Open AccessApplication of GSTAR(1,1) model for layer peat soil predicted based on resistivity log data
Author(s) -
R. Thompson Jonathan,
Yundari Yundari,
Nurhasanah Nurhasanah,
Odilo Yupama Engkoe Nada
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2106/1/012031
Subject(s) - peat , electrical resistivity and conductivity , soil science , measure (data warehouse) , layer (electronics) , geology , geotechnical engineering , environmental science , engineering , materials science , data mining , geography , computer science , archaeology , electrical engineering , composite material
In this study, GSTAR modeling was carried out with the inverse of distance weight matrix obtained from Geoelectrical Resistivity data at several peatland locations around the Universitas Tanjungpura, Pontianak. This data can identify the subsurface layer of the soil through the electric current that binds into the soil. However, due to the limitation of the tool to measure the resistivity value, it can only measure 1/5 of the depth of the observation length. To overcome this problem, predictions are made at the next depth using the GSTAR model. The study began by measuring the resistivity value of the land using the geoelectric method and mapping it. Through this GSTAR modeling, predictions are made for the unobserved subsurface to determine the type of soil layer. Knowing the type of deeper soil layer can help contractors build plant concrete stakes to keep buildings safe on peatland. The results of the GSTAR(1.1) model are not accurate enough to estimate the resistivity value data. This is possible because the correlation between rock ages is not the same, so further analysis is required.