Spatiotemporal variation of vegetation and its future development potential in Gansu province
JIN Feng1,2, GE Wenyan3,4, QIN Wei5, HAN Jianqiao3,4, MA Tao6, ZHENG An2
1. School of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; 2. Water Resources Department of Gansu Province, 730000, Lanzhou, China; 3. Northwest A&F University, 712100, Yangling, Shaanxi, China; 4. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, 712100, Yangling, Shaanxi, China; 5. Soil and Water Conservation Ecological Engineering Technology Research Center of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, 100048, Beijing, China; 6. Gansu Institute of Soil and Water Conservation, 730020, Lanzhou, China
摘要为探究甘肃省生态治理成效及未来植被提升空间，基于全省2000—2020年生长季（4—9月） MODIS EVI数据及2020年土地利用/覆被数据，采用线性回归方程及基于滑动窗口的相似栖息地潜力模型分析全省植被覆盖的时空变化特征及未来植被恢复潜力。结果表明：1）2000—2020年间，甘肃省生长季EVI以0.002/a速率显著上升，2012年后有所减缓，2016年以后再次大幅提升，近20年全省植被覆盖整体持续改善。2）2000—2020年甘肃省生长季EVI总体由东南向西北递减，年均变化速率介于-0.006~0.010/a；90%区域的植被覆盖有所改善，以陇东和陇南为主的1/3省域植被覆盖显著快速提升。3）陇南与河西分别为全省同期EVI的高值和低值区，且后者的植被覆盖增加最弱；陇中、陇东的植被覆盖变化相对缓慢。4）省内植被恢复指数成效显著，当前植被恢复潜力实现度较高，剩余植被恢复潜力度较低。其中，47.4%的裸地具备转化为绿地的潜力，草地和林地则分别有28.1%和2.5%的面积具备进一步提升的潜力。总之，近20年来甘肃省植被覆盖整体明显改善，但其空间分异特征尚未改变；剔除非自然植被后，全省整体植被覆盖度仅有10%左右的提升空间。
Abstract：[Background]Being an important part of terrestrial ecosystem, vegetation plays a crucial role in soil maintenance, climate regulation and carbon sequestration. As a typical climate-sensitive and ecologically fragile region, Gansu province is inseparable from vegetation for soil and water conservation and ecological restoration. Therefore, large-scaled soil and water conservation projects and ecological projects have been implemented to restore vegetation and improve ecological environment at the end of the last century and the beginning of this century. This study is aimed to explore the effectiveness of afforestation and the restoration potential of future vegetation in Gansu province.[Methods] The linear regression method and sliding-window similar habitat potential model (SWSHPM) were applied to analyze the spatiotemporal variations of vegetation and its future restoration potential, using MODIS (moderate resolution imaging spectroradiometer) EVI (enhanced vegetation index) data of the growing season (April-September) from 2000 to 2020 and the land use and land cover (LULC) data of 2020.[Results] 1) Generally, EVI increased significantly during the growing season from 2000 to 2020 across the study area, with an average annual growth rate of 0.002/a. The growth rate slowed down from 2012 to 2016 and then speeded up again, indicating the continuous improvement of the overall vegetation coverage in Gansu province during the past 20 years. 2) In terms of spatial variation, EVI decreased from the southeast to the northwest during the growing season in Gansu province, with average annual slopes of -0.006-0.010/a. Besides, the vegetation coverage demonstrated significant and rapid increases in about one-third of the study region, dominated by Longdong and Longnan areas. 3) Longnan and Hexi were the high value and low value areas of EVI, respectively. And the increase of the latter vegetation was the weakest. In addition, spatial variations of EVI in Longzhong and Longdong were relatively small. 4) The vegetation restoration potential index (VRPI) in Gansu province achieved remarkable results. The current vegetation restoration potential achieved degree (VRPAD) was relatively high. The surplus vegetation restoration potential degree (SVRPD) was relatively low. Specifically, 47.4% of the bare land has the potential to be transformed into grassland and forest land. Additionally, 28.1% of grassland area and 2.5% of woodland area had the potential to be improved in the future, respectively.[Conclusions] Overall, the vegetation coverage in Gansu province has improved significantly from 2000 to 2020, while its characteristics of spatial heterogeneity remained unchanged. Besides, there were only about 10% in vegetation coverage for improvement in the future after removing the unnatural vegetation in the study area.
