陕西省植被覆盖时空变异及其恢复潜力

李媛媛; 孙景妍; 杨香云; 齐雁冰

doi:10.13961/j.cnki.stbctb.2024.01.034

您当前的位置：

首页 >

文章列表页 >

陕西省植被覆盖时空变异及其恢复潜力

试验研究

- 陕西省植被覆盖时空变异及其恢复潜力
- Spatio-temporal Variation of Fractional Vegetation Cover and its Recovery Potential in Shaanxi Province
- 水土保持通报 2024年44卷第1期页码：346-356
- 作者机构：
  
  西北农林科技大学资源环境学院, 陕西杨凌,712100
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“黑垆土腐殖质层诊断特性构建与系统分类研究”(42277310);陕西省科技计划项目“陕西省土壤信息服务平台”(2022PT-28)
- DOI：10.13961/j.cnki.stbctb.2024.01.034
  中图分类号： S157.2
- 纸质出版：2024
- 稿件说明：
移动端阅览
李媛媛, 孙景妍, 杨香云, 等. 陕西省植被覆盖时空变异及其恢复潜力[J]. 水土保持通报, 2024,44(1):346-356.

Li Yuanyuan, Sun Jingyan, Yang Xiangyun, et al. Spatio-temporal Variation of Fractional Vegetation Cover and its Recovery Potential in Shaanxi Province[J]. Bulletin of Soiland Water Conservation, 2024, 44(1): 346-356.
李媛媛, 孙景妍, 杨香云, 等. 陕西省植被覆盖时空变异及其恢复潜力[J]. 水土保持通报, 2024,44(1):346-356. DOI： 10.13961/j.cnki.stbctb.2024.01.034.

Li Yuanyuan, Sun Jingyan, Yang Xiangyun, et al. Spatio-temporal Variation of Fractional Vegetation Cover and its Recovery Potential in Shaanxi Province[J]. Bulletin of Soiland Water Conservation, 2024, 44(1): 346-356. DOI： 10.13961/j.cnki.stbctb.2024.01.034.

摘要

[目的] 系统分析退耕还林以来植被覆盖时空变异特征

评估植被恢复的潜力

为陕西省生态环境建设的可持续发展提供科学的理论依据和实施建议。[方法] 以MODIS NDVI数据为基础

采用Sen+Mann-Kendall模型和Hurst指数探究了2000-2020年陕西省及秦巴山区、关中平原和黄土高原3个亚区植被覆盖度(fractional vegetation cover

FVC)的时空变化特征

并运用相似生境法测算了不同区域的植被恢复潜力。[结果] ①2000-2020年陕西省FVC增长率为0.002 9/a

74.58 %的区域有所改善。其中:黄土高原区FVC改善面积达84.46 %

且以显著改善为主;秦巴山区FVC改善面积为74.40 %

以轻微改善为主;而关中平原区FVC具有退化趋势

退化区域占64.56 %。②全省FVC持续性改善面积占19.80 %

黄土高原区和秦巴山区以持续性改善为主

面积比例分别为27.83 %和13.68 %

而关中平原区以持续性退化为主。③黄土高原区西北部及其与关中平原接壤地带的植被恢复空间较大

而子午岭林区植被恢复空间较小;秦巴山区森林覆盖率较高

几乎没有恢复空间;关中平原受城市化的影响

植被恢复空间小。[结论] 近几十年来

陕西省植被覆盖度显著提高

但受气候、地形、植被类型和人类活动等因素的影响

植被覆盖变化具有明显的空间异质性。陕西省植被恢复的增长速度趋于放缓

持续改善能力已经较低

植被覆盖趋于平稳

但是黄土高原西北部地区及其与关中平原的接壤处植被覆盖恢复潜力仍较大。

Abstract

[Objective] The spatio-temporal variation characteristics of vegetation cover since returning farmland to forest were systematically analyzed. The potential of vegetation restoration were evaluated

in order to provide scientific theoretical basis and implementation suggestions for the sustainable development of ecological environment construction in Shaanxi Province.[Methods] The spatial and temporal variations of fractional vegetation cover (FVC) were investigated from 2000 to 2020 based on MODIS NDVI data

