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首页> 外文会议>ISPRS (International Society for Photogrammetry and Remote Sensing) Workshop on Spatial Analysis and Decision Making; Dec 3-5, 2003; Hong Kong, China >Studying spatio-temporal patterns of land-use change in arid environment of China
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Studying spatio-temporal patterns of land-use change in arid environment of China

机译：研究中国干旱环境下土地利用变化的时空格局

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摘要

Remotely sensed data have been the most important data source for environment change study in the past 30 years. Large collections of remote sensing imagery have provided a solid foundation for spatio-temporal analyses of the environment and the impact of human activities. This study seeks an efficient and practical methodology for integrating multi-temporal and multi-scale remotely sensed data from various sources with a monitoring time frame of 30 years, including historical and state-of-the-art high-resolution satellite imagery. Based on this, spatio-temporal patterns of environmental change, which is largely represented by changes in land cover (e.g., vegetation and water), were analysed for the given time frame. Multi-scale and multi-temporal remotely sensed data, including Landsat MSS, TM, ETM and SPOT HRV, were used to detect changes in land use in the past 30 years in Tarim River, Xinjiang, China. The study shows that by using the auto-classification approach an overall accuracy of 85%-90% with a Kappa coefficient 0.66-0.78 was achieved for the classification of individual images. The temporal trajectory of land-use change was established and its spatial pattern was analysed to obtain a better understanding of the human impact on the fragile ecosystem of China's arid environment.
机译：在过去的30年中，遥感数据一直是环境变化研究中最重要的数据源。大量遥感影像为环境和人类活动影响的时空分析提供了坚实的基础。这项研究寻求一种有效且实用的方法，用于整合来自各种来源的多时相和多尺度的遥感数据，监视时间范围为30年，包括历史和最新的高分辨率卫星图像。在此基础上，针对给定的时间范围分析了环境变化的时空格局，这种格局主要由土地覆盖的变化（例如植被和水）代表。包括Landsat MSS，TM，ETM和SPOT HRV在内的多尺度，多时相遥感数据被用于检测中国新疆塔里木河过去30年的土地利用变化。研究表明，通过使用自动分类方法，单个图像的分类的总体准确度达到85％-90％，卡伯系数为0.66-0.78。建立了土地利用变化的时间轨迹，并分析了其空间格局，以更好地了解人类对中国干旱环境脆弱生态系统的影响。

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