Vegetation coverage change of the demonstration area of ecologically friendly development in the Yangtze River Delta, China based on GEE and BRT during 1984-2019

doi:10.13287/j.1001-9332.202103.011

Abstract

Abstract: The demonstration area of ecologically friendly development in the Yangtze River Delta is a major national strategy area, and thus eco-environmental protection should be a priority for the sustainable development. Exploring the spatial-temporal variations of franctional vegetation coverage (FVC) is conducive to accurate assessing the ecological quality of environment, which is of great significance to regional sustainable development. In this study, the characteristics and trends of spatial-temporal variation of vegetation cover during 1984-2019 in the demonstration area were analyzed based on Google Earth Engine (GEE). The effects of different ecological factors on FVC were quantified by the boosted regression tree (BRT). Results showed that,the changing trend of FVC in the study area shifted from decreasing to increasing trend from 1984 to 2019. The spatial distribution of FVC in the study area varied with both stages and regions. FVC was mainly degraded. Compared with the year 1984, the area of vegetation degradation and improvement in 2019 accounted for 49.8% and 12.8%, respectively. The vegetation degradation mainly occurred in the north of Wujiang, south of Jiashan, and northeast of Qingpu. Human activities severely weakened the influence of natural factors on FVC. Our findings suggested that the GEE is an effective tool for monitoring the dynamics of vegetation coverage.

Key words: integrated demonstration area, fractional vegetation coverage, Google Earth Engine, boosted regression tree

LIU Yao-yi, ZENG Peng, ZHANG Ran, SUN Feng-yun, CHE Yue. Vegetation coverage change of the demonstration area of ecologically friendly development in the Yangtze River Delta, China based on GEE and BRT during 1984-2019[J]. Chinese Journal of Applied Ecology, 2021, 32(3): 1033-1044.

