生态与农村环境学报 ›› 2022, Vol. 38 ›› Issue (4): 418-427.doi: 10.19741/j.issn.1673-4831.2021.0245

• 区域环境与发展 • 上一篇    下一篇

滇东喀斯特地区石漠化时空演化特征及驱动机制研究

卢涛1,2, 张军3, 胡文英1,2   

  1. 1. 云南师范大学地理学部, 云南 昆明 650500;
    2. 云南省高校资源与环境遥感重点实验室, 云南 昆明 650500;
    3. 云南大学地球科学学院, 云南 昆明 650504
  • 收稿日期:2021-04-20 出版日期:2022-04-22 发布日期:2022-04-22
  • 通讯作者: 胡文英,E-mail:402042525@qq.com E-mail:402042525@qq.com
  • 作者简介:卢涛(1991-),男,贵州纳雍人,主要从事资源环境遥感研究。E-mail:1824739294@qq.com
  • 基金资助:
    国家重点研发计划(2018YFE0184300);云南大学研究生创新人才培养项目(C176230200);高分辨率对地观测系统重大专项省域产业化应用项目(89-Y40G19-9001-18/20)

Spatio-temporal Evolution Characteristics and Driving Mechanism of Rocky Desertification in Karst Area of Eastern Yunnan

LU Tao1,2, ZHANG Jun3, HU Wen-ying1,2   

  1. 1. Faculty of Geography, Yunnan Normal University, Kunming 650500, China;
    2. Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China;
    3. School of Earth Sciences, Yunnan University, Kunming 650504, China
  • Received:2021-04-20 Online:2022-04-22 Published:2022-04-22

摘要: 如何科学认识石漠化时空演化规律及其驱动机理,是开展石漠化治理的首要前提和关键。为此,以1987-2020年Landsat遥感影像为主要数据源,结合RS、GIS技术及地理探测器方法,探究云南省曲靖市近30 a来石漠化时空动态演化特征,并定量揭示石漠化演化的驱动机制。结果表明:(1)1987-2020年间,曲靖市潜在、轻度、中度、重度和极度石漠化区域面积占比分别从8.56%、9.71%、4.85%、0.98%、0.35%减少到8.35%、9.29%、4.32%、0.79%和0.29%。其中,潜在、轻度和中度石漠化区域面积变化较为反复,年均变化率分别为0.16%、-0.22%和-0.19%。重度和极度石漠化区域面积减幅较大,年均变化率分别为-0.56%和-0.32%;(2)曲靖市石漠化区域面积大、分布范围广,主要集中连片分布于峰丛洼地、丘陵、干热河谷地带及县与县的交界处,整体上呈东南部重、中部和西北部轻的宏观格局;(3)影响曲靖市石漠化发育演化的主要单因子是农业总产值(0.281)和耕地面积(0.233),交互式探测器结果表明,坡度∩耕地面积(q=0.465)>耕地面积∩总人口(q=0.374)>耕地面积∩人口密度(q=0.302)>年均降水∩坡度(q=0.283)>耕地面积∩距居民点距离(q=0.278),各驱动因子交互作用对石漠化演化的影响大于单因子作用,表明曲靖市喀斯特石漠化是多种驱动因素交互作用的结果。

关键词: 石漠化, 时空演化, 驱动机制, 地理探测器

Abstract: As one of the most prominent problems in the interweaving of social economy and ecological environment in the karst area of southwest China, rocky desertification has been a hot and difficult topic in the academic circles for a long time. How to scientifically understand the temporal and spatial evolution of karst rocky desertification and its driving mechanism is the primary premise and key to karst rocky desertification control. Taking Landsat TM/OLI remote sensing images from 1987 to 2020 as the main data source, combined with remote sensing, GIS technology and geographical detector method, the spatial-temporal dynamic evolution characteristics of rocky desertification in Qujing City of Yunnan Province in the past 30 years were analyzed, and the driving mechanism of rocky desertification evolution was quantitatively explored. The results show that: (1) During 1987-2020, the area proportions of potential, mild, moderate, severe and extreme heavy rocky desertification in Qujing City decreased from 8.56%, 9.71%, 4.85%, 0.98% and 0.35% to 8.35%, 9.29%, 4.32%, 0.79% and 0.29%, respectively. Among them, the area proportion of potential, mild and moderate rocky desertification fluctuated, and the annual change rates were 0.16%, -0.22% and -0.19%, respectively. The average annual change rates of severe and extreme rocky desertification were -0.56% and -0.32%, respectively; (2) Rocky desertification in Qujing City is large in area and wide in distribution. mainly distributed in the peak cluster depressions, hills, dry-hot valleys and the inter-county boundary regions. The overall pattern of rocky desertification is severe in the southeast, mild in the middle and northwest. (3) The main single factors affecting the development and evolution of rocky desertification in Qujing City were the gross agricultural output value (0.281) and the cultivated land area (0.233). Interactive detector further reveals that the slope ∩ cultivated land area (q=0.465) > cultivated land area ∩ total population (q=0.374) > cultivated land area ∩ population density (q=0.302) > average annual precipitation ∩ slope (0.283) > cultivated land area ∩ distance from settlements (q=0.278), the interaction effects of driving factors on rocky desertification evolution is greater than that of the influence of single factor effect, showing the karst rocky desertification of Qujing City is the result of the interaction of multiple driving factors.

Key words: rocky desertification, spatial-temporal evolution, driving mechanism, Geo-Detector

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