靳峰, 戈文艳, 秦伟, 韩剑桥, 马涛, 郑安. 甘肃省植被时空变化及其未来发展潜力[J]. 中国水土保持科学, 2023, 21(1): 110-118.
JIN Feng, GE Wenyan, QIN Wei, HAN Jianqiao, MA Tao, ZHENG An. Spatiotemporal variation of vegetation and its future development potential in Gansu province. SSWC, 2023, 21(1): 110-118.
PIAO Shilong, FRIEDLINGSTEIN P, CIAIS P, et al. Effect of climate and CO2 changes on the greening of the northern Hemisphere over the past two decades[J]. Geophysical Research Letters, 2006, 33:23402.
[2]
SUN Wenyi, SONG Xiaoyan, MU Xingmin, et al. Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau[J]. Agricultural and Forest Meteorology, 2015, 209/210(1):87.
[3]
ZHANG Daojun, JIA Qiqi, WANG Peng, et al. Analysis of spatial variability in factors contributing to vegetation restoration in Yan'an, China[J]. Ecological Indicators, 2020, 113:106278.
[4]
银朵朵, 王艳慧. 温带大陆性半干旱季风气候区植被覆盖度时空变化及其地形分异研究[J]. 生态学报, 2021, 41(3):1158. YIN Duoduo, WANG Yanhui. Temporal and spatial changes of vegetation coverage and its topographic differentiation in temperate continental semi-arid monsoon climate region[J]. Acta Ecologica Sinica, 2021, 41(3):1158.
[5]
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. 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.
[6]
李军媛, 徐维新, 程志刚, 等. 1982-2006年中国半干旱、干旱区气候与植被覆盖的时空变化[J]. 生态环境学报, 2012, 21(2):268. LI Junyuan, XU Weixin, CHEN Zhigang, et al. Spatial-temporal changes of climate and vegetation cover in the semi-arid and arid regions of China during 1982-2006[J]. Ecology and Environmental Sciences, 2012, 21(2):268.
[7]
ZHAO Xia, ZHOU Daojing, FNAG Jingyun. Satellite-based studies on large-scale vegetation changes in China[J]. Journal of Integrative Plant Biology, 2012, 54(10):713.
[8]
LI Shuangshuang, YANG Saini, LIU Xianfeng, et al. NDVI-based analysis on the influence of climate change and human activities on vegetation restoration in the Shaanxi-Gansu-Ningxia Region, central China[J]. Remote Sensing, 2015, 7(9):11163.
[9]
孙锐, 陈少辉, 苏红波. 2000-2016年黄土高原不同土地覆盖类型植被NDVI时空变化[J]. 地理科学进展, 2019, 38(8):1248. SUN Rui, CHEN Shaohui, SU Hongbo. Spatiotemporal variations of NDVI of different land cover types on the Loess Plateau from 2000 to 2016[J]. Progress in Geography, 2019, 38(8):1248.
[10]
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.
[11]
丁海勇, 丁昕玮. 基于SPOT NDVI的甘肃省植被覆盖变化及其与气候、地形因子的关系[J]. 长江流域资源与环境, 2020, 29(12):2665. DING Haiyong, DING Xiwei. Vegetation cover change and its responses to climate and topography in Gansu province based on SPOT NDVI[J]. Resources and Environment in the Yangtze Basin, 2020, 29(12):2665.
[12]
高健健, 穆兴民, 孙文义. 2000-2012年黄土高原植被覆盖的时空变化[J]. 人民黄河, 2015, 37(11):85. GAO Jianjian, MU Xingmin, SUN Wenyi. Spatial-temporal changes of vegetation restoration on Loess Plateau from 2000 to 2012[J]. Yellow River, 2015, 37(11):85.
