基于序列模式的土地利用变化分析——以广西壮族自治区为例

doi:10.31497/zrzyxb.20200512

自然资源学报 ›› 2020, Vol. 35 ›› Issue (5): 1160-1171.doi: 10.31497/zrzyxb.20200512

基于序列模式的土地利用变化分析——以广西壮族自治区为例

廖伟华¹, 聂鑫², 蒋卫国³

1.广西大学数学与信息科学学院,南宁 530004;
2.广西大学公共管理学院,南宁 530004;
3.北京师范大学地理科学部,遥感科学国家重点实验室,北京 100875

收稿日期:2019-03-15 出版日期:2020-05-28 发布日期:2020-05-28
通讯作者: 聂鑫（1983- ）,男,湖北武汉人,博士,教授,主要从事土地资源管理研究。E-mail: toefl678@163.com
作者简介:廖伟华（1975- ）,男,湖南耒阳人,硕士,副教授,主要从事空间数据挖掘研究。E-mail: gisliaowh@163.com
基金资助:
国家自然科学基金项目（71763001,71973038）; 国家重点研发计划专项项目（2016YFC0503002）; 广西重点研发计划项目（桂科AB18126007）

Analysis of land use change based on sequence model: Taking Guangxi Zhuang Autonomous Region as an example

LIAO Wei-hua¹, NIE Xin², JIANG Wei-guo³

1. College of Mathematics and Information Science, Guangxi University, Nanning 530004, China;
2. School of Public Administration, Guangxi University, Nanning 530004, China;
3. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Received:2019-03-15 Online:2020-05-28 Published:2020-05-28

摘要/Abstract

摘要： 土地利用变化是一个长期的过程,同时具有一定的复杂性。传统的转移矩阵方法只能在两期土地利用数据之间相互比较而不能总结长期整体的变化规律,频繁项集不能导出变化序列。针对这些方法的不足,本文提出了基于序列模式的土地利用变化序列分析模型。首先给出土地序列数据库的定义,然后根据土地序列数据实际特点和垂直格式的序列模式SPADE算法,给出土地变化序列模式的计算过程和方法。在以中国广西为实例的研究中,计算了1970s—2015年共7期22种二级土地利用类型的变化序列。研究区土地利用变化主要发生在林地之间,部分林地转换为厂矿、采石场、交通道路等建设用地类型;城镇用地主要由旱地和水田转换而来;在研究期内没有任何一个土地单元转化成水田。

关键词: 土地利用变化, 序列模式, 长期变化, 广西, SPADE算法

Abstract: Land use change is a long-term process with certain complexity. The traditional transfer matrix method can only compare the two phases of land use data, but cannot summarize the long-term overall change law. The frequent itemsets method cannot derive the sequence trajectory. To overcome the shortcomings of these methods, this paper proposes a land use change model based on sequence model. According to the actual characteristics of land sequence data and the vertical format sequence pattern SPADE algorithm, taking Guangxi, China as an example, we calculated the sequence of 22 secondary land use types in 7 periods from 1970s to 2015. The results show that, in the 35 years, land use types changed in 6.58% of Guangxi, and the change areas were mainly concentrated in roads, towns and settlements; the top 3 types of land use change 1-sequence support degree in Guangxi are {wood land}, {other wood land} and {sparse forest land}, and the support degree values are 0.5109, 0.3810 and 0.2333, respectively. The top 3 types of the 2-sequence support degree are {wood land, other wood land}, {other wood land, wood land} and {sparse forest land, wood land}, and the support degree values are 0.2040, 0.0699 and 0.0640, respectively. The top 3 types of the 3-sequence support degree are {sparse forest land, other wood land, wood land}, {sparse forest land, wood land, other wood land} and {high coverage grassland, wood land, other wood land}, and the support degree values are 0.0065, 0.0044 and 0.0031, respectively. The land use change 3-sequence {with forest land, other woodland, and other construction sites} has a support degree of 0.0007. The land use change in the study area mainly occurs in forest land, and some forest land is converted into construction land types such as mines, quarries and traffic roads; urban land is mainly converted from dry land and paddy fields; there is no land unit converted into paddy fields during the study period. The land use change sequence analysis model proposed in this paper can calculate the sequence of multi-period land use change as a whole, and make up for the shortcomings of studying land use change from a long-term scale.

Key words: land use change, SPADE algorithm, long term change, sequence model, Guangxi

廖伟华, 聂鑫, 蒋卫国. 基于序列模式的土地利用变化分析——以广西壮族自治区为例[J]. 自然资源学报, 2020, 35(5): 1160-1171.

LIAO Wei-hua, NIE Xin, JIANG Wei-guo. Analysis of land use change based on sequence model: Taking Guangxi Zhuang Autonomous Region as an example[J]. JOURNAL OF NATURAL RESOURCES, 2020, 35(5): 1160-1171.

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基于序列模式的土地利用变化分析——以广西壮族自治区为例

Analysis of land use change based on sequence model: Taking Guangxi Zhuang Autonomous Region as an example

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