中国植被覆盖度时空演变及其对气候变化和城市化的响应
收稿日期: 2022-07-25
修回日期: 2022-09-20
网络出版日期: 2023-06-05
基金资助
深圳市科技计划资助项目(KQTD20180410161218820);广东省基础与应用基础研究基金(2021A1515012600);自然资源部城市国土资源监测与仿真重点实验室开放基金资助课题(KF-2021-06-104)
Spatiotemporal variations of fractional vegetation cover and its response to climate change and urbanization in China
Received date: 2022-07-25
Revised date: 2022-09-20
Online published: 2023-06-05
植被覆盖变化不仅与气候因子密切相关,而且也受人类活动的影响。目前,从省级尺度研究中国植被时空变化特征以及定量分析气候因子结合人类活动对植被覆盖影响研究仍较少。基于Google Earth Engine(GEE)平台和2000—2020年Landsat数据及同期气候与夜间灯光数据,采用像元二分法、线性回归分析、变异系数、偏相关分析和贡献度模型等方法对中国植被覆盖度时空演变及其对气候变化和城市化的响应进行了分析。结果表明:(1) 2000—2020年中国植被覆盖度以0.32%·a-1的速率增长。植被覆盖区域以高覆盖度为主,面积占研究区域的38%,总体呈现从东南至西北递减的趋势。(2) 黄土高原、云南省、西藏自治区和新疆维吾尔自治区西部植被覆盖度呈现增长趋势。植被年际波动在南部比北部、东部比西部稳定。黑龙江省植被覆盖度最高,为91.7%;新疆维吾尔自治区最低,为14.4%;宁夏回族自治区植被覆盖度以0.98%·a-1的速率增长,植被得到显著改善。(3) 气候因子和城市化对植被覆盖度的影响存在明显空间差异性。气温和降水量对中国北部地区植被覆盖度的影响分别为负相关和正相关,城市化主要影响经济较为发达的省份。气温是宁夏回族自治区的主要贡献因子,平均贡献度为84.3%;降水量是台湾省的主要贡献因子,平均贡献度为71.7%;城市化贡献度最大的城市为上海,平均贡献度为26.5%。
关键词: 植被覆盖度; Google Earth Engine; 气候变化; 城市化; Landsat
陈淑君 , 许国昌 , 吕志平 , 马铭悦 , 李晗羽 , 朱玉岩 . 中国植被覆盖度时空演变及其对气候变化和城市化的响应[J]. 干旱区地理, 2023 , 46(5) : 742 -752 . DOI: 10.12118/j.issn.1000-6060.2022.375
The variation in fractional vegetation cover (FVC) is not only closely related to climatic factors but is influenced by human activities. Only a few studies have been conducted on the spatiotemporal characteristics of FVC in China at the provincial scale and quantitative analysis of the impact of climate factors combined with human activities on FVC. Based on the Google Earth Engine platform and Landsat data for 2000—2020, as well as contemporaneous climate and nighttime lighting data, the study is analyzed using the dimidiate pixel method, linear regression analysis, coefficient of variation, partial correlation analysis, and contribution model. The results showed the following: (1) The rate of increasing of FVC in China is 0.32%·a-1 from 2000 to 2020. The vegetation cover area is dominated by the high cover level, accounting for 38% of the study area, with an overall decreasing trend from southeast to northwest. (2) FVC of the Loess Plateau, Yunnan Province, Tibet Autonomous Region, and western Xinjiang Uygur Autonomous Region showed an increasing trend. Interannual fluctuations in the FVC are more stable in the south than in the north and in the east than in the west. Heilongjiang Province has the highest vegetation cover at 91.7%, while Xinjiang Uygur Autonomous Region has the lowest at 14.4. The rate of variation of FVC in the Ningxia Hui Autonomous Region is 0.98%·a-1, with significant improvement in FVC. (3) A significant spatial variability was observed in the effects of climatic factors and urbanization on FVC. Temperature and precipitation have negative and positive correlations on FVC in northern China, respectively, and urbanization mainly affects the more economically developed provinces. Temperature is the main contribution factor in the Ningxia Hui Autonomous Region, with an average contribution of 84.3%. Precipitation is the main contribution factor in Taiwan Province, with an average contribution of 71.7%. Moreover, urbanization is the main contribution factor in Shanghai, with an average contribution of 26.5%.
