Research on Land Ecological Security Diagnosis and Dynamic Early Warning for China’s Top 100 Counties
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Indicator System
2.2.1. Theoretical Framework Construction
2.2.2. Indicator System Design
2.3. Data Sources
2.4. Research Methods
2.4.1. Vertical and Horizontal Pull-Off Method
2.4.2. Cluster Analysis
2.4.3. CNN-LSTM Hybrid Neural Network Model
3. Results and Analysis
3.1. Analysis of Temporal Patterns in Land Ecological Security Across the Top 100 Counties
3.1.1. Analysis of Alert Situation in County Areas
3.1.2. Analysis of Comprehensive Alert Situation
3.1.3. Analysis of Subsystem Alert Situation
3.2. Predictive Analysis of Land Ecological Security Alerts in the Top 100 Counties
3.2.1. Early Warning Trends for County Areas
3.2.2. Comprehensive Early Warning Trends
3.2.3. Subsystem Early Warning Trends
4. Conclusions and Discussions
4.1. Conclusions
- (1)
- From 2010 to 2023, the land ecological security warning levels across all counties in the Top 100 Counties improved progressively. The proportion of counties achieving ‘Relatively Safe (Low Alert)’ or higher levels increased from 2% in 2010 to 68% in 2023. The ‘Critically Safe (Medium Alert)’ proportion rose from 6% to 40% before stabilising at around 30%. Conversely, the proportion below ‘Critically Safe (Medium Alert)’ declined rapidly from 92% in 2010 to 7% in 2023. The highest proportion of counties (21%) transitioned from ‘Relatively Unsafe (High Alert)’ to ‘Relatively Safe (Low Alert)’ from 2010 to 2023. Moreover, based on the magnitude of alert level changes, counties classified as ‘significantly improved’ (those advancing by at least three levels) constituted the largest share (32%). Counties classified as ‘relatively lagging’—where the alert level never exceeded ‘Critically Safe (Medium Alert)’—ranked second (22%). Counties categorised as ‘consistently leading’—maintaining an alert level no lower than ‘Critically Safe (Medium Alert)’ while predominantly achieving ‘Safe (No Alert)’ in recent years—represented the smallest proportion (14%). This indicates that most counties have made significant progress in land ecological security, yet some still face considerable ecological pressures requiring enhanced ecological governance and protection measures.
- (2)
- From 2010 to 2023, the overall comprehensive early warning index for land ecological security among the Top 100 Counties exhibited a ‘stepwise leap’ trend, achieving a transformative progression from the ‘Relatively Unsafe (High Alert)’ to the ‘Relatively Safe (Low Alert)’ level. This evolution unfolded in four phases: ‘fluctuation and adjustment—rapid improvement—plateau consolidation—steady-state optimisation’. This progression indicates that, driven by policies such as ‘ecological civilisation development’, the ‘dual carbon strategy’, and ‘high-quality county-level development’, the Top 100 Counties have significantly enhanced regional ecological security through greening industrial structures, intensifying resource utilisation, and institutionalising ecological governance.
- (3)
- From 2010 to 2023, the six significant subsystems’ land ecological security in the Top 100 Counties diverged markedly in their evolutionary trajectories. Dual-core drivers of ‘driving-management’ propelled the warning level from ‘Unsafe (Giant Alert)’ to ‘Safe (No Alert)’, becoming the core engine for ecological security enhancement. This advancement primarily stemmed from synchronous growth in economic scale and digital governance investment. Pressure-impact fluctuations showed positive trends, with the alert level approaching ‘Relatively Safe (Low Alert)’ status. However, structural constraints such as high population density, heavy industry dominance, and inefficient ecological–economic conversion continued to exert limitations. The ‘state-response’ warning level fluctuates within the ‘Critically Safe (Medium Alert)’ range, reflecting coexisting ecosystem fragility and governance response lag. Fiscal investment efficiency and institutional refinement require urgent enhancement.
