摘要
黄河流域在中国社会经济发展和生态安全方面的地位十分重要,过去几十年的自然演变和人类活动对其造成了深远影响,系统科学地认识黄河流域的环境格局变化是实现黄河流域高质量发展的重要前提。基于Google Earth Engine平台和复杂网络分析方法,解译并分析了1986年至2018年黄河流域的连续年度土地利用/覆被变化(LUCC)。基于1000个独立验证点进行的评估显示解译的覆盖黄河流域33年的年度土地利用/覆被数据集的7个一级类的总体准确率为82.6%,15个二级类的总体准确率为74.7%。分析结果显示黄河流域的土地系统在整个研究期间呈现出复杂的时空变化,主要的LUCC模式包括:不变或很小的变化、伴随耕地流失的城市扩张、草地恢复、果园和梯田扩张和森林增加。基于复杂网络方法对黄河流域土地系统的分析表明,土地利用/覆被转移网络中的高覆盖草地、低植被覆盖地表和落叶常绿混交林与其他地类的转移较频繁,地类节点的中介中心性和度值较高,是黄河流域土地系统中的关键地类。另外与人类活动关系密切的果园和梯田、谷物耕地和城市及建设用地节点组成了较为活跃的网络社区结构,它们都有较高的结构多样性、接近中心性,这些地类之间的转移是土地系统中重要的地类转移类型。时间序列的转移网络分析表明黄河流域的土地系统在1993—1998年、2001—2007年、2011—2014年存在三个不稳定时期,这三个不稳定时期的出现可能分别由大量的农业土地开发、退耕还林还草工程和果园梯田的大量增加导致。对黄河流域的长时间土地利用/覆被动态的系统性分析提供了关于环境政策和社会经济活动对土地系统造成何种影响的见解,表明黄河流域正朝着实现农民生计安全,区域经济增长和生态环境保护的可持续发展的目标迈进,并为LUCC研究提供了新的数据处理方式和新的系统科学视角,有助于实现区域的高质量可持续发展和理解人与自然系统之间的相互作用关系。
The Yellow River Basin plays an important role in China′s economic and social development and ecological security. The natural evolution and human activities in past decades had a profound impact on the Basin. A systematic and scientific understanding of the environmental changes in the Yellow River Basin is an important premise to achieve the high-quality development of the Basin. Using landsat imagery(17080 scenes) and the classification and regression trees algorithm, mapped and analyzed the annual continuous land use/cover change(LUCC) of the Yellow River Basin based on the Google Earth Engine platform and complex network analysis methods, and provided a set of 90 m resolution continuous annual land use/cover maps from 1986 to 2018. The assessment based on 1000 independent validation points collected in Google Earth indicated that these maps achieved an overall accuracy of 82.6% for 7 first-degree classes and 74.7% for 15 second-degree classes. The analysis of the land system showed that the Yellow River Basin presented complex temporal and spatial changes during the study period. The main LUCC patterns included no change or little change, urban expansion with croplands loss, grasslands restoration, orchard and terrace expansion, and forests growth. In the land use/cover transfer network, high coverage grasslands, low-vegetated lands, and the mixed forests were the key land class nodes in the land system of the Yellow River Basin, with high degrees and frequent transfers with other classes. In addition, the nodes of orchard and terrace, croplands, and urban and built-up all had high diversity and closeness and form one relatively active network community structure. The transfers between them were more important land transfer types in the land system. Time series transfer network analysis showed that the land system of the Yellow River Basin had three unstable periods in 1993—1998, 2001—2007, and 2011—2014 with lower average shortest-path length and higher network density and network transitivity. The possible reasons for these three periods are the reclamation of a large amount of agricultural land, the implementation of the Grain for Green program, and the large increase in orchard and terrace, respectively. Based on the data and analysis results, we can further understand the role of the land system in the mutual feedback between society and the environment. The results of LUCC analysis revealed the land use/cover dynamics caused by frequent human activities in the Yellow River Basin, provided insights on the impact of environmental policies and socio-economic activities on the land system, which showed that the Yellow River is moving towards achieving the sustainable development goals of livelihood security, economic growth, and ecological protection. Research provided new data processing methods and new system science perspectives for LUCC analysis, which can help to achieve high-quality regional development and to understand the interaction between human and natural systems.
作者
纪秋磊
梁伟
傅伯杰
吕一河
严建武
张为彬
金朝
兰志洋
JI Qiulei;LIANG Wei;FU Bojie;LÜ Yihe;YAN Jianwu;ZHANG Weibin;JIN Zhao;LAN Zhiyang(School of Geography and Tourism,Shaanxi Normal University,Xi′an 710119,China;State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China;Xi′an Gu Bo Electronic Intelligent Technology Co.,Ltd,Xi′an 710068,China;State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Northwest A&F University,Yangling 712100,China)
出处
《生态学报》
CAS
CSCD
北大核心
2022年第6期2122-2135,共14页
Acta Ecologica Sinica
基金
国家自然科学面上基金项目(42071144,41771118)
国家重点研发计划重点专项(2016YFC0501601)
中央高校基本科研业务费专项资金(GK202003060)。