[1] | 郭永强. 黄土高原植被覆盖变化归因分析及其对水储量的影响[D]. 咸阳: 西北农林科技大学, 2020. |
[1] | [Guo Yongqiang. Attribution analysis of vegetation coverage change and its impact on water storage on the Loess Plateau[D]. Xianyang: Northwest A & F University, 2020. ] |
[2] | 王晓江, 胡尔查, 李爱平, 等. 基于MODIS NDVI的内蒙古大青山自然保护区植被覆盖度的动态变化特征[J]. 干旱区资源与环境, 2014, 28(8): 61-65. |
[2] | [Wang Xiaojiang, Hu Ercha, Li Aiping, et al. Dynamic changes of vegetation coverage in Daqingshan Nature Reserve based on MODIS NDVI image[J]. Journal of Arid Land Resources and Environment, 2014, 28(8): 61-65. ] |
[3] | 刘垚燚, 曾鹏, 张然, 等. 基于GEE和BRT的1984—2019年长三角生态绿色一体化发展示范区植被覆盖度变化[J]. 应用生态学报, 2021, 32(3): 1033-1044. |
[3] | [Liu Yaoyi, Zeng Peng, Zhang Ran, et al. 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. ] |
[4] | 龙爽, 郭正飞, 徐粒, 等. 基于Google Earth Engine的中国植被覆盖度时空变化特征分析[J]. 遥感技术与应用, 2020, 35(2): 326-334. |
[4] | [Long Shuang, Guo Zhengfei, Xu Li, et al. Spatiotemporal variations of fractional vegetation coverage in China based on Google Earth Engine[J]. Remote Sensing Technology and Application, 2020, 35(2): 326-334. ] |
[5] | Liu H, Li X J, Mao F J, et al. Spatiotemporal evolution of fractional vegetation cover and its response to climate change based on MODIS data in the subtropical region of China[J]. Remote Sensing, 2021, 13(5): 913, doi: 10.3390/rs13050913. |
[6] | 张学玲, 张莹, 牛德奎, 等. 基于TM NDVI的武功山山地草甸植被覆盖度时空变化研究[J]. 生态学报, 2018, 38(7): 2414-2424. |
[6] | [Zhang Xueling, Zhang Ying, Niu Dekui, et al. Spatial-temporal dynamics of upland meadow coverage on Wugong Mountain based on TM NDVI[J]. Acta Ecologica Sinica, 2018, 38(7): 2414-2424. ] |
[7] | 李跃彬, 胡文英. 基于Google Earth Engine平台的昆明市近30年植被覆盖变化研究[J]. 云南师范大学学报(自然科学版), 2020, 40(6): 71-75. |
[7] | [Li Yuebin, Hu Wenying. The study of vegetation cover change in Kunming under the Google Earth Engine platform for nearly 30 years[J]. Journal of Yunnan Normal University (Natural Sciences Edition), 2020, 40(6): 71-75. ] |
[8] | 王瑾. 内蒙古自治区植被覆盖度变化的驱动因素与气候因子响应[D]. 徐州: 中国矿业大学, 2020. |
[8] | [Wang Jin. Driving analysis and climate response of vegetation cover change in Inner Mongolia[D]. Xuzhou: China University of Mining and Technology, 2020. ] |
[9] | Piao S L, Yin G D, Tan J G, et al. Detection and attribution of vegetation greening trend in China over the last 30 years[J]. Global Change Biology, 2015, 21(4): 1601-1609. |
[10] | Piao S L, Mohammat A, Fang J Y, et al. NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China[J]. Global Environmental Change, 2006, 16(4): 340-348. |
[11] | 赵明伟, 王妮, 施慧慧, 等. 2001—2015年间我国陆地植被覆盖度时空变化及驱动力分析[J]. 干旱区地理, 2019, 42(2): 324-331. |
[11] | [Zhao Mingwei, Wang Ni, Shi Huihui, et al. Spatial-temporal variation and its driving forces of vegetation coverage in China from 2001 to 2015[J]. Arid Land Geography, 2019, 42(2): 324-331. ] |
[12] | Xia N, Li M C, Cheng L. Mapping impacts of human activities from nighttime light on vegetation cover changes in Southeast Asia[J]. Land, 2021, 10(2): 185, doi: 10.3309/land10020185 |
[13] | Cai Y F, Zhang F, Duan P, et al. Vegetation cover changes in China induced by ecological restoration-protection projects and land-use changes from 2000 to 2020[J]. Catena, 2022, 217: 106530, doi: 10.1016/j.catena.2022.106530. |
[14] | Song D X, Wang Z H, He T, et al. Estimation and validation of 30 m fractional vegetation cover over China through integrated use of Landsat 8 and Gaofen 2 data[J]. Science of Remote Sensing, 2022, 6: 100058, doi: 10.1016/J.SRS.2022.100058. |
