Remote Sensing Dynamic Monitoring on Temporal and Spatial Changes of Vegetation Coverage in Sichuan Province from 2009 to 2020

He Liping; Jian Ji

doi:10.13961/j.cnki.stbctb.2022.02.028

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Remote Sensing Dynamic Monitoring on Temporal and Spatial Changes of Vegetation Coverage in Sichuan Province from 2009 to 2020

- Remote Sensing Dynamic Monitoring on Temporal and Spatial Changes of Vegetation Coverage in Sichuan Province from 2009 to 2020
- Bulletin of Soiland Water Conservation Vol. 42, Issue 2, Pages: 203-209(2022)
- 作者机构：
  
  成都理工大学地球科学学院,四川,成都,610059
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2022.02.028
  CLC： Q948
- Published：2022
- 稿件说明：
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He Liping, Jian Ji. Remote Sensing Dynamic Monitoring on Temporal and Spatial Changes of Vegetation Coverage in Sichuan Province from 2009 to 2020[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 203-209.
DOI：

He Liping, Jian Ji. Remote Sensing Dynamic Monitoring on Temporal and Spatial Changes of Vegetation Coverage in Sichuan Province from 2009 to 2020[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 203-209. DOI： 10.13961/j.cnki.stbctb.2022.02.028.

摘要

[目的] 监测和分析四川省2009—2020年植被覆盖度时空变化特征，为定量评估区域生态环境提供重要的基础研究数据，也为城市规划及可持续城市发展提供科学参考。[方法] 借助Google Earth Engine云计算平台，获取了2009—2020年四川省Landsat系列影像，利用像元二分模型对研究区植被覆盖度进行了定量估算。[结果] ①2009—2020年间，四川省主要以高、中高植被覆盖度为主，其面积可达全省面积的80%，而低、中低植被覆盖度面积所占比例低于10%。②从空间上分布，四川省植被覆盖度空间差异比较明显，植被覆盖度较低区域主要分布在成都平原经济区及川西部分地区； ③从空间变化特征上分析，2009—2020年研究区的植被覆盖度整体呈现基本稳定趋势(44.39%)，植被覆盖度改善的区域面积(30.78%)大于植被覆盖度退化区域(24.82%)，其中明显退化区域面积所占比例最少，仅占全省面积的4.96%。[结论] 总体上，2009—2020年四川省的植被覆盖状况良好，以高、中高植被覆盖度为主，植被覆盖度呈现基本稳定趋势。

Abstract

[Objective] The temporal and spatial variation characteristics of vegetation coverage in Sichuan Province from 2009 to 2020 were monitored and analyzed

in order to provide important basic research data for quantitative assessment of the regional ecological environment

and scientific references for urban planning and sustainable urban development. [Methods] Landsat images of Sichuan Province from 2009 to 2020 were acquired from the Google Earth Engine cloud computing platform

and the vegetation coverage area was quantitatively estimated by the binary pixel model. [Results] ① In the 11 years from 2009 to 2020

Sichuan Province was mainly dominated by high and medium high vegetation coverage

accounting for 80% of the province’s area

while the proportion of low and medium low vegetation coverage was less than 10%. ② From the perspective of spatial distribution

the spatial difference of fractional vegetative cover (FVC) in Sichuan Province was obvious. The areas with low FVC were mainly located in the Chengdu Plain Economic Zone and some areas in Western Sichuan Province. ③ From the analysis of spatial change characteristics

FVC in the study area showed a basically stable trend (44.39%) from 2009 to 2020. The area of FVC improvement (30.78%) was larger than that of FVC degradation (24.82%)

and the area of obvious degradation accounted for the least proportion (only 4.96% of the province’s area). [Conclusion] On the whole

vegetation coverage in Sichuan Province from 2009 to 2020 was in good condition

mainly with high and medium high vegetation coverage. The vegetation coverage showed a basically stable trend. From 2009 to 2020

the area of Sichuan Province was mainly dominated by high and medium high FVC levels that accounted for 80% of the province’s area

while the area of low and medium low FVC accounted for less than 10% of the area.

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references

赵英时.遥感应用分析原理与方法[M].北京：遥感应用分析原理与方法,2003.

颜明,贺莉,王随继,等.基于NDVI的1982—2012年黄河流域多时间尺度植被覆盖变化[J].中国水土保持科学,2018,16(3):86-94.

