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林业科学 ›› 2022, Vol. 58 ›› Issue (4): 141-151.doi: 10.11707/j.1001-7488.20220415

• 研究论文 • 上一篇    下一篇

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. 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 100091
  • 收稿日期:2021-11-21 出版日期:2022-04-25 发布日期:2022-07-20
  • 通讯作者: 郄光发
  • 基金资助:
    科技基础资源调查专项(2019FY202501);科技基础资源调查专项(2019FY202504)

Temporal and Spatial Changes Monitoring of Vegetation Coverage for the Ecological Core Area of Chongli Winter Olympic Games

Bingxiang Tan1,Mingtan Shen1,Guangfa Qie2,*,Zhao Qi1,Chenrui He1   

  1. 1. Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration Research Institute of Forest Resources Information Techniques, CAF Beijing 100091
    2. Chinese Academy of Forestry Beijing 100091
  • Received:2021-11-21 Online:2022-04-25 Published:2022-07-20
  • Contact: Guangfa Qie

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, 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, 2014—2016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; 2016—2020年改善型和退化型在海拔1 700 m以下区域有分布优势, 明显退化型表现出极强分布优势; 2014—2020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)2014—2016年和2016—2020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, 2014—2016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, 2016—2020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; 2014—2016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1 533~1 700 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

Abstract:

Objective: Based on the results of remote sensing quantitative estimation of vegetation 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 environmental protection and forest fire prevention in the study area. Method: In this 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 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 cover 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 whole 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 coverage. 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 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 2020, 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, while 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 distribution on shady slope. From 2016 to 2020, the slightly improved vegetation had a dominant distribution on sunny 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 levels 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 differences 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 Olympics 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 vegetation cover(FVC), dimidiate pixel model, topographic differentiation features, remote sensing, Chongli

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