Dynamic monitoring and drivers of ecological environmental quality in the Three-North region, China: Insights based on remote sensing ecological index

被引:3
|
作者
Zhang, Leyi [1 ,2 ,3 ,4 ]
Li, Xia [4 ]
Liu, Xiuhua [1 ,2 ,3 ]
Lian, Zhiyang [5 ]
Zhang, Guozhuang [4 ]
Liu, Zuyu [1 ,2 ,3 ]
An, Shuangxian [4 ]
Ren, Yuexiao [4 ]
Li, Yile [4 ]
Liu, Shangdong [1 ,2 ,3 ]
机构
[1] Changan Univ, Sch Water & Environm, Xian 710054, Peoples R China
[2] Changan Univ, Key Lab Subsurface Hydrol & Ecol Effect Arid Reg, Minist Educ, Xian 710054, Peoples R China
[3] Changan Univ, Key Lab Ecohydrol & Water Secur Arid & Seim Arid R, Minist Water Resources, Xian 710054, Peoples R China
[4] Changan Univ, Sch Land Engn, Xian 710054, Peoples R China
[5] China Siwei Surveying & Mapping Technol Co Ltd, Beijing 100094, Peoples R China
基金
中国国家自然科学基金;
关键词
Remote sensing ecological index; Google earth engine; Shapley additive explanations; Ecological restoration projects; Three-north ecological project; LOESS PLATEAU; FOREST;
D O I
10.1016/j.ecoinf.2024.102936
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The Three-North Ecological Project (TNEP) in China's arid and semiarid regions is a key ecological barrier. Various ecological restoration projects have been undertaken in the TNEP to significantly enhance the vegetation cover. However, amidst the global climate change, it remains unclear whether the integrated ecological environmental quality (EEQ) of a region would improve through current or future ecological restoration projects. This study developed a remote sensing ecological index (RSEI) based on the Google Earth Engine (GEE) to characterize EEQ and revealed its trend from 2000 to 2022 in the TNEP and its sub-regions. Additionally, a SHapley Additive eXplanation (SHAP) interpretable machine learning model was employed to identify the dominant factors and thresholds influencing the EEQ in the TNEP and its sub-regions. The study further elucidated the role of land-use variations in EEQ, particularly those driven by ecological projects. The results indicated that from 2000 to 2022, the annual RSEI of the TNEP was predominantly poor or bad: it accounted for 55.4 % of the total RSEI. Notwithstanding an overall improvement (44.4 % of the total) consistent with the greenness compared with that of Northwest China (NWC), EEQ exhibited a marginal deterioration owing to the reduced wetness and increased heat and dryness. Future trends are likely to reflect those of the past 23 years, with improvement still predominant (37.5 % of the total), albeit with limited sustainability (including NWC). Precipitation (PRE) emerged as the dominant factor influencing the RSEI in the TNEP, North China (NC), and NWC (SHAP values of 0.1, 0.13, and 0.07, respectively). Meanwhile, the vapor pressure deficit (VPD) was critical for Northeast China (NEC) (SHAP value of 0.07). This study determined that the threshold for PRE to transition from inhibiting to promoting RSEI was 400 mm, whereas that for VPD to switch from promoting to inhibiting was 0.6 kPa. The land-use variations in forests, shrubs, grasslands, and croplands driven by ecological restoration and agricultural policies exerted a positive impact on RSEI. In contrast, grassland degradation and urbanization adversely affected it. These observations are important for accurately assessing the quality of ecological environments, effectively implementing ecological projects, and ensuring a sustainable regional development. Additionally, these have provided scientific references for determining whether to expand the implementation of ecological restoration measures in arid regions to enhance the ecological environment and establish a robust ecological security barrier.
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页数:22
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