References 38

[1]	Zhang YH, Ye AZ. Spatial and temporal variations in vegetation coverage observed using AVHRR GIMMS and Terra MODIS data in the mainland of China. International Journal of Remote Sensing, 2020, 41: 4238-4268
[2]	Jiang WG, Yuan LH, Wang WJ, et al. Spatio-temporal analysis of vegetation variation in the Yellow River Basin. Ecological Indicators, 2015, 51: 117-126
[3]	Piao SL, Yin GD, Tan JG, et al. Detection and attribution of vegetation greening trend in China over the last 30 years. Global Change Biology, 2015, 21: 1601-1609
[4]	陶帅, 邝婷婷, 彭文甫, 等. 2000—2015年长江上游NDVI时空变化及驱动力——以宜宾市为例. 生态学报, 2020, 40(14): 5029-5043 [Tao S, Kuang T-T, Peng W-P, et al. Analyzing the spatio-temporal variation and drivers of NDVI in upper reaches of the Yangtze River from 2000 to 2015: A case study of Yibin City. Acta Ecologica Sinica, 2020, 40(14): 5029-5043]
[5]	Compton JT, John RG, Thomas EG. African land-cover classification using satellite data. Science, 1985, 227: 369-375
[6]	郭铌. 植被指数及其研究进展. 干旱气象, 2003, 21(4): 71-75 [Guo N. Vegetation index and its advances. Journal of Arid Meteorology, 2003, 21(4): 71-75]
[7]	裴志林, 杨勤科, 王春梅, 等. 黄河上游植被覆盖度空间分布特征及其影响因素. 干旱区研究, 2019, 36(3): 546-555 [Pei Z-L, Yang Q-K, Wang C-M, et al. Spatial distribution of vegetation coverage and its affecting factors in the upper reaches of the Yellow River. Arid Zone Research, 2019, 36(3): 546-555]
[8]	宋富强, 邢开雄, 刘阳, 等. 基于MODIS/NDVI的陕北地区植被动态监测与评价. 生态学报, 2011, 31(2): 354-363 [Song F-Q, Xing K-X, Liu Y, et al. Monitoring and assessment of vegetation variation in Northern Shaanxi based on MODIS/NDVI. Acta Ecologica Sinica, 2011, 31(2): 354-363]
[9]	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. 资源科学, 2004, 26(4): 153-159 [Li M-M, Wu B-F, Yan C-Z, et al. Estimation of vege-tation fraction in the upper basin of Miyun Reservoir by remote sensing. Resources Science, 2004, 26(4): 153-159]
[10]	齐亚霄, 张飞, 陈瑞, 等. 2001—2015年天山北坡植被覆盖动态变化研究. 生态学报, 2020, 40(11): 3677-3687 [Qi Y-X, Zhang F, Chen R, et al. Vegetation coverage dynamics in northern slope of Tianshan Mountains from 2001 to 2015. Acta Ecologica Sinica, 2020, 40(11): 3677-3687]
[11]	董弟文, 阿布都热合曼·哈力克, 王大伟, 等. 1994—2016年和田绿洲植被覆盖时空变化分析. 生态学报, 2019, 39(10): 3710-3719 [Dong D-W, Abdirahman·Halik, Wang D-W. Spatio-temporal varia-tions in vegetation cover in Hotan Oasis from 1994 to 2016. Acta Ecologica Sinica, 2019, 39(10): 3710-3719]
[12]	国务院. 国务院关于长三角生态绿色一体化发展示范区总体方案的批复 [EB/OL]. (2019-12-12) [2019-12-12]. http://www.gov.cn/zhengce/content/2019-10/29/content_5446300.htm [State Council. Reply of the State Council on the Overall Plan of the Demon-stration Area in the Yangtze River Delta on Ecologically Friendly Development. [EB/OL]. (2019-12-12) [2019-12-12]. http://www.gov.cn/zhengce/content/2019-10/29/content_5446300.htm]
[13]	刘新宇, 胡静, 沈爱萍. 长三角生态绿色一体化发展示范区生态环境管理机制研究. 中国发展, 2019, 19(6): 1-5 [Liu X-Y, Hu J, Shen A-P. Research on the ecological management mechanism of the Yangtze River Delta Eco-green Integration Development Demonstration Plot. China Development, 2019, 19(6): 1-5]
[14]	上海市青浦区统计局. 1990—2019年青浦区统计年鉴 [EB/OL]. (2020-08-06) [2020-08-15]. https://www.shqp. gov.cn/ stat/tjzltjnj/ [Shanghai Qingpu District Statistics Bureau. 1990-2019 Qingpu District Statistical Yearbook [EB/OL]. (2020-08-06) [2020-08-15]. https://www.shqp.gov.cn/stat/tjzltjnj/]
[15]	苏州市统计局. 1989—2019苏州统计年鉴 [EB/OL]. (2019-12-04) [2020-08-15]. http://tjj.suzhou.gov.cn/sztjj/tjnj/nav_list.shtml [Suzhou Statistics Bureau. Suzhou Statistical Yearbook in 1989-2019 [EB/OL]. (2019-12-04) [2020-08-15]. http://tjj.suzhou.gov.cn/sztjj/tjnj/nav_list.shtml]
[16]	吴江档案局. 吴江年鉴1988—1986年 [EB/OL]. (2015-03-12) [2020-08-15]. http://www.wujiangtong.com/fzg/webPage/FZG BookCategory.aspx?categoryid=9[Wujiang Archives Bureau. Wujiang Yearbook in 1988-1986 [EB/OL]. (2015-03-12) [2020-08- 15]. http://www.wujiangtong.com/fzg/webPage/FZG_BookCategory.aspx?categoryid=9]
[17]	嘉兴市统计局. 1997—2019嘉兴统计年鉴 [EB/OL]. (2019-12-31) [2020-08-15]. http://tjj.jiaxing.gov.cn/col/ col1512382/index.html [Jiaxing Statistics Bureau. Jiaxing Statistical Yearbook in 1997-2019 [EB/OL]. (2019-12-31) [2020-08-15]. http://tjj.jiaxing.gov.cn/col/col1512382/index.html]
[18]	嘉善县人民政府. 嘉善年鉴1993—2018 [EB/OL]. (2020-07-30) [2020-08-15]. http://www.jiashan.gov.cn/col/ col1600394/index.html [Jiashan County People’s Government. Jiashan Yearbook in 1993-2018 [EB/OL]. (2020-07-30) [2020-08-15]. http://www.jiashan.gov.cn/col/col1600394/index.html]
[19]	Toby NC, David AR. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 1997, 62: 241-252