- (4)
- Over the next five years, the projected comprehensive land ecological safety early warning index for the Top 100 Counties exhibits a ‘gradual stabilisation and upward trend’, rising from 54.99 in 2023 to 58.80 by 2028, marking a historic transition from ‘Relatively Safe (Low Alert)’ to ‘Safe (No Alert)’ status by 2028. The projected values of the subsystem early warning indices exhibit a polarised pattern of ‘three increases, two stagnations, and one decline’. The sustained optimisation of the driving, management, and pressure subsystems stems from green investment, digital governance, and capacity optimisation. The response and impact subsystems remain stagnant and volatile, exposing fiscal inefficiency and slow conversion of ecological dividends. The state subsystem shows a declining trend due to the lag in ecological baseline recovery. The key to achieving land ecological security development in the Top 100 Counties lies in channelling the spillover benefits from the three improving subsystems to the two stagnant ones while reversing the inertia of the state subsystem through ecological restoration.
4.2. Discussions
5. Policy Recommendations and Research Prospects
5.1. Policy Recommendations
5.2. Research Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type | Indicator | Unit | Attribute | Weights |
---|---|---|---|---|
Driving | gross regional product | ten thousand yuan | + | 0.0387 |
Distance to higher administrative centres | km | − | 0.0377 | |
Total population at the end of the year | ten thousand people | − | 0.0399 | |
Disposable income per capita | yuan | + | 0.0411 | |
Pressure | Population density | person per square kilometre | − | 0.0402 |
Share of secondary sector in GDP | % | − | 0.0418 | |
Industrial emissions of SO2 | ton | − | 0.0417 | |
Surface PM2.5 mass concentration | μg/m3 | − | 0.0468 | |
State | Annual precipitation | mm | + | 0.0480 |
Average annual sunshine hours | h | + | 0.0443 | |
Water area | hectares | + | 0.0463 | |
Cultivated land area | hectares | − | 0.0480 | |
Impact | Night light data | nWcm-7sr-1 | − | 0.0481 |
Savings balance for urban and rural residents | ten thousand yuan | + | 0.0491 | |
Growth rate of retail sales of consumer goods | % | + | 0.0479 | |
Value added of the tertiary sector as a percentage of GDP | % | + | 0.0475 | |
Response | General budget expenditures of local finances | ten thousand yuan | + | 0.0474 |
Number of persons employed in agriculture, forestry and fisheries | person | + | 0.0419 | |
Impervious surface area | hectares | − | 0.0443 | |
Total industrial output value above scale | ten thousand yuan | − | 0.0403 | |
Management | Total investment in fixed assets | ten thousand yuan | + | 0.0402 |
Total public library collections | thousand volumes | + | 0.0394 | |
Number of beds in hospitals and health centres | bed | + | 0.0395 |
Early Warning Index | Warning Level | Vigilance | Indicator Lamp |
---|---|---|---|
(0.00, 42.90) | Unsafe | Giant Alert | Red Light |
[42.90, 48.03) | Relatively Unsafe | High Alert | Orange Light |
[48.03, 52.67) | Critically Safe | Medium Alert | Green Light |
[52.67, 58.01) | Relatively Safe | Low Alert | Cyan Light |
[58.01, 100.00) | Safe | No Alert | Blue Light |
Model Name | Coefficient of Determination | Mean Absolute Error |
---|---|---|
ARIMA | 0.5096 | 0.5525 |
SVR | 0.6918 | 0.7249 |
LSTM | 0.8164 | 0.2940 |
CNN-LSTM | 0.9588 | 0.1347 |
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Xu, F.; Cui, Y.; Weng, Y. Research on Land Ecological Security Diagnosis and Dynamic Early Warning for China’s Top 100 Counties. Sustainability 2025, 17, 9271. https://doi.org/10.3390/su17209271
Xu F, Cui Y, Weng Y. Research on Land Ecological Security Diagnosis and Dynamic Early Warning for China’s Top 100 Counties. Sustainability. 2025; 17(20):9271. https://doi.org/10.3390/su17209271
Chicago/Turabian StyleXu, Fei, Yalun Cui, and Yijing Weng. 2025. "Research on Land Ecological Security Diagnosis and Dynamic Early Warning for China’s Top 100 Counties" Sustainability 17, no. 20: 9271. https://doi.org/10.3390/su17209271
APA StyleXu, F., Cui, Y., & Weng, Y. (2025). Research on Land Ecological Security Diagnosis and Dynamic Early Warning for China’s Top 100 Counties. Sustainability, 17(20), 9271. https://doi.org/10.3390/su17209271