Modelling above-ground live trees biomass and carbon stock estimation of tropical lowland Dipterocarp forest: integration of field-based and remotely sensed estimates

Zaki, Nurul Ain Mohd; Latif, Zulkiflee Abd; Suratman, Mohd Nazip

doi:10.1080/01431161.2017.1421793

Cited by 31 publications

(15 citation statements)

References 57 publications

(66 reference statements)

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“…Moreover, Maggi et al [61] also concluded very steep slope areas contain little vegetation cover compared to low slope areas. On the contarary, Zaki et al [62] studied the forest carbon stock on tropical lowland dipterocarp forest and revealed that above ground carbon stock and below ground carbon stock tends to increase with slope. The distribution of biomass and carbon stocks in the forest is known to vary due to the presence of various tree species, [68] and our result in this study supports the growing indications that forest ecosystems growing at lower slope store higher amounts of carbon than forest ecosystems at higher slopes.…”

Section: Carbon Estimationmentioning

confidence: 99%

Biomass and Carbon Stock Variation along slopes in Tropical Forest of Nepal: A case of Depard Community Forest, Makwanpur, Nepal

Bohara

Miya

Timilsina

et al. 2021

J. Multidiscip. Appl. Nat. Sci.

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This study was conducted to assess biomass and carbon stock along slopes in Depard community forest, Manahari-6, Makwanpur district of Nepal. In Nepal, carbon stock estimation has been less practiced in community forest. A random sampling method was applied in this study to collect biophysical data i.e. DBH and height by non-destructive method to estimate the quantity of tree biomass and carbon stock. 21 sample plots with 1% sampling intensity were established within the study area. The circular area of 250 m2 was predetermined with the radius of 8.92 m for this study. Secondary data were collected through published and unpublished literature. Data were pooled and analyzed with SPSS software. The total biomass and carbon stock were calculated to be 1381.30 t/ha and 649.21 t/ha, respectively. The biomass and carbon stock were highest (563.12 t/ha and 242.42 t/ha) in 0-5% slope, and lowest in >20% of slope (334.75 t/ha and 143.60 t/ha). The difference of biomass and carbon in slopes may be due to the accumulation of more organic matter and other minerals in the less sloped areas through rainfall, landslide.

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Section: Carbon Estimationmentioning

confidence: 99%

Biomass and Carbon Stock Variation along slopes in Tropical Forest of Nepal: A case of Depard Community Forest, Makwanpur, Nepal

Bohara

Miya

Timilsina

et al. 2021

J. Multidiscip. Appl. Nat. Sci.

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“…Noteworthily, the migration biology of fungal spores and insect-pests could be determined based on the previous experience of field observation and secondary data generated from geoinformatics-based maps [17]. Furthermore, in case of forestry tree species, the morphological field data could be used to develop correlation / regression-based statistical models for estimation of biomass and carbon sequestration potential 18 . The realized gain of RS & GIS technology is pertinent in the tree improvement programmes, where the field experiments laid earlier need to be evaluated for heritability and other genetic parameters estimates.…”

Section: Viewsmentioning

confidence: 99%

Global Forestry Perspective: COVID-19 Impact and Assessment

Bhandari

Pandey

Dabral

et al. 2021

Natl. Acad. Sci. Lett.

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Corona virus disease 2019 (COVID-19) caused by corona virus SARS-CoV-2 is believed to be originated in Wuhan province of China, which has spread all over the world. It has severely impacted the social, cultural, educational, research and development programmes throughout the globe. Since the inception of various lifeforms on planet earth, forests' plays an important role in the evolutionary history of organisms and fitness persuades the existence of modern-day species in different ecosystems. The visible effect of pandemic leads to the lockdown with positive implications on the earth biosphere as a whole; while on other hand, lockdown seized and reduced the urbanization and developmental projects, especially the research and development progress in the field of forestry and allied sciences. This viewpoint addresses key questions and point-out with detailed exploration of the problemas how COVID-19 pandemic impacts forestry research all over the world? We also suggest possible solutions, and define the role and association of disciplines, such as bioinformatics, remote sensing and statistical modules along with previously explored and collected field data as a sustainable measure to resolve the problems of forestry sector of this mighty challenge.

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“…This technology can simplify and facilitate the forest information using multiple sources of spatial data due to it ability in the acquisition of remotely sensed data about an object, area or phenomenon or area under investigation [8]. Remote sensing can provide benefits in quantifying forest structure, mapping aboveground biomass (AGB), monitoring temporal changes, estimating timber volume and planning purposes [9], [10]. Besides, it can overcome the issue in monitoring any forest disturbances or to be specific, logging operations that occurred deep in the forest by using conventional method is found to be difficult, such as transportation being blocked by fallen timber and cannot proceed the journey [11] also for land use land cover classification and mapping is time consuming and high cost to process [12].…”

Section: Introductionmentioning

confidence: 99%

Land use and land cover change analysis using satellite images in Gua Musang, Kelantan

Rahman

Shukri

Latip

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The use of multisensor remote sensing to characterise forest structure has significant promise for mapping and understanding forest biological processes, making remote sensing an effective technology in detecting deforestation for forest management and monitoring. The aim of this study is to detect land use and land cover (LULC) changes due to deforestation at Gua Musang, Kelantan using satellite images. The Landsat 8 OLI satellite images were obtained from United State Geological Survey (USGS) for year 2017 to 2019. The supervised classification with maximum likelihood algorithm was applied for image classification to generate land use land cover categories. Then, LULC change detection between 2017, 2018 and 2019 were conducted to analyse the change and pattern. Based on the results, it shows the percentage of each land use changes within three (3) years from 2017 to 2019 for Landsat 8 OLI. Percentage of deforestation due to logging areas for year 2017 to 2019 is 5.95%. Percentage of forest area is 5.57%. For water bodies, the percentages just only cover 0.36% in 3 years. The highest land use change is no changes which is 88.12% happened towards the land from 2017 and 2019. This shows within three years there is no great changes at the area. The overall accuracy for each map is more than 80% which are acceptable. From the analysis, there were no significant changes of LULC during this period due to the increased of timber extraction, agricultural land expansion, urban growth, and poor governance structures.

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Modelling above-ground live trees biomass and carbon stock estimation of tropical lowland Dipterocarp forest: integration of field-based and remotely sensed estimates

Abstract: Modelling above-ground live trees biomass and carbon stock estimation of tropical lowland Dipterocarp forest: integration of field-based and remotely sensed estimates,

Cited by 31 publications

References 57 publications

Biomass and Carbon Stock Variation along slopes in Tropical Forest of Nepal: A case of Depard Community Forest, Makwanpur, Nepal

Biomass and Carbon Stock Variation along slopes in Tropical Forest of Nepal: A case of Depard Community Forest, Makwanpur, Nepal

Global Forestry Perspective: COVID-19 Impact and Assessment

Land use and land cover change analysis using satellite images in Gua Musang, Kelantan

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