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

Zhu, Bin; Liao, Jingjuan; Shen, Guozhuang

doi:10.3390/rs13204059

Cited by 7 publications

(4 citation statements)

References 78 publications

(102 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This mapping is scenario-based, resulting in a well-developed quantification 92 . Extraction of mangrove information for high accuracy, via optimizing the images used by integrating the results of spectroradiometer measurements and medium resolution, remains essential 93 . In this regard, further research related to the analysis of ecosystem services in mangrove ecosystems is warranted to assess the balance of ecosystem services between beneficiaries (humans) and mangrove resources.…”

Section: Discussionmentioning

confidence: 99%

“…92 Extraction of mangrove information for high accuracy, via optimizing the images used by integrating the results of spectroradiometer measurements and medium resolution, remains essential. 93 In this regard, further research related to the analysis of ecosystem services in mangrove ecosystems is warranted to assess the balance of ecosystem services between beneficiaries (humans) and mangrove resources. This analysis involves several aspects related to mangrove management, which is often known as community-based management.…”

Section: Best Model For Mangrove Species Classificationmentioning

confidence: 99%

See 1 more Smart Citation

Mangrove ecosystem species mapping from integrated Sentinel-2 imagery and field spectral data using random forest algorithm

Simarmata,

Wikantika,

Darmawan

et al. 2024

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

Mangroves maintain coastal balance and have the greatest potential for carbon sequestration. Most mapping studies on mangroves have focused on their extent and distribution and rarely featured mangrove species. Therefore, the objective of our study is to investigate mangrove species mapping from integrated Sentinel-2 imagery and field spectral data using a random forest (RF) algorithm. Study areas are located in East and South Lampung, Indonesia. The field samples used represented 144 points of mangrove species. The classification method used an RF algorithm and four models with varying parameters: model 1 with Sentinel-2; model 2 with both Sentinel-2 and field spectral data; model 3 with Sentinel-2, field spectral data, and spectrally transformed data; and model 4 only with spectrally transformed data. The results showed that Rhizophora mucronata, Sonneratia alba, Avicennia lanata, and Avicennia marina were the most common mangrove species in these areas, with reflectance values in the range of 0.002 to 0.493, 0.006 to 0.833, 0.014 to 0.768, and 0.002 to 0.758. Permutation importance (PI) that affects the classification model is the red band, near-infrared, and green normalized difference vegetation index, where the most PI in model 3 is 0.283. The highest level of agreement for mangrove species is found in model 3. Model 3 is the best parameter for RF classification that showed the best mapping accuracy, with the overall accuracy, user accuracy, producer accuracy, and kappa value being 81.25%, 81.68%, 81.25%, and 0.80, respectively.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Best Model For Mangrove Species Classificationmentioning

confidence: 99%

Mangrove ecosystem species mapping from integrated Sentinel-2 imagery and field spectral data using random forest algorithm

Simarmata,

Wikantika,

Darmawan

et al. 2024

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

show abstract

“…The Qinglangang Nature Mangrove Reserve is situated in Wenchang, on the east coast of Hainan Province, China. This reserve accommodates the largest number of man-grove species [28] and the largest area of seagrass in China [29], with a certain amount of coral reef [30], making it a rare continuum of mangrove, seagrass meadow and coral reef habitats within the country [31]. In recent years, these three habitats have suffered degradation to varying degrees [30,32,33] due to human activities such as marine pollution and land reclamation and natural causes such as typhoons.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity of Fish Taxonomic and Functional Diversity Evaluated by eDNA and Gillnet along a Mangrove–Seagrass–Coral Reef Continuum

Qiu

Ooi

Chen

et al. 2023

Animals

View full text Add to dashboard Cite

The effective and reliable monitoring of fish communities is important for the management and protection of marine ecosystems. Environmental DNA (eDNA) metabarcoding is a relatively new method that has been widely used in recent years, while traditional sampling via fish catching (i.e., gillnets) is one of the most common and reliable fish monitoring methods used to date. We compared the taxonomic and functional diversity of fish detected within a mangrove–seagrass–coral reef continuum using both survey methods. One liter seawater and gillnet samples were collected in August 2021 from mangrove forests, seagrass meadows and coral reef habitats (n = 3 each) in Hainan, China. Surveys using eDNA and gillnets identified 139 genera belonging to 66 families and 58 genera belonging to 42 families, respectively. Regardless of the survey method, fish detected in mangrove, seagrass and coral reef habitats were heterogeneous in their communities; however, the shared species between habitats suggest some degree of connectivity. There were no significant differences between habitats in terms of taxonomic and functional diversity, but a higher taxonomic diversity was detected using eDNA. Both methods were able to distinguish fish assemblages between different habitats; however, gillnet surveys performed better than eDNA surveys for distinguishing mangrove from seagrass assemblages. Therefore, the concurrent use of eDNA and gillnet survey methods provides a more comprehensive approach to understanding the heterogeneity of fish taxonomic and functional diversity along mangrove–seagrass–coral reef continuums.

show abstract

“…Protection and expansion of mangrove forests: Mangrove forests provide significant coastal protection and sequester large amounts of carbon. Protecting and expanding these ecosystems can offer a dual benefit of adaptation and mitigation [124][125][126].…”

mentioning

confidence: 99%

Climate Adaptation Measures for Enhancing Urban Resilience

Rezvani,

de Almeida,

Falcão

2023

Buildings

View full text Add to dashboard Cite

Climate change threatens urban areas globally. Enhancing resilience is crucial, yet the comprehensive clustering of practical climate adaptation measures for use in construction industry decision-making is notably absent. This study investigates and categorizes various climate adaptation measures, justifying each through a lens of risk management, asset management, and previous scientific work. It takes advantage of the innovative digital platform Netobra, which offers an ecosystem for the construction industry, to provide real-world, practical implications of these measures. Informed by the Urban Resilience Evaluation System, ISO 31000 (risk management), and ISO 55000 (asset management), the study sets out to demonstrate the value of these measures in bolstering urban resilience and improving decision-making in the construction industry. Moreover, the study integrates a hotspot detection mechanism for areas at high risk of climate impacts, using multicriteria decision analysis (MCDA)—analytic hierarchy process (AHP) mapping on Netobra. These identified hotspots and corresponding climate adaptation measures will further be incorporated into a Risk-Informed Asset-Centric (RIACT) process, providing valuable insights for climate change mitigation and adaptation strategies in urban development. Through its in-depth analysis, the study aims to contribute to the understanding of how diverse climate adaptation measures can be practically applied in various sectors, thereby enhancing urban resilience and effective risk and asset management.

show abstract

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

Cited by 7 publications

References 78 publications

Mangrove ecosystem species mapping from integrated Sentinel-2 imagery and field spectral data using random forest algorithm

Mangrove ecosystem species mapping from integrated Sentinel-2 imagery and field spectral data using random forest algorithm

Heterogeneity of Fish Taxonomic and Functional Diversity Evaluated by eDNA and Gillnet along a Mangrove–Seagrass–Coral Reef Continuum

Climate Adaptation Measures for Enhancing Urban Resilience

Contact Info

Product

Resources

About