Recent Advancement in Mangrove Forests Mapping and Monitoring of the World Using Earth Observation Satellite Data

Giri, Chandra

doi:10.3390/rs13040563

Cited by 32 publications

(17 citation statements)

References 13 publications

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“…Remote sensing technology allows monitoring of mangrove forests to be faster, more efficient, and with a broader scope than with conventional methods [86]. Remote sensing has been used to identify attributes such as biomass [87][88][89], carbon stocks [90,91], species [92][93][94][95], and mangrove health [96][97][98].…”

Section: Mangrove Extentmentioning

confidence: 99%

Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Nguyen

Hardy

Le³

et al. 2021

Forests

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Mangrove forests can ameliorate the impacts of typhoons and storms, but their extent is threatened by coastal development. The northern coast of Vietnam is especially vulnerable as typhoons frequently hit it during the monsoon season. However, temporal change information in mangrove cover distribution in this region is incomplete. Therefore, this study was undertaken to detect change in the spatial distribution of mangroves in Thanh Hoa and Nghe An provinces and identify reasons for the cover change. Landsat satellite images from 1973 to 2020 were analyzed using the NDVI method combined with visual interpretation to detect mangrove area change. Six LULC classes were categorized: mangrove forest, other forests, aquaculture, other land use, mudflat, and water. The mangrove cover in Nghe An province was estimated to be 66.5 ha in 1973 and increased to 323.0 ha in 2020. Mangrove cover in Thanh Hoa province was 366.1 ha in 1973, decreased to 61.7 ha in 1995, and rose to 791.1 ha in 2020. Aquaculture was the main reason for the loss of mangroves in both provinces. Overall, the percentage of mangrove loss from aquaculture was 42.5% for Nghe An province and 60.1% for Thanh Hoa province. Mangrove restoration efforts have contributed significantly to mangrove cover, with more than 1300 ha being planted by 2020. This study reveals that improving mangrove restoration success remains a challenge for these provinces, and further refinement of engineering techniques is needed to improve restoration outcomes.

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Section: Mangrove Extentmentioning

confidence: 99%

Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Nguyen

Hardy

Le³

et al. 2021

Forests

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“…Remote sensing technology offers scientists and major planners to have alternative options of strategies in the management of talent natural resources and environment (Kuenzer et al, 2011;Hu et al, 2020). The use of remote sensing techniques offers the cost and time effectiveness in conducting large-scale mangrove biomass assessments (Kovacs et al, 2010;Giri, 2016;Castillo et al, 2017;Cissell et al, 2018;Giri, 2021). For this reason, the relationships between field-measured biomass data and remote sensing data are assessed and used to develop a model that allows predicting mangrove biomass of different locations of the study sites.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Above-Ground Mangrove Biomass Using Landsat-8 Data- Derived Vegetation Indices: A Case Study in Quang Ninh Province, Vietnam

Nguyen

Röder

2021

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This study aimed to map the status of mangrove forests over the coasts of Hai Ha District and Mong Cai City in Quang Ninh Province by using 2019 Landsat-8 imagery. It then developed the AGB estimation model of mangrove forests based on the AGB estimation-derived plots inventory and vegetation indices-derived from Landsat-8 data. As results, there were five land covers identified, including mangrove forests, other vegetation, wetlands, built-up, and water, with the overall accuracy assessments of 80.0% and Kappa coefficient of 0.74. The total extent of mangrove forests was estimated at 4291.2 ha. The best AGB estimation model that was selected to estimate the AGB and AGC of mangrove forests for the whole coasts of Hai Ha District and Mong Cai City is AGB= 30.38 + 911.95*SAVI (R2=0.924, PValue <0.001). The model validation assessment has confirmed that the selected AGB model can be applied to Hai Ha and Mong Cai coasts with the mean difference between AGB observed and AGB predicted at 16.0 %. This satisfactory AGB model also suggests a good potential for AGB and AGC mapping, which offer the carbon trading market in the study site. As the AGB model selected, the total AGB and AGC of mangrove forests were estimated at about 14,600,000 tons and 6,868,076 tons with a range of from 94.0 - 432.0 tons ha-1, from 44.2 - 203.02 tons ha-1, respectively. It also suggests that the newly-developed AGB model of mangrove forests can be used to estimate AGC stocks and carbon sequestration of mangrove forests for C-PFES in over the coasts of Hai Ha District and Mong Cai City, which is a very importantly financial source for mangrove forest managers, in particular for local mangrove protectors.

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“…Mangrove forests are important woody plant communities that grow in the intertidal zone between land and sea. They are widely distributed in tropical and subtropical regions of the world between 30 • N and 30 • S latitude [1]. Mangrove forests can sequestrate carbon, mitigate climate change, maintain marine and land biodiversity, purify water, protect coastlines and coastal infrastructure and export economic products, thus providing important social, ecological and economic services for surrounding areas [2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…If the loss rate of mangrove forests continues, about 40% of the world's mangrove forests will completely disappear by the end of this century. The services and products provided by mangrove forests will be significantly reduced or lost, which will have a negative impact on human survival and development [1]. Therefore, the protection of mangrove forests is urgent and has reached a broad international consensus.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Simulation of Mangrove Forests under Different Scenarios: A Case Study of Mangrove Protected Areas, Hainan Island, China

2021

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Mangrove forests are important woody plant communities that grow in the intertidal zone between land and sea. They provide important social, ecological and economic services to coastal areas. In recent years, the growth environment of mangrove forests has been threatened. Mangrove forests have become one of the most endangered ecosystems in the world. To better protect mangrove forests, effective monitoring methods are essential. In this study, a spatio-temporal simulation method for mangrove forests was proposed in the mangrove protected areas of Hainan Island, China. This method compared the simulation accuracy of different models in terms of spatial characteristics, evaluated the applicability of driving factors in mangrove simulation and predicted the future spatio-temporal distribution and change trends of mangrove forests under different scenarios. The simulation results of different models showed that AutoRF (random forest with spatial autocorrelation) performs best in spatial characteristic simulation. Driving factors such as the Enhanced Vegetation Index (EVI), various location indices and the spatial autocorrelation factor can significantly improve the accuracy of mangrove simulations. The prediction results for Hainan Island showed that the mangrove area increased slowly under a natural growth scenario (NGS), decreased significantly under an economic development scenario (EDS) and increased significantly under a mangrove protection scenario (MPS) with 4460, 2704 and 5456 ha respectively by 2037. The contraction of mangrove forests is closely related to the expansion of aquaculture ponds, building land and cultivated land. Mangrove contraction is more severe in marginal or fragmented areas. The expansion of mangrove forests is due to the contraction of aquaculture ponds, cultivated land and other forests. The areas around existing mangrove forests and on both sides of the riverbank are typical areas prone to mangrove expansion. The MPS should be the most suitable development direction for the future, as it can reasonably balance economic development with mangrove protection.

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Recent Advancement in Mangrove Forests Mapping and Monitoring of the World Using Earth Observation Satellite Data

Abstract: Mangrove forests are distributed in the inter-tidal region between the sea and the land in the tropical and subtropical regions of the world largely between 30° N and 30° S latitude [...]

Cited by 32 publications

References 13 publications

Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Estimation of Above-Ground Mangrove Biomass Using Landsat-8 Data- Derived Vegetation Indices: A Case Study in Quang Ninh Province, Vietnam

Spatio-Temporal Simulation of Mangrove Forests under Different Scenarios: A Case Study of Mangrove Protected Areas, Hainan Island, China

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