Gitelson A A, Kaufman Y J, Stark R, et al. Novel algorithms for remote estimation of vegetation fraction [J]. Remote Sensing of Environment, 2002,80(1):76-87.

朱高龙,柳艺博,居为民,等.4种常用植被指数的地形效应评估[J].遥感学报,2013,17(1):210-234.

马锋,卓静,何慧娟,等.陕西省榆林市植被生态演变及其驱动机制[J].水土保持通报,2020,40(5):257-261,267.

何国兴,柳小妮,张德罡,等.甘肃省高寒草甸植被覆盖度反演及其时空变化研究[J].草地学报,2021,29(3):593-602.

乔文慧,王强.2001—2016年福建省海岸带植被覆盖变化特征[J].水土保持通报,2020,40(1):236-242.

李梓钰,陈启慧,黄峰,等.吐鲁番盆地骆驼刺保护区植被覆盖度时空演变[J].干旱区研究,2021,38(4):1104-1110.

杨绘婷,徐涵秋,施婷婷,等.基于植被信息季节变换的植被覆盖度变化:以福建省连江县为例[J].应用生态学报,2019,30(1):285-291.

李晶,刘乾龙,刘鹏宇.1998—2018年呼伦贝尔市植被覆盖度时空变化及驱动力分析[J]. 2022,42(1):220-235.

皮新宇,曾永年,贺城墙.融合多源遥感数据的高分辨率城市植被覆盖度估算[J].遥感学报,2021,25(6):1216-1226.

Niu Yaxiao,Han Wenting,Zhang Huihui, et al. Estimating fractional vegetation cover of maize under water stress from UAV multispectral imagery using machine learning algorithms [J]. Computers and Electronics in Agriculture, 2021,189(8):106414.

李苗苗,吴炳方,颜长珍,等.密云水库上游植被覆盖度的遥感估算[J].资源科学,2004,26(4):153-159.

Hansen M C, Potapov P V, Moore R, et al. High-resolution global maps of 21st century forest cover change[J]. science, 2013, 342(6160): 850-853.

Tamiminia H, Salehi B, Mahdianpari M, et al. Google Earth Engine for geo-big data applications: A meta-analysis and systematic review [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 164: 152-170.

Fashae O A, Adagbasa E G, Olusola A O, et al. Land use/land cover change and land surface temperature of Ibadan and environs, Nigeria [J]. Environmental Monitoring and Assessment, 2020, 192(2): 1-18.

Chen Bangqian, Xiao Xiangming, Li Xiangping, et al. A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform [J]. Isprs Journal of Photogrammetry and Remote Sensing, 2017,131:104-120.

Sun Zhongchang, Xu Ru, Du Wenjie, et al. High-resolution urban land mapping in China from sentinel 1A/2 imagery based on Google Earth Engine[J]. Remote Sensing, 2019, 11(7): 752.

陈炜,黄慧萍,田亦陈,等.基于Google Earth Engine平台的三江源地区生态环境质量动态监测与分析[J].地球信息科学学报,2019,21(9):1382-1391.

Pereira O J R, Merino E R, Montes C R, et al. Estimating water pH using cloud-based landsat images for a new classification of the Nhecollndia Lakes (Brazilian Pantanal)[J]. Remote Sensing, 2020, 12(7): 1090.

赵海凤.四川省森林生态系统服务价值计量与分析[D].北京：北京林业大学,2014.

黄从德.四川森林生态系统碳储量及其空间分异特征[D].四川成都：四川农业大学,2008.

Holben, Brent N. Characteristics of maximum-value composite images from temporal AVHRR data [J]. International Journal of Remote Sensing, 1986,7(11):1417-1434.

Carlson T N, Ripley D A. On the relation between NDVI, fractional vegetation cover, and leaf area index [J]. Remote Sensing of Environment, 1997,62(3):241-252.

李晶,崔绿园,闫萧萧,等.草原矿区长时序植被覆盖度变化趋势对比分析[J].测绘通报，2019(8):130-134,157.

张本昀,喻铮铮,刘良云,等.北京山区植被覆盖动态变化遥感监测研究[J].地域研究与开发,2008,27(1):108-112.

李林叶,田美荣,梁会,等.2000—2016年呼伦贝尔草原植被覆盖度时空变化及其影响因素分析[J].生态与农村环境学报,2018,34(7):584-591.

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