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基于Landsat遥感影像的围场县植被覆盖时空格局变化
引用本文:周智勇.基于Landsat遥感影像的围场县植被覆盖时空格局变化[J].水文地质工程地质,2020,47(6):81-90.
作者姓名:周智勇
作者单位:1. 河北省水文工程地质勘查院, 河北 石家庄 050021;
基金项目:中国地质调查局地质调查项目(DD20190310)
摘    要:基于Google Earth Engine遥感云平台收集1987—2016年Landsat系列遥感卫星影像,采用像元二分模型对承德市围场满族蒙古族自治县植被覆盖度进行估算,结合气象数据和地形信息,分析近30年来研究区植被覆盖动态变化规律。结果表明:围场县1987—2016年的归一化植被指数(NDVI)值总体上呈上升趋势,全县NDVI平均值从0.63提高到了0.78,植被覆盖状况不断改善。研究区植被改善情况中,1987—2016年NDVI大于0.15的面积比例占到全县植被面积的49.28%,占比最大。1987—2016年NDVI小于等于-0.15的植被面积比例仅为0.82%。1987—2016年,各级植被覆盖度的转移矩阵体现出2016年的植被状况明显好于1987年,极高覆盖度植被转入面积高达7 991.84 km2。1987—2016年植被覆盖景观破碎程度不断降低,平均斑块面积指数从13.147 8扩大到31.703 4,植被覆盖类型趋于集中分布,连通性好。研究区总体气候变化趋势对植被生长具有不利影响,不同坡度和坡向的植被覆盖状况不同,人类活动和社会经济因素的影响为研究区植被改善情况发挥着重要作用。

关 键 词:Landsat    围场    NDVI    植被覆盖度    时空格局
收稿时间:2020-08-14

Change in temporal-spatial pattern of vegetation coverage in Weichang County based on Landsat remote sensing image
Institution:1. Hebei Provincial Prospecting Institute of Hydrogeology and Engineering Geology, Shijiazhuang, Hebei 050021, China;2. Hebei Provincial Remote Sensing Centre, Shijiazhuang, Hebei 050021, China
Abstract:Based on the Google Earth engine remote sensing cloud platform, the Landsat series remote sensing satellite images from 1987 to 2016 were collected, and the vegetation coverage of Weichang Manchu and Mongolian Autonomous County in Chengde was estimated by using the pixel binary model, and the dynamic changes in vegetation coverage in the study area in the past 30 years were analyzed through combining the meteorological data and terrain information. The results indicate that the normalized vegetation index (NDVI) value of Weichang County from 1987 to 2016 showed an overall upward trend, and the average NDVI value of Weichang County increased from 0.63 to 0.78, and the vegetation coverage status improved continuously. Among the vegetation improvement in the study area, 49.28% of the county's vegetation area was accounted for with the NDVI difference value > 0.15 from 1987 to 2016 (with the largest proportion), while the proportion of vegetation area with NDVI difference value less than -0.15 from 1987 to 2016 was only 0.82%. The transfer matrix of vegetation coverage at all levels from 1987 to 2016 shows that the vegetation condition in 2016 was obviously better than that in 1987, and the area of vegetation with extremely high coverage was 7 991.84 km2. From 1987 to 2016, the fragmentation degree of vegetation coverage landscape decreased continuously, the average patch area index increased from 13.147 8 to 31.703 4, and the vegetation coverage types tended to be centralized distribution with good connectivity. The overall climate change trend in the study area has adverse effects on vegetation growth. The vegetation coverage of different slope and aspect is different. The influence of human activities and socio-economic factors plays an important role in vegetation improvement in the study area.
Keywords:
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