Monitoring rapid vegetation succession in estuarine wetland using time series MODIS-based indicators: An application in the Yangtze River Delta area

Zhao, Bin; Yan, Yaner; Guo, Haiqiang; He, Meimei; Gu, Yongjian; Li, Bo

doi:10.1016/j.ecolind.2008.05.009

Cited by 120 publications

(66 citation statements)

References 38 publications

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“…Actually no land use/cover type has shown a noticeable domination over others, except for cumulated four months precipitation where agricultural area shows higher performance in the four stations. The comparison of the four stations shows a difference in coefficient of Pearson within the same land use/cover class; this could be due to several factors, such as difference in soil moisture [14], plant community [36], anthropogenic activities and vegetation phenology [37][38][39]. Correlation is significant at the 0.01 level (2-tailed).…”

Section: Ndvi As Lulc Indicatormentioning

confidence: 99%

“…As mentioned by Li et al [19], estimating vegetation dynamics from NDVI or EVI is not a straightforward achievement. Although in this work quality assessment was done on the MOD13Q1 product to eliminate noises, other factors, such as plant community [36], anthropogenic perturbation, vegetation phenology and sensor conditions [38][39][40], may influence the temporal dynamics of the two indices and their response to rainfall. Figure 5 shows that NDVI and EVI are strongly correlated for all land use/covers with Pearson's coefficient value ranging from 0.976 to 0.984.…”

Section: Evi As Lulc Indicator and Comparative Analysis With Ndvimentioning

confidence: 99%

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Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Zoungrana

Christopher

Amekudzi

et al. 2014

Climate

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Section: Ndvi As Lulc Indicatormentioning

confidence: 99%

Section: Evi As Lulc Indicator and Comparative Analysis With Ndvimentioning

confidence: 99%

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Zoungrana

Christopher

Amekudzi

et al. 2014

Climate

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“…When underlying mechanisms in an ecosystem are known, we have greater clarity about which parameters caused system fragility. For instance, vegetation and water are both the key variables characterizing wetlands [45]. The index that was suggested to provide the most reliable indicator (MVWR) is also a combination of vegetation and water cover information.…”

Section: Discussionmentioning

confidence: 99%

“…It uses the information content of four spectral bands (green, red, NIR and SWIR), and therefore, it potentially contains more information about the wetland's physical status. It has been argued that an index based on combining vegetation and water may reflect a wetland ecosystem functioning more efficiently than either vegetation or water index alone [45]. The new index we propose is based on an existing composite index called the Vegetation Water Ratio (VWR).…”

Section: Spectral Indicesmentioning

confidence: 99%

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Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

et al. 2017

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Abstract:The response of an ecosystem to external drivers may not always be gradual and reversible. Discontinuous and sometimes irreversible changes, called 'regime shifts' or 'critical transitions', can occur. The likelihood of such shifts is expected to increase for a variety of ecosystems, and it is difficult to predict how close an ecosystem is to a critical transition. Recent modelling studies identified indicators of impending regime shifts that can be used to provide early warning signals of a critical transition. The identification of such transitions crucially depends on the ability to monitor key ecosystem variables, and their success may be limited by lack of appropriate data. Moreover, empirical demonstrations of the actual functioning of these indicators in real-world ecosystems are rare. This paper presents the first study which uses remote sensing data to identify a critical transition in a wetland ecosystem. In this study, we argue that a time series of remote sensing data can help to characterize and determine the timing of a critical transition. This can enhance our abilities to detect and anticipate them. We explored the potentials of remotely sensed vegetation (NDVI), water (MNDWI), and vegetation-water (VWR) indices, obtained from time series of MODIS satellite images to characterize the stability of a wetland ecosystem, Dorge Sangi, near the lake Urmia, Iran, that experienced a regime shift recently. In addition, as a control case, we applied the same methods to another wetland ecosystem in Lake Arpi, Armenia which did not experience a regime shift. We propose a new composite index (MVWR) based on combining vegetation and water indices, which can improve the ability to anticipate a critical transition in a wetland ecosystem. Our results revealed that MVWR in combination with autocorrelation at-lag-1 could successfully provide early warning signals for a critical transition in a wetland ecosystem, and showed a significantly improved performance compared to either vegetation (NDVI) or water (MNDWI) indices alone.

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Tracking three decades of land use and land cover transformation trajectories in China's large river deltas

Bai

et al. 2019

Land Degrad Dev

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Large river deltas are characterized by complicated land use/land cover (LULC) dynamics driven by intertwined natural and anthropogenic processes. Understanding spatiotemporal LULC dynamics associated with multiple drivers can help mitigate the adverse ecological impacts resulting from human activities. This research tracked spatiotemporal LULC trajectories in relation to multiple natural and anthropogenic driving processes and explored their correlations within four large river deltas (the Liaohe River Delta [LRD], Yellow River Delta [YRD], Yangtze River Delta [YtRD], and Pearl River Delta [PRD]) in China from 1980 to 2010. The results showed that the coastal wetlands had undergone transformations with 39% in LRD, 85.1% in YRD, 96.5% in YtRD, and 100% in PRD, respectively. The LULC transformations were linked with six major driving processes (accretion, erosion, reclamation, restoration, succession, and regressive succession) and were impacted by complex coupled effects between natural and anthropogenic drivers. Reclamation‐related LULC transformation types dominated in the four river deltas and had greater spatiotemporal interactions than the other driving processes. Reclamation and restoration as well as accretion and erosion showed high positive correlations in all four river deltas, but other pairwise correlations of driving processes presented regional variations. This study presents an overview of the patterns and processes of complex multitemporal LULC dynamics and can be replicated elsewhere in areas where land reclamation activities are entangled with natural processes. A ‘scrolling’ development pattern with reasonable magnitudes of land reclamation for the river deltas is proposed as a spatial strategy to minimize the adverse ecological impacts of human activity.

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Monitoring rapid vegetation succession in estuarine wetland using time series MODIS-based indicators: An application in the Yangtze River Delta area

Cited by 120 publications

References 38 publications

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

Tracking three decades of land use and land cover transformation trajectories in China's large river deltas

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