Trends in the Normalized Difference Vegetation Index for Mangrove Areas in Northwestern Mexico

Flores-Cárdenas, Francisco; Millán-Aguilar, Olivia; Díaz-Lara, Luis; Rodríguez-Arredondo, Lidia; Hurtado‐Oliva, Miguel Ángel; Manzano–Sarabia, Marlenne

doi:10.2112/jcoastres-d-17-00022.1

Cited by 13 publications

(11 citation statements)

References 25 publications

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“…To the best of our knowledge, this is the first study that quantifies early forest recovery times in the MMFR using annual Landsat time series. Previous studies on mangrove regeneration have focused on quantifying new mangrove cover [32,33]. Although knowledge of new areas colonized by mangrove is certainly important and required to improve the management of mangrove areas, measurements other than area are required to quantify mangrove regeneration in the MMFR.…”

Section: Time Series Analysismentioning

confidence: 99%

“…Studies on time series analysis have the potential to provide information of the past and current changes of mangrove forests [31][32][33][34][35][36][37]. Time series based on vegetation indices have been used to analyse changes in mangrove cover and phenology [32,33,36]. Nevertheless, the use of these types of time series to quantify the mangrove forest recovery after disturbances is still limited [32,33,35].…”

Section: Introductionmentioning

confidence: 99%

“…Time series based on vegetation indices have been used to analyse changes in mangrove cover and phenology [32,33,36]. Nevertheless, the use of these types of time series to quantify the mangrove forest recovery after disturbances is still limited [32,33,35]. In this study, we focused on the MMFR located in Peninsular Malaysia, as this reserve is silviculturally managed and provides a unique opportunity to establish whether (i) time series of Landsat sensor data could be used to detect the clear-felling events that regularly take place in the reserve, and (ii) the NDMI annual time series could be used to trace back and quantify the early recovery of mangrove forest patches after a clear-felling event.…”

Section: Introductionmentioning

confidence: 99%

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An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

et al. 2019

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Time series of satellite sensor data have been used to quantify mangrove cover changes at regional and global levels. Although mangrove forests have been monitored using remote sensing techniques, the use of time series to quantify the regeneration of these forests still remains limited. In this study, we focus on the Matang Mangrove Forest Reserve (MMFR) located in Peninsular Malaysia, which has been under silvicultural management since 1902 and provided the opportunity to investigate the use of Landsat annual time series (1988–2015) for (i) detecting clear-felling events that take place in the reserve as part of the local management, and (ii) tracing back and quantifying the early regeneration of mangrove forest patches after clear-felling. Clear-felling events were detected for each year using the Normalized Difference Moisture Index (NDMI) derived from single date (cloud-free) or multi-date composites of Landsat sensor data. From this series, we found that the average period for the NDMI to recover to values observed prior to the clear-felling event between 1988 and 2015 was 5.9 ± 2.7 years. The maps created in this study can be used to guide the replantation strategies, the clear-felling planning, and the management and monitoring activities of the MMFR.

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Section: Time Series Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

et al. 2019

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“…Recently, the sensibility and range of mangroves distribution in the Americas were explained by greenness trends (Cavanaugh et al 2018). Other greenness studies on mangrove forests have been site-specific and they have identified land cover changes (Rahman et al 2013), mangrove degradation (Alatorre et al 2016, Ishtiaque et al 2016, Flores-Cárdenas et al 2017, disturbances by chilling events (Zhang et al 2016) and biomass change (Fuller and Wang 2014). Despite these efforts, there is still lacking information at country-specific scale to better understand the influence of climate variability on greenness trends of mangroves and to provide insights for changes in phenology, productivity, and ultimately carbon stocks.…”

Section: Introductionmentioning

confidence: 99%

Greenness trends and carbon stocks of mangroves across Mexico

Vázquez‐Lule

Colditz

Herrera-Silveira³

et al. 2019

Environ. Res. Lett.

