三峡库区空间管理决策优化:生态效应评估与情景模拟

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"论文研究-Integrating Ecological Effects Assessment and Scenario-Based Simulation to Optimize Spatial Management Decisions: a Case Study of Three Gorges Reservoir Area" 这篇论文主要探讨了如何将生态效益评估与情景模拟结合起来,以优化空间管理决策,特别以三峡库区为例进行了深入研究。作者团队包括刘明皓、冯源和袁敏等,他们来自重庆邮电大学计算机科学与技术学院和空间信息系统研究中心,并得到了多项科研基金的支持。 文章首先强调了揭示土地利用覆被变化时空演变规律以及辨识生态安全对于土地可持续发展的重要性。通过对土地利用和覆盖变化(LUCC)的深入研究,可以了解人类活动与自然环境之间的相互作用,为制定更合理的土地管理政策提供依据。 论文中提到了使用DYNA-CLUE软件进行城乡用地动态模拟。DYNA-CLUE(Dyna-Clustering and Land Use Evolution)是一种动态土地利用模型,它能够模拟土地利用的未来发展趋势,基于当前的土地利用情况和一系列驱动因素(如人口增长、经济发展等),预测不同情景下的土地变化模式。 论文构建了三种不同的发展情景:低速发展、惯性发展和快速发展,以此来分析不同情景下三峡库区的生态效应。低速发展可能反映较为保守的政策,侧重于生态保护;惯性发展则假设土地利用将继续沿袭现有趋势;快速发展则考虑了经济快速增长对土地利用的影响。通过比较这些情景下的生态效益,可以为决策者提供关于最优土地管理策略的依据。 在情景模拟过程中,论文可能涉及了生态足迹分析、生物多样性评估、生态系统服务价值计算等生态效益评估方法。这些方法可以帮助量化不同土地利用方式对环境的影响,比如碳排放、水源保护、土壤保持等。 此外,论文还可能探讨了政策干预的可能性,例如设立保护区、实施土地整理项目或调整土地利用结构,以期在经济发展和生态保护之间找到平衡点。这些干预措施的实施效果可以通过模拟结果进行评估。 这篇论文结合了计算机技术,特别是GIS(地理信息系统)和动态模型,为优化空间管理决策提供了科学依据。其研究成果对于类似地区的土地规划和可持续发展具有很高的参考价值。

The LULC simulation data we utilized to create future EN maps was produced by X. Liu et al. (2017), which was conducted at the national level. The reason we apply national-level simulated data to a local area is as follows. Firstly, China has a top-down land use planning system (also known as spatial planning) with five levels. The quantitative objectives in national plans are handed down to county-level plans through provincial and prefectural level plans (Zhong et al., 2014). That means land use patterns of nine cities in WUA are required to reflect relevant upper-level plans, for example, to satisfy the land use quota made by Hubei provincial plans and the national plans. Secondly, there are interdependencies across places so what happens in one region produces effects not only on this location but on other regions (Overman et al., 2010). And the increase of construction land in one place will shift protection pressure on natural ecosystems elsewhere for a sustainable goal. The land use simulation at the national level allocated land resources from a top-down perspective and links land use changes in a region to events taking place in other locations through global simulation. However, the Kappa coefficient of the simulated data in WUA is 0.55 and the overall accuracy is 0.71, which is lower than the statistic value at the national-level data. Although the Kappa between 0.4~0.6 is moderate and at an acceptable level (Appiah et al., 2015; Ding et al., 2013; Ku, 2016), the simulated accuracy of the land use data needs to be improved. Future work on exploring the impact of LULC dynamics on EN will develop based on the high-accuracy simulated data and updating the initial simulated time to 2020, by integrating the impacts of socioeconomic factors, climate change, regional planning, land use policy, etc.

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