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.pdf
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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 shad
17、y 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 distribution on shady slope.From 2016 to 2020,the slightly improved vegetation had a dominant distribution on s
18、unny slope and semi-sunny slope,and the significantly degraded and slightly degraded vegetation had a dominant distribution on shady slope.【Conclusion】1)The vegetation coverage was spatially low in the middle and high in the surrounding areas.The structure of vegetation coverage among different leve
19、ls in 2014,2016 and 2020 was stable,but the local vegetation coverage was seriously degraded.The overall trend is to increase vegetation coverage.2)The vegetation coverage of the study area showed a regular distribution at different levels of altitude,slope and aspect;there are significant differenc
20、es between the types of vegetation coverage changes and topographical factors.Obviously the degraded areas gathered where the slope is less than 8 and the altitude is 1 533-1 700 m,but do not show obvious differentiation in the slope direction,mainly due to the construction land for the Winter Olymp
21、ics venues.Obviously improved vegetation coverage is concentrated in sunny and semi-sunny slope areas,indicating that the effects of artificial afforestation are more obvious.3)The focus of forest fire prevention is in the mountainous areas with a high vegetation coverage.Key words:fraction vegetati
22、on cover(FVC);dimidiate pixel model;topographic differentiation features;remote sensing;Chongli植被覆盖度(fraction vegetation cover,FVC)指单位面积内植被地上部分(包括叶、茎、枝)在地表的垂直投影面积占统计区总面积的百分比(Gitelson et al.,2002),是量化植被覆盖地表状况的重要指标,是衡量地区生态环境质量变化的重要参数,也是森林防火的重要参考因子。植被覆盖度测量可采用地面测量和遥感估测 2种方法,地面测量常用于田间尺度,遥感估测常用于区域尺度。遥感估测植
23、被覆盖度的方法很多,其中基于植被指数的混合像元二分模型法因参数意义明确、模型简单、结果可靠被广泛应用(李彩霞等,2021)。当前,植被覆盖度研究主要集中在分布格局(Shen et al.,2019;何国兴等,2021)、变化特征(Zhang et al.,2019;佟 斯 琴 等,2016)、驱 动 因 素(Hao et al.,2021)、现状评价(尚白军等,2021)、预测分析(Li et al.,2021)和生态监测应用(戚曌等,2021)等方面,从自然因素(Song et al.,2020;覃巧婷等,2021)、人为因素(张翀等,2021)或两因素共同作用(李彩霞等,2021)角度探讨
24、植被覆盖变化的驱动力。在局部地区气候条件相对一致的前提下,地形是影响植被空241第 4 期谭炳香等:冬奥会崇礼生态核心区植被覆盖时空变化遥感监测间分布的主要生境因子之一(申丽娜等,2017),不同海拔、坡度和坡向植被生长所需物质能量与空间资源的差异以及人为活动决定植被的发展方向,植被覆盖变化在地形上具有明显分异规律(He et al.,2021;韩磊等,2021;杨灿等,2021)。河北省张家口市崇礼区地处我国北方农牧交错地带,为京津冀风沙源区、水源涵养区和 2022 年北京冬奥会主要举办地之一,该区生态环境相对脆弱,土地利用景观类型、植被覆盖度变化等均会给生态环境和人们生产生活带来影响。为实
25、现冬奥核心区生态环境长久性优良的目标,20162019 年,崇礼区相继完成冬奥核心区绿化工程 3 万 hm2,森林覆盖率超过 80%,植被覆盖度大幅提高,生态环境得到明显改善,但冬奥会场馆、场地和配套设施建设难免对植被覆盖造成破坏,进而影响整个区域的生态环境。客观估测和分析冬奥会场地建设前后植被覆盖度的变化状况和驱动因素、分析植被覆盖度变化在不同地形上的分布特点和规律,能够对崇礼冬奥核心区全域生态景观的统筹规划建设效果做出科学评价,为今后生态资源保护和修复提供依据,对京津冀地区的水土保持、防风治沙、生态建设、森林防火等均具有重要参考价值。鉴于此,本研究以北京冬奥会崇礼生态核心区为研究区,基于冬
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