Mangrove forests mapping using Sentinel-1 and Sentinel-2 satellite images

Sharifi, Alireza; Felegari, Shilan; Tariq, Aqil

doi:10.1007/s12517-022-10867-z

Cited by 17 publications

(7 citation statements)

References 47 publications

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“…SPOT-5 imagery has been used widely in mangrove monitoring studies until the satellites were decommissioned in 2015 such as the works by Valderrama-Landeros et al 58 as reported by Valderrama-Landeros et al 59 and Pham et al 60 and today SPOT-5 archives remain an important tool for historical mapping of ecosystems as presented in this study. Sentinel images are more widely used in mangrove mapping and monitoring studies 61 – 63 as they are more easily accessible and up to date and often perform better in classification compared to other medium resolution images such as Landsat 8 OLI due to their higher spatial resolution 64 . Using SPOT-5 2013 and Sentinel 2A 2023 imagery, it was observed that mangroves cover at both Le Morne and Ferney were distinctly identified on the images due to the particular spectral signature of mangroves largely based on their MSI data.…”

Section: Discussionmentioning

confidence: 99%

Mangrove mapping and monitoring using remote sensing techniques towards climate change resilience

Sunkur,

Kantamaneni,

Bokhoree

et al. 2024

Sci Rep

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Mangroves are amongst the richest ecosystems in the world providing valuable goods and services to millions of people while enhancing the resilience of coastal communities against climate change induced hazards, especially island nations. However, these mangroves are severely affected by many anthropogenic activities. Therefore, understanding the spatial variability of mangroves in island nations is highly essential in the events of ongoing climatic change. Thus, this study assessed the use of remote sensing techniques and GIS to map and monitor mangrove cover change at selected sites, namely Le Morne and Ferney, on the tropical island of Mauritius. Freely available 2013 SPOT-5 and 2023 Sentinel 2A images were retrieved and processed using ArcGIS Pro tools and SNAP; mangroves were mapped based on Google Earth Pro historical imagery and ground truthing at the respective sites. Following the application of selected vegetation indices, GLCM and PCA analysis, mosaicked images were classified using the Random Trees algorithm. Kappa values of all the classified images were in the 90 s; Le Morne showed a significant increase in mangrove cover over the decadal scale with main class change from mudflat to mangroves. This study demonstrates how geo-spatial tools are crucial for monitoring mangroves as they provide spatially explicit and time sensitive information. Decision makers, researchers, and relevant stakeholders can utilize this data to bolster tailored mitigation and adaptation strategies at specific sites, thereby enhancing resilience to climate change.

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Section: Discussionmentioning

confidence: 99%

Mangrove mapping and monitoring using remote sensing techniques towards climate change resilience

Sunkur,

Kantamaneni,

Bokhoree

et al. 2024

Sci Rep

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“…The images were retrieved as surface reflectance from GEE platform and were already processed for atmospheric attenuations and topographic effects (Mpakairi et al, 2022a , 2022b ). To ensure high data quality, cloud-quality filters and a cloud mask were also applied, eliminating potentially cloud-covered or low-quality data and ensuring that only high-quality and cloud-free pixels were used for analysis (Sharifi et al, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Chlorophyll-a unveiled: unlocking reservoir insights through remote sensing in a subtropical reservoir

Mpakairi,

Muthivhi,

Dondofema

et al. 2024

Environ Monit Assess

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Effective water resources management and monitoring are essential amid increasing challenges posed by population growth, industrialization, urbanization, and climate change. Earth observation techniques offer promising opportunities to enhance water resources management and support informed decision-making. This study utilizes Landsat-8 OLI and Sentinel-2 MSI satellite data to estimate chlorophyl-a (chl-a) concentrations in the Nandoni reservoir, Thohoyandou, South Africa. The study estimated chl-a concentrations using random forest models with spectral bands only, spectral indices only (blue difference absorption (BDA), fluorescence line height in the violet region (FLH_violet), and normalized difference chlorophyll index (NDCI)), and combined spectral bands and spectral indices. The results showed that the models using spectral bands from both Landsat-8 OLI and Sentinel-2 MSI performed comparably. The model using Sentinel-2 MSI had a higher accuracy of estimating chl-a when spectral bands alone were used. Sentinel-2 MSI’s additional red-edge spectral bands provided a notable advantage in capturing subtle variations in chl-a concentrations. Lastly, the –chl-a concentration was higher at the edges of the Nandoni reservoir and closer to the reservoir wall. The findings of this study are crucial for improving the management of water reservoirs, enabling proactive decision-making, and supporting sustainable water resource management practices. Ultimately, this research contributes to the broader understanding of the application of earth observation techniques for water resources management, providing valuable information for policymakers and water authorities.

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“…These functions have been considered to play an important role in reducing CO2 levels in the Earth's atmosphere. Carbondioxide (CO2) absorbed during photosynthesis is used for the growth and development of mangrove plants [1,2]. Photosynthesis absorbs CO2 gas from the atmosphere and stores it as organic matter in the form of plant biomass.…”

Section: Introductionmentioning

confidence: 99%

Mapping mangrove above ground carbon stock of benoa bay bali using sentinel-1 satellite imagery

Hidayah,

Utama,

As-Syakur

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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Mangrove forest ecosystems distributed in tropical countries play an important role in carbon sequestration. The presence of mangrove forests is estimated to be capable of reducing CO2 levels caused by air pollution. The process of photosynthesis absorbs CO2 gas from the atmosphere and stores it as organic matter in the form of plant biomass. The amount of carbon stock stored in mangrove forests can be estimated using a regression model based on satellite imagery pixel values and above ground biomass (AGB) measurements. This study used the backscattering value of SAR Sentinel 1 images and field AGB measurements to map carbon stocks in the mangrove forest ecosystem of Benoa Bay, Bali. The processed backscattering value is the result of VV and VH polarization in the SAR Sentinel 1 image acquired in 2022. Meanwhile, AGB is calculated using the allometric equation based on the mangrove’s species found at the study site. The biomass at the study location was estimated to be in the range of 64.18 Mg/Ha to 175.24 Mg/Ha, with an average of 115.34 ± 25.33 Mg/Ha. Therefore, the carbon stock of Benoa Bay can be estimated to have values in the range of 30.16 MgC/Ha to 82.36 MgC/Ha, with an average of 54.21 ± 11.09 MgC/Ha. In terms of estimating AGB biomass based on SAR pixel values, the VH polarization produces a better model (R2 = 0.635) than the VV polarization.

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Mangrove forests mapping using Sentinel-1 and Sentinel-2 satellite images

Cited by 17 publications

References 47 publications

Mangrove mapping and monitoring using remote sensing techniques towards climate change resilience

Mangrove mapping and monitoring using remote sensing techniques towards climate change resilience

Chlorophyll-a unveiled: unlocking reservoir insights through remote sensing in a subtropical reservoir

Mapping mangrove above ground carbon stock of benoa bay bali using sentinel-1 satellite imagery

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