A method of characterizing land-cover swap changes in the arid zone of China
文献类型:SCI/SSCI论文
作者 | Yuan Y. C.; Li, B. L.; Gao, X. Z.; Liu, H. J.; Xu, L. L.; Zhou, C. H.; Yang J. |
发表日期 | 2016 |
关键词 | land cover swap swap-change status flagged swap-change categories swap-change process arid/semiarid zone horqin sandy land diversity desertification transitions dynamics patterns climate area |
英文摘要 | Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a suite of indices are presented to characterize land-cover swaps that may seriously damage the ecosystem in arid or semiarid zones, based on swap-change areas extracted from remotely sensed images. First, swap percentage of total area and swap intensity of total changes were used to determine the status of land-cover swap change in an area. Then, dominated swap category and individual swap-change intensity for a land-cover category were used to determine flagged land-cover swap-change categories. Finally, swap-change mode and Pielou's index were used to determine the land-cover swap-change processes of dominant categories. A case study is conducted using this approach, based on two land-cover maps in the 1980s and 2000 in Naiman Qi, Tongliao City, Inner Mongolia, China. This study shows that the approach can clearly quantify the severity and flagged classes of land-cover swap-change and reveal their relationship with ecological processes of the ecosystem. These results indicate that the approach can give deep insights into swap change, which can be very valuable to land-cover policy making and management. |
出处 | Frontiers of Earth Science |
卷 | 10 |
期 | 1 |
页 | 74-86 |
收录类别 | SCI |
语种 | 英语 |
ISSN号 | 2095-0195 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/43344] |
专题 | 地理科学与资源研究所_历年回溯文献 |
推荐引用方式 GB/T 7714 | Yuan Y. C.,Li, B. L.,Gao, X. Z.,et al. A method of characterizing land-cover swap changes in the arid zone of China. 2016. |
入库方式: OAI收割
来源:地理科学与资源研究所
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