Estimation of aboveground biomass in mangrove forests using vegetation indices from SPOT-5 image

Muhd-Ekhzarizal, M. E.; Mohdhasmadi, I; Hamdan, O.; Mohamad-Roslan, M. K.; Noor-Shaila, S.

doi:10.26525/jtfs2018.30.2.224233

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…Several methods, which confirmed that remote sensing is possible to estimate mangrove biomass, have been already developed and published. Remote sensing is a great data source facilitating field surveys by avoiding the destructive method and reducing time and cost for field surveys (Anaya et al, 2009;Muhd-Ekhzarizal, Mohd-Hasmadi, Hamdan, Mohamad-Roslan, & Noor-Shaila, 2018;Winarso et al, 2017).…”

Section: Estimation Mangrove Biomassmentioning

confidence: 99%

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Nguyen

et al. 2019

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Mangroves are recognized as a highly valuable resource due to their provision of multiple ecosystem services. Therefore, mangrove ecosystems mapping and monitoring is a crucial objective, especially for tropical regions. Thai Binh province is one of the most important mangrove ecosystems in Vietnam. The mangrove ecosystem in this province has faced threats of deforestation from urban development, land reclamation, tourism activities, and natural disasters. Recently, to maintain the fundamental functions of the ecosystems, a large mangrove area was planted in Thai Binh. The aim of this research is to detect the change in the mangrove areas and to create an aboveground biomass map for mangrove forests in Thai Binh province. Landsat and Sentinel-2 satellite images from 1998 to 2018 were analysed using the supervised classification method to detect mangrove area change. Mangrove Above-ground Biomass (AGB) was estimated using linear regression between vegetation indices and field AGB survey. The accuracy assessment for the classified images of 1998, 2003 and 2007, 2013 and 2018 are 93%, 86%, 96%, 94% and 91% respectively with kappa of 0.8881, 0.7953, 0.9357, 0.9114 and 0.8761. The mangrove cover in the study area was estimated at 5874.93 ha in 1998. This figure decreased significantly to 4433.85 ha in 2007, before recovery began to take place in the study area, which was estimated at 6587.88 ha in 2018. In 1998, the average AGB in this study area was 22.57 ton/ha, and in 2018 it was 37.74 ton/ha with a standard error of 12.41 ton/ha and the root mean square error (RMSE) was ±12.08 ton/ha.

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Section: Estimation Mangrove Biomassmentioning

confidence: 99%

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Nguyen

et al. 2019

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“…Generally, carbon storage values are higher in better conserved sites (Muhd-Ekhzarizal et al, 2018;Kendie et al, 2019). The rural area is part of a conservation unit (National Forest category), although the portion studied is bordering an agricultural site, but the area sampled is distant from urbanized areas that poses continuous anthropic pressure.…”

Section: Discussionmentioning

confidence: 99%

Although it lacks connectivity, isolated urban forest fragments can deliver similar amounts of ecosystem services as in protected areas

Aguiar,

Brun,

Higuchi

et al. 2023

CERNE

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“…Where; V was individual tree volume, D indicated diameter at breast height, H signified tree height, B was wood biomass in stem, and WD describes wood density for every mangrove species (Muhd-Ekhzarizal et al 2018).…”

Section: Discussionmentioning

confidence: 99%

Species composition and growth performance of mangrove forest at the coast of Tanah Merah, East Nusa Tenggara

Sadono¹,

Soeprijadi²,

Susanti³

et al. 2020

Biodiversitas

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The availability information about species composition and growth performance of mangrove forest are required to determine the best strategies for sustainable ecosystems management, particularly at the coastal area. This study aimed to quantify the number of species composition and growth performance of mangrove stand that established at the coast of Tanah Merah, East Nusa Tenggara. Forest inventory was conducted using nine permanent sampling plot which evenly distributed in every zonation of mangrove. Data were collected in each life stage of vegetation, namely seedling, sapling, pole, and tree. Several parameters were calculated to describe species composition, including important value index, richness, heterogeneity, and evenness. Four indicators were selected to assess the growth performance of mangrove stand in this location, i.e. mean diameter, average height, timber volume, and wood biomass. Results demonstrated the species composition of mangrove forest consisted of 9 different plants. The highest important value index of seedling was noted in A. marina (124.09) while the greatest important value index of sapling, pole, and tree were recorded in S. alba by approximately 86.57, 130.01, 118.58 respectively. This location had low level of richness (1.22) and heterogeneity (0.88) but having high level of evenness (0.99). The mean diameter and height of mangrove stand in this area was 15.2 cm and 8.3 m with an average timber volume and wood biomass around 90.7 m3 ha-1 and 65.1 Mg ha-1 respectively. Based on these findings, we suggested to conduct enrichment planting for improving plant biodiversity of mangrove forest at the coast of Tanah Merah.

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Estimation of aboveground biomass in mangrove forests using vegetation indices from SPOT-5 image

Cited by 11 publications

References 9 publications

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Although it lacks connectivity, isolated urban forest fragments can deliver similar amounts of ecosystem services as in protected areas

Species composition and growth performance of mangrove forest at the coast of Tanah Merah, East Nusa Tenggara

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