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应用生态学报 ›› 2025, Vol. 36 ›› Issue (1): 208-218.doi: 10.13287/j.1001-9332.202501.027

• 研究报告 • 上一篇    下一篇

核温度植被干旱指数对东北地区城市化的响应

黎国庆, 张春亢*, 张显云, 杨正雄峰, 文鹏帆, 杨庆骅   

  1. 贵州大学矿业学院, 贵阳 550025
  • 收稿日期:2024-06-04 修回日期:2024-11-18 出版日期:2025-01-18 发布日期:2025-07-18
  • 通讯作者: *E-mail: chkang_chd@163.com
  • 作者简介:黎国庆, 男, 2000年生, 硕士研究生。主要从事遥感干旱监测研究。E-mail: gzdxlgq1001@163.com
  • 基金资助:
    中国科学院战略性先导科技专项子课题(XDA28060201)、国家自然科学基金项目(41701464)、贵州大学培育项目(贵大培育[2019]26号)和贵州省省级科技计划项目(黔科合支撑[2022]一般204)

Response of kernel temperature vegetation drought index to urbanization in Northeast China

LI Guoqing, ZHANG Chunkang*, ZHANG Xianyun, YANG Zhengxiongfeng, WEN Pengfan, YANG Qinghua   

  1. Mining College of Guizhou University, Guiyang 550025, China
  • Received:2024-06-04 Revised:2024-11-18 Online:2025-01-18 Published:2025-07-18

摘要: 明确东北地区不同城市化水平与干旱的响应关系,对东北地区的生态保护与城市化协调发展具有重要意义。本研究利用核归一化植被指数(kNDVI)代替归一化植被指数(NDVI)构建核温度植被干旱指数(kTVDI),采用Sen-MK方法、Moran指数分析2013—2022年东北地区kTVDI的时空变化和空间集聚特征,并分析不同程度城市化区域与乡村区域的kTVDI差值及其变化趋势。结果表明: 总体上,不同年份、不同时期的kTVDI与土壤湿度的相关性高于温度植被干旱指数(TVDI)与土壤湿度的相关性,且kTVDI在高值区的抗噪性优于TVDI,对表征东北地区西部旱情的适用性强。2013—2022年间,东北地区干旱强度自东北向西南加强;春、秋季干旱胁迫较强,夏季受旱程度较弱,春季旱情有加重趋势,夏、秋季旱情正不断缓解。小兴安岭、长白山脉以及黑龙江东部区域为kTVDI的低-低聚集区,高-高聚集区主要分布在辽西丘陵以及东北平原一带。高-高聚集区增加的区域与哈尔滨、长春、吉林所在的城市三角区基本重合,表明该城市群的人类活动对干旱有加强作用。不同程度的城市化均导致区域干旱加重,且中等水平城市化对区域干旱加重的影响强于高水平城市化。城市绿地能够一定程度削弱城市化对干旱的影响。

关键词: 核温度植被干旱指数, 干旱监测, 城市化, 东北地区

Abstract: Clarifying the relationship between urbanization level and drought in the Northeast China is of great significance for ecological protection and the coordinated development of urbanization. We used kernel normalized difference vegetation index (kNDVI) instead of the normalized difference vegetation index (NDVI) in constructing the kernel temperature vegetation drought index (kTVDI). We then applied the Sen-MK method and Moran’s index to analyze the spatiotemporal variation and spatial clustering of the kTVDI in the Northeast China from 2013 to 2022, and to examine the differences in kTVDI and their trends in areas with varying levels of urbanization and rural areas. The results showed that the correlation between kTVDI and soil moisture was stronger than that between temperature vegetation drought index (TVDI) and soil moisture in different years and periods. Additionally, kTVDI showed higher noise resistance in high-value areas compared to TVDI, making it more applicable to drought monitoring in the western part of Northeast China. From 2013 to 2022, drought intensity in Northeast China increased from northeast to southwest. Drought stress was stronger in spring and autumn, while that in summer was weaker, with a trend of worsening in spring and alleviating in summer and autumn. The Lesser Khingan Mountains, Changbai Mountains, and eastern Heilongjiang region formed a low-low clustering area for kTVDI, while high-high clustering areas were mainly distributed in the western Liaoning hills and the northeast plain. The expanding high-high clustering area largely overlapped with the urban triangle region of Harbin, Changchun, and Jilin, indicating that human activities within this urban cluster strengthened the drought. Areas with different levels of urbanization all experienced intensified regional drought, with moderate levels of urbanization having a stronger impact on the exacerbation of drought than high levels of urbanization. Urban green spaces could somewhat mitigate the impact of urbanization on drought.

Key words: kernel temperature vegetation drought index, drought monitoring, urbanization, Northeast China