Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data
The study uses 30 years of the third generation of Advanced Very-High-Resolution Radiometer (AVHRR) NDVI3g monthly data from 1982 to 2012 to identify the natural clusters and important driving factors of the upstream watersheds in Taiwan through hierarchical cluster analysis (HCA) and redundancy ana...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/12/9/1206 |
| _version_ | 1797520226867216384 |
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| author | Hui Ping Tsai Wei-Ying Wong |
| author_facet | Hui Ping Tsai Wei-Ying Wong |
| author_sort | Hui Ping Tsai |
| collection | DOAJ |
| description | The study uses 30 years of the third generation of Advanced Very-High-Resolution Radiometer (AVHRR) NDVI3g monthly data from 1982 to 2012 to identify the natural clusters and important driving factors of the upstream watersheds in Taiwan through hierarchical cluster analysis (HCA) and redundancy analysis (RDA), respectively. Subsequently, as a result of HCA, six clusters were identified based on the 30 years of monthly NDVI data, delineating unique NDVI characteristics of the upstream watersheds. Additionally, based on the RDA results, environmental factors, including precipitation, temperature, slope, and aspect, can explain approximately 52% of the NDVI variance over the entire time series. Among environmental factors, nine factors were identified significantly through RDA analysis for explaining NDVI variance: average slope, temperature, flat slope, northeast-facing slope, rainfall, east-facing slope, southeast-facing slope, west-facing slope, and northwest-facing slope, which reflect an intimate connection between climatic and orthographic factors with vegetation. Furthermore, the rainfall and temperature represent different variations in all scenarios and seasons. With consideration of the characteristics of the clusters and significant environmental factors, corresponding climate change adaptation strategies are proposed for each cluster under climate change scenarios. Thus, the results provide insight to assess the natural clustering of the upstream watersheds in Taiwan, benefitting future sustainable watershed management. |
| first_indexed | 2024-03-10T07:53:47Z |
| format | Article |
| id | doaj.art-034499f8d8294dcd96af05bec29fe50a |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T07:53:47Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-034499f8d8294dcd96af05bec29fe50a2023-11-22T12:00:50ZengMDPI AGAtmosphere2073-44332021-09-01129120610.3390/atmos12091206Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g DataHui Ping Tsai0Wei-Ying Wong1Department of Civil Engineering, National Chung Hsing University, Taichung 40227, TaiwanDepartment of Civil Engineering, National Chung Hsing University, Taichung 40227, TaiwanThe study uses 30 years of the third generation of Advanced Very-High-Resolution Radiometer (AVHRR) NDVI3g monthly data from 1982 to 2012 to identify the natural clusters and important driving factors of the upstream watersheds in Taiwan through hierarchical cluster analysis (HCA) and redundancy analysis (RDA), respectively. Subsequently, as a result of HCA, six clusters were identified based on the 30 years of monthly NDVI data, delineating unique NDVI characteristics of the upstream watersheds. Additionally, based on the RDA results, environmental factors, including precipitation, temperature, slope, and aspect, can explain approximately 52% of the NDVI variance over the entire time series. Among environmental factors, nine factors were identified significantly through RDA analysis for explaining NDVI variance: average slope, temperature, flat slope, northeast-facing slope, rainfall, east-facing slope, southeast-facing slope, west-facing slope, and northwest-facing slope, which reflect an intimate connection between climatic and orthographic factors with vegetation. Furthermore, the rainfall and temperature represent different variations in all scenarios and seasons. With consideration of the characteristics of the clusters and significant environmental factors, corresponding climate change adaptation strategies are proposed for each cluster under climate change scenarios. Thus, the results provide insight to assess the natural clustering of the upstream watersheds in Taiwan, benefitting future sustainable watershed management.https://www.mdpi.com/2073-4433/12/9/1206normalized difference vegetation index (NDVI)clusterupstream watershedsclimate changeadaptation strategy |
| spellingShingle | Hui Ping Tsai Wei-Ying Wong Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data Atmosphere normalized difference vegetation index (NDVI) cluster upstream watersheds climate change adaptation strategy |
| title | Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data |
| title_full | Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data |
| title_fullStr | Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data |
| title_full_unstemmed | Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data |
| title_short | Cluster and Redundancy Analyses of Taiwan Upstream Watersheds Based on Monthly 30 Years AVHRR NDVI3g Data |
| title_sort | cluster and redundancy analyses of taiwan upstream watersheds based on monthly 30 years avhrr ndvi3g data |
| topic | normalized difference vegetation index (NDVI) cluster upstream watersheds climate change adaptation strategy |
| url | https://www.mdpi.com/2073-4433/12/9/1206 |
| work_keys_str_mv | AT huipingtsai clusterandredundancyanalysesoftaiwanupstreamwatershedsbasedonmonthly30yearsavhrrndvi3gdata AT weiyingwong clusterandredundancyanalysesoftaiwanupstreamwatershedsbasedonmonthly30yearsavhrrndvi3gdata |