摘要
生态敏感性是指生态系统有外界干扰的情况下,其适应能力及遭到破坏后生态系统恢复能力强弱。生态敏感性评价能为分析和预测区域的生态环境问题提供科学依据。论文以吕梁山区13个国家级贫困县为研究区域,针对吕梁山区的生态环境特点,在GIS和RS技术支持下,选取高程、坡度、植被覆盖指数(NDVI)、土地利用、土壤质地及降水侵蚀力6个因子进行生态环境敏感性评价。结果表明:吕梁山区极高敏感区占研究区面积0.44%,高度敏感区占46.74%,中度敏感区占39.60%,低度敏感区占12.11%,不敏感区占1.11%,生态环境敏感程度总体偏高,其中岢岚县、隰县、静乐县生态环境敏感程度最高,永和县、临县、汾西县相对较低。研究结果可为政府部门制定区域生态安全防范策略提供一定的参考。
Ecological sensitivity refers to the adaptability and restoration ability of ecosystem when it is disturbed by constant external interference and destruction.Ecological sensitivity evaluation can provide scientific basis for analysis and prediction of regional ecological environment problems.According to the characteristics of the ecological environment in Lvliang mountainous area,13 national poverty-stricken Counties in Lvliang mountainous area were selected as the study area.With the support of GIS and RS technology,these six factors were used to evaluate the sensitivity of ecological environment which included elevation,slope,vegetation coverage index(NDVI),land use,soil texture and rainfall erosivity.The results show that the sensitivity of the ecological environment in Lvliang mountainous area was generally high.In the whole study area,the extremely sensitive area accounted for 0.44%,the highly sensitive area accounted for 46.74%,the moderately sensitive area accounted for 39.60%,the low sensitive area accounted for 12.11%,and the non sensitive area accounted for 1.11%.Moreover,Kelan County,Xi County and Jingle County had the highest sensitivity to ecological environment,while Yonghe County,Linxian County and Fenxi County were relatively low.The results can provide some references for the government departments to formulate regional ecological security prevention strategies.
作者
张会霞
刘丽荣
ZHANG Huixia;LIU Lirong(Institute of Geographical Science,Taiyuan Normal University,Jinzhong 030619,China)
出处
《生态科学》
CSCD
2020年第6期30-37,共8页
Ecological Science
基金
国家自然科学基金青年科学基金项目(41501219)
山西省自然科学基金项目(201901D111291)。
关键词
吕梁山区
生态敏感性评价
变异系数
加权叠加
lvliang mountainous area
ecological sensitivity evaluation
variance coefficient
weighted superposition
