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All Journal Journal of Tropical Soils International Journal of Multidisciplinary Approach Research and Science
Adi Jaya
University of Palangka Raya
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Economics, Econometrics & Finance Environmental Science Immunology & microbiology Social Sciences

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Water Retention and Saturation Degree of Peat Soil in Sebangau Catchment Area, Central Kalimantan Akhmat Sajarwan; Adi Jaya; Irwan Sukri Banuwa
JOURNAL OF TROPICAL SOILS Vol 26, No 1: January 2021
Publisher : UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5400/jts.2021.v26i1.29-42

Abstract

Water is an essential factor in forming, utilization, management, and sustainability of peat soil. This study was to obtain characteristics of water retention and porosity of peat soil. Peat samples were taken from the Natural Laboratory of Peat Forest, Central Kalimantan at shallow, medium, and deep peat at 0-50cm (surface) and 50-100 cm (subsurface), while laboratory analyses carried out at Soil Laboratory, Universitas Gajahmada. The result shows that volumetric moisture content at the surface lower than subsurface, except for deep peat. The total pore for the surface was 84.67-86.98%, while subsurface layers were 83.53-86.93%. For surface layer, saturated degree (S) medium peat higher than shallow and deep peat, while for shallow subsurface peat higher than medium and deep peat. S value all pF levels of surface for medium and deep peat higher than the subsurface. Bulk density for surface was 0.094g.cm-3 (rb(wet)) and 0.22g.cm-3(rb (dry)) for shallow peat while medium peat are 0.084–0.087g.cm-3(rb(wet)) and 0.18–0.20g.cm-3(rb(dry)), deep peat 0.064–0.090g.cm-3(rb(wet)) and 0.11–0.16g.cm-3(rb(dry)). For subsurface, bulk density of medium peat are 0.094–0.107g.cm-3 (rb(wet)) and 0.16–0.20g.cm-3 (rb(dry)), deep peat are 0.067–0.090g.cm-3 (rb(wet)) and 0.10–0.17g.cm-3 (rb(wet)). The particle density of surface and subsurface for shallow peat higher than medium and deep peat, with values 0.67-0.77g.cm3, 0.61-0.66g.cm3, and 0.53-0.63g.cm3 for shallow, medium, and deep peat, respectively. Total pores for the surface layer decrease with increasing dry bulk density (R = 0.624) and particle density (R = 0.375). This fact seems to confirm a directly proportional relationship between parameters bulk and particle density with total pores.
Analysis of the Carrying Capacity and Environmental Capacity of the Bukit Tangkiling Natural Park Muhammad Rasidi; Bambang S. Lautt; Yetrie Ludang; Sidik R. Usup; Adi Jaya
International Journal of Multidisciplinary Approach Research and Science Том 1 № 02 (2023): International Journal of Multidisciplinary Approach Research and Science
Publisher : Pt. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v1i02.70

Abstract

The Bukit Tangkiling Park area was determined based on the Decree of the Minister of Agriculture of the Republic of Indonesia number: 046/Kpts/Um/1/1977 on January 25, 1997, with an area of 533 Ha. Bukit Tangkiling Nature Park has sloping lowlands, undulating to hilly terrain, and very steep slopes of 2% to 45% at 25 to 170 metres above sea level. Year-to-year tourism increases. An increase in tourist visits can damage natural resources and the environment by exceeding the carrying capacity and capacity of the environment. Cifuentes (1992)'s method is used to calculate the natural tourist environment's carrying capacity in protected areas. The assessment to determine the maximum number of visits to a tourist area is based on the physical, biological and management conditions in the tourist area by considering three main aspects; physical carrying capacity (PCC), real carrying capacity (RCC) and effective carrying capacity (ECC). The research was conducted with the aim of analyzing the value of the effective carrying capacity (ECC). The maximum number of tourists that can visit the Bukit Tangkiling Natural Tourism Park without disrupting the ecology. PCC = 219.063, RCC = 5.475, MC = 0.9, ECC = 4,927 people/day. ECC of 353 people/day. This value is less than the Nature tourist Carrying Capacity Value and does not harm the environment of the natural tourist region. This allows Bukit Tangkiling Park growth.
Estimation of Palm Oil Biomass Carbon from Sentinel-2 Image using the Random Forest Classification Method Muhammad Ardiansyah; Baba Barus; Gita Puspita; Adi Jaya
International Journal of Multidisciplinary Approach Research and Science Том 1 № 02 (2023): International Journal of Multidisciplinary Approach Research and Science
Publisher : Pt. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v1i02.95

Abstract

Oil palm is a carbon absorbing plant that stores it in biomass. To monitor biomass, especially in large areas of oil palm plantations, remote sensing data can be used combined with machine learning algorithms. The aims of this study were to estimate oil palm biomass carbon according to age class using non-destructive methods, as well as analyze the relationship between the reflectance of Sentinel 2 image oil palm and oil palm biomass carbon, and estimate the distribution of oil palm biomass carbon using a learning algorithm random forest (RF) engine. Measurement of biomass at the study site was carried out non-destructively using stratified purposive sampling. The closeness of the relationship between Sentinel 2 image and measured oil palm biomass is assessed from the coefficient of determination of the regression equation. Estimation of the distribution of biomass carbon in all research locations was carried out using the RF method with the Dzetsaka classification tool. The results showed that the highest biomass carbon stock was obtained in oil palm aged 20 years with an average of 59.6 tons C/ha, while the lowest biomass carbon stock was obtained in oil palm aged 17 years with an average of 32.9 tons C/ha. The reflectance value of Sentinel-2 image on the blue, green, red, and near infrared channels has a positive correlation to biomass carbon from oil palm with an R² greater than 0.8. The classification of biomass carbon with the RF approach applied to Sentinel-2 image gives an adequate accuracy value of 76.40% in the combination of the proportion of training and testing data 60% : 40%.
Co-Authors Akhmat Sajarwan Baba Barus Bambang S. Lautt Gita Puspita Irwan Sukri Banuwa Muhammad Ardiansyah Muhammad Rasidi Sidik R. Usup Yetrie Ludang