数字农科院2.0

Long-Term Dynamic Monitoring and Driving Force Analysis of Eco-Environmental Quality in China

文献类型: 外文期刊

作者: Weiwei Zhang;Zixi Liu;Kun Qin;Shaoqing Dai;Huiyuan Lu;Miao Lu;Jianwan Ji;Zhaohui Yang;Chao Chen;Peng Jia

作者机构:

关键词: eco-environmental quality;GeoDetector;Google Earth Engine;remote sensing ecological index

期刊名称: Remote Sensing

ISSN: 2072-4292

年卷期: 2024 年 16 卷 6 期

页码:

收录情况: SCIE(2024版) ; ; EI(2024版)

摘要: Accurate assessments of the historical and current status of eco-environmental quality (EEQ) are essential for governments to have a comprehensive understanding of regional ecological conditions, formulate scientific policies, and achieve the United Nations Sustainable Development Goals (SDGs). While various approaches to EEQ monitoring exist, they each have limitations and cannot be used universally. Moreover, previous studies lack detailed examinations of EEQ dynamics and its driving factors at national and local levels. Therefore, this study utilized a remote sensing ecological index (RSEI) to assess the EEQ of China from 2001 to 2021. Additionally, an emerging hot-spot analysis was conducted to study the spatial and temporal dynamics of the EEQ of China. The degree of influence of eight major drivers affecting EEQ was evaluated by a GeoDetector model. The results show that from 2001 to 2021, the mean RSEI values in China showed a fluctuating upward trend; the EEQ varied significantly in different regions of China, with a lower EEQ in the north and west and a higher EEQ in the northeast, east, and south in general. The spatio-temporal patterns of hot/cold spots in China were dominated by intensifying hot spots, persistent cold spots, and diminishing cold spots, with an area coverage of over 90%. The hot spots were concentrated to the east of the Hu Huanyong Line, while the cold spots were concentrated to its west. The oscillating hot/cold spots were located in the ecologically fragile agro-pastoral zone, next to the upper part of the Hu Huanyong Line. Natural forces have become the main driving force for changes in China’s EEQ, and precipitation and soil sand content were key variables affecting the EEQ. The interaction between these factors had a greater impact on the EEQ than individual factors.

分类号:

  • 相关文献

[1]基于GEE云平台与Sentinel数据的高分辨率水稻种植范围提取——以湖南省为例. 桑国庆,唐志光,毛克彪,邓刚,王靖文,李佳. 2022

[2]基于Sentinel-1/2数据的中国南方单双季稻识别结果一致性分析. 杨靖雅,胡琼,魏浩东,蔡志文,张馨予,宋茜,徐保东. 2022

[3]基于多时相遥感植被指数的柑橘果园识别. 梁晨欣,黄启厅,王思,王聪,余强毅,吴文斌. 2021

[4]东北三省2020-2022年间10 m空间分辨率耕地资源空间分布数据集. 申格,刘航,李丹丹,陈实,邹金秋. 2023

[5]Assessment of land-use/cover changes and its ecological effect in rapidly urbanized areas-taking pearl river delta urban agglomeration as a case. Hu Panpan,Li Feng,Sun Xiao,Liu Yali,Chen Xinchuang,Hu Dan. 2021

[6]Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019. Liu Yifeng,Guo Bing,Lu Miao,Zang Wenqian,Yu Tao,Chen Donghua. 2022

[7]The Changes in Dominant Driving Factors in the Evolution Process of Wetland in the Yellow River Delta during 2015–2022. Cuixia Wei,Bing Guo,Miao Lu,Wenqian Zang,Fei Yang,Chuan Liu,Baoyu Wang,Xiangzhi Huang,Yifeng Liu,Yang Yu,Jialin Li,Mei Xu. 2023

[8]A Novel Framework for Exploring the Spatial Characteristics of Leisure Tourism Using Multisource Data: A Case Study of Qingdao, China. Shang, Yiqun,Wen, Caiyun,Bai, Yangchun,Hou, Dongyang. 2022

[9]Spatiotemporal Changes in NDVI and Its Driving Factors in the Kherlen River Basin. Yu, Shan,Du, Wala,Zhang, Xiang,Hong, Ying,Liu, Yang,Hong, Mei,Chen, Siyu. 2023

[10]Uncovering the Drivers and Regional Variability of Cotton Yield in China. Yaqiu Zhu,Bangyou Zheng,Qiyou Luo,Weihua Jiao,Yadong Yang. 2023

[11]Spatio-temporal evolution and driving factors of China’s agro-processing industry. Shuai Hao,Liping Liu,Guogang Wang. 2025

[12]Improving digital mapping of soil organic matter in cropland by incorporating crop rotation. Yuan Liu,Songchao Chen,Qiangyi Yu,Zejiang Cai,Qingbo Zhou,Sonoko Dorothea Bellingrath-Kimura,Wenbin Wu. 2023

[13]Mapping of lakes in the Qinghai-Tibet Plateau from 2016 to 2021: trend and potential regularity. Zhichong Yang,Si Bo Duan,Xiaoai Dai,Yingwei Sun,Meng Liu. 2022

[14]Rapid early-season maize mapping without crop labels. Nanshan You,Jinwei Dong,Jing Li,Jianxi Huang,Zhenong Jin. 2023

[15]Water quality related to Conservation Reserve Program (CRP) and cropland areas: Evidence from multi-temporal remote sensing. Dameng Yin , Le Wang, Zhenduo Zhu, Susan Spierre Clark , Ying Cao, Jordan Besek, Ning Dai. 2021

[16]Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data. Menglin Si,Zhao Liang Li,Françoise Nerry,Bo Hui Tang,Pei Leng,Hua Wu,Xia Zhang,Guofei Shang. 2022

[17]Generating Salt-Affected Irrigated Cropland Map in an Arid and Semi-Arid Region Using Multi-Sensor Remote Sensing Data. Deji Wuyun,Junwei Bao,Luís Guilherme Teixeira Crusiol,Tuya Wulan,Liang Sun,Shangrong Wu,Qingqiang Xin,Zheng Sun,Ruiqing Chen,Jingyu Peng,Hongtao Xu,Nitu Wu,Anhong Hou,Lan Wu,Tingting Ren. 2022

[18]From frequency to intensity – A new index for annual large-scale cropping intensity mapping. Jianbin Tao,Qiyue Jiang,Xinyue Zhang,Jianxi Huang,Yun Wang,Wenbin Wu. 2023

[19]Paddy Rice Phenological Mapping throughout 30-Years Satellite Images in the Honghe Hani Rice Terraces. Jianbo Yang,Jianchu Xu,Ying Zhou,Deli Zhai,Huafang Chen,Qian Li,Gaojuan Zhao. 2023

[20]Temporal segmentation method for 30-meter long-term mapping of abandoned and reclaimed croplands in Inner Mongolia, China. Deji Wuyun,Liang Sun,Zhongxin Chen,Luís Guilherme Teixeira Crusiol,Jinwei Dong,Nitu Wu,Junwei Bao,Ruiqing Chen,Zheng Sun,Hasituya,Hongwei Zhao. 2025

作者其他论文 更多>>