the Sen+Mann-Kendall method and Hurst index. Vegetation restoration potential was assessed by using the 'similar habitat method' in Shaanxi Province

as well as in three subregions of the Loess Plateau

Qinling-Bashan Mountain

and the Guanzhong Plain.[Results] ① The average growth rate of FVC in Shaanxi Province was 0.002 9/a from 2000 to 2020

and 74.58 % of the area had increased in FVC. Areas of significant and slight FVC increase were detected in the Loess Plateau and Qinling-Bashan Mountain where 84.46 % and 74.40 % of the areas

respectively

showed increased FVC. Slight FVC degradation trends were detected in the Guanzhong Plain where 64.56 % of the area

showed decreased FVC. ② The areas showing persistent increase in FVC accounted for 19.80 % of the entire Shaanxi Province

and accounted for 27.83 % and 13.68 % in the Loess Plateau and Qinling-Bashan Mountain

respectively. The area showing persistent decreases in FVC were predominantly in the Guanzhong Plain. ③ For the Loess Plateau region

greater vegetation recovery potential areas were detected in the northern area and the transitional area with the Guanzhong Plain

and the vegetation recovery potential was low in the Ziwuling forest area. Low vegetation recovery potentials were found in the Qinling-Bashan Mountain and Guanzhong Plain areas because of the high vegetation coverage background and the high rate of urbanization

respectively.[Conclusion] Shaanxi Province experienced significant FVC increases during 2000-2020 due to it being a key region of ecological project implementation. However

the heterogeneous spatial-temporal variation of FVC was affected by climate

topography

plant species

and human activities. The growth rate of vegetation restoration in Shaanxi Province tended to slow down

the continuous improvement ability has been lower

and the vegetation cover tended to be stable. However

the northwest region of the Loess Plateau and its border with Guanzhong Plain still has a large potential for vegetation cover restoration.

关键词

Keywords

references

邓元杰,姚顺波,侯孟阳,等.退耕还林还草工程对生态系统碳储存服务的影响:以黄土高原丘陵沟壑区子长县为例[J].自然资源学报,2020,35(4):826-844. Deng Yuanjie, Yao Shunbo, Hou Mengyang, et al. Assessing the effects of the Green for Grain Program on ecosystem carbon storage service by linking the InVEST and FLUS models:A case study of Zichang County in hilly and gully region of Loess Plateau[J]. Journal of Natural Resources, 2020,35(4):826-844.

Feng Dingrao, Wang Jinman, Fu Meichen, et al. Spatiotemporal variation and influencing factors of vegetation cover in the ecologically fragile areas of China from 2000 to 2015:a case study in Shaanxi Province[J]. Environmental Science and Pollution Research, 2019,26(28):28977-28992.

Wang Guangyu, Innes J L, Lei Jiafu, et al. China's forestry reforms[J]. Science, 2007,318(5856):1556-1557.

Wang Yunqiang, Shao Ming'an, Liu Zhipeng, et al. Investigation of factors controlling the regional-scale distribution of dried soil layers under forestland on the loess plateau, China[J]. Surveys in Geophysics, 2012,33(2):311-330.

庞国伟,山琳昕,杨勤科,等.陕西省不同地貌类型区植被覆盖度时空变化特征及其影响因素[J].长江科学院院报, 2021,38(3):51-58. Pang Guowei, Shan Linxin, Yang Qinke, et al. Vegetation coverage in different landforms of Shaanxi Province:spatial and temporal variations and influencing factors[J]. Journal of Yangtze River Scientific Research Institute, 2021,38(3):51-58.

Cai Yunfei, Zhang Fei, Duan Pan, 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.

Brandt M, Rasmussen K, Peñuelas J, et al. Human population growth offsets climate-driven increase in woody vegetation in Sub-Saharan Africa[J]. Nature Ecology&Evolution,2017,1(4):0081.

Jiang Meichen, He Yuexin, Song Conghe, et al. Disaggregating climatic and anthropogenic influences on vegetation changes in Beijing-Tianjin-Hebei region of China[J]. Science of the Total Environment, 2021,786:147574.

崔凤娇,邵锋,齐锋,等.植被对城市热岛效应影响的研究进展[J].浙江农林大学学报, 2020,37(1):171-181. Cui Fengjiao, Shao Feng, Qi Feng, et al. Research advances in the influence of vegetation on urban heat island effect[J]. Journal of Zhejiang A&F University, 2020,37(1):171-181.

