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A New Global Land-Use and Land-Cover Change Product at a 1-km Resolution for 2010 to 2100 Based on Human-Environment Interactions

机译:新的全球土地利用和陆地覆盖产品,以1公里的2010年至2100分辨率为基于人类环境互动

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Global land-use and land-cover change (LUCC) data are crucial for modeling a wide range of environmental conditions. So far, access to high-resolution LUCC products at a global scale for public use is difficult because of data and technical issues. This article presents a Future Land-Use Simulation (FLUS) system to simulate global LUCC in relation to human-environment interactions, which is built and verified by using remote sensing data. IMAGE has been widely used in environmental studies despite its relatively coarse spatial resolution of 30 arc-min, which is about 55 km at the equator. Recently, an improved model has been developed to simulate global LUCC with a 5-min resolution (about 10 km at the equator).We found that even the 10-km resolution, however, still produced major distortions in land-use patterns, leading urban land areas to be underestimated by 19.77 percent at the global scale and global land change relating to urban growth to be underestimated by 60 to 97 percent, compared with the 1-km resolution model proposed through this article. These distortions occurred because a large percentage of small areas of urban land was merged into other landuse classes. During land-use change simulation, a majority of small urban clusters were also lost using the IMAGE product. Responding to these deficiencies, the 1-km FLUS product developed in this study is able to provide the spatial detail necessary to identify spatial heterogeneous land-use patterns at a global scale. We argue that this new global land-use product has strong potential in radically reducing uncertainty in global environmental modeling.
机译:全球土地利用和陆地覆盖变化(LUCC)数据对于建模各种环境条件至关重要。到目前为止,由于数据和技术问题,可以获得全球公共使用量表的高分辨率Lucc产品。本文介绍了未来的土地利用仿真(FLU)系统,以模拟全球LUCC与人类环境相互作用,通过使用遥感数据构建和验证。尽管其相对粗糙的空间分辨率为30弧分钟,但在环境研究中已广泛用于环境研究中,赤道约为55公里。最近,已经开发了一种改进的模型来模拟全球LUCC,分辨率为5分钟(赤道约10公里)。我们发现即使是10公里的分辨率,也仍然在土地使用模式中产生了重大扭曲,导致与本文提出的1公里的解决方案相比,全球规模和城市增长的全球土地变化有关的全球范围和全球土地变化,与城市成长有关的全球土地变化。这些扭曲发生,因为大量的城市土地的大部分是合并到其他土地使用的课程。在土地利用变化模拟期间,使用图像产品也丢失了大多数小城区。响应这些缺陷,本研究中开发的1公里的FLUS产品能够在全球范围内提供识别空间异构土地使用模式所需的空间细节。我们认为,这种新的全球土地利用产品在彻底减少全球环境建模中的不确定性方面具有很强的潜力。

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