Temporal and Spatial Variations of Vegetation Coverage in Zhejiang Province Based on MODIS Data

SONG Li-wang; DENG Jian; WANG Wei-min; QI De-hui

doi:10.11988/ckyyb.20200285

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Journal of Changjiang River Scientific Research Institute ›› 2021, Vol. 38 ›› Issue (5) : 40-46. DOI: 10.11988/ckyyb.20200285

WATER-SOIL CONSERVATION AND ECOLOGICAL RESTORATION

Temporal and Spatial Variations of Vegetation Coverage in Zhejiang Province Based on MODIS Data

SONG Li-wang, DENG Jian, WANG Wei-min, QI De-hui

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Abstract

In the purpose of providing theoretical support for the eco-environment construction and soil-water loss prevention in Zhejiang Province, we estimated the vegetation coverage of Zhejiang Province in 2009-2018 using an improved dimidiate pixel model based on monthly NDVI values obtained from using MVC maximum synthesis method according to MODIS_NDVI data in 2009-2018. Moreover, in line with DEM data and the division of forest land in the Plan for the Protection and Utilization of Forest Land in Zhejiang Province (2010-2020), we probed into the spatial-temporal changes in the vegetation coverage of Zhejiang Province. Results unveiled that: 1) From 2009 to 2018, Zhejiang Province featured an overall high vegetation coverage, with a slow downward trend. 2) The spatial pattern of vegetation coverage in 2018 differed little with that in 2009. Vegetation coverage in south and west mountainous and hilly area was the highest, followed by that in central Zhejiang hilly basin area, east Zhejiang coastal hilly island area, and northern Zhejiang plain area in sequence. Areas with stable vegetation coverage accounted for 62.79% of the total area; the area of vegetation degradation was larger than the area of improvement. Vegetation degradation was most serious in the northern Zhejiang plain area, accounting for 6.73% of the total area. In particular, the south Zhejiang mountain area witnessed the most notable improvement of vegetation coverage, occupying 4.87% of the total area. 3) The change of vegetation coverage with geographical factors was relatively stable; within different elevation ranges, areas with obvious degradation were below 100 m, and obvious improvement above 200 m; within different slope ranges, areas with evident degradation were between 0° and 5°, and apparent improvement above 15°; vegetation coverage changed slightly with slope gradient.

Key words

vegetation coverage / MODIS_NDVI / difference of vegetation chage / spatiotemporal change / Zhejiang Province

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SONG Li-wang, DENG Jian, WANG Wei-min, QI De-hui. Temporal and Spatial Variations of Vegetation Coverage in Zhejiang Province Based on MODIS Data[J]. Journal of Changjiang River Scientific Research Institute. 2021, 38(5): 40-46 https://doi.org/10.11988/ckyyb.20200285

References

[1] 陈洪磊,欧阳炜,吕凤玲,等.官渡河流域植被覆盖变化与地形因子相关性[J].水土保持研究,2019,26(3):135-140,147.
[2] 张诗羽,张毅,王昌全,等.岷江上游流域植被覆盖度及其与地形因子的相关性[J].水土保持通报,2018,38(1):69-75.
[3] 魏建瑛,徐建英,樊斐斐.卧龙自然保护区植被覆盖度变化及其对地形因子的响应[J].长江流域资源与环境,2019,28(2):440-449.
[4] GITELSON AA,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.
[5] 赵丽红,王屏,欧阳勋志,等.南昌市植被覆盖度时空演变及其对非气候因素的响应[J].生态学报,2016,36(12):3723-3733.
[6] 毛德华,王宗明,罗玲,等.基于MODIS和AVHRR数据源的东北地区植被NDVI变化及其与气温和降水间的相关分析[J].遥感技术与应用,2012(1):77-85.
[7] 王静,周伟奇,许开鹏,等.京津冀地区城市化对植被覆盖度及景观格局的影响[J].生态学报,2017,37(21):7019-7029.
[8] 刘宪锋,朱秀芳,潘耀忠,等.1982—2012年中国植被覆盖时空变化特征[J].生态学报,2015,35(16):5331-5342.
[9] 张灿,徐涵秋,张好,等.南方红壤典型水土流失区植被覆盖度变化及其生态效应评估:以福建省长汀县为例[J].自然资源学报,2015,30(6):917-928.
[10] 李恒凯,刘小生,李博,等.红壤区植被覆盖变化及与地貌因子关系:以赣南地区为例[J].地理科学,2014,34(1):103-109.
[11] 吴志杰,何国金,黄绍霖,等.南方丘陵区植被覆盖度遥感估算的地形效应评估[J].遥感学报,2017,21(1):159-167.
[12] 熊俊楠,彭超,程维明,等.基于MODIS-NDVI的云南省植被覆盖度变化分析[J].地球信息科学学报,2018,20(12):1830-1840.
[13] 何月,樊高峰,张小伟,等.浙江省植被NDVI动态及其对气候的响应[J].生态学报,2012,32(14):4352-4362.
[14] 高大伟,张小伟,蔡菊珍,等.浙江省植被覆盖时空动态及其与生态气候指标的关系[J].应用生态学报,2010,21(6):1518-1522.
[15] 何月,樊高峰,张小伟,等.浙江省植被物候变化及其对气候变化的响应[J].自然资源学报,2013,28(2):220-233.
[16] 李洪伟.浙江省植被覆盖的时空变化研究[D].金华:浙江师范大学,2010.
[17] 张丽,何晓旭,魏鸣.基于NDVI的淮河流域植被覆盖度动态变化[J].长江流域资源与环境,2012,21(增刊1):51-56.
[18] XU Shuang, SHEN Run-ping, YANG Xiao-yue. A Comparative Study of Different Vegetation Indices for Estimating Vegetation Coverage Based on the Dimidiate Pixel Model[J]. Remote Sensing for Land & Resources, 2012, 24(4): 95-100.
[19] 赵婷,白红英,邓晨晖,等.2000—2016年秦岭山地植被覆盖变化地形分异效应[J].生态学报,2019,39(12):4499-4509.
[20] 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.
[21] SL 190—2007,土壤侵蚀分类分级标准[S].北京:中国水利水电出版社,2008.
[22] 蔡宏,何政伟,安艳玲,等.基于RS和GIS的赤水河流域植被覆盖度与各地形因子的相关强度研究[J].地球与环境,2014,42(4):518-524.
[23] 汤巧英,戚德辉,宋立旺,等.基于GIS和RS的延河流域植被覆盖度与地形因子的相关性研究[J].水土保持研究,2017,24(4):198-203.
[24] 额日敦同拉嘎.基于DEM的内蒙古大青山林地景观格局分析[D].呼和浩特:内蒙古师范大学,2013.
[25] 位宏,徐丽萍,李晓蕾,等.玛纳斯河流域植被覆盖度随地形因子的变化特征[J].中国农业气象,2018,39(12):814-824
[26] 朱林富,谢世友,华杨,等.基于MODIS EVI的重庆植被覆盖变化的地形效应[J].自然资源学报,2017,32(12):2023-2033.
[27] 刘尧文,沙晋明.基于Landsat影像的多时相植被覆盖度与地形因子关系研究:以平潭岛为例[J].福建师范大学学报(自然科学版),2016,32(4):89-98.