京津风沙源区不同分区植被覆盖度变化及归因分析

doi:10.13287/j.1001-9332.202108.018

应用生态学报 ›› 2021, Vol. 32 ›› Issue (8): 2895-2905.doi: 10.13287/j.1001-9332.202108.018

京津风沙源区不同分区植被覆盖度变化及归因分析

孟琪¹, 武志涛^1*, 杜自强¹, 张红²

¹山西大学黄土高原研究所, 太原 030006;
²山西大学环境与资源学院, 太原 030006

收稿日期:2021-02-17 接受日期:2021-05-21 出版日期:2021-08-15 发布日期:2022-02-15
通讯作者: *E-mail: wuzhitao@sxu.edu.cn
作者简介:孟琪, 女, 1994年生, 硕士研究生。主要从事植被变化与生态遥感研究。E-mail: mengqi4028@163.com
基金资助:
国家自然科学基金项目(41977412,U1810101,41871193)和山西省高等学校科技创新项目(2020L0014)资助

Variation in fractional vegetation cover and its attribution analysis of different regions of Beijing-Tianjin Sand Source Region, China

MENG Qi¹, WU Zhi-tao^1*, DU Zi-qiang¹, ZHANG Hong²

¹Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China;
²College of Environment and Resource Science, Shanxi University, Taiyuan 030006, China

Received:2021-02-17 Accepted:2021-05-21 Online:2021-08-15 Published:2022-02-15
Contact: *E-mail: wuzhitao@sxu.edu.cn
Supported by:
National Natural Science Foundation of China (41977412, U1810101, 41871193) and the Scientific and Technological Innovation Project of Higher Education Institutions in Shanxi Province (2020L0014).

摘要/Abstract

摘要： 以2000—2018年MODIS NDVI影像为数据源,基于像元二分模型估算京津风沙源区植被覆盖度(FVC),分析京津风沙源区FVC的时空变化特征,并结合自然因素和人类活动,运用地理探测器模型探究自然、人类活动对区域尺度FVC空间分布的影响。结果表明:2000—2018年,京津风沙源区FVC呈增加趋势,增长速率为0.013·(10 a)^-1,植被增加率为8.2%,FVC较高的区域在燕山丘陵山地水源保护区,其次是农牧交错带沙化土地治理区和浑善达克沙地治理区,FVC较低的区域为北部干旱草原沙地治理区。不同分区各驱动因子对FVC空间分布的解释力不同。自然因素中,年降水量是控制北部干旱草原治理区、浑善达克沙地治理区和燕山丘陵山地水源保护区FVC空间分布的主要驱动因子,坡度是控制农牧交错带沙化土地治理区的主要驱动因子;人类活动中,年末大牲畜头数是控制北部干旱草原治理区和农牧交错带沙化土地治理区FVC空间分布的主要驱动因子,人口密度是控制浑善达克沙地治理区和燕山丘陵山地水源保护区FVC空间分布的主要驱动因子;其他因子对FVC空间分布的影响则存在区域差异。交互探测器结果显示,双因子交互作用以双协同作用和非线性协同作用为主。人类活动与年降水量、坡度等自然因素的共同作用能够更充分地解释FVC空间分布。风险探测器识别的适宜植被生长的范围为年降水量316.4～486.0 mm、平均相对湿度48.4%～57.6%、年均温2.5～7.9 ℃的区域,其他驱动因子则在不同分区之间存在差异。

