Estimation of aboveground biomass in mangrove forests using high-resolution satellite data

Hirata, Yasumasa; Tabuchi, Ryuichi; Patanaponpaiboon, Pipat; Poungparn, Sasitorn; Yoneda, Reiji; Fujioka, Yoshimi

doi:10.1007/s10310-013-0402-5

Cited by 58 publications

(34 citation statements)

References 25 publications

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“…The estimation of standing biomass is known to provide an indication of carbon allocation to plant tissues: an indispensable information when making local and regional carbon sequestration accounting (Kairo et al 2008;Aheto et al 2011). Such in situ estimation of biomass is also known to give a better and more accurate result than using satellite data (Hirata et al 1998). Even though many studies have been carried out on biomass of upland forest and plantations in Africa (Brown 1997), biomass estimation of mangrove forests have rarely been done compared to other continents.…”

Section: Mangrove Forest Attributes and Biomass In The Urban And Ruramentioning

confidence: 99%

Comparative Assessment of Mangrove Biomass and Fish Assemblages in an Urban and Rural Mangrove Wetlands in Ghana

Nortey¹,

Aheto

Blay

et al. 2016

Wetlands

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Mangrove wetlands are one of the most important ecosystems on earth, providing habitats for both marine and terrestrial organisms as well as supporting essential human services. However, high dependence of humans on these systems is leading to significant transformation of mangrove wetlands and reduction in their ecosystem services including fisheries. The objectives of this study were to estimate the biomass of two mangrove wetlands in Ghana within urban and rural contexts and determine the fish fauna assemblages as part of baseline setting. The study used the structural parameters of mangrove species and allometry to estimate the biomass of both forest systems. Fish community structure were determined based on ecological surveys. The findings show that the standing biomass of the mangrove forests were significantly higher (p < 0.01) in the rural wetland (394.49 t/ha) compared to the urban wetland (126.29 t/ ha). Fish fauna assemblages, referring to species richness and diversity were higher in the urban wetland at 4.21 and 2.64 respectively compared to the rural wetland at 3.46 and 2.09 respectively. This paper concludes that a well-developed mangrove system with high mangrove biomass may not necessarily imply high fish species richness and diversity.

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Section: Mangrove Forest Attributes and Biomass In The Urban And Ruramentioning

confidence: 99%

Comparative Assessment of Mangrove Biomass and Fish Assemblages in an Urban and Rural Mangrove Wetlands in Ghana

Nortey¹,

Aheto

Blay

et al. 2016

Wetlands

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“…Therefore, mangrove biomass estimation by means of field investigation combined with remotely sensed data is considered the ideal and practical method [14]. Remote sensing-based models commonly utilize field survey data (diameter at breast height (DBH), tree height, and density) and allometric equations to acquire biomass estimations for developing biomass models [15,16]. Remote sensing models for estimating mangrove vegetation biomass have been established in LandSat [17], IKONOS [18], QuickBird [19], SAR [20], Rardarsat [21], SRTM [22] (coupled with ICEsat/GLAS, Landsat ETM+) and LiDAR [23] data, etc.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

et al. 2015

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Abstract:Previous research studies have demonstrated that the relationship between remote sensing-derived parameters and aboveground biomass (AGB) could vary across different species types. However, there are few studies that calibrate reliable statistical models for mangrove AGB. This study quantifies the differences of accuracy in AGB estimation between the results obtained with and without the consideration of species types using Worldview-2 images and field surveys. A Back Propagation Artificial Neural Network (BP ANN) based model is developed for the accurate estimation of uneven-aged and dense mangrove forest biomass. The contributions of the input variables are further quantified using a "Weights" method based on BP ANN model. Two types of mangrove species, Sonneratia apetala (S. apetala) and Kandelia candel (K. candel), are examined in this study. Results show that the species type information is the most important variable for AGB estimation, and the red edge band and the associated vegetation indices from WorldView-2 images are more sensitive to mangrove AGB than other bands and vegetation indices. The RMSE of biomass estimation at the incorporation of species as a dummy variable is 19.17% OPEN ACCESSRemote Sens. 2015, 7 12193 lower than that of the mixed species level. The results demonstrate that species type information obtained from the WorldView-2 images can significantly improve of the accuracy of the biomass estimation.

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“…The delineation of individual tree crowns in high resolution imagery provides the basic unit of measurement from which a number of useful tree attributes can be derived, including crown size, tree species and AGB (Hirata et al 2014). Information on individual tree crowns can also be aggregated to derive TCC and tree density.…”

Section: Tree Crown Delineationmentioning

confidence: 99%

Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone : Application of WorldView-2 and Landsat 8

Karlson¹

2015

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Woodlands constitute the subsistence base of the majority of people in the Sudano-Sahelian zone (SSZ). Trees and grasses provide key ecosystem goods and services, including soil protection, fuelwood, food products and fodder. However, climate change in combination with rapidly increasing populations and altered land use practices put increasing pressure on the vegetation cover in this region. Low availability of in situ data on vegetation structure and composition hampers research and monitoring of this essential resource. Satellite and aerial remote sensing represents important alternative data sources in this context. The main advantages of remote sensing are that information can be collected with high frequency over large geographical areas at relatively low costs. This thesis explores the utility of remote sensing for mapping and analysing vegetation, primarily trees, in the SSZ. A comprehensive literature review was first conducted to describe how the application of remote sensing for analysing vegetation has developed in the SSZ between 1975 and 2014, and to identify important research gaps. Based on the gaps identified in the literature review, the capabilities of two new satellite sensors (WorldView-2 and Landsat 8) for mapping woodland structure and composition were tested in an agroforestry landscape located in central Burkina Faso. The tree attributes in focus included tree crown area (m 2 ), tree species, tree canopy cover (%) and aboveground biomass (tons ha -1 ). The data processing methods encompassed objectbased image analysis for tree crown delineation, and use of the Random Forest algorithm for tree species classification (WorldView-2) and estimation of tree canopy cover and aboveground biomass (Landsat 8).The literature review revealed that the use of remote sensing has increased extensively in the SSZ, especially since 2010. Remote sensing is increasingly used by diverse scientific disciplines although the contribution from African authors remains relatively low. The main application area has been to analyze changes in vegetation productivity and broad vegetation types, while relatively few studies have used remote sensing to map tree attributes at a higher level of detail, and to analyze interactions between the vegetation cover and environmental factors.This thesis shows that the WorldView-2 satellite represents a useful data source for mapping individual tree attributes, including tree crown area and tree species. The individual tree crown delineation achieved promising results: 85.4% of the reference trees were detected in the WorldView-2 data and tree crown area was estimated with an average error of 45.6%. Both detection and delineation accuracy was influenced by tree size, the degree of crown closure and the composition of the undergrowth vegetation. In addition, WorldView-2 data produced high classification accuracies for five locally important tree species, which are common throughout the SSZ. The highest overall classification accuracy (82.4%) was produced using multi-tempor...

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Estimation of aboveground biomass in mangrove forests using high-resolution satellite data

Cited by 58 publications

References 25 publications

Comparative Assessment of Mangrove Biomass and Fish Assemblages in an Urban and Rural Mangrove Wetlands in Ghana

Comparative Assessment of Mangrove Biomass and Fish Assemblages in an Urban and Rural Mangrove Wetlands in Ghana

Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone : Application of WorldView-2 and Landsat 8

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