1、第 58 卷 第 4 期2 0 2 2 年 4 月林业科学SCIENTIASILVAESINICAEVol.58,No.4Apr.,2 0 2 2doi:10.11707/j.1001-7488.20220415收稿日期:2021-11-21;修回日期:2022-03-17。基金项目:科技基础资源调查专项(2019FY202501,2019FY202504)。郄光发为通讯作者。冬奥会崇礼生态核心区植被覆盖时空变化遥感监测谭炳香1沈明潭1郄光发2戚瞾1贺晨瑞1(1.中国林业科学研究院资源信息研究所国家林业和草原局林业遥感与信息技术重点实验室北京 100091;2.中国林业科学研究院北京 1000
2、91)摘要:【目的】基于植被覆盖度遥感定量估测结果,统计分析植被覆盖度的时空变化特征和地形分异效应,探讨植被覆盖变化的驱动因素,为研究区生态规划和生态环境保护、森林防火提供参考依据。【方法】以北京冬奥会崇礼生态核心区为研究区,以 GF-1 WFV 和 Sentinel-2 多光谱影像为数据源,采用像元二分模型法对研究区 2014、2016 和 2020 年 3 个时期的植被覆盖度进行遥感估测,结合数字高程模型,利用差值指数、马尔科夫模型、植被覆盖动态度和地形分布指数分析植被覆盖度的时空变化特征及其在地形上的分异性。【结果】1)研究区植被覆盖度在空间上呈显著差异性,表现为中部低、四周高的分布格局
3、,与整个研究区的地形地貌特征紧密相关,山区植被覆盖度高,平原区或山谷等人类活动区植被覆盖度相对偏低。2)研究区植被整体以中、中高和高植被覆盖度为主,3个时期 3 种植被覆盖等级面积占比分别为 81.59%、90.00%和 86.88%,均大于 80%,植被覆盖处于较好水平,生长状况良好。3)海拔梯度上,20142016 年改善型和明显退化型在海拔 1 800 m 以下区域有分布优势,在海拔1 800 m 以上区域无分布优势;轻微退化型在海拔 1 700 m 以下和 2 000 m 以上区域有分布优势;20162020 年改善型和退化型在海拔 1 700 m 以下区域有分布优势,明显退化型表现出
4、极强分布优势;20142020 年明显改善型在海拔 1 700 m 以下区域有分布优势,在海拔 2 000 m 以上区域分布优势较弱,而明显退化型在海拔 1 700 m 以下区域表现出强优势分布,在海拔 1 700 m 以上区域则无分布优势。4)20142016 年和 20162020 年植被覆盖退化主要分布在坡度小于 8的平缓区域,8以上区域无分布优势,其他植被覆盖度变化类型在坡度上趋于稳定。5)坡向上,20142016 年改善型植被在阳坡和半阳坡有分布优势,明显退化型在阴坡有分布优势,20162020 年轻微改善型在阳坡和半阳坡有分布优势,明显退化型和轻微退化型在阴坡有分布优势;20142
5、016 年改善型在阳坡和半阳坡有分布优势,轻微退化型在阴坡和半阴坡有分布优势。【结论】1)植被覆盖度在空间上呈中间低、四周高的分布格局,在时间上表现为 2014、2016 和 2020 年不同等级间的植被覆盖度结构平稳,局部植被覆盖度出现降低现象,总体趋势为植被覆盖度增加。2)植被覆盖度在海拔、坡度和坡向不同等级上呈规律性分布,植被覆盖变化类型与地形因子存在显著差异,明显减少型区域聚集在坡度小于 8、海拔 1 5331 700 m 区域,在坡向上没有明显表现出分异性,主要为土地利用方式转换所致;植被覆盖明显改善型聚集在阳坡和半阳坡地区,说明人工造林效果比较明显。3)森林防火重点区域为植被覆盖度
6、高的山区。关键词:植被覆盖度;像元二分模型;地形分异特征;遥感;崇礼区中图分类号:S757文献标识码:A文章编号:1001-7488(2022)04-0141-11Temporal and Spatial Changes Monitoring of Vegetation Coverage for the Ecological Core Area of Chongli Winter Olympic Games Tan Bingxiang1 Shen Mingtan1 Qie Guangfa2 Qi Zhao1 He Chenrui1(1.Key Laboratory of Forestry Re
7、mote Sensing and Information System,National Forestry and Grassland AdministrationResearch Institute of Forest Resources Information Techniques,CAFBeijing 100091;2.Chinese Academy of ForestryBeijing 100091)Abstract:【Objective】Based on the results of remote sensing quantitative estimation of vegetati
8、on coverage,the temporal and spatial characteristics of vegetation coverage and topographic differentiation effects were analyzed statistically,and the driving factors of vegetation coverage changes were also discussed,which were expected to provide a reference for ecological planning,ecological env
9、ironmental protection and forest fire prevention in the study area.【Method】In this 林业科学58 卷study,Chongli core area of Beijing Winter Olympic Games was taken as the research area,GF-1 WFV and Sentinel-2 multispectral images were used as data sources,and the pixel dichotomy method of DNVI was used to
10、estimate the vegetation coverage of the study area in 2014,2016 and 2020.Combined with digital elevation model,the spatial and temporal variation characteristics of vegetation cover and its topographic differentiation were analyzed by difference index,Markov model,dynamic attitude of vegetation cove
11、r and topographic distribution index.【Result】1)The spatial difference of vegetation coverage in the study area is significant,showing a pattern of low vegetation coverage in the middle and high vegetation coverage in the periphery,which is closely related to the topography and geomorphology of the w
12、hole study area.The vegetation coverage in the mountainous area is high,while that in the plain area or the mountain base is the area of human activities,and the vegetation coverage is relatively low.2)The vegetation status of the study area was mainly dominated by middle and high vegetation coverag
13、e.In 2014,2016 and 2020,the areas covered by the three planting grades accounted for 81.59%,90.00%and 86.88%,respectively.The vegetation coverage of the three periods in the study area was at a good level(more than 80%),indicating that the vegetation growth status in the study area was perfect.3)For
14、 the elevation gradient,from 2014 to 2016,the improved type and the significantly degraded type had a distribution advantage below 1 800 m,but there was no distribution advantage above 1 800 m,and the slightly degraded type had a distribution advantage below 1 700 m and above 2 000 m.From 2016 to 20
15、20,the improved type and degraded type under 1 700 m had a distribution advantage,and the obvious degraded type showed a strong distribution advantage.From 2014 to 2020,the significantly improved type had a distribution advantage below 1 700 m and had a weak distribution advantage above 2 000 m,whil
16、e the significantly degraded type showed a strong dominance distribution below 1 700 m and had no distribution advantage above 1 700 m.4)From 2014 to 2016,the improved type had a dominant distribution on sunny and semi-sunny slopes,while the slightly degraded type had a dominant distribution on shady and semi-shady slopes.5)From 2014 to 2016,the improved vegetation had a dominant distribution on sunny slope and semi-sunny slope,and the significantly degraded vegetation had a dominant distributio