS technical support. Cabello et al. [
8] used a satellite remote-sensing technique to investigate the ecological functions of a protected area and found remote-sensing to be an important and effective tool.
The Wenchuan earthquake was a highly destructive earthquake in Chinese history, killing thousands of people, damaging buildings, causing widespread landslides, floods [
9], and epidemic outbreaks [
10,
11], seriously affecting the ecological environment of Wenchuan County. Remote sensing and GIS tools were extensively used after this deadly event (Cao et al. [
11]; Guo et al. [
12]; Xu et al. [
13]) to evaluate the quality of the ecological environment in the affected areas. Hu [
14] evaluated and analyzed the ecological environmental quality of Wenchuan before and after the earthquake, and prepared a spatial distribution map of ecological damage. Wang [
15] carried out analysis of the landslides and collapse of buildings in Yinxing Town using 3S technology.
A number of evaluation models and methods have been developed for ecological evaluations, such as analytic hierarchy process, artificial neural networks, cellular automata [
16], panel data-cluster analysis [
17], matter element analysis [
18], and ecological footprint models [
19]. These methods have their own advantages and disadvantages, some of which are difficult to implement, such as neural-network methods; others are too subjective in determining the weight of indicators, such as the analytic hierarchy process. The gray-relation method is an analysis method in gray system theory that measures the degree of correlation between factors based on similarity or dissimilarity. Gray-correlation analysis does not require sample size, or the typical distribution law. It is a relatively simple and reliable analysis method in system analysis [
20]. At the same time, since entropy reflects the relative importance of indicators according to their objective information, it can avoid the subjectivity of weight determination compared with the analytic hierarchy process.
The Conceptual Model of Pressure-State-Response (PSR) was proposed by the Organization for Economic Co-Operation and Development (OECD) and the United Nations Environmental Program (UNEP) [
21]. This model evaluates ecological security using pressure, status, and response indicators. Based on the above analysis, we discuss the quality of the ecological environment of Wenchuan County after the earthquake using gray-correlation analysis. An ecoenvironmental evaluation system could be established in accordance with the PSR model and remote sensing, survey data can be used to calculate evaluation indices, and weights of indicators were determined through an entropy-weighted method. Finally, a spatiotemporal analysis on the changes of ecological conditions in Wenchuan after the earthquake was carried out.
4. Discussion
Hu used data from 2006 and 2008 to evaluate the ecological environment quality before and after the Wenchuan earthquake [
14]; Cao et al. calculated and analyzed the ecological security and recovery of Wenchuan County in 2007, 2008, and 2013 [
27]. In order to verify whether the results of this study are reliable, the results obtained in this study were compared with the results of these two similar studies.
Since Hu used the 2006 data in calculating the pre-earthquake ecological environment quality, their study is quite different from the 2007 data used in this study, so only the 2008 results were compared. Among the results obtained by Hu, in 2008 the region that accounted for Wenchuan County’s environmental quality rating of “good” and “relatively good” was 67.3%, the “generally good” area accounted for 27.9%, while 4.8% of the region was “poor” and “terrible”. The results obtained in this study corresponded to values of 38.2%, 21.7%, and 40.0%, respectively.
The difference between the results obtained in this study and those obtained by Cao et al. is shown in
Figure 8, where
Figure 8a is the area ratio difference of different ecological levels in 2007, 2008, and 2013, and 8b is the difference in area ratios for different ecological security change levels for 2007–2008 and 2008–2013. Combined with specific values and figures, it can be seen that the results obtained by the two studies have a relatively consistent trend as a whole, but there are significant differences in individual data items. In 2007, the largest area proportion oof ecological safety level in the two studies was V, but the value obtained in this study was 46.4%, and the value obtained by Cao et al. is 60.7%. In 2008, Cao showed that the proportion of the region with a “critically safe” rating and below was 39.2%, and the corresponding value in this study was 61.8%. Cao’s research showed that the proportion of the region with a “critically safe” rating and above was 92.4%, while the corresponding value in this study was 76.3%. For 2007–2008 and 2008–2013 ecological security change levels, the two studies had obvious differences in the LI, NC, and LD levels. However, LI, NC, and LD are three adjacent levels, all of which indicate small changes, and it is possible to make a difference due to variations in rank.
Based on the above analysis, the results of this study and the two other studies on the ecological environment of Wenchuan County are different. One of the reasons is that the latter two studies both use the comprehensive index method for environmental assessment and the Analytic Hierarchy Process (AHP) to determine the index weight. The results of this study were quite different from those of Hu. This may because Hu’s evaluation object was on ecological environment quality, and the selected evaluation index was very different from this paper. Because the evaluation objects were consistent, this study and Cao’s research were more uniform in the selection of indicators, but due to the different data used, the calculation method of indicators, and the method of determining the weights, the final results still had differences. In the overall trend, this study was consistent with the two other studies, so the results obtained in this study have a certain reference significance.
5. Conclusions
The present study evaluated ecological security using the PSR model and presented indicators based on the available data. Multisource remote-sensing image and statistical data were used to calculate the evaluation index, and weights of indicators were determined by entropy. At the same time, gray-correlation analysis was used to evaluate the restoration of the ecological environment after the Wenchuan County earthquake. The calculated ecological security correlation was divided into five grades, from “safe” to “very unsafe”. We evaluated the difference in ecological safety level in 2007–2008, 2008–2013, 2013–2017, and 2007–2017. Based on the discussed results, the changes in ecological safety were classified and divided into seven classes. Finally, the security correlation of the pressure, status, and response layers was calculated, and the impact of each indicator in each layer on ecological safety was analyzed. Based on the detailed analysis, the following conclusions were drawn:
- (1)
The 2008 earthquake caused substantial reduction in the level of ecological security in Wenchuan County compared to 2007. After five years of recovery, the overall level of ecological security in Wenchuan County in 2013 has significantly improved. In the next four years, the ecological security level in Wenchuan County continued to improve, but it was still worse than that in 2007, before the earthquake.
- (2)
In 2008, the security level of the pressure layer in almost all areas was above “critically safe”. Due to the reduced security of the state layer caused by the earthquake and poor resistance to the deteriorating environment, the security correlation of the response layer was low and, the overall level of ecological security in 2008 was lower than the other three years. The ecological status of Wenchuan County in 2007 was inferior to that of 2017 since the degree of security correlation of its status layer was lower than that of 2007. However, the environmental pressure in Wenchuan County in 2017 was lower than in 2007, and the environmental response capability was very strong. Therefore, the overall ecological safety level that was enhanced in 2017 was high.
Our results clearly show that Wenchuan County currently has a high degree of ecological security, with a good environmental status and strong environmental response. However, environmental pressure is relatively high due to economic development, increasing urbanization rate, and other reasons; the environmental conditions of some regions have not recovered to the ecological conditions that existed prior to the earthquake. The areas still need to maintain ecological environment stability.