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Developing algorithms for estimating total suspended solids (TSS) using unmanned aerial vehicle: A case study in the Upper Citarum River, Indonesia

Journal of Degraded and Mining Lands Management · Vol. 12 No. 2 (2025) · pp. 7379–7388

DOI
10.15243/jdmlm.2025.122.7379
ISSN
2502-2458, 2339-076X
Published
2025-01-01
Publisher
Brawijaya University
Language
eng
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Monitoring total suspended solids (TSS) is essential as suspended sediments impact the environment and human health in various ways. However, TSS data are limited in many regions because the methods currently applied through in situ measurements are time-consuming and labor-intensive. The study aimed to develop algorithms to estimate TSS using data derived from UAVs and field measurements. Remote sensing technology, such as unmanaged aerial vehicle (UAV), was applied to obtain imagery data to estimate TSS content. These results were then compared with laboratory analysis of in-situ water samples, determined by gravimetric methods following standard protocols. The results showed that the algorithm developed using three-band ratios, the blue/green + red/green + NIR (near infra red)/green, produces a high R2 (0.70), indicating that this combination is reliable for use in estimating TSS content in a river section. The high accuracy of the red band for suspended sediment prediction is attributed to its spectral signature in turbid water, which shows higher reflectance compared to clean water. The results of this study have the potential to help river managers obtain TSS data quickly at a relatively low cost.

Keywords

Collaboration network of the authors

40 authors · 134 co-authorship links · 19 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • UIN Sunan Ampel Surabaya
  • Institut Teknologi Sepuluh Nopember
  • Meteorological, Climatological, And Geophysical Agency
  • National Taiwan University of Science and Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Wahyu Wisnu WijayaAffiliation unknown6
Diah AuliyaniAffiliation unknown5
Esa Bagus NugrahantoAffiliation unknown4
Dian Candra Rini NovitasariUIN Sunan Ampel Surabaya3
Rahardyan Nugroho AdiAffiliation unknown3
Ghaluh Indah Permata SariNational Taiwan University of Science and Technology2
Fajar YuliantoAffiliation unknown2
Gatot NugrohoAffiliation unknown2
Muhammad Iqbal Taufiqurrahman SunariyaAffiliation unknown2
Aris FananiUIN Sunan Ampel Surabaya1
Eka Alifia KusnantiInstitut Teknologi Sepuluh Nopember1
Mohammad HafiyusholehAffiliation unknown1
Diah Devi PramestiUIN Sunan Ampel Surabaya1
Hani KhaulasariUIN Sunan Ampel Surabaya1
Lutfi HakimUIN Sunan Ampel Surabaya1
Risma Madurahma PutriUIN Sunan Ampel Surabaya1
Ahmad Hanif AsyharUIN Sunan Ampel Surabaya1
Dian C. Rini NovitasariAffiliation unknown1
Dina Zatusiva HaqAffiliation unknown1
Bunga Yuwa PhiadelviraAffiliation unknown1
Nurwita Mustika SariAffiliation unknown1
Dony KushardonoAffiliation unknown1
Zylshal ZylshalAffiliation unknown1
Anisa Nur AzizahInstitut Teknologi Sepuluh Nopember1
Putroue Keumala IntanUIN Sunan Ampel Surabaya1
Dian C.R. NovitasariAffiliation unknown1
Eko PriyantoAffiliation unknown1
Suwarsono SuwarsonoAffiliation unknown1
Nunung Puji NugrohoAffiliation unknown1
Muhammad Rokhis KhomarudinAffiliation unknown1
Eddy HermawanAffiliation unknown1
Udhi Catur NugrohoAffiliation unknown1
Hana Listi FitrianaAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://jdmlm.ub.ac.id/index.php/jdmlm/oai, first harvested 9 Nov 2026, last seen 9 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Developing algorithms for estimating total suspended solids (TSS) using unmanned aerial vehicle: A case study in the Upper Citarum River, Indonesia </dc:title>
	<dc:creator>Setiawan, Fajar</dc:creator>
	<dc:creator>Basuki, Tyas Mutiara</dc:creator>
	<dc:creator>Santosa, Budi Heru</dc:creator>
	<dc:creator>Pramono, Irfan Budi</dc:creator>
	<dc:creator>Chulafak, Galdita Aruba</dc:creator>
	<dc:creator>Rahmadya, Aldiano</dc:creator>
	<dc:creator>Nada, Firda Maftukhakh Hilmya</dc:creator>
	<dc:subject xml:lang="en-US">algorithm </dc:subject>
	<dc:subject xml:lang="en-US">remote sensing </dc:subject>
	<dc:subject xml:lang="en-US">sedimentation</dc:subject>
	<dc:subject xml:lang="en-US">soil erosion </dc:subject>
	<dc:description xml:lang="en-US">Monitoring total suspended solids (TSS) is essential as suspended sediments impact the environment and human health in various ways. However, TSS data are limited in many regions because the methods currently applied through in situ measurements are time-consuming and labor-intensive. The study aimed to develop algorithms to estimate TSS using data derived from UAVs and field measurements. Remote sensing technology, such as unmanaged aerial vehicle (UAV), was applied to obtain imagery data to estimate TSS content. These results were then compared with laboratory analysis of in-situ water samples, determined by gravimetric methods following standard protocols. The results showed that the algorithm developed using three-band ratios, the blue/green + red/green + NIR (near infra red)/green, produces a high R2 (0.70), indicating that this combination is reliable for use in estimating TSS content in a river section. The high accuracy of the red band for suspended sediment prediction is attributed to its spectral signature in turbid water, which shows higher reflectance compared to clean water. The results of this study have the potential to help river managers obtain TSS data quickly at a relatively low cost.</dc:description>
	<dc:publisher xml:lang="en-US">Brawijaya University</dc:publisher>
	<dc:date>2025-01-01</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://jdmlm.ub.ac.id/index.php/jdmlm/article/view/16951</dc:identifier>
	<dc:identifier>10.15243/jdmlm.2025.122.7379</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Degraded and Mining Lands Management; Vol. 12 No. 2 (2025); 7379-7388</dc:source>
	<dc:source>2502-2458</dc:source>
	<dc:source>2339-076X</dc:source>
	<dc:source>10.15243/jdmlm.2025.122</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/16951/1269</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Journal of Degraded and Mining Lands Management</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>