生态环境学报 ›› 2021, Vol. 30 ›› Issue (7): 1522-1531.DOI: 10.16258/j.cnki.1674-5906.2021.07.021

• 研究论文 • 上一篇    下一篇

基于CA-Markov多情景模拟的海南岛土地利用变化及其生态环境效应

刘强1,2(), 杨众养3,4, 陈毅青3,4,*(), 雷金睿3,4, 陈宗铸3,4, 陈小花3,4   

  1. 1.海南热带雨林国家公园管理局,海南 海口 570100
    2.国家林业和草原局华东调查规划设计院,浙江 杭州 310019
    3.海南省林业科学研究院(海南省红树林研究院),海南 海口 571100
    4.海南省热带林业资源监测与应用重点实验室,海南 海口 571100
  • 收稿日期:2021-02-24 出版日期:2021-07-18 发布日期:2021-10-09
  • 通讯作者: *陈毅青(1975年生),男,高级工程师,硕士,研究方向为森林生态。E-mail: 13876350188@126.com
  • 作者简介:刘强(1969年生),男,高级工程师,研究方向为森林生态与资源监测管理。E-mail: 2568060444@qq.com
  • 基金资助:
    海南省财政科技计划项目(jcxk202003);海南省财政科技计划项目(jscx202024)

Multi-scenario Simulation of Land Use Change and Its Eco-environmental Effect in Hainan Island Based on CA-Markov Model

LIU Qiang1,2(), YANG Zhongyang3,4, CHEN Yiqing3,4,*(), LEI Jinrui3,4, CHEN Zongzhu3,4, CHEN Xiaohua3,4   

  1. 1. Administration of Hainan Tropical Rainforest National Park, Haikou 570100, China
    2. East China Inventory and Planning Institute, National Forestry and Grassland Administration, Hangzhou 310019, China
    3. Hainan Academy of Forestry (Hainan Academy of Mangrove), Haikou 571100, China
    4. Key Laboratory of Tropical Forestry Resources Monitoring and Application of Hainan Province, Haikou 571100, China
  • Received:2021-02-24 Online:2021-07-18 Published:2021-10-09

摘要:

以海南岛为研究区域,基于2010年和2020年两期土地利用数据,利用 CA-Markov模型预测了3种模拟情景下2030年和2040年土地利用空间分布格局,定量分析了海南岛2010—2040年土地利用变化及其生态环境效应。结果表明,(1)2010—2020年间,海南岛土地利用类型以林地为主,面积占比达62%以上,其次耕地。该时期土地利用类型转移的主要特征是林地、耕地、水域转为建设用地,建设用地面积增加483.55 km2,增长率高达53.27%。(2)利用CA-Markov模型模拟3种情景下海南岛2030年和2040年的建设用地均呈现较大幅度的增长,其中耕地保护情景模拟下的耕地面积最多,生态保护情景模拟下的林地和水域面积有所增加。(3)海南岛生态环境质量呈现出中部高、四周低的阶梯式空间分布格局,2010—2040年间海南岛生态环境质量逐期降低,由2010年的0.6064下降至2040年的0.5878。在3种模拟情景中,生态保护情景下的海南岛生态环境质量最高,其次是耕地保护情景,基准情景最差。(4)2010—2040年间,林地转为建设用地是导致海南岛生态环境质量恶化的主要类型和主导因素,耕地转为林地则是致使未来生态环境质量改善的主要土地利用变化类型,生态贡献率超过70%。总体而言,海南岛生态环境质量恶化的趋势大于生态环境质量改善的趋势。

关键词: 生态环境质量, 土地利用转型, CA-Markov, 情景模拟, 时空变化

Abstract:

Based on the land use data of Hainan Island in 2010 and 2020, the spatial distribution patterns of land use in 2030 and 2040 were predicted by using CA-Markov model, and the land use change and eco-environmental effects in Hainan Island in 2010?2040 were quantitatively analyzed. The results showed that, (1) from 2010 to 2020, forest land was the main type of land use in Hainan Island, accounting for more than 62% of the land area, followed by cultivated land. During this period, forest land, cultivated land and water area were converted into construction land, and the area of construction land increased by 483.55 km2, with a growth rate of 53.27%. (2) CA-Markov model was used to simulate the three scenarios, and the area of construction land in Hainan Island showed a significant increase in 2030 and 2040. The cultivated land area was the largest under the cultivated land protection scenario simulation, while the area of forest land and water area increased under the ecological protection scenario simulation. (3) The eco-environmental quality in Hainan Island showed a stepped spatial distribution pattern, namely the central part was high and the surrounding area was low. In 2010?2040, the eco-environmental quality in Hainan Island decreased gradually, from 0.6064 in 2010 to 0.5878 in 2040. Among the three simulation scenarios, the eco-environmental quality in Hainan Island was the highest under the ecological protection scenario, followed by cultivated land protection scenario, and the worst under the baseline scenario. And (4) from 2010 to 2040, the dominant factor causing the deterioration of the eco-environmental quality in Hainan Island was that the conversion of forest land to construction land. The conversion of cultivated land to forest land was the main type of land use change leading to the improvement of the eco-environmental quality in the future, and the ecological contribution rate was more than 70%. In general, the deterioration trend of the eco-environmental quality in Hainan Island was greater than the improvement trend of the eco-environmental quality.

Key words: ecological environment quality, land use transformation, CA-Markov, simulation scenario, spatiotemporal variation

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