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基于多源数据的新疆干旱特征及干旱模型研究

秦大辉, 杨灵, 谌伦超, 段云飞, 贾宏亮, 李贞培, 马建琴. 2022. 基于多源数据的新疆干旱特征及干旱模型研究. 自然资源遥感, 34(1): 151-157. doi: 10.6046/zrzyyg.2021074
引用本文: 秦大辉, 杨灵, 谌伦超, 段云飞, 贾宏亮, 李贞培, 马建琴. 2022. 基于多源数据的新疆干旱特征及干旱模型研究. 自然资源遥感, 34(1): 151-157. doi: 10.6046/zrzyyg.2021074
QIN Dahui, YANG Ling, CHEN Lunchao, DUAN Yunfei, JIA Hongliang, LI Zhenpei, MA Jianqin. 2022. A study on the characteristics and model of drought in Xinjiang based on multi-source data. Remote Sensing for Natural Resources, 34(1): 151-157. doi: 10.6046/zrzyyg.2021074
Citation: QIN Dahui, YANG Ling, CHEN Lunchao, DUAN Yunfei, JIA Hongliang, LI Zhenpei, MA Jianqin. 2022. A study on the characteristics and model of drought in Xinjiang based on multi-source data. Remote Sensing for Natural Resources, 34(1): 151-157. doi: 10.6046/zrzyyg.2021074

基于多源数据的新疆干旱特征及干旱模型研究

  • 基金项目:

    工程结构安全评估与防灾技术四川省青年科技创新研究团队项目(2019JDTD0017)

详细信息
    作者简介: 秦大辉(1980-),男,博士,副教授,主要从事图像处理、摄影测量、计算机视觉、防灾减灾等方面的研究。Email: qindahui@qq.com
  • 中图分类号: TP79

A study on the characteristics and model of drought in Xinjiang based on multi-source data

  • 综合考虑大气降水-植被生长-海拔相互作用等多元成因,以新疆地区2001—2019年的MODIS数据、TRMM降水数据以及该地区数字高程模型(digital elevation model,DEM)数据为遥感数据源,计算降水集中指数(precipitation concentration index,PCI)、温度植被干旱指数(temperature vegetation dryness index,TVDI)以及DEM等参数,利用主成分分析建立了改进的综合干旱监测模型。利用该模型对研究区进行时空分析,结果表明: 干旱发生频率在空间上主要呈现中部高四周低的特点,研究时段内约47.7%的区域发生了干旱,其中32.3%的干旱区其干旱频率可达60%以上,主要集中于塔里木盆地以及吐鲁番盆地; 研究区旱情变化趋势存在较大差异,3—9月线性回归斜率正值数值远大于负值,根据结果预测研究区2020年干旱情况主要表现为春旱和夏旱。
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  • [1]

