测绘通报 ›› 2019, Vol. 0 ›› Issue (9): 94-98.doi: 10.13474/j.cnki.11-2246.2019.0293

• 技术交流 • 上一篇    下一篇

时空过程对象的LULC时空演变分析算法

李石华1, 汪祎勤1, 周峻松1, 金宝轩2   

  1. 1. 云南省基础地理信息中心, 云南 昆明 650034;
    2. 云南省自然资源厅信息中心, 云南 昆明 650224
  • 收稿日期:2019-04-04 修回日期:2019-05-16 出版日期:2019-09-25 发布日期:2019-09-28
  • 通讯作者: 汪祎勤。E-mail:412224475@qq.com E-mail:412224475@qq.com
  • 作者简介:李石华(1980-)男,博士,高级工程师,主要从事遥感数字图像处理、资源环境遥感、区域LUCC时空动态模拟与分析等工作。E-mail:lsh8010@163.com
  • 基金资助:
    国家自然科学基金(41861051;41561086;41661086);国家测绘地理信息局地理国情监测示范项目(测国土函〔2014〕35号)

Spatio-temporal variation analysis algorithm of LULC based on spatio-temporal process object

LI Shihua1, WANG Yiqin1, ZHOU Junsong1, JIN Baoxuan2   

  1. 1. Yunnan Provincial Geomatics Centre, Kunming 650034, China;
    2. Information Center Department of Natural Resources of Yunnan Province, Kunming 650224, China
  • Received:2019-04-04 Revised:2019-05-16 Online:2019-09-25 Published:2019-09-28

摘要: 地理时空变化是地理学研究的重要内容之一,如何用计算机技术来表达空间数据的时空变化独具前瞻性。从揭示LULC时空演变过程和挖掘时空演变规律出发,讨论了基于地类图斑的时空演变过程类型与判定方法,并构建了一种基于地类图斑的时空变化分析算法。通过对抚仙湖流域近40年来LULC时空演变分析,验证了算法的可靠性与有效性。表明该方法可用于地表覆盖等地理要素的时空变化过程分析,能较好地揭示地理要素及其属性在时间轴上的改变过程。

关键词: 时空演变, 时空过程对象, LULC, 地类图斑, 地表覆盖

Abstract: Geographical components spatio-temporal change is one of the important contents in geography research. And perspective study is that how to use computer technology to express the spatio-temporal change of spatial data. Aiming at revealing the spatio-temporal variation of land use/land cover (LULC) process and mining spatio-temporal variation rules, the types and methods of spatio-temporal variation of LULC patches are discussed, and a spatio-temporal variation analysis algorithm for analyzing LULC patches is constructed. The reliability and effectiveness of the algorithm are verified according to analysis of spatio-temporal variation of LULC in the past 40 years in the Fuxian Lake Basin. The results show that, the method can be used to analyze the spatio-temporal variation process of geographical elements such as surface cover, and can efficiently reveal the change process of geographic elements and their attributes on the time axis.

Key words: spatio-temporal variation, spatio-temporal process object, LULC, patches, surface cover

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