摘要
以新疆某铁矿及其周边区域作为研究对象,运用2007—2016年多时相TM/ETM+、OLI影像,分析铁矿及其周边区域植被覆盖度指数(fractional vegetation cover,FVC)及植被生长状况指数(vegetation condition index,VCI),评价研究区植被覆盖度、植被生长状况时空变化特征及铁矿开采对周边环境的影响,为矿区环境治理提供决策支持。结果表明,FVC及VCI指数能够较好地反映出研究区植被覆盖度及植被生长状况等级不高且铁矿区域几乎无植被生长的实际状况,为研究区生态风险防范提供理论支持。2007—2016年,研究区整体植被覆盖度及植被生长状况呈波动上升趋势,较低植被覆盖度等级和植被生长状况较差等级同时向较好等级发展。FVC及VCI较高等级主要分布在南坡及西南坡。但铁矿面积逐年增大,铁矿开采对其所在区域及周边区域造成了严重的植被退化和生态破坏,极易导致水土流失及山体滑坡等灾害的发生,应及时采取防控措施。
In Xinjiang iron ore and its surrounding area,using 2007—2016 multi temporal TM/ETM ＋ and OLI images,analysis of the iron ore and its surrounding large areas of vegetation cover index（ FVC） and the growth of vegetation condition index（ VCI）,the vegetation coverage,temporal and spatial changes of vegetation growth and the effect of iron ore mining on the surrounding environment were evaluated,to provide decision support for mine environment.The results showed that FVC and VCI index can reflect the low level of coverage vegetation and vegetation growth status in the study area,and there was almost no actual vegetation growth in iron ore area,which could provide theoretical support for ecological risk prevention. In 2007—2016,the overall vegetation coverage and vegetation growth in the study area fluctuated upward,and the lower vegetation coverage degree and poor vegetation growth status degree developed to a better level at the same time. The higher grades of FVC and VCI were mainly distributed in the southern and southwestern slope. But the iron ore mining area increased year by year,and the area and the surroundingarea has caused serious degradation of vegetation and ecological damage,which could easily lead to soil erosion and landslides and other disasters. Thus,prevention and control measures should be taken in time.
作者
庞冬
谭林
何秉宇
PANG Dong1,TAN Lin1,HE Bingyu1,2(1. Institute of Resources and Environmental Science, Xinjiang University,Urumqi 830046,China; 2. Laboratory of Wisdom City and Environmental Modeling, Urnmqi 830046, Chin)
出处
《浙江农业学报》
CSCD
北大核心
2018年第5期863-871,共9页
Acta Agriculturae Zhejiangensis
基金
新疆科技支疆项目(2016E02102)