[20]	Fensholt R, Sandholt I. Evaluation of MODIS and NOAA AVHRR vegetation indices with in situ measurements in a semi-arid environment. International Journal of Remote Sensing, 2005, 26: 2561-2594
[21]	Jiapaer G, Chen X, Bao A. A comparison of methods for estimating fractional vegetation cover in arid regions. Agricultural and Forest Meteorology, 2011, 151: 1698-1710
[22]	Pei J, Niu Z, Wang L, et al. Quantifying the spatio-temporal variations and impact factors for vegetation cove-rage in the karst regions of Southwest China using Landsat data and Google Earth Engine. SPIE Asia-Pacific Remote Sensing, 2018, 10780: 107800E
[23]	Zhang XF, Liao CH, Li J, et al. Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data. International Journal of Applied Earth Observation and Geoinformation, 2013, 21: 506-512
[24]	甘春英, 王兮之, 李保生, 等. 连江流域近18年来植被覆盖度变化分析. 地理科学, 2011, 31(8): 1019-1024 [Gan C-Y, Wang X-Z, Li B-S, et al. Changes of vegetation coverage during recent 18 years in Lianjiang River watershed. Scientia Geographica Sinica, 2011, 31(8): 1019-1024]
[25]	刘垚燚, 田恬, 曾鹏, 等. 基于Google Earth Engine平台的1984—2018年太湖水域变化特征. 应用生态学报, 2020, 31(9): 3163-3172 [Liu Y-Y, Tian T, Zeng P, et al. Surface water change characteristics of Taihu Lake from 1984-2018 based on Google Earth Engine. Chinese Journal of Applied Ecology, 2020, 31(9): 3163-3172]
[26]	尹才, 刘淼, 孙凤云, 等. 基于增强回归树的流域非点源污染影响因子分析. 应用生态学报, 2016, 27(3): 911-919 [Yin C, Liu M, Sun F-Y, et al. Influen-cing factors of non-point source pollution of watershed based on boosted regression tree algorithm. Chinese Journal of Applied Ecology, 2016, 27(3): 911-919]
[27]	李春林, 刘淼, 胡远满, 等. 基于增强回归树和Logistic回归的城市扩展驱动力分析. 生态学报, 2014, 34(3): 727-737 [Li C-L, Liu M, Hu Y-M, et al. Driving forces analysis of urban expansion based on boosted regression tree and logistic regression. Acta Ecologica Sinica, 2014, 34(3): 727-737]
[28]	Sun FY, Mejia A, Che Y. Disentangling the contributions of climate and basin characteristics to water yield across spatial and temporal scales in the Yangtze River Basin: A combined hydrological model and boosted regression approach. Water Resources Management, 2019, 33: 3449-3468
[29]	Sun FY, Liu M, Wang YC, et al. The effects of 3D architectural patterns on the urban surface temperature at a neighborhood scale: Relative contributions and marginal effects. Journal of Cleaner Production, 2020, 258: 120706
[30]	Andrew DR, Trevor FK, Mirco M, et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology, 2013, 169: 156-173
[31]	任媛, 刘普幸. 基于EVI和MNDWI指数的石羊河流域水体、植被时空变化特征. 冰川冻土, 2018, 40(4): 853-861 [Ren Y, Liu P-X. Temporal and spatial variations of water and vegetation in Shiyang River basin based on EVI and MNDWI. Journal of Glaciology and Geocryology, 2018, 40(4): 853-861]
[32]	Piao SL, Friedlingstein P, Ciais P, et al. Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophysical Research Letters, 2006, 33: L23402
[33]	吴炳伦, 孙华, 石军南, 等. 2000—2018年深圳市植被覆盖动态变化与预测. 应用生态学报, 2020, 31(11): 4020-4029 [Wu B-L, Sun H, Shi J-N, et al. Dynamic change and prediction of vegetation cover in Shenzhen, China from 2000 to 2018. Chinese Journal of Applied Ecology, 2020, 31(11): 4020-4029]
[34]	邓元杰, 姚顺波, 侯孟阳, 等. 长江流域中上游植被NDVI时空变化及其地形分异效应. 长江流域资源与环境, 2020, 29(1): 66-78 [Deng Y-J, Yiao S-B, Hou M-Y, et al. Temporal and spatial variation of vegetation NDVI and its topographic differentiation effect in the middle and upper reaches of the Yangtze River Basin. Resources and Environment in the Yangtze Basin, 2020, 29(1): 66-78]
[35]	张国平, 刘纪远, 张增祥. 近10年来中国耕地资源的时空变化分析. 地理学报, 2003, 58(3): 323-332 [Zhang G-P, Liu J-Y, Zhang Z-X. Spatial-temporal change of cropland in China for the past 10 years based on remote sensing. Scientia Geographica Sinica, 2003, 58(3): 323-332]
[36]	金妍. 江南水乡河网水系结构变迁及空间分区保护研究. 硕士论文. 上海: 华东师范大学, 2013 [Jin Y. The Study of River Network Structural Changes and Space Partition Protection in South of Yangtze River. Master Thesis. Shanghai: East China Normal University, 2013]
[37]	张滔, 唐宏. 基于Google Earth Engine的京津冀2001—2015年植被覆盖变化与城镇扩张研究. 遥感技术与应用, 2018, 33(4): 593-599 [Zhang T, Tang H. Vegetation cover change and urban expansion in Beijing-Tianjin-Hebei during 2001-2015 based on Google Earth Engine. Remote Sensing Technology and Application, 2018, 33(4): 593-599]
[38]	Marcos A, Sérgio B, Egidio A, et al. Seasonality of vege-tation types of South America depicted by moderate reso-lution imaging spectroradiometer (MODIS) time series. International Journal of Applied Earth Observations and Geoinformation, 2018, 69: 148-163