Combining two water type classification schemes for semi-analytical estimation of suspended particulate matter concentrations in various water bodies Article Swipe
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.jag.2025.104909
Retrieval of suspended particulate matter concentration (SPM) from remote-sensing reflectance (Rrs) is useful for frequent and widespread monitoring of water quality. However, Rrs values vary not only with SPM but also with particle composition (organic-dominated or mineral-dominated) and colored dissolved organic matter (CDOM), making it difficult to accurately estimate SPM in diverse aquatic environments using a single algorithm. In this study, two water type classification schemes: optical water type classification scheme and particle composition classification scheme, were integrated into a semi-analytical method to improve the accuracy of SPM estimation in various water bodies. By combining these two classification schemes, we classified water bodies around the world into 12 water types and developed an SPM estimation algorithm for each water type. Using 4,513 in situ Rrs-SPM measurements, the performance of the new SPM estimation algorithm was compared to that of 11 existing SPM estimation algorithms, and the results show that the median absolute percentage error (MdAPE) was reduced from 51.3 to 58.9% to 43.2%. The performance of the proposed method was also evaluated using 226 satellite matchups, with an MdAPE of 43.4%. Further comparative analysis and showcases based on several satellite images demonstrate that the two water type classification schemes play different roles that can effectively enhance the accuracy of SPM estimation.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jag.2025.104909
- OA Status
- gold
- References
- 33
- OpenAlex ID
- https://openalex.org/W4415258118
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4415258118Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.jag.2025.104909Digital Object Identifier
- Title
-
Combining two water type classification schemes for semi-analytical estimation of suspended particulate matter concentrations in various water bodiesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-10-16Full publication date if available
- Authors
-
Mailisu, Dalin Jiang, Bunkei MatsushitaList of authors in order
- Landing page
-
https://doi.org/10.1016/j.jag.2025.104909Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.jag.2025.104909Direct OA link when available
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
33Number of works referenced by this work
Full payload
| id | https://openalex.org/W4415258118 |
|---|---|
| doi | https://doi.org/10.1016/j.jag.2025.104909 |
| ids.doi | https://doi.org/10.1016/j.jag.2025.104909 |
| ids.openalex | https://openalex.org/W4415258118 |
| fwci | 0.0 |
| type | article |
| title | Combining two water type classification schemes for semi-analytical estimation of suspended particulate matter concentrations in various water bodies |
| biblio.issue | |
| biblio.volume | 144 |
| biblio.last_page | 104909 |
| biblio.first_page | 104909 |
| topics[0].id | https://openalex.org/T12120 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9965000152587891 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2305 |
| topics[0].subfield.display_name | Environmental Engineering |
| topics[0].display_name | Air Quality Monitoring and Forecasting |
| topics[1].id | https://openalex.org/T10032 |
| topics[1].field.id | https://openalex.org/fields/19 |
| topics[1].field.display_name | Earth and Planetary Sciences |
| topics[1].score | 0.9898999929428101 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1910 |
| topics[1].subfield.display_name | Oceanography |
| topics[1].display_name | Marine and coastal ecosystems |
| topics[2].id | https://openalex.org/T14249 |
| topics[2].field.id | https://openalex.org/fields/23 |
| topics[2].field.display_name | Environmental Science |
| topics[2].score | 0.9750999808311462 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2311 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Water Quality Monitoring and Analysis |
| is_xpac | False |
| apc_list.value | 2250 |
| apc_list.currency | USD |
| apc_list.value_usd | 2250 |
| apc_paid.value | 2250 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2250 |
| language | en |
| locations[0].id | doi:10.1016/j.jag.2025.104909 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210179989 |
| locations[0].source.issn | 1569-8432, 1872-826X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1569-8432 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | International Journal of Applied Earth Observation and Geoinformation |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | International Journal of Applied Earth Observation and Geoinformation |
| locations[0].landing_page_url | https://doi.org/10.1016/j.jag.2025.104909 |
| locations[1].id | pmh:oai:doaj.org/article:7d534f1e8ca34db7867b8fbfd0f750c7 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | International Journal of Applied Earth Observations and Geoinformation, Vol 144, Iss , Pp 104909- (2025) |
| locations[1].landing_page_url | https://doaj.org/article/7d534f1e8ca34db7867b8fbfd0f750c7 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5120026849 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Mailisu |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | None Mailisu |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5057736064 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-5676-5860 |
| authorships[1].author.display_name | Dalin Jiang |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Dalin Jiang |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5060768667 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-6397-1144 |
| authorships[2].author.display_name | Bunkei Matsushita |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Bunkei Matsushita |
