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All Journal Indonesian Journal of Energy
Firman Afrianto
Doctoral Degree in Urban and Regional Planning Gadjah Mada University
Energy

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Big Data and Satellite Imagery for Energy Efficiency Mapping in Indonesia: : A Future Shaped by Advanced Analytics Firman Afrianto; Andini Putri Salsabillah; Annisa Dira Hariyanto
Indonesian Journal of Energy Vol. 8 No. 1 (2025): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v8i1.229

Abstract

In the sophisticated realm of big data, analyzing energy efficiency in Indonesia has become crucial for identifying savings opportunities. This study utilizes large-scale raster data, including CO2 emissions from the OCO-2 GEOS satellite, nocturnal satellite images from VIIRS, and demographic and infrastructural data from WorldPOP and EsriWorld Cover. Through advanced regression techniques in machine learning—Support Vector Regression, Artificial Neural Network, and particularly Random Forest—the research analyzes and forecasts energy efficiency across various Indonesian provinces. The analysis highlights a notable increase in CO2 emissions from 2019 to 2023, with a significant reduction in night-time light emissions in 2020 due to the pandemic, which temporarily decreased human activities. Despite these fluctuations, the continuous increase in population density and built-up areas underscores the persistent influence of urbanization on emissions. The Random Forest model, which provided the most accurate predictions, indicates an expected rise in total CO2 emissions until 2030, driven by urbanization and economic growth, followed by a decline by 2045 due to targeted governmental policies. These insights contribute significantly to understanding the distribution of energy efficiency and support the development of sustainable energy policies in Indonesia. The study not only enriches scientific literature but also guides policy-making, offering a framework for tailored energy efficiency improvements. This research marks a pivotal advancement in utilizing big data and satellite technology to optimize energy use in a context that was previously underexplored.
Illuminating Energy Efficiency: Satellite-Guided Insights for Optimizing Urban Street Lighting Across Indonesian Cities Firman Afrianto; Dimas Tri Rendra Graha; Nuryantiningsih Pusporini; Alifianto Setiawan
Indonesian Journal of Energy Vol. 8 No. 1 (2025): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v8i1.230

Abstract

This study introduces a ground-breaking method for enhancing urban energy management by integrating high-resolution night-time satellite imagery from SDGSAT-1 with detailed ground-truth verification of street lighting across major cities in Central Java and DIY. Utilizing the Glimmer Imager for Urbanization (GIU) with 10-meter resolution, this research precisely identifies different urban street lamp types and evaluates their impact on energy consumption. As the demand for public street lighting grows with urban expansion, there is a pressing need for efficient energy management to sustain urban development and reduce environmental footprints. This study focuses on Semarang, Yogyakarta, and Solo, aiming to assess energy efficiency by examining how different street lighting affects energy usage across various road network types. By employing pan sharpening techniques to enhance image resolution and zonal statistics for in-depth analysis, the research finds significant correlations, especially in the red spectral band. This correlation suggests the potential of using SDGSAT-1 data to estimate streetlight energy consumption where direct measurements are unavailable. The findings also reveal significant variations in energy consumption across different road types, attributed to varying traffic and lighting needs. By highlighting these disparities, the study underscores the potential of transitioning to LED lighting, which can reduce energy consumption by up to 69%. This research not only demonstrates the capabilities of satellite imagery in urban energy management but also offers practical insights for cities looking to improve lighting efficiency, reduce costs, and promote sustainability in urban planning.
Co-Authors Alifianto Setiawan Andini Putri Salsabillah Annisa Dira Hariyanto Dimas Tri Rendra Graha Nuryantiningsih Pusporini