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Application of landscape metrics and a Markov chain model to assess land cover changes within a forested watershed, Taiwan
Analysis of land cover changes is fundamental for providing information about watershed land management, monitoring, and planning. This study reveals large‐scale land cover transformation under the effects of frequent natural disturbances within the Taimali watershed in eastern Taiwan during 2005–20...
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Published in: | Hydrological processes 2015-11, Vol.29 (24), p.5031-5043 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Analysis of land cover changes is fundamental for providing information about watershed land management, monitoring, and planning. This study reveals large‐scale land cover transformation under the effects of frequent natural disturbances within the Taimali watershed in eastern Taiwan during 2005–2011. A landscape analysis approach combining landscape metrics and a Markov chain model is used to understand land cover changes with regard to natural disturbances. Results of the composition metrics analysis show that the landslide area within the region has expanded 7.5 times (15.5 km²), but the forested area has shrunk by 10.6% (20.9 km²). Spatial configuration metrics analysis indicates that patches of forest are becoming small, irregular, and spatially fragmented, while landslide patches are expanding and becoming spatially aggregated. Land cover changes in the area are considered to have occurred mainly through loss and fragmentation of forest cover, and an increase in the number and area of landslides. During 2005–2011, the most noticeable area changes related to transitions from forest cover to landslides (15.8 km²) and channels (6.7 km²). However, the greatest transition probabilities were for human‐made patches changing into forest cover and channel corridors over the study period. Through the Markov chain analysis, three projected proportions of land cover for the periods 2017–2035 are produced. These three predictive scenarios pose different risks to downstream life and property. |
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ISSN: | 0885-6087 1099-1085 |
DOI: | 10.1002/hyp.10542 |