| authorships[2].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.jag.2025.104909 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-17T00:00:00 |
| display_name | Combining two water type classification schemes for semi-analytical estimation of suspended particulate matter concentrations in various water bodies |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12120 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9965000152587891 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2305 |
| primary_topic.subfield.display_name | Environmental Engineering |
| primary_topic.display_name | Air Quality Monitoring and Forecasting |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1016/j.jag.2025.104909 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210179989 |
| best_oa_location.source.issn | 1569-8432, 1872-826X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1569-8432 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | International Journal of Applied Earth Observation and Geoinformation |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | International Journal of Applied Earth Observation and Geoinformation |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.jag.2025.104909 |
| primary_location.id | doi:10.1016/j.jag.2025.104909 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210179989 |
| primary_location.source.issn | 1569-8432, 1872-826X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1569-8432 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | International Journal of Applied Earth Observation and Geoinformation |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | International Journal of Applied Earth Observation and Geoinformation |
| primary_location.landing_page_url | https://doi.org/10.1016/j.jag.2025.104909 |
| publication_date | 2025-10-16 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W2126068541, https://openalex.org/W2115932749, https://openalex.org/W2088665921, https://openalex.org/W3025417591, https://openalex.org/W1521595634, https://openalex.org/W2145148749, https://openalex.org/W2615064060, https://openalex.org/W2289865770, https://openalex.org/W2012987850, https://openalex.org/W4405446438, https://openalex.org/W3027958853, https://openalex.org/W3138775503, https://openalex.org/W4387132582, https://openalex.org/W1995811252, https://openalex.org/W4321076624, https://openalex.org/W4390079577, https://openalex.org/W2048956808, https://openalex.org/W2158228421, https://openalex.org/W2572463531, https://openalex.org/W2462025444, https://openalex.org/W2944172471, https://openalex.org/W1982281954, https://openalex.org/W4312220555, https://openalex.org/W4402153194, https://openalex.org/W4409252521, https://openalex.org/W4311799708, https://openalex.org/W2395967699, https://openalex.org/W2336247563, https://openalex.org/W2038317098, https://openalex.org/W1973860676, https://openalex.org/W568092464, https://openalex.org/W149594569, https://openalex.org/W2996160164 |
| referenced_works_count | 33 |
| abstract_inverted_index.a | 55, 79 |
| abstract_inverted_index.11 | 139 |
| abstract_inverted_index.12 | 107 |
| abstract_inverted_index.By | 93 |
| abstract_inverted_index.In | 58 |
| abstract_inverted_index.an | 112, 177 |
| abstract_inverted_index.in | 50, 89, 122 |
| abstract_inverted_index.is | 11 |
| abstract_inverted_index.it | 44 |
| abstract_inverted_index.of | 1, 18, 86, 128, 138, 165, 179, 208 |
| abstract_inverted_index.on | 187 |
| abstract_inverted_index.or | 35 |
| abstract_inverted_index.to | 46, 82, 136, 159, 161 |
| abstract_inverted_index.we | 99 |
| abstract_inverted_index.226 | 173 |
| abstract_inverted_index.Rrs | 22 |
| abstract_inverted_index.SPM | 28, 49, 87, 113, 131, 141, 209 |
| abstract_inverted_index.The | 163 |
| abstract_inverted_index.and | 15, 37, 71, 110, 144, 184 |
| abstract_inverted_index.but | 29 |
| abstract_inverted_index.can | 203 |
| abstract_inverted_index.for | 13, 116 |
| abstract_inverted_index.new | 130 |
| abstract_inverted_index.not | 25 |
| abstract_inverted_index.the | 84, 104, 126, 129, 145, 149, 166, 193, 206 |
| abstract_inverted_index.two | 61, 96, 194 |
| abstract_inverted_index.was | 134, 155, 169 |
| abstract_inverted_index.51.3 | 158 |
| abstract_inverted_index.also | 30, 170 |
| abstract_inverted_index.each | 117 |
| abstract_inverted_index.from | 7, 157 |
| abstract_inverted_index.into | 78, 106 |
| abstract_inverted_index.only | 26 |
| abstract_inverted_index.play | 199 |
| abstract_inverted_index.show | 147 |
| abstract_inverted_index.situ | 123 |
| abstract_inverted_index.that | 137, 148, 192, 202 |
| abstract_inverted_index.this | 59 |
| abstract_inverted_index.type | 63, 68, 196 |
| abstract_inverted_index.vary | 24 |
| abstract_inverted_index.were | 76 |
| abstract_inverted_index.with | 27, 31, 176 |
| abstract_inverted_index.(Rrs) | 10 |
| abstract_inverted_index.(SPM) | 6 |
| abstract_inverted_index.4,513 | 121 |
| abstract_inverted_index.58.9% | 160 |
| abstract_inverted_index.MdAPE | 178 |
| abstract_inverted_index.Using | 120 |
| abstract_inverted_index.based | 186 |
| abstract_inverted_index.error | 153 |
| abstract_inverted_index.roles | 201 |
| abstract_inverted_index.these | 95 |
| abstract_inverted_index.type. | 119 |
| abstract_inverted_index.types | 109 |
| abstract_inverted_index.using | 54, 172 |
| abstract_inverted_index.water | 19, 62, 67, 91, 101, 108, 118, 195 |
| abstract_inverted_index.world | 105 |
| abstract_inverted_index.43.2%. | 162 |
| abstract_inverted_index.43.4%. | 180 |
| abstract_inverted_index.around | 103 |
| abstract_inverted_index.bodies | 102 |
| abstract_inverted_index.images | 190 |
| abstract_inverted_index.making | 43 |
| abstract_inverted_index.matter | 4, 41 |
| abstract_inverted_index.median | 150 |
| abstract_inverted_index.method | 81, 168 |
| abstract_inverted_index.scheme | 70 |
| abstract_inverted_index.single | 56 |
| abstract_inverted_index.study, | 60 |
| abstract_inverted_index.useful | 12 |
| abstract_