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应用生态学报 ›› 2017, Vol. 28 ›› Issue (6): 1808-1816.doi: 10.13287/j.1001-9332.201706.035

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基于NDVI时间序列轨迹的草原露天矿区植被时空动态特征

贾铎1,2, 王藏姣1,2, 牟守国1,2*, 赵华1,2   

  1. 1中国矿业大学环境与测绘学院, 江苏徐州 221116
    2中国矿业大学江苏省资源环境信息工程重点实验室, 江苏徐州 221116
  • 收稿日期:2016-11-22 发布日期:2017-06-18
  • 通讯作者: *E-mail:mushouguo@163.com
  • 作者简介:贾铎,男,1993年生,硕士研究生.主要从事遥感应用研究.E-mail:jiaduo_geo@163.com
  • 基金资助:
    本文由国家重点基础研究发展计划项目(2013CB227904)、国家科技基础性工作专项(2014FY110800)和国家重点研发计划项目(2016YFC0501107)资助

Vegetation spatial and temporal dynamic characteristics based on NDVI time series trajectories in grassland opencast coal mining

JIA Duo1,2, WANG Cang-jiao1,2, MU Shou-guo1,2*, ZHAO Hua1,2   

  1. 1School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China
    2Jiangsu Province Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China
  • Received:2016-11-22 Published:2017-06-18
  • Contact: *E-mail:mushouguo@163.com
  • Supported by:
    This work was supported by the National Key Basic Research and Development Plan of China (2013CB227904), the Special Project of Science and Technology Basic Work of Ministry of Science and Technology of China (2014FY110800), and the National Key Research and Development Program (2016YFC0501107)

摘要: 采矿作用下草原露天矿区植被时空动态特征尚不明确.以胜利露天矿区为例,选取MODIS和Landsat影像,利用ESTARFM构建2001—2015年植被生长期一致的年际Landsat时间序列,以时间分割算法拟合像元NDVI时间序列轨迹,结合轨迹形态特征提取早期扰动型、持续扰动型、扰动稳定型、扰动稳定恢复型和扰动恢复型5种植被动态类型及各类型的时间特征.结果表明:胜利矿区植被动态类型以扰动恢复型为主,占各类型像元总数的55.2%,扰动稳定型和持续下降型次之,分别为25.6%和11.0%,早期扰动型和扰动稳定恢复型较小,分别为3.5%和4.7%.扰动多发于2004—2009年,稳定期多始于2008年,空间上多分布于露天采场和排土场,恢复期多始于2008年和2010年,其空间范围较小且集中于矿井外围和排土场.扰动持续时长以1年为主,稳定期持续时长以7年为主,恢复期持续时长中稳定恢复型为2~5年,扰动恢复型为8年.

Abstract: The spatiotemporal dynamic patterns of vegetation in mining area are still unclear. This study utilized time series trajectory segmentation algorithm to fit Landsat NDVI time series which generated from fusion images at the most prosperous period of growth based on ESTARFM algorithm. Combining with the shape features of the fitted trajectory, this paper extracted five vegetation dynamic patterns including pre-disturbance type, continuous disturbance type, stabilization after disturbance type, stabilization between disturbance and recovery type, and recovery after disturbance type. The result indicated that recovery after disturbance type was the dominant vegetation change pattern among the five types of vegetation dynamic pattern, which accounted for 55.2% of the total number of pixels. The follows were stabilization after disturbance type and continuous disturbance type, accounting for 25.6% and 11.0%, respectively. The pre-disturbance type and stabilization between disturbance and recovery type accounted for 3.5% and 4.7%, respectively. Vegetation disturbance mainly occurred from 2004 to 2009 in Shengli mining area. The onset time of stable state was 2008 and the spatial locations mainlydistributed in open-pit stope and waste dump. The reco-very state mainly started since the year of 2008 and 2010, while the areas were small and mainly distributed at the periphery of open-pit stope and waste dump. Duration of disturbance was mainly 1 year. The duration of stable period usually sustained 7 years. The duration of recovery state of the type of stabilization between disturbances continued 2 to 5 years, while the type of recovery after disturbance often sustained 8 years.