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MODIS Satellite Imagery for Monitoring Carbon Sequestration Potential and Its Drivers in Jambi Province, Indonesia

Jurnal Geografi · Vol. 17 No. 1 (2025) · hlm. 152–164

DOI
10.24114/jg.v17i1.62343
ISSN
2549-7057, 2085-8167
Terbit
2025-03-29
Penerbit
Universitas Negeri Medan
Bahasa
en
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Inggris

Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values ​​and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.

Inggris

Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values ​​and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.

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  • Universitas Gadjah Mada
  • Indonesia University of Education
  • Muhammadiyah University of Yogyakarta
  • Diamond Harbour Women's University
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Rekan penulisOrganisasiArtikel bersama
Projo DanoedoroUniversitas Gadjah Mada2
I Kade Alfian Kusuma WirayudaUniversitas Gadjah Mada1
Andung Bayu SekaranomUniversitas Gadjah Mada1
Sudaryatno SudaryatnoUniversitas Gadjah Mada1
Bagus WiratmokoUniversitas Gadjah Mada1
Totok Wahyu WibowoUniversitas Gadjah Mada1
Wahyu NurbandiUniversitas Gadjah Mada1
Muhammad KamalUniversitas Gadjah Mada1
Muhammad Sufwandika WijayaUniversitas Gadjah Mada1
Sanjiwana ArjasakusumaUniversitas Gadjah Mada1
Totok GunawanUniversitas Gadjah Mada1
Sugeng Juwono MardihusodoUniversitas Gadjah Mada1
Kusbaryanto KusbaryantoMuhammadiyah University of Yogyakarta1
Tri Wulandari KesetyaningsihMuhammadiyah University of Yogyakarta1
Achmad FadilahUniversitas Gadjah Mada1
Irfan Zaki IrawanUniversitas Gadjah Mada1
Kapil GhoshDiamond Harbour Women's University1
Lili SomantriIndonesia University of Education1
Iqbal Eko NoviandiIndonesia University of Education1
Agil Akbar FahreziIndonesia University of Education1
Rahmat Azul MizanUniversitas Gadjah Mada1
Nur Mohammad FardaUniversitas Gadjah Mada1
Ni Kadek Oki FebriantiUniversitas Gadjah Mada1

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Sumber metadata: OAI-PMH (metadata jurnal) http://jurnal.unimed.ac.id/2012/index.php/geo/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">MODIS Satellite Imagery for Monitoring Carbon Sequestration Potential and Its Drivers in Jambi Province, Indonesia</dc:title>
	<dc:title xml:lang="en-US">MODIS Satellite Imagery for Monitoring Carbon Sequestration Potential and Its Drivers in Jambi Province, Indonesia</dc:title>
	<dc:creator xml:lang="en">Widayani, Prima</dc:creator>
	<dc:creator xml:lang="en">Arrafi, Muhammad</dc:creator>
	<dc:subject xml:lang="en">Carbon</dc:subject>
	<dc:subject xml:lang="en">MODIS</dc:subject>
	<dc:subject xml:lang="en">Net Primary Productivity (NPP)</dc:subject>
	<dc:description xml:lang="en">Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values ​​and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.</dc:description>
	<dc:description xml:lang="en-US">Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values ​​and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Medan</dc:publisher>
	<dc:date>2025-03-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/62343</dc:identifier>
	<dc:identifier>10.24114/jg.v17i1.62343</dc:identifier>
	<dc:source xml:lang="en">JURNAL GEOGRAFI; Vol. 17 No. 1 (2025): JURNAL GEOGRAFI; 152-164</dc:source>
	<dc:source>2549-7057</dc:source>
	<dc:source>2085-8167</dc:source>
	<dc:source>10.24114/jg.v17i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/62343/26284</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Prima Widayani, Muhammad Arrafi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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