[15] | Chen Z Q, Yu B L, Yang C S, et al. An extended time series (2000—2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration[J]. Earth System Science Data, 2021, 13(3): 889-906. |
[16] | 陈伟, 王哲, 赵海盟, 等. 利用线性融合方法进行金花茶自然保护区植被覆盖度时空变化研究[J]. 测绘通报, 2021, 67(11): 1-6. |
[16] | [Chen Wei, Wang Zhe, Zhao Haimeng, et al. Research on temporal and spatial variation of fractional vegetation cover in Golden Camellia National Nature Reserve using linear fusion method[J]. Bulletin of Surveying and Mapping, 2021, 67(11): 1-6. ] |
[17] | 吴昌广, 周志翔, 肖文发, 等. 基于MODIS NDVI的三峡库区植被覆盖度动态监测[J]. 林业科学, 2012, 48(1): 22-28. |
[17] | [Wu Changguang, Zhou Zhixiang, Xiao Wenfa, et al. Dynamic monitoring of vegetation coverage in Three Gorges Reservoir area based on MODIS NDVI[J]. Scientia Silvae Sinicae, 2012, 48(1): 22-28. ] |
[18] | 晋成名, 杨兴旺, 景海涛. 基于RS的陕北地区植被覆盖度变化及驱动力研究[J]. 自然资源遥感, 2021, 33(4): 258-264. |
[18] | [Jin Chengming, Yang Xingwang, Jing Haitao. A RS-based study on changes in fractional vegetation cover in north Shaanxi and their driving factors[J]. Remote Sensing for Natural Resources, 2021, 33(4): 258-264. ] |
[19] | 穆少杰, 李建龙, 陈奕兆, 等. 2001—2010年内蒙古植被覆盖度时空变化特征[J]. 地理学报, 2012, 67(9): 1255-1268. |
[19] | [Mu ShaoJie, Li Jianlong, Chen Yizhao, et al. Spatial differences of variations of vegetation coverage in Inner Mongolia during 2001—2010[J]. Acta Geographica Sinica, 2012, 67(9): 1255-1268. ] |
[20] | 李杰, 张军, 刘陈立, 等. 基于MODIS-NDVI的中老缅交界区近16年植被覆盖时空变化特征[J]. 林业科学, 2019, 55(8): 9-18. |
[20] | [Li Jie, Zhang Jun, Liu Chenli, et al. Spatiotemporal variation of vegetation coverage in recent 16 years in the border region of China, Laos, and Myanmar based on MODIS-NDVI[J]. Scientia Silvae Sinicae, 2019, 55(8): 9-18. ] |
[21] | 阿多, 赵文吉, 宫兆宁, 等. 1981—2013华北平原气候时空变化及其对植被覆盖度的影响[J]. 生态学报, 2017, 37(2): 576-592. |
[21] | [A Duo, Zhao Wenji, Gong Zhaoning, et al. Temporal analysis of climate change and its relationship with vegetation cover on the North China Plain from 1981 to 2013[J]. Acta Ecologica Sinica, 2017, 37(2): 576-592. ] |
[22] | Zhou Q, Zhao X, Wu D H, et al. Impact of urbanization and climate on vegetation coverage in the Beijing-Tianjin-Hebei Region of China[J]. Remote Sensing, 2019, 11(20): 2452, doi: 10.3390/rs11202452. |
[23] | Tang R Y, Zhao X, Zhou T, et al. Assessing the impacts of urbanization on albedo in Jing-Jin-Ji Region of China[J]. Remote Sensing, 2018, 10(7): 1096-1096. |
[24] | 赫英明, 刘向培, 王汉杰. 基于EVI的中国最近10 a植被覆盖变化特征分析[J]. 气象科学, 2017, 37(1): 51-59. |
[24] | [He Yingming, Liu Xiangpei, Wang Hanjie. Variation characteristics of vegetation cover in the latest 10 years over China based on EVI[J]. Scientia Meteorologica Sinica, 2017, 37(1): 51-59. ] |
[25] | 林隆超, 王晓飞, 刘延平, 等. 退耕还林工程背景下延安植被覆盖时空变化及其对气候的响应[J]. 陕西气象, 2022(4): 1-6. |
[25] | [Lin Longchao, Wang Xiaofei, Liu Yanping, et al. Tempo-spatial variation of vegetation cover and its response to climate in Yan’an region under the background of returning farmland to forest project[J]. Journal of Shaanxi Meteorology, 2022(4): 1-6. ] |
[26] | 陈春波, 李刚勇, 彭建. 近20 a新疆天然草地NPP时空分析[J]. 干旱区地理, 2022, 45(2): 522-534. |
[26] | [Chen Chunbo, Li Gangyong, Peng Jian. Spatiotemporal analysis of net primary productivity for natural grassland in Xinjiang in the past 20 years[J]. Arid Land Geography, 2022, 45(2): 522-534. ] |
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