基于Logistic-CA-Markov模型的石漠化空间变化规律研究

马士彬; 张勇荣; 安裕伦

doi:10.11932/karst20150608

基于Logistic-CA-Markov模型的石漠化空间变化规律研究

doi: 10.11932/karst20150608

1.
六盘水师范学院环境与资源科学系/贵州师范大学地理与环境科学学院/贵州省山地资源与环境遥感应用重点实验室
2.
六盘水师范学院环境与资源科学系
3.
贵州师范大学地理与环境科学学院/贵州省山地资源与环境遥感应用重点实验室

基金项目: 贵州省科学技术基金项目（黔科合J字[2012]2309号）；国家自然科学基金项目（41161002）；贵州省科技合作计划项目（黔科合LH字[2015]7610号）

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出版历程
- 发布日期: 2015-12-25

Spatial evolution simulation of karst rocky desertification based on Logistic-CA-Markov models

1.
Department of Environmental and Resources Sciences, Liupanshui Normal University, Liupanshui/School of Geographic and Environmental Sciences, Guizhou Normal University/Guizhou Mountain Resources and Environmental Remote Sensing Application Laboratory
2.
Department of Environmental and Resources Sciences, Liupanshui Normal University, Liupanshui
3.
School of Geographic and Environmental Sciences, Guizhou Normal University/Guizhou Mountain Resources and Environmental Remote Sensing Application Laboratory

摘要

摘要: 为了揭示岩溶地区石漠化发生、发展的一般规律，文章以贵州省六枝特区为例，获取了1990、2000、2010年石漠化数据。利用Logistic-CA-Markov模型探讨石漠化发生的驱动因子及各类型间的转移情况，并在两种情景模式下对研究区2020年石漠化空间分布进行模拟。结果表明：（1）利用Logistic模型回归分析石漠化驱动因子，能够较好的反映其分布状况，CA-Markov耦合模型模拟石漠化空间分布，精度达到理论要求。（2)无石漠化、潜在石漠化、轻度石漠化、中度石漠化演变过程中受人为因素影响大于自然因素，而强度和极强度石漠化则相反。（3）在现有石漠化演化速率情景下，各等级石漠化的演变轨迹为修复与恶化并存模式，最突出的是潜在和轻度石漠化。（4）在喀斯特山地生态产业修复和封山育林结合情景下，石漠化修复与恶化并存的双重轨迹模式改为以修复为主的单一轨迹模式，其中轻度和中度石漠化治理效果最为突出。因此石漠化治理措施重点应针对轻度和中度石漠化分布区，注重协调人地矛盾，防止利用过程中返回式演变。
- 喀斯特 /
- 石漠化 /
- 元胞自动机 /
- 马尔科夫 /
- 空间演变
Abstract: In order to reveal the occurrence and evolution of rocky desertification in karst area, the rocky desertification data in 1990, 2000 and 2010 were obtained from the study area: Liuzhi, Guizhou Province. The driving factors and the transformation between all the types of the rocky desertification were assessed by using Logistic-CA-Markov models. The spatial distribution of the rocky desertification in 2020 was simulated in two scenarios. The results show that firstly using regression analysis of Logistic model to analyse the driving factors well reflects the probability distribution of the factors, while the result of CA-Markov coupling model can reflect the complexity and randomness of spatial variation of the regional rocky desertification. Secondly,except for the extremely strong rocky desertification, topography and land use types greatly influence on the development of various types of rocky desertification. Therefore, the occurrence and distribution of rocky desertification is strongly dependent on topographic features and result of different land uses. Thirdly, for scenarioⅠwhere a rocky desertification rate is as quick as currently observed, both environmental restoration and deterioration meanwhile occur in the areas with moderately, lightly and potentially rocky desertification. For scenarioⅡ(areas with eco-reconstruction and land reforestation), the trend of environmental restoration becomes predominant, in which the effect of lightly and moderately rocky desertification controls are noticeable. Accordingly, it is suggested that the key regions for desertification control should focus on the areas with lightly and moderately rocky desertifications;and the effective control measures should be complete reforestation in moderately rocky desertification areas.In the meantime, more attentions need to be paid to coordinating human-land conflict to avoid the deterioration of eco-environment in case of land use in rocky desertification areas.
- karst /
- rocky desertification /
- cellular automaton /
- Markov /
- spatial evolution

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