Comparison of Carbon Storage Measurement Methods on Agroforestry Systems in Sakon Nakhon Province, Northeast Thailand

Abstract

The current global climate has changed dramatically. One of the main causes is human activities that contribute to the emission of large amounts of carbon dioxide (CO 2) from reserve areas into the atmosphere, causing global warming. The objective of this research is the comparison of measurement methods of carbon storage on agroforestry systems in Sakon Nakhon Province, northeast Thailand. The research methodologies comprised 1) the transfer of knowledge to farmers who participated in the project and 2) monitoring carbon sequestration with satellite imagery. The overall results concluded that farmers obtained knowledge and understanding of the causes of global warming as well as adjusted toward the changes in the weather and atmosphere. More than 80% of farmers were able to perform measurements themselves, recording the Diameter at Breast Height (DBH) and total height of the trees. The results of biomass measurement were attained by monitoring carbon sequestration in the agroforestry areas and equalled 38,649.48 tonnes of carbon dioxide equivalent (tCO 2 e). The carbon sequestration assessment with satellite imagery was able to assess carbon collection, which was equivalent to 36,343.08 tCO 2 e.

Using a Split-Window Algorithm for the Retrieval of the Land Surface Temperature via Landsat-8 Oli/Tirs

“…In addition, many research studies currently focus on developing a method to detect the land surface temperature using remote sensing technology. Remote sensing technology is accepted as being modern and efficient, and it can be applied to rapidly monitor and detect global phenomena (Uttaruk & Laosuwan, 2018;Rotjanakusol & Laosuwan, 2019;Uttaruk & Laosuwan, 2020). In the meantime, many research papers have indicated using a mathematical model in conjunction with remote sensing technology to analyse the land surface temperature, such as radiative transfer equation (RTE), Mono-Window (MW), split window (SW), Dual-Angle (DA) and single-channel (SC) (Ren et al, 2011;Yu et al, 2014;Chen et al, 2015;.…”

Forecasting Time Series Change of the Average Enhanced Vegetation Index to Monitoring Drought Condition by Using Terra/Modis Data

“…The aim to apply this technology is to reduce time spent in physical exploration in the actual area. Nowadays, a lot of satellite data, both low and high spatial resolution, are used (Uttaruk & Laosuwan, 2020b;Prohmdirek et al, 2020;Auntarin et al, 2021;Piamdee & Laosuwan, 2021). The study of time series forecast is to study the changing pattern of data that have occurred from the past until the present time (Gu, 2007) the extent of data change depends on the pattern of data to be studied (Furtuna et al, 2015), which is the same as natural resources data.…”