黄健熙,吴炳方,曾源,等.水平和垂直尺度乔、灌、草覆盖度遥感提取研究进展[J].地球科学进展, 2005,20(8):871-881. Huang Jianxi, Wu Bingfang, Zeng Yuan, et al. Review of tree, shrub, grass cover of horizontal and vertical scale retrieval from remotely sensed data[J]. Advance in Earth Sciences, 2005,20(8):871-881.

Lu Ang, Tian Peng, Mu Xingmin, et al. Fuzzy logic modeling of land degradation in a loess plateau watershed, China[J]. Remote Sensing, 2022,14(19):4779.

Qi J, Marsett R C, Moran M S, et al. Spatial and temporal dynamics of vegetation in the San Pedro River basin area[J]. Agricultural and Forest Meteorology, 2000,105(1-3):55-68.

Wang Lixia, Yu Dongyang, Liu Zhao, et al. Study on NDVI changes in Weihe Watershed based on CA-Markov model[J]. Geological Journal, 2018,53:435-441.

易海杰,张晓萍,何亮,等.黄土高原不同地貌类型区植被恢复潜力及其土地利用变化[J].农业工程学报, 2022,38(18):255-263. Yi Haijie, Zhang Xiaoping, He Liang, et al. Vegetation restoration potential and land use change in different geomorphological areas of the Loess Plateau[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022,38(18):255-263.

Zhang Daojun, Xu Xin, Yao Shunbo, et al. A novel similar habitat potential model based on sliding-window technique for vegetation restoration potential mapping[J]. Land Degradation&Development, 2020,31(6):760-772.

高海东,庞国伟,李占斌,等.黄土高原植被恢复潜力研究[J].地理学报, 2017,72(5):863-874. Gao Haidong, Pang Guowei, Li Zhanbin, et al. Evaluating the potential of vegetation restoration in the Loess Plateau[J]. Acta Geographica Sinica, 2017,72(5):863-874.

钱娅. 2006-2015年江苏省植被覆盖度的演变趋势与预测研究[D].江苏南京:南京信息工程大学, 2021. Qian Ya. Evolution trend and prediction of vegetation coverage in Jiangsu Province from 2006 to 2015[D]. Nanjing, Jiangsu:Nanjing University of Information Science and Technology, 2021.

吕振涛,李生宇,范敬龙,等.蒙古国植被自然恢复潜力[J].中国沙漠, 2021,41(5):192-201. Lv Zhentao, Li Shengyu, Fan Jinglong, et al. Natural restoration potential of vegetation in Mongolia[J]. Journal of Desert Research, 2021,41(5):192-201.

赵广举,穆兴民,田鹏,等.黄土高原植被变化与恢复潜力预测[J].水土保持学报, 2021,35(1):205-212. Zhao Guangju, Mu Xingmin, Tian Peng, et al. Prediction of vegetation variation and vegetation restoration potential in the loess plateau[J]. Journal of Soil and Water Conservation, 2021,35(1):205-212.

郭芬芬,范建容,严冬,等.基于像元二分模型的昌都县植被盖度遥感估算[J].中国水土保持, 2010(5):65-67. Guo Fenfen, Fan Jianrong, Yan Dong, et al. Remote sensing estimation of vegetation coverage in Changdu County based on pixel dichotomy model[J]. Soil and Water Conservation in China, 2010(5):65-67.

王举凤.内蒙古草原植被覆盖度对气候变化的响应[D].陕西杨凌:西北农林科技大学, 2020. Wang Jufeng. Response of photosynthetic vegetation coverage to climate change in Inner Mongolia grassland[D]. Yangling, Shaanxi:Northwest A&F University, 2020.

陈学兄,毕如田,张小军,等.太原市城区植被覆盖变化地形分异效应[J].水土保持通报, 2020,40(5):299-309. Chen Xuexiong, Bi Rutian, Zhang Xiaojun, et al. Topographic differentiation effect on vegetation cover change in urban districts of Taiyuan city[J]. Bulletin of Soil and Water Conservation, 2020,40(5):299-309.

