摘要
近30年来,随着对地观测技术、资源调查与信息传输技术的增强,地里国情各领域积累了海量的空间数据。在时间序列内对海量空间数据处理分析,为环境变化预测、生态恢复重建、资源合理开发提供科学的数据参考。国家对土地资源普查监测频次逐年提高,以此来了解资源现状、以及变化情况。传统模型对数据处理分析存在一定限制。在此背景下,选取黑河上游山区作为实验区,构建Logistic-CA-Markov(LCM)模拟与预测模型,探讨其对实验区LUCC(land use and cover change)的模拟效果,以及预测未来30年实验区LUCC情况。结果表明,对时空数据的时间序列变化与空间维度演化,LCM模型具有较强的模拟能力。
Over the past 30 years,with the development of remote sensing,nature resource investigation and geo-information transmission technology,it has accumulated a huge amount of spatial data in the nation geo-condition monitor area. The processing and analysis of mass spatial data,especially,it is in a long time series,is provided to provide scientific reference for prediction of environmental change,ecological restoration and reconstruction,and reasonable exploitation of resources. The frequency of investigation for nation nature resources are increased,in order to known the current situation of nature resources and change in future. Heihe mountain area was select as the experimentation area,constructing the Logistic-CA-Markov model to simulate the land use and cover change（ LUCC） from 1986 to 2014 year,and predict LUCC in next 30 years. The result showed that logistic-CAMarkov model have a high quality simulation and prediction map.
出处
《科学技术与工程》
北大核心
2016年第15期139-143,共5页
Science Technology and Engineering
基金
国家自然科学基金项目(4961038)
四川省教育厅自然科学基金项目(16ZB0351)
四川乐山市科技局重点基金项目成都理工大学工程技术学院基金项目(C122014014)共同资助
