Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review

Vashum, Kuimi T.; Jayakumar, S.

doi:10.4172/2157-7625.1000116

Cited by 247 publications

(188 citation statements)

References 63 publications

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“…In contrast, remote sensing-based approaches have become popular due to their unique characteristics in data collection and presentation; that is, multitemporal remote sensing images not only reveal spatial variability, spatial distributions, and patterns of forests but also provide the potential to estimate their changes over time [4][5][6][7]. A large number of research papers on biomass estimation using remote sensing data have been published in the past three decades, as summarized in previous literature review papers (e.g., [4,6,[11][12][13][14][15][16][17]). …”

Section: Introductionmentioning

confidence: 99%

“…In particular, Landsat images have been the most widely used for forest aboveground biomass (AGB) estimation in the past three decades [5,6,20,24,26,[28][29][30][31][32][33][34][35][36], mainly because they are freely downloadable, have a long history, and have medium spatial resolution. The studies deal with different climate zones and forest ecosystems, from tropical to subtropical, temperate, and boreal forests [4][5][6][7][12][13][14][15]20,28,32,[37][38][39][40][41][42][43]. However, one common problem is the data saturation in Landsat imagery; that is, spectral reflectance values are not sensitive to the change in biomass of dense and multilayer canopy forests, which results in low accuracy of AGB estimation, especially when AGB is high, such as greater than 130 Mg/ha [5,6,29].…”

Section: Introductionmentioning

confidence: 99%

“…Various remotely sensed images from optical sensors and radar and lidar systems have been utilized to estimate and map forest biomass/carbon by combining with ground sample plot data [5,6,[11][12][13][14][15]. The optical imagery-based technologies are commonly used for biomass estimation due to high correlations between spectral bands and biomass [4,6,[17][18][19][20][21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

et al. 2016

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Abstract:The data saturation problem in Landsat imagery is well recognized and is regarded as an important factor resulting in inaccurate forest aboveground biomass (AGB) estimation. However, no study has examined the saturation values for different vegetation types such as coniferous and broadleaf forests. The objective of this study is to estimate the saturation values in Landsat imagery for different vegetation types in a subtropical region and to explore approaches to improving forest AGB estimation. Landsat Thematic Mapper imagery, digital elevation model data, and field measurements in Zhejiang province of Eastern China were used. Correlation analysis and scatterplots were first used to examine specific spectral bands and their relationships with AGB. A spherical model was then used to quantitatively estimate the saturation value of AGB for each vegetation type. A stratification of vegetation types and/or slope aspects was used to determine the potential to improve AGB estimation performance by developing a specific AGB estimation model for each category. Stepwise regression analysis based on Landsat spectral signatures and textures using grey-level co-occurrence matrix (GLCM) was used to develop AGB estimation models for different scenarios: non-stratification, stratification based on either vegetation types, slope aspects, or the combination of vegetation types and slope aspects. The results indicate that pine forest and mixed forest have the highest AGB saturation values (159 and 152 Mg/ha, respectively), Chinese fir and broadleaf forest have lower saturation values (143 and 123 Mg/ha, respectively), and bamboo forest and shrub have the lowest saturation values (75 and 55 Mg/ha, respectively). The stratification based on either vegetation types or slope aspects provided smaller root mean squared errors (RMSEs) than non-stratification. The AGB estimation models based on stratification of both vegetation types and slope aspects provided the most accurate estimation with the smallest RMSE of 24.5 Mg/ha. Relatively low AGB (e.g., less than 40 Mg/ha) sites resulted in overestimation and higher AGB (e.g., greater than 140 Mg/ha) sites resulted in underestimation. The smallest RMSE was obtained when AGB was 80-120 Mg/ha. This research indicates the importance of stratification in mitigating the data saturation problem, thus improving AGB estimation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

et al. 2016

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“…The carbon stock is about 45 to 50% of the total above-ground biomass of a tree (Vashum et al, 2012). Therefore, the carbon stock of each individual trees was calculated by multiplying by 0.47.…”

Section: Quantification Of Carbon Stock As National Level Ecosystem Smentioning

confidence: 99%

Assessing and mapping ecosystem services of trees outside forest

Tassew¹

2017

J. Ecol. Nat. Environ.

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The overall objective of the study was to map trees outside forest (TOF) in croplands, and their contribution to the supply of ecosystem services for local and national beneficiaries using participatory research, Google Earth and ArcMap in Ghana, as the case study area. A satellite image available from Google Earth was used to map croplands, and ArcMap was used to calculate the local and national ecosystem service hot spot areas based on the values assigned to each TOF individuals. The research identified and mapped a total of 786 TOF individuals and 50 TOF species in 147 ha of croplands in the study area. Ficus exasperate, Morinda lucida, Ceiba pentandra, Spathodea campanulata, Mangifera indica, Sterculia tragacantha, Funtumia elastic, Ficus carpensis, Vernonia amygdalina and Trilipisium madagascariense were the top ten most dominant species in terms of species occurrence. Fifteen different local ecosystem services supplied by TOF species, and the hotspot areas were identified and mapped. The total carbon stored by all 786 TOF in 147 ha of the study area was 759 tons of carbon. The most important TOF species and hotspot locations that require special planning, conservation, and management focus were identified and mapped. There was a poor correlation between the importance and location of the key species for local and national beneficiaries which might lead to a conflict of interest and illegal tree felling.

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“…Measurement of diameter at breast height (DBH), height, volume and wood density is carried out without felling the trees (Gibbs et al, 2007;Vashum and Jayakumar, 2012). This method has been extensively used to determine the biomass in view of also ensuring the protection of trees in the forest area.…”

Section: Forest Biomassmentioning

confidence: 99%

Carbon Stocking in the Natural Forests – The Case of Malaysia

Ratnasingam

Ramasamy

Toong

et al. 2015

Not Bot Hort Agrobot Cluj

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Forested land in the world is about 28% of the global land area, accounting for 80% of the terrestrial carbon stored as biomass and soil organic carbon. Human activities, namely fossil fuel combustion and deforestation resulted in anthropogenic emissions into the atmosphere. Deforestation is being focused in this study in view of the role of forests as carbon stocks. Carbon is normally referred to as biomass of the tree. Several studies revealed that carbon is mostly sequestered in the aboveground part of biomass. As Southeast Asia has the highest level of deforestation, this study focused on observing carbon stocks in Malaysian forests. The conducted estimation of forest carbon stocks reveals carbon stock increment owing to the increment in the forested land. Yet, the forest transition process necessary for expanding the areas of forested land appears to be difficult to achieve. The economic development in the agricultural sector, land conversion for industrialization and settlement, expansion of wood-based industry and employment opportunities in the wood-based sector may hamper forest transition.

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Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review

Cited by 247 publications

References 63 publications

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

Assessing and mapping ecosystem services of trees outside forest

Carbon Stocking in the Natural Forests – The Case of Malaysia

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