Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China
Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982...
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MDPI AG
2021-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/1/15 |
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| author | Peng Xue Huiyu Liu Mingyang Zhang Haibo Gong Li Cao |
| author_facet | Peng Xue Huiyu Liu Mingyang Zhang Haibo Gong Li Cao |
| author_sort | Peng Xue |
| collection | DOAJ |
| description | Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes. |
| first_indexed | 2024-03-10T03:23:49Z |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-10T03:23:49Z |
| publishDate | 2021-12-01 |
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| series | Remote Sensing |
| spelling | doaj.art-28a4b95bb4b94278b4b91db0bfa469922023-11-23T12:11:48ZengMDPI AGRemote Sensing2072-42922021-12-011411510.3390/rs14010015Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast ChinaPeng Xue0Huiyu Liu1Mingyang Zhang2Haibo Gong3Li Cao4Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, ChinaJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, ChinaJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, ChinaJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, ChinaMonitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.https://www.mdpi.com/2072-4292/14/1/15net primary productivity (NPP)multiple time scalesnonlinear trendvegetation type dynamicsEEMD method |
| spellingShingle | Peng Xue Huiyu Liu Mingyang Zhang Haibo Gong Li Cao Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China Remote Sensing net primary productivity (NPP) multiple time scales nonlinear trend vegetation type dynamics EEMD method |
| title | Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China |
| title_full | Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China |
| title_fullStr | Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China |
| title_full_unstemmed | Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China |
| title_short | Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China |
| title_sort | nonlinear characteristics of npp based on ensemble empirical mode decomposition from 1982 to 2015 a case study of six coastal provinces in southeast china |
| topic | net primary productivity (NPP) multiple time scales nonlinear trend vegetation type dynamics EEMD method |
| url | https://www.mdpi.com/2072-4292/14/1/15 |
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