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All Journal Indonesian Journal of Geography Geoplanning : Journal of Geomatics and Planning Forum Geografi Edukasi: Jurnal Pendidikan Sosial Horizon: Jurnal Pendidikan Sosial Jurnal Penelitian Pendidikan IPA (JPPIPA) Geodika: Jurnal Kajian Ilmu dan Pendidikan Geografi Sosial Khatulistiwa: Jurnal Pendidikan IPS GeoEco Geosfera Indonesia
Ajun Purwanto
PGRI Pontianak University
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Education Environmental Science Materials Science & Nanotechnology Physics Social Sciences

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Utilization of Deep Learning for Mapping Land Use Change Base on Geographic Information System: A Case Study of Liquefaction Purwanto, Ajun; Paiman
Jurnal Penelitian Pendidikan IPA Vol 9 No 10 (2023): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i10.5032

Abstract

This study aims to extract buildings and roads and determine the extent of changes before and after the liquefaction disaster. The research method used is automatic extraction. The data used are Google Earth images for 2017 and 2018. The data analysis technique uses the Deep Learning Geography Information System. The results showed that the extraction results of the built-up area were 23.61 ha and the undeveloped area was 147.53 ha. The total length of the road before the liquefaction disaster occurred was 35.50 km. The extraction result after the liquefaction disaster was that the area built up was 1.20 ha, while the buildings lost due to the disaster were 22.41 ha. The total road length prior to the liquefaction disaster was 35.50 km, only 11.20 km of roads were lost, 24.30 km. Deep Learning in Geographic Information Systems (GIS) is proliferating and has many advantages in all aspects of life, including technology, geography, health, education, social life, and disasters.
Carbon Stocks Estimation Using the Stock Difference Method of Various Land Use Systems Based on Geospatial in Kualan Watershed Purwanto, Ajun; Sulha
Jurnal Penelitian Pendidikan IPA Vol 10 No 11 (2024): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i11.6818

Abstract

Indonesia controls 75%-80% of the world's carbon stocks, so the amount of carbon stocks must be utilized optimally. This study aims to determine carbon stocks, potential emissions, and economic value of carbon stocks in each land use. The method used is secondary data analysis and field checking. The data collected were Sentinel 2A acquisitions in 2020 and 2022, Digital Elevation Model (DEM), and land use land cover in 2020-2023. Data analysis used SNAP and ArcGIS 10.8. The tool used for data analysis is spatial analysis map algebra. The results showed mixed dryland agriculture has the most extensive carbon stock, at 2,614,178 tons/ha, with potential emissions of 9,585,320 tons/ha. The most minor carbon stock is in mining land use, which is 0 tons/ha with potential emissions of 0 tons/ha. The highest C02 value in USD is the forest land use group. In the Secondary Dryland Forest, Secondary Swamp Forest, and Plantation Forest groups, it is 17,517,400.50 USD, while the lowest is mining land use, which is 0 USD. Overall, the CO2 value of land use in the study area is 34,246,314.45 USD. Integrating remote sensing data analysis and field surveys in geospatial technology is one of the new approaches to studying carbon stocks and CO2 emissions in topsoil from various land uses. By utilizing geospatial technology, efforts to estimate carbon stocks on the surface are easier and faster.
Co-Authors Adella Rahayu Pangestu Agus Sudiro Arif Rohman Ayu Rianingsih Ayu Rianingsih Dony Andrasmoro Ekawati Ellyta Ellyta Eviliyanto Eviliyanto, Eviliyanto Fera Fera Fitriani Dwi Susanti Florensia Rentia Florensia Rintia Francista Francista Francista Francista Galuh Bayuardi Hardi Dominikus Bancin Holifah Nurfitri Holifah Nurfitri Mohd Hairy Ibrahim Nurul Ramdhania Paiman Paiman Rahmatullah Rizieq Rika Angela Rosanti, Rosanti RR. Ella Evrita Hestiandari Rustam -, Rustam Sulha Wiwik Cahyaningrum Yoga Prasetya Adi Nugraha