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Mangroves cover less than 0.1% of Earth's surface, store large amounts of carbon per unit area, but are threatened by global environmental change. The capacity of mangroves productivity could be characterized by their canopy greenness, but this property has not been systematically tested across gradients of mangrove forests and national scales. Here, we analyzed time series of Normalized Difference Vegetation Index (NDVI), mean air temperature and total precipitation between 2001 and 2015 (14 years) to quantify greenness and climate variability trends for mangroves not directly influenced by land use/land cover change across Mexico. Between 2001 and 2015 persistent mangrove forests covered 432 800 ha, representing 57% of the total current mangrove area for Mexico. We found a temporal greenness increase between 0.003 [0.001-0.004] and 0.004 [0.002-0.005] yr −1 (NDVI values±95%CI) for mangroves located over the Gulf of California and the Pacific Coast, with many mangrove areas dominated by Avicennia germinans. Mangroves developed along the Gulf of Mexico and Caribbean Sea did not show significant greenness trends, but site-specific areas showed significant negative greenness trends. Mangroves with surface water input have above ground carbon stocks (AGC) between 37.7 and 221.9 Mg C ha −1 and soil organic carbon density at 30 cm depth (SOCD) between 92.4 and 127.3 Mg C ha −1 . Mangroves with groundwater water input have AGC of 12.7 Mg C ha −1 and SOCD of 219 Mg C ha −1 . Greenness and climate variability trends could not explain the spatial variability in carbon stocks for most mangrove forests across Mexico. Site-specific characteristics, including mangrove species dominance could have a major influence on greenness trends. Our findings provide a baseline for national-level monitoring programs, carbon accounting models, and insights for greenness trends that could be tested around the world.

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“…On the other hand, lower NDVI values may indicate weaker photosynthetic activity and overall poorer vegetation health, due to likely unfavorable growing conditions (e.g., water stress, exposure to herbicide). The NDVI is typically used as indicator to monitor ecosystem health (e.g., Bento et al 2018;Flores-Cardenas et al 2018;Mariano et al 2018) and crop phenology (e.g., Mashaba et al 2016;Martin and Latheef 2017;Inurreta-Aguirre et al 2018). A number of studies (e.g., Thelen et al 2004;Dicke et al 2012;Lewis et al 2014;Prakash et al 2017) have demonstrated that NDVI is an effective index in detecting herbicide damage on plants.…”

Section: Remote Sensing Datamentioning

confidence: 99%

Remote‐sensing Based Assessment of Long‐term Riparian Vegetation Health in Proximity to Agricultural Lands with Herbicide Use History

Yousef

Gebremichael

Ghebremichael

et al. 2019

Integr Envir Assess & Manag

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Riparian ecosystems provide various ecosystem services including habitat for a variety of plant and animal communities, biofiltering, and stabilizing stream and river systems. Due to their location, riparian zones often share long borders with agricultural fields where herbicides are commonly applied to eliminate unwanted plants. There is a general concern that exposure of riparian vegetation to off‐target drifted herbicides may adversely impact their health and diversity. We utilized the Normalized Difference Vegetation Index (NDVI) to investigate the long‐term (between 1992 and 2011) trend of riparian vegetation health at 17 locations in the Midwest and Great Plains areas of the United States, where herbicide usage was likely most intense. Assessment of NDVI data demonstrated that long‐term vegetation health did not decline for the studied riparian zones located in proximity to croplands during spring months (April and May). During summer (June and July), while the long‐term vegetation health did not decline for the majority of the sites, there were a few cases in Kansas and Nebraska with a decline in vegetation health (negative‐trending NDVI). Cluster analysis of the negative‐trending NDVI pixels showed that the majority of these pixels were randomly distributed throughout these riparian sites, indicating a lack of shared common causing factors. Similarly, proximity analysis suggested that distance from croplands was not associated with the decline of vegetation health found in these sites, suggesting that exposure to herbicide drift may not be a plausible factor because this would have shown higher impact on pixels closer to the cropland. Changes in canopy coverage and vegetation diversity also did not show any dependence on distance from croplands. Finally, the remote‐sensing–based NDVI data sets used provide only an indirect way of assessing the impact of herbicide drift, and therefore, further work based on field survey data is recommended to completely isolate the impacts of herbicides. Integr Environ Assess Manag 2019;15:528–543. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

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Trends in the Normalized Difference Vegetation Index for Mangrove Areas in Northwestern Mexico

Cited by 13 publications

References 25 publications

An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

Greenness trends and carbon stocks of mangroves across Mexico

Remote‐sensing Based Assessment of Long‐term Riparian Vegetation Health in Proximity to Agricultural Lands with Herbicide Use History

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