[13]
郭铌, 朱燕君, 王介民, 等. 近22年来西北不同类型植被NDVI变化与气候因子的关系[J]. 植物生态学报, 2008,32(2):319. GUO Ni, ZHU Yanjun, WANG Jiemin, et al. The relationship between NDVI and climate elements for 22 years in different vegetation areas of Northwest China[J]. Chinese Journal of Plant Ecology, 2008,32(2):319.
[14]
ZHAO Xiaoyang, XIA Haoming, LIU Baoying, et al. Spatiotemporal comparison of drought in Shaanxi-Gansu-Ningxia from 2003 to 2020 using various drought indices in Google Earth Engine[J]. Remote Sensing, 2022, 14(7):1570.
[15]
何国兴, 韩天虎, 柳小妮, 等. 甘肃省草地植被NDVI时空变化特征及驱动因素研究[J]. 草地学报, 2021, 29(5):1004. HE Guoxing, HAN Tianhu, LIU Xiaoni, et al. Spatio-temporal variation and the driving factors of NDVI of grassland vegetation in Gansu province[J] Acta Agrestia Sinica, 2021, 29(5):1004.
[16]
戴声佩, 张勃, 王海军. 中国西北地区植被NDVI的时空变化及其影响因子分析[J]. 地球信息科学学报, 2010, 12(3):315. DAI Shengpei, ZHANG Bo, WANG Haijun. Spatio-temporal change of vegetation index NDVI in Northwest China and its influencing factors[J]. Journal of Geo-information Science, 2010, 12(3):315.
[17]
张华, 徐存刚, 王浩. 2001-2018年西北地区植被变化对气象干旱的响应[J]. 地理科学, 2020, 40(6):1029. ZHANG Hua, XU Cungang, WANG Hao. Response of vegetation change to meteorological drought in Northwest China from 2001 to 2018[J]. Scientia Geographica Sinica, 2020, 40(6):1029.
[18]
赵鸿雁, 陈英, 周翼, 等. 甘肃中东部植被生长季NDVI时空变化及其对气候因子的响应[J]. 干旱区地理, 2019, 42(6):1427. ZHAO Hongyan, CHEN Ying, ZHOU Yi, et al. Spatiotemporal variation of NDVI in vegetation growing season and its responses to climatic factors in mid and eastern Gansu province from 2008 to 2016[J]. Arid Land Geography, 2019, 42(6):1427.
[19]
李小亚, 张勃, 靳自宝. 基于MODIS-NDVI的甘肃河东地区植被覆盖度动态监测[J]. 水土保持研究, 2013, 20(1):112. LI Xiaoya, ZHANG Bo, JIN Zibao. Dynamic monitoring of vegetation coverage change in Hedong Area of Gansu based on MODIS-NDVI[J]. Research of Soil and Water Conservation, 2013, 20(1):112.
[20]
肖强, 陶建平, 肖洋. 黄土高原近10年植被覆盖的动态变化及驱动力[J]. 生态学报, 2016, 36(23):7594. XIAO Qiang, TAO Jianping, XIAO Yang. Dynamic vegetation cover changeover the past 10 years on the Loess Plateau, China[J]. Acta Ecologica Sinica, 2016, 36(23):7594.
[21]
杨尚武, 张勃. 基于SPOT NDVI的甘肃河东植被覆盖变化及其对气候因子的响应[J]. 生态学杂志, 2014, 33(2):455. YANG Shangwu, ZHANG Bo. Vegetation cover change and its response to climatic factors using SPOT NDVI in Hedong of Gansu Province[J]. Chinese Journal of Ecology, 2014, 33(2):455.
[22]
李海东, 秦卫华, 张涛, 等.西藏高寒河谷流动沙地植被恢复潜力综合评价模型[J]. 农业工程学报, 2015, 31(16):220. LI Haidong, QIN Weihua, ZHANG Tao, et al. Comprehensive evaluation model for vegetation potentiality on moving sandy land in alpine valley of Tibet, China[J]. Transaction of the CSAE, 2015, 31(16):220.
2023, Vol. 21 