    Abuzar M K, Shafiq M, Mahmood S A, et al. Drought risk assessment in the Khushab region of Pakistan using satellite remote sensing and geospatial methods[J]. International Journal of Economic and Environment Geology, 2019, 10(1):48-56. [2] 沈润平, 郭佳, 张婧娴, 等. 基于随机森林的遥感干旱监测模型的构建[J]. 地球信息科学学报, 2017, 19(1):125-133. [2] Shen R P, Guo J, Zhang J X, et al. Construction of a drought monitoring model using the random forest based remote sensing[J]. Journal of Geo-Information Science, 2017, 19(1):125-133.[3] 刘英, 岳辉, 侯恩科. MODIS数据在陕西省干旱监测中的应用[J]. 自然资源遥感, 2019, 31(2):172-179.doi: 10.6046/gtzyyg.2019.02.24. [3] Liu Y, Yue H, Hou E K. Drought monitoring based on MODIS in Shaanxi[J]. Remote Sensing for Land and Resources, 2019, 31(2):172-179.doi: 10.6046/gtzyyg.2019.02.24. [4] 王展鹏, 宋立生, 兰子焱, 等. 考虑下垫面类型的干旱指数比较研究[J]. 遥感技术与应用, 2019, 34(4):865-873.[4] Wang Z P, Song L S, Lan Z Y, et al. Evaluation of drought indices of metrology,hydrology and agriculture over the continental United States[J]. Remote Sensing Technology and Application, 2019, 34(4):865-873.[5] Sun X, Wang M, Li G, et al. Regional-scale drought monitor using synthesized index based on remote sensing in northeast China[J]. Open Geosciences, 2020, 12(1):163-173. [6] Kogan F N. Application of vegetation index and brightness temperature for drought detection[J]. Advances in Space Research, 1995, 15(11):91-100.[7] 温庆志, 孙鹏, 张强, 等. 基于多源遥感数据的农业干旱监测模型构建及应用[J]. 生态学报, 2019, 39(20):7757-7770.[7] Wen Q Z, Sun P, Zhang Q, et al. An integrated agricultural drought monitoring model based on multi-source remote sensing data:Model development and application[J]. Acta Ecologica Sinica, 2019, 39(20):7757-7770.[8] 杜灵通, 田庆久, 王磊, 等. 基于多源遥感数据的综合干旱监测模型构建[J]. 农业工程学报, 2014, 30(9):126-132.[8] Du L T, Tian Q J, Wang L, et al. A synthesized drought monitoring model based on multi-source remote sensing data[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(9):126-132.[9] 刘高鸣, 谢传节, 何天乐, 等. 基于多源数据的农业干旱监测模型构建[J]. 地球信息科学学报, 2019, 21(11):1811-1822. [9] Liu G M, Xie C J, He T L, et al. Agricultural drought monitoring model constructing based on multi-source data[J]. Journal of Geo-Information Science, 2019, 21(11):1811-1822.[10] 赵慧, 姚俊强, 李新国, 等. 新疆气候干湿变化特征分析[J]. 中山大学学报(自然科学版), 2020, 59(5):126-133.[10] Zhao H, Yao J Q, Li X G, et al. The characteristics of climate change in Xinjiang during1961—2015[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2020, 59(5):126-133.[11] 黄静, 张运, 汪明秀, 等. 近17年新疆干旱时空分布特征及影响因素[J]. 生态学报, 2020, 40(3):1077-1088.[11] Huang J, Zhang Y, Wang M X, et al. Spatial and temporal distribution characteristics of drought and its relationship with meteorological factors in Xinjiang in last 17 years[J]. Acta Ecologica Sinica, 2020, 40(3):1077-1088.[12] Arun K K C, Reddy G P O, Masilamani P, et al. Integrated drought monitoring index:A tool to monitor agricultural drought by using time-series datasets of space-based earth observation satellites[J]. Advances in Space Research, 2021, 67(1):298-315. [13] 史晓亮, 吴梦月, 丁皓. SPEI和植被遥感信息监测西南地区干旱差异分析[J]. 农业机械学报, 2020, 51(12):184-192.[13] Shi X L, Wu M Y, Ding H. Difference analysis of SPEI and vegetation remote sensing information in drought monitoring in southwest China[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(12):184-192.[14] 陈丙寅, 杨辽, 陈曦, 等. 基于改进型TVDI在干旱区旱情监测中的应用研究[J]. 干旱区地理, 2019, 42(4):902-913.[14] Chen B Y, Yang L, Chen X, et al. Application of modified TVDI in drought monitoring in arid areas[J]. Arid Land Geography, 2019, 42(4):902-913.[15] 余灏哲, 李丽娟, 李九一. 基于TRMM降尺度和MODIS数据的综合干旱监测模型构建[J]. 自然资源学报, 2020, 35(10):2553-2568.[15] Yu H Z, Li L J, Li J Y. Establishment of comprehensive drought monitoring model based on downscaling TRMM and MODIS data[J]. Journal of Natural Resources, 2020, 35(10):2553-2568. [16] Vicente-Serrano S M, Begueria S, Lopez-Moreno J I, et al. A multiscalar drought index sensitive to global warming:The standardized precipitation evapotranspiration index[J]. Journal of Climate, 2010, 23(7):1696-1718. [17] Irannezhad M, Ahmadi B, Klove B, et al. Atmospheric circulation patterns explaining climatological drought dynamics in the boreal environment of Finland,1962—2011[J]. International Journal of Climatology, 2017, 37(s1):801-817. [18] 陈诚, 赵书河. 基于TRMM降雨数据的中国黄淮海地区干旱监测分析[J]. 自然资源遥感, 2016, 28(1):122-129.doi: 10.6046/gtzyyg.2016.01.18. [18] Chen C, Zhao S H. Drought monitoring and analysis of Huanghuai Hai plain based on TRMM precipitation data[J]. Remote Sensing for Land and Resources, 2016, 28(1):122-129.doi: 10.6046/gtzyyg.2016.01.18. [19] 吕潇然, 尹晓天, 宫阿都, 等. 基于植被状态指数的云南省农业干旱状况时空分析[J]. 地球信息科学学报, 2016, 18(12):1634-1644. [19] Lyu X R, Yin X T, Gong A D, et al. Temporal and spatial analysis of agricultural drought in Yunnan Province based on vegetation condition index[J]. Journal of Geo-Information Science, 2016, 18(12):1634-1644.[20] 任怡, 王义民, 畅建霞, 等. 基于多源指标信息的黄河流域干旱特征对比分析[J]. 自然灾害学报. 2017, 26(4):106-115.

    [20] Ren Y, Wang Y M, Chang J X, et al. Drought characteristics analysis of the Yellow River basin based on the index of multi-source information[J]. Journal of Natural Disasters, 2017, 26(4):106-115.

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出版历程
收稿日期:  2021-03-15
刊出日期:  2022-03-14

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