Remote Sensing Based Vegetation Indices for Estimating Above Ground Carbon  Sequestration in Orchards

Uttaruk, Yannawut; Laosuwan, Teerawong

doi:10.17707/agricultforest.62.4.21

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…Therefore, NDVI is widely used to analyze and to predict the vegetation phenology dynamic, which is resulted from its nearby environment. The NDVI can be calculated using Equation 1 (Tucker, 1979;Uttaruk and Laosuwan, 2016).…”

Section: Methods Ndvi Analysismentioning

confidence: 99%

Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology

Uttaruk

Laosuwan

2017

J. Ecol. Eng.

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Drought is a natural phenomenon as it often occurs in the area of Yasothon province, northeastern of Thailand. It causes effects on vegetation condition in the area. Drought information might be useful for local government to prepare for prevention and mitigation plan in the future. For this reason, the primary objective of the research was to conduct the examination of this province to find severe drought years. Firstly, the researcher needed to find Normalized Differences Vegetation Index (NDVI) and Vegetation Condition Index (VCI) by analyzing monthly Landsat data acquired at different periods of time from January to December 2014, 2015, and 2016, covering 4,096 km 2 . Then, the researcher needed to find relationship between VCI and monthly rainfall represented in term of space and time. As results, VCI and its relationship with monthly rainfall were congruent. VCI showed that the drought area was 33.87% or 1,387.32 km 2 of studied area in 2014, 16.24% or 665.19 km 2 of studied area in 2015 and 27.95% or 1,144.83 km 2 of studied area in 2016. Therefore, the most and the least severe drought years were 2014, 2016, and 2015 respectively.

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Section: Methods Ndvi Analysismentioning

confidence: 99%

Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology

Uttaruk

Laosuwan

2017

J. Ecol. Eng.

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“…(1) Adjust the value of digital number to top of atmosphere reflectance (Uttaruk and Laosuwan, 2016),…”

Section: Methodsmentioning

confidence: 99%

“…This will lead to a tremendous change in the weather atmosphere. Significant GHGs are including Carbon dioxide (CO 2 ), Methane (CH 4 ), Nitrous oxide (N 2 O), Hydrofluorocarbons (HFC), Perfluorinated compounds (PFC), and Nitrogen trifluoride (NF 3 ) (Uttaruk and Laosuwan, 2016). The CO 2 is a GHG that we give importance the most as it has up to 80 percent ratio of GHG that was released from human activities.…”

Section: Introductionmentioning

confidence: 99%

Methods of Estimation for Above Ground Carbon Stock in Nongbua-Nonmee Community Forest, Maha Sarakham Province, Thailand

Uttaruk¹,

Laosuwan²

2020

AgricultForest

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The climate of the world today has changed greatly. This is mainly due to human activity causing large emissions of carbon dioxide (CO 2) from the reserve into the atmosphere, which is the main cause of global warming. This research methodology comprised of training for people in the community and local government sector, so they acquired knowledge and understanding of the causes and consequences of global warming. The people will also learn the adjustment toward weather atmosphere, the method in relieving global warming issues with the potential of the community forest as well as tree measurement techniques. The research method was based from the analysis of the carbon stock from the community forest from 3 different methods; which are 1) method of tree measurement by farmers in the community 2) Measurement, Reporting and Verification (MRV) online method, and 3) the application of Geoinformatics Technology (GIT). The research results found that 50 participants in the training session possessed over 80 percent of understanding toward causes and consequences from global warming, adjustment toward the change of weather atmosphere, and way to relieve the severity of global warming issue with a potential of community forest. Participants were also able to learn tree measurement techniques as well as able to record results. The results from the data analysis from the field survey, MRV online tool, and Geoinformatics Technology found that the community forest can complete the process of carbon stock that is equivalent to 5,256.66 tCO 2 e, 5,061.32 tCO 2 e, 5,058.01 tCO 2 e respectively.

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“…Under the same conditions, the albedo will decrease as the sun's zenith angle increases. The albedo was estimated using Equation 2 (Uttaruk and Laosuwan, 2016):…”

Section: Calculation Of Albedomentioning

confidence: 99%

Influence of Land Use and Rainfall on Carbon Stock Dynamics for Oil Palm and Rubber

et al. 2020

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The expansion of agricultural commodities including oil palm plantations potentially causes an increase of greenhouse gas emissions by amplifying carbon dioxide (CO2) in the atmosphere. In the long term, this amplification will alter climate change. However, oil palm also has the potency to reduce greenhouse gas emissions by absorbing CO2 through photosynthesis. This study aims to determine the carbon stock that can be absorbed by oil palm and rubber plants, and to determine the relationship of rainfall with carbon stock in oil palm plants. The study used satellite image data based on Landsat and combined with rainfall data from near Perbaungan District, North Sumatra. Three Landsat data (acquisition date: (i) 12 February 2000, (ii) 8 March 2009, and (iii) 11 August 2019) were processed to estimate carbon stock. The procedure for estimating carbon stock was as follows: determining the sample and digitizing the sampling points, converting the digital value of the numbers into the spectral spectrum, calculating the albedo values, calculating the long-wave and short-wave radiations, computing biomass, and the absorbed carbon stock. The results showed that the carbon stock in oil palm was greater than that of rubber plants as oil palm has a greater biomass. The greater the plant biomass, the bigger the carbon stock absorbed. Further, the findings revealed that rainfall in dry season has a contribution to carbon stock in oil palm and rubber. The higher the total rainfall during dry season will increase the absorbed carbon stocks.

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Remote Sensing Based Vegetation Indices for Estimating Above Ground Carbon Sequestration in Orchards

Cited by 6 publications

References 8 publications

Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology

Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology

Methods of Estimation for Above Ground Carbon Stock in Nongbua-Nonmee Community Forest, Maha Sarakham Province, Thailand

Influence of Land Use and Rainfall on Carbon Stock Dynamics for Oil Palm and Rubber

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