干旱区生态

锡林郭勒草原生态恢复工程效果的评价

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  • 1. 环境演变与自然灾害教育部重点实验室, 北京师范大学资源学院, 北京100875;
    2. 中山大学地理科学与规划学院, 广州510275;
    3. 农业部资源遥感与数字农业重点开放实验室, 北京100081;
    4. 日本名古屋大学大学院工学研究科, 名古屋464-8601
卓莉(1973-), 女, 湖南人, 博士, 主要从事遥感应用与地理信息系统研究。E-mail: lizhuo2005@gmail.com

收稿日期: 2006-11-20

  修回日期: 2007-01-15

  网络出版日期: 2007-05-25

基金资助

农业部资源遥感与数字农业重点开放实验室开放基金项目; 国家杰出青年科学基金项目(40425008); 国家 自然科学基金项目(40601010); 中国博士后基金项目(20060390208)

Assessment of Grassland Ecological Restoration Project in Xilin Gol Grassland

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  • 1. Key Laboratory of Environment Change and Natural Disaster, Ministry of Education of China, College of Resource Science and Technology, Beijing Normal University, Beijing 100875, China;
    2. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China;
    3. Key Laboratory of Resources Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;
    4. Graduate School of Engineering, Nagoya University, Nagoya 464-8601, Japan

Received date: 2006-11-20

  Revised date: 2007-01-15

  Online published: 2007-05-25

Supported by

Supported by Key Laboratory of Resources Remote Sensing & Digital Agriculture, the Ministry of Agriculture; The National Science Fund for Distinguished Young Scholars, No.40425008; National Natural Science Foundation of China, No. 40601010; China Postdoctoral Science Foundation, No.20060390208

摘要

针对锡林郭勒草原的严重退化, 近年来启动了草原生态恢复工程, 但工程实施的效果由于范围广、时间短而很难予评价。利用锡林郭勒草原地区1999~2004 年的SPOT-VGT 10 天最大值合成NDVI 时间序列数据, 在求得各年NDVI 年最大值(NDVImax) 的基础上, 通过搜寻各像元邻域内NDVImax 的最大值以及与之相应的气候因子, 建立起了像元尺度上的气候—植被生长基准响应模型, 并以此为依据运用相对残差趋势法识别出了处于恢复阶段的草原区域。 最后, 将遥感监测结果与羊单位统计资料进行对比分析, 结果发现, 在县级行政区域尺度上的平均恢复趋势与基于羊单位和NPP 构建的放牧压力趋势具有较好的反比例关系, 初步证明了该方法在时间序列较短情况下的有效性。

本文引用格式

卓莉, 曹鑫, 陈晋, 陈仲新, 史培军 . 锡林郭勒草原生态恢复工程效果的评价[J]. 地理学报, 2007 , 62(5) : 471 -480 . DOI: 10.11821/xb200705003

Abstract

Xilin Gol grassland has been experiencing severe degradation since the livestock kept on increasing in the past decades. Recent 'Grassland Ecological Restoration Project' is being developed for improvement of the degraded grassland and sustainable development. However, due to the short-time of the project implementation, it is difficult to monitor the restored area and assess the effect of the project. In this study, SPOT-VGT maximum value composite (MVC) NDVI temporal series data from 1999 to 2004 of Xilin Gol was used to model climate-vegetation response relationships in pixel scale. The model was based on the maximum NDVI in the neighborhood and their climate factors including accumulated temperature and accumulated precipitation. Then the restored areas were identified by positive trend of normalized residuals between model predicted NDVI and actual values. The result was validated by grazing pressure index (GPI), which was defined as the sheep unit divided by NPP. Negative relationship was found between the trend of residual and GPI at county level, which proved the effectiveness of the method for short-term temporal data.

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