严岳鸿,何祖霞,苑虎,等.坡向差异对广东古兜山自然保护区蕨类植物多样性的生态影响[J].生物多样性, 2011,19(1):41-47. Yan Yuehong, He Zuxia, Yuan Hu, et al. The ecological response of fern diversity to different slopes in Gudoushan Nature Reserve, Guangdong[J]. Biodiversity Science, 2011,19(1):41-47.

朱红春,陈楠,刘海英,等.自1:10000比例尺DEM提取地形起伏度:以陕北黄土高原的实验为例[J].测绘科学, 2005,30(4):86-88. Zhu Hongchun, Chen Nan, Liu Haiying, et al. Research on the relief based on 1:10000 DEMs:A case study in the loess plateau of North Shaanxi Province[J]. Science of Surveying and Mapping, 2005,30(4):86-88.

王佃来,刘文萍,黄心渊.基于Sen+Mann-Kendall的北京植被变化趋势分析[J].计算机工程与应用, 2013,49(5):13-17. Wang Dianlai, Liu Wenping, Huang Xinyuan. Trend analysis in vegetation cover in Beijing based on Sen+Mann-Kendall method[J]. Computer Engineering and Applications, 2013,49(5):13-17.

Ali R, Kuriqi A, Abubaker S R, et al. Long-term trends and seasonality detection of the observed flow in Yangtze River using Mann-Kendall and Sen's innovative trend method[J]. Water, 2019,11(9):1855.

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[J].生态学报, 2014,34(17):5007-5020. Yan Enping, Lin Hui, Dang Yongfeng, et al. The spatiotemporal changes of vegetation cover in Beijing-Tianjin sandstorm source control region during 2000-2012[J]. Acta Ecologica Sinica, 2014,34(17):5007-5020.

刘迎春,王秋凤,于贵瑞,等.黄土丘陵区两种主要退耕还林树种生态系统碳储量和固碳潜力[J].生态学报, 2011,31(15):4277-4286. Liu Yingchun, Wang Qiufeng, Yu Guirui, et al. Ecosystems carbon storage and carbon sequestration potential of two main tree species for the grain for green project on China's hilly Loess Plateau[J]. Acta Ecologica Sinica, 2011,31(15):4277-4286.

成佩昆,胡守庚,孙涛,等.陕西省退耕还林工程对植被恢复的效应:基于PCSE修正的面板数据模型[J].干旱区研究, 2018,35(6):1477-1486. Cheng Peikun, Hu Shougeng, Sun Tao, et al. Effect of grain for green project on vegetation regeneration in Shaanxi Province:Based on PCSE panel data model[J]. Arid Zone Research, 2018,35(6):1477-1486.

李登科,王钊.退耕还林后陕西省植被覆盖度变化及其对气候的响应[J].生态学杂志, 2020,39(1):1-10. Li Dengke, Wang Zhao. Changes of fractional vegetation coverage after returning farmland to forests and its response to climate in Shaanxi[J]. Chinese Journal of Ecology, 2020,39(1):1-10.

张斯源,樊逸飞,颜礼,等.基于长时序MODIS的陕西省近20年生态质量时空变化及其驱动力研究[J].水土保持学报, 2023,37(2):111-119. Zhang Siyuan, Fan Yifei, Yan Li, et al. Temporal and spatial variation and driving forces of eco-environmental quality in Shaanxi Province in recent 20 years based on long time series MODIS data[J]. Journal of Soil and Water Conservation, 2023,37(2):111-119.

杜国明,李宁宁,张娜,等.全国耕地"非粮化"时空格局分析[J].东北农业大学学报(社会科学版), 2022,20(2):17-27. Du Guoming, Li Ningning, Zhang Na, et al. Analysis on the spatio-temporal pattern of non-grain cultivated land in China[J]. Journal of Northeast Agricultural University (Social Science Edition), 2022,20(2):17-27.

浏览量

536

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

陕西省荒漠化土地治理综合效益评价

基于生态足迹模型的区域生态经济发展评估--陕西省及其各市域实证分析

基于GIS和人工神经网络的区域水资源压力评价模型及其验证

基于ArcEngine的陕西省土壤信息系统构建

数字经济对长江经济带农业生态产品价值转化效率的影响