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Estimation of Soil Organic Matter on Paddy Field using Remote Sensing Method

SAINS TANAH - Journal of Soil Science and Agroclimatology · Vol. 16 No. 2 (2019) · hlm. 159–168

DOI
10.20961/stjssa.v16i2.35395
ISSN
2356-1424, 1412-3606
Terbit
2019-12-30
Penerbit
Universitas Sebelas Maret
Bahasa
en

Abstrak

Soil organic matter (SOM) is one of the important parameters in agriculture management, thus estimating its distribution on the land will be essential. Remote sensing can be utilized to map the SOM distribution in the large-scale area. The objective of this research was to determine the estimation of SOM distribution on the paddy field in Sukoharjo Regency, Indonesia using Landsat 8 OLI imagery. The sampling points were determined by purposive sampling based on an overlay of land use classification map of paddy field, NDSI (Normalized Difference Soil Index) map, and soil type map. The analysis method was used simple linear regression (SLR) and multiple linear regression (MLR) between SOM content and a digital number of Landsat 8 OLI imagery. The SLR analysis resulted that all band except band 1 and 5 of Landsat 8 OLI Imagery have the capability to estimating SOM. The MLR model based on best subset analysis resulted in the combination of bands 3, 4, 6, and 7 was the best model for estimating SOM distribution (R2=0.399).  The MLR model was used to create SOM distribution map on paddy field in Sukoharjo Regency and resulted in the SOM range of the area is distributed from very low (<1%) to moderate (2.1–4.2%) with the largest area was on low level (1–2%) about 11,028 ha. The result indicates that Landsat 8 OLI Imagery could be used for mapping the SOM distribution.

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  • Sebelas Maret University
  • Southern Federal University
  • Gifu University
  • National Research and Innovation Agency
  • Lambung Mangkurat University
  • Graphic Era Hill University
  • Chitkara University
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Rekan penulisOrganisasiArtikel bersama
Mujiyo MujiyoSebelas Maret University9
Sumani SumaniSebelas Maret University8
Rahayu RahayuSebelas Maret University7
Sri HartatiSebelas Maret University5
Ganjar HerdiansyahSebelas Maret University5
Muhamad Khoiru ZakiGifu University5
Widyatmani Sih DewiSebelas Maret University5
Aktavia HerawatiSebelas Maret University5
Slamet MinardiSebelas Maret University4
Adhia Azhar FauzanGifu University4
Keigo NodaGifu University4
Vita Ratri CahyaniSebelas Maret University3
Taufiq Perak SanjayaSebelas Maret University3
Ongko CahyonoSebelas Maret University2
Suntoro SuntoroSebelas Maret University2
Muhammad Rizky RomadhonLambung Mangkurat University2
Jihad KhadaffiSebelas Maret University1
F C MentariSebelas Maret University1
Hery WidijantoSebelas Maret University1
Alena TimoshenkoSouthern Federal University1
Kolesnikov SergeySouthern Federal University1
Natalia EvstegneevaSouthern Federal University1
Natalia TsepinaSouthern Federal University1
Kamil KazeevSouthern Federal University1
Tatiana MINKINASouthern Federal University1
Avnish ChauhanGraphic Era Hill University1
Lidya Zaela WijayaSebelas Maret University1
Vishnu D RajputChitkara University1
Bambang Hendro SunarmintoUniversitas Gadjah Mada1
Setiawan Khoirul HimmiNational Research and Innovation Agency1
Didi TarmadiNational Research and Innovation Agency1
Bramantyo WikantyosoNational Research and Innovation Agency1
Sri Rezeki FebrianiSebelas Maret University1
Maria Theresia Sri BudiastutiSebelas Maret University1
T WidodoSebelas Maret University1

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Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.uns.ac.id/tanah/oai, pertama di-harvest 10 Nov 2026, terakhir terlihat 10 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Estimation of Soil Organic Matter on Paddy Field using Remote Sensing Method</dc:title>
	<dc:creator xml:lang="en">Habibi, Luthfan Nur</dc:creator>
	<dc:creator xml:lang="en">Komariah, Komariah</dc:creator>
	<dc:creator xml:lang="en">Ariyanto, Dwi Priyo</dc:creator>
	<dc:creator xml:lang="en">Syamsiyah, Jauhari</dc:creator>
	<dc:creator xml:lang="en">Tanaka, Takashi S.T.</dc:creator>
	<dc:subject xml:lang="en">Landsat 8 OLI</dc:subject>
	<dc:subject xml:lang="en">NDSI</dc:subject>
	<dc:subject xml:lang="en">PCA</dc:subject>
	<dc:subject xml:lang="en">Precision agriculture</dc:subject>
	<dc:subject xml:lang="en">Regression</dc:subject>
	<dc:description xml:lang="en">Soil organic matter (SOM) is one of the important parameters in agriculture management, thus estimating its distribution on the land will be essential. Remote sensing can be utilized to map the SOM distribution in the large-scale area. The objective of this research was to determine the estimation of SOM distribution on the paddy field in Sukoharjo Regency, Indonesia using Landsat 8 OLI imagery. The sampling points were determined by purposive sampling based on an overlay of land use classification map of paddy field, NDSI (Normalized Difference Soil Index) map, and soil type map. The analysis method was used simple linear regression (SLR) and multiple linear regression (MLR) between SOM content and a digital number of Landsat 8 OLI imagery. The SLR analysis resulted that all band except band 1 and 5 of Landsat 8 OLI Imagery have the capability to estimating SOM. The MLR model based on best subset analysis resulted in the combination of bands 3, 4, 6, and 7 was the best model for estimating SOM distribution (R2=0.399).  The MLR model was used to create SOM distribution map on paddy field in Sukoharjo Regency and resulted in the SOM range of the area is distributed from very low (&amp;lt;1%) to moderate (2.1–4.2%) with the largest area was on low level (1–2%) about 11,028 ha. The result indicates that Landsat 8 OLI Imagery could be used for mapping the SOM distribution.</dc:description>
	<dc:publisher xml:lang="en">Universitas Sebelas Maret</dc:publisher>
	<dc:date>2019-12-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.uns.ac.id/tanah/article/view/35395</dc:identifier>
	<dc:identifier>10.20961/stjssa.v16i2.35395</dc:identifier>
	<dc:source xml:lang="en">SAINS TANAH - Journal of Soil Science and Agroclimatology; Vol. 16 No. 2 (2019): December; 159-168</dc:source>
	<dc:source>2356-1424</dc:source>
	<dc:source>1412-3606</dc:source>
	<dc:source>10.20961/stjssa.v16i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://jurnal.uns.ac.id/tanah/article/view/35395/25620</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2019 Luthfan Nur Habibi, Komariah Komariah, Dwi Priyo Ariyanto, Jauhari Syamsiyah, Takashi S. T. Tanaka</dc:rights>
</oai_dc:dc>