关键词: 植被覆盖度, 自然因素, 人类活动, 地理探测器, 京津风沙源工程区

Abstract: Based on the MODIS NDVI data from 2000 to 2018, we estimated the fractional vegetation cover (FVC) using the dimidiate pixel model and analyzed the spatiotemporal characteristics of FVC in the Beijing-Tianjin sand source region (BTSSR). The geographical detector model was used to estimate the impacts of natural and human factors on FVC spatial distribution at the regional scale. The results showed that the FVC of the BBTSR showed an increasing trend from 2000 to 2018, with an annual growth rate of 0.013·(10 a)^-1 and a vegetation increase rate of 8.2%. The area with high FVC was concentrated in the Yanshan Mountain water source protection area, followed by the pastoral transitional zone desertified land control area and the Otindag sandy land area. The area with poor FVC was concentrated in the northern arid grassland area. The explanatory power of driving factors to FVC varied across different regions. Among the natural factors, annual precipitation was the main driving factor for the spatial distribution of FVC in the northern arid grassland area, the Otindag sandy land area and the Yanshan Mountain water source protection area. Slope was the main driving factor for the spatial distribution of FVC in the pastoral transitional zone desertified land control area. Among different human activities, the number of large livestock at the year-end was the main driving factor controlling the spatial distribution of FVC in the northern arid grassland area and the pastoral transitional zone desertified land control area, while population density was the main driving factor controlling the spatial distribution of FVC in the Otindag sandy land area and the Yanshan Mountain water source protection area. There were regional differences in the influen-ce of other factors on FVC spatial distribution. The results of the interaction detector showed that the two-factor interactions were mainly the double-synergy and nonlinear synergy. The interaction of human activities with annual precipitation and slope could more fully explain the spatial variations of FVC. The range of suitable vegetation growth identified by the risk detector was the area with annual precipitation of 316.4-486.0 mm, average relative humidity of 48.4%-57.6%, and average annual temperature of 2.5-7.9 ℃, while other driving factors were different in different zones.

Key words: fractional vegetation cover, natural factor, human activity, geographical detector model, Beijing-Tianjin sand source region

孟琪, 武志涛, 杜自强, 张红. 京津风沙源区不同分区植被覆盖度变化及归因分析[J]. 应用生态学报, 2021, 32(8): 2895-2905.

MENG Qi, WU Zhi-tao, DU Zi-qiang, ZHANG Hong. Variation in fractional vegetation cover and its attribution analysis of different regions of Beijing-Tianjin Sand Source Region, China[J]. Chinese Journal of Applied Ecology, 2021, 32(8): 2895-2905.

参考文献

[1] 陈效逑, 王恒. 1982—2003年内蒙古植被带和植被覆盖度的时空变化. 地理学报, 2009, 64(1): 84-94 [Chen X-Q, Wang H. Spatial and temporal variations of vegetation belts and vegetation cover degrees in Inner Mongolia from 1982 to 2003. Acta Geographica Sinica, 2009, 64(1): 84-94]
[2] Wang, Q, Zhang QP, Zhou W. Grassland coverage changes and analysis of the driving forces in Maqu County. Physics Procedia, 2012, 33: 1292-1297
[3] 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]
[4] 游珍, 李占斌, 袁琼, 等. 干旱区植被覆盖度的建设阈值分析. 水土保持研究, 2005, 12(3): 88-90 [You Z, Li Z-B, Yuan Q, et al. Study on the threshold of vegetation coverage in arid area. Research of Soil and Water Conservation, 2005, 12(3): 88-90]
[5] 郭瑞霞, 尚夏明, 李煜. 基于MODIS_NDVI的甘肃省会宁县植被覆盖度变化监测. 甘肃科技, 2019, 35(1): 42-45 [Guo R-X, Shang X-M, Li Y. Vegetation coverage change monitoring based on MODIS_NDVI in Huining County, Gansu. Gansu Science and Technology, 2019, 35(1): 42-45]
[6] 王金强, 李俊峰, 王昭阳, 等. 基于像元二分模型的典型绿洲区近20年植被覆盖变化及分析. 节水灌溉, 2019(1): 96-101 [Wang J-Q, Li J-F, Wang Z-Y, et al. Analysis of vegetation coverage change in typical oasis area in recent 20 years based on dimidiate pixel model. Water Saving Irrigation, 2019(1): 96-101]
[7] 韩富圆, 王天明, 孙阳. 基于Landsat遥感数据武汉地区植被覆盖度动态变化监测分析. 测绘与空间地理信息, 2019, 42(4): 90-92 [Han F-Y, Wang T-M, Sun Y. Monitoring and analyzing dynamic change of vegetation coverage in Wuhan Area based on Landsat remote sensing data. Geomatics and Spatial Information Technology, 2019, 42(4): 90-92]
[8] 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 Ri-ver. Arid Zone Research, 2019, 36(3): 546-555]
[9] 李美丽, 尹礼昌, 张园, 等. 基于MODIS-EVI的西南地区植被覆盖时空变化及驱动因素研究. 生态学报, 2021, 41(3): 1138-1147 [Li M-L, Yin L-C, Zhang Y, et al. Spatio-temporal dynamics of fractional vegetation coverage based on MODIS-EVI and its driving factors in Southwest China. Acta Ecological Sinica, 2021, 41(3): 1138-1147]
[10] 金凯, 王飞, 韩剑桥, 等. 1982—2015年中国气候变化和人类活动对植被NDVI变化的影响. 地理学报, 2020, 75(5): 961-974 [Jin K, Wang F, Han J-Q, et al. Contribution of climatic change and human activities to vegetation NDVI change over China during 1982-2015. Acta Geographica Sinica, 2020, 75(5): 961-974]
[11] 王正雄, 蒋勇军, 张远嘱, 等. 基于GIS与地理探测器的岩溶槽谷石漠化空间分布与驱动因素分析. 地理学报, 2019, 74(5): 1025-1039 [Wang Z-X, Jiang Y-J, Zhang Y-Z, et al. Spatial distribution and driving factors of karst rocky desertification based on GIS and geodetectors. Acta Geographica Sinica, 2019, 74(5): 1025-1039]
[12] 顾松圃. 京津风沙源区生态环境治理存在的问题与对策. 山西水土保持科技, 2008(1): 36-38 [Gu S-P. Problems and countermeasures of ecological environment control in Beijing-Tianjin Sand Source Region. Soil and Water Conservation Science and Technology in Shanxi, 2008(1): 36-38]
[13] 武志涛. 京津风沙源区植被变化及固碳效益研究. 博士论文. 北京: 北京师范大学, 2013 [Wu Z-T. Vegetation Dynamics and Benefits of Carbon Sequestration in the Beijing-Tianjin Sand Source Region. PhD Thesis. Beijing: Beijing Normal University, 2013]
[14] 单楠. 京津风沙源区植被指数(NDVI)对气候变化响应研究. 硕士论文. 北京: 中国林业科学研究院, 2013 [Shan N. The Reasearch on Normalized Different Vegetation Index (NDVI) Response to the Climate Changes in Beijing-Tianjin Sand Source Region. Master Thesis. Beijing: Chinese Academy of Forestry, 2013]
[15] 马志婷. 1960—2014年中国干旱时空变化及其对植被的影响. 硕士论文. 太原: 山西大学, 2018 [Ma Z-T. Spatial and Temporal Variation of Drought and Its Impact on Vegetation in China during 1960-2014. Master Thesis. Taiyuan: Shanxi University, 2018]
[16] 吴思佳, 吴伟, 陈文惠, 等. 基于地理探测器的闽三角城市群植被覆盖时空变化及影响因素研究. 福建师范大学学报:自然科学版, 2019, 35(5): 81-88 [Wu S-J, Wu W, Chen W-H, et al. Study on temporal and spatial changes of vegetation coverage and its influen-cing factors in the Urban Agglomeration of Min Delta based on the Geographical Detector Method. Journal of Fujian Normal University: Natural Science, 2019, 35(5): 81-88]
[17] 张彪, 李庆旭, 王爽, 等. 京津风沙源区防风固沙功能的时空变化及其区域差异. 自然资源学报, 2019, 34(5): 1041-1053 [Zhang B, Li Q-X, Wang S, et al. Spatial-temporal changes and regional differences of the sand fixing service in the Beijing-Tianjin sandstorm source region. Journal of Natural Resources, 2019, 34(5): 1041-1053]
[18] 张金茜, 巩杰, 柳冬青. 地理探测器方法下甘肃白龙江流域景观破碎化与驱动因子分析. 地理科学, 2018, 38(8): 1370-1378 [Zhang J-X, Gong J, Liu D-Q. Dynamics and driving factors of landscape fragmentation based on GeoDetector in the Bailongjiang Watershed of Gansu Province. Scientia Geographica Sinica, 2018, 38(8): 1370-1378]
[19] 王欢, 高江波, 侯文娟. 基于地理探测器的喀斯特不同地貌形态类型区土壤侵蚀定量归因. 地理学报, 2018, 73(9): 1674-1686 [Wang H, Gao J-B, Hou W-J. Quantitative attribution analysis of soil erosion in different morphological types of geomorphology in karst areas based on the geographical detector method. Acta Geographica Sinica, 2018, 73(9): 1674-1686]
[20] 南精转, 任学军. 京津风沙源治理区造林工程存在问题与建议. 山西水土保持科技, 2014(2): 30-31 [Nan J-Z, Ren X-J. Problems and suggestions of affo-restation project in Beijing-Tianjin Sand Source Region. Soil and Water Conservation Science and Technology in Shanxi, 2014(2): 30-31]
[21] 内蒙古自治区统计局. 内蒙古统计年鉴. 北京: 中国统计出版社, 2000 [Inner Mongolia Autonomous Region Statistics Bureau. Inner Mongolia Statistical Yearbook. Beijing: China Statistics Press, 2000]
[22] 山西省统计局. 山西省统计年鉴. 北京: 中国统计出版社, 2000 [Shanxi Statistics Bureau. Shanxi Statistical Yearbook. Beijing: China Statistics Press, 2000]
[23] 河北省统计局. 河北省统计年鉴. 北京: 中国统计出版社, 2000 [Hebei Statistics Bureau. Hebei Statistical Yearbook. Beijing: China Statistics Press, 2000]
[24] 北京统计年鉴. 北京市统计年鉴. 北京: 中国统计出版社, 2000 [Beijing Statistics Bureau. Beijing Statistical Yearbook. Beijing: China Statistics Press, 2000]
[25] 天津统计年鉴. 天津市统计年鉴. 北京: 中国统计出版社, 2000 [Tianjin Statistics Bureau. Tianjin Statistical Yearbook. Beijing: China Statistics Press, 2000]
[26] 国家林业局. 中国林业统计年鉴. 北京: 中国林业出版社, 2002 [National Forestry Administration. China Forestry Statistical Yearbook. Beijing: China Forestry Press, 2002]
[27] 王伟, 阿里木·赛买提, 吉力力·阿不都外力. 基于地理探测器模型的中亚NDVI时空变化特征及其驱动因子分析. 国土资源遥感, 2019, 31(4): 32-40 [Wang W, Samat A, Abuduwaili J. Geo-detector based spatio-temporal variation characteristics and driving factors analysis of NDVI in Central Asia. Remote Sensing for Land and Resources, 2019, 31(4): 32-40]
[28] 刘大元, 张雪梅, 岳跃民, 等. 基于Geodetector的广西喀斯特植被覆盖变化及其影响因素分析. 农业现代化研究, 2019, 40(6): 1038-1047 [Liu D-Y, Zhang X-M, Yue Y-M, et al. Vegetation cover change and its influencing factors in karst regions of Guangxi based on Geodetector. Research of Agricultural Modernization, 2019, 40(6): 1038-1047]
[29] 张勇. 近20年科尔沁沙地植被覆盖变化研究——以科尔沁左翼后旗为例. 硕士论文. 呼和浩特: 内蒙古师范大学, 2008 [Zhang Y. Study on the Vegetation Cover Change in Horqin Sandy Land during the Recent 20 Years. Master Thesis. Hohhot: Inner Mongolia Normal University, 2008]
[30] 王劲峰, 徐成东. 2017地理探测器: 原理与展望. 地理学报, 2017, 71(1): 116-134 [Wang J-F, Xu C-D. Geodetector of spatial stratified heterogeneity: Principle and applications in environmental and social sciences. Acta Geographica Sinica, 2017, 71(1): 116-134]
[31] 李涛, 廖和平, 褚远恒, 等. 重庆市农地非农化空间非均衡及形成机理. 自然资源学报, 2016, 31(11): 1844-1857 [Li T, Liao H-P, Chu Y-H, et al. Spatial disequilibrium and its formation mechanism of farmland conversion in Chongqing. Journal of Natural Resources, 2016, 31(11): 1844-1857]
[32] Zhu LJ, Meng JJ, Zhu LK. Applying Geodetector to disentangle the contributions of natural and anthropogenic factors to NDVI variations in the middle reaches of the Heihe River Basin. Ecological Indicators, 2020, 117: 106545
[33] 杨忍, 刘彦随, 龙花楼, 等. 基于格网的农村居民点用地时空特征及空间指向性的地理要素识别——以环渤海地区为例. 地理研究, 2015, 34(6): 1077-1087 [Yang R, Liu Y-S, Long H-L, et al. Spatial-temporal characteristic of rural residential land use change and spatial directivity identification based on grid in the Bohai Rim in China. Geograohical Research, 2015, 34(6): 1077-1087]
[34] 马俊明. 基于GIS的京津风沙源林业工程监测与评价系统. 硕士论文. 北京: 北京林业大学, 2019 [Ma J-M. The Monitoring and Evaluation System of Beijing-Tianjin Sand Forestry Engineering Based on GIS. Master Thesis. Beijing: Beijing Forestry University, 2019]
[35] 马天啸, 宋现锋, 赵昕, 等. 2000—2010年黄河源区植被覆盖率时空变化及影响因素. 干旱区研究, 2016, 33(6): 1217-1225 [Ma T-X, Song X-F, Zhao X, et al. Spatiotemporal variation of vegetation coverage and its affecting factors in the Headwaters of the Yellow River during the period of 2000-2010. Arid Zone Research, 2016, 33(6): 1217-1225]
[36] 裴亮, 黄森旺, 陈丽萍. 京津风沙源区植被的时空变化及其对气候因子的响应. 中国沙漠, 2013, 33(5): 1593-1597 [Pei L, Huang S-W, Chen L-P. Vegetation spatio-temporal changes and the relationship with climate factors in Beijing-Tianjin Sand Source Region. Journal of Desert Research, 2013, 33(5): 1593-1597]
[37] 严恩萍, 林辉, 党永峰, 等. 2000—2012年京津风沙源治理区植被覆盖时空演变特征. 生态学报, 2014, 34(17): 5007-5020 [Yan E-P, Lin H, Dang Y-F, et al. The spatiotemporal changes of vegetation cover in Beijing-Tianjin sandstorm source control region during 2000-2012. Acta Ecologica Sinica, 2014, 34(17): 5007-5020]
[38] 刘巧霞. 京津风沙源治理工程的管理机制对当地生态效益的推动. 现代园艺, 2020, 43(20): 151-152 [Liu Q-X. The promotion of local ecological benefits by the management mechanism of Beijing-Tianjin sand source control project. Modern Horticulture, 2020, 43(20): 151-152]
[39] 李愈哲, 樊江文, 于海玲. 京津风沙源治理工程不同恢复措施对草地恢复过程的差异性影响. 草业学报, 2018, 27(5): 1-14 [Li Y-Z, Fan J-W, Yu H-L. The effects of different restoration practices on temperate grassland ecosystems in the Beijing-Tianjin Sand Source Control Project. Acta Prataculturae Sinica, 2018, 27(5): 1-14]
[40] 王俊秀. 京津风沙源治理工程经济效益分析. 内蒙古水利, 2017(1): 34 [Wang J-X. Economic benefit analysis of Beijing-Tianjin Sand Source Control Project. Inner Mongolia Water Resources, 2017(1): 34]
[41] 刘笑冰, 李宇佳, 刘芳. 基于生态文明视角的造林工程成本核算研究——以北京市京津风沙源治理二期工程为例. 林业经济, 2019, 41(3): 119-124 [Liu X-B, Li Y-J, Liu F. Study on cost accounting of affo-restation project from the ecological civilization: Taking Beijing-Tianjin Sandstorm Source Treatment Phase Ⅱ Project as an example. Forestry Economics, 2019, 41(3): 119-124]

京津风沙源区不同分区植被覆盖度变化及归因分析

Variation in fractional vegetation cover and its attribution analysis of different regions of Beijing-Tianjin Sand Source Region, China

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[10]	刘强, 吴志伟, 林世滔, 李顺, 方志斌. 松材线虫病发生点格局及影响因素 [J]. 应用生态学报, 2022, 33(9): 2530-2538.
[11]	贺鹏, 毕如田, 徐立帅, 王婧姝, 曹晨斌. 基于地理探测的黄土高原植被生长对气候的响应 [J]. 应用生态学报, 2022, 33(2): 448-456.
[12]	刘辉, 宋孝玉, 贾琼, 祝德名. 近20年内蒙古鄂托克旗草地降水利用效率时空演变的驱动力量化 [J]. 应用生态学报, 2022, 33(12): 3253-3262.
[13]	林妍敏, 李文慧, 南雄雄, 张俊华, 胡志瑞, 倪细炉, 王芳. 基于地理探测器的宁夏贺兰山植被覆盖度时空分异及驱动因子 [J]. 应用生态学报, 2022, 33(12): 3321-3327.
[14]	叶璇, 康帅直, 赵永华, 韩磊, 项曦明, 李帆. 陕北黄土高原植被恢复与生态系统服务的时空关系 [J]. 应用生态学报, 2022, 33(10): 2760-2768.
[15]	洪乐乐, 沈艳, 马红彬, 张鹏, 霍新茹, 温华晨. 2000—2019年宁夏植被净初级生产力时空变化及其驱动因素 [J]. 应用生态学报, 2022, 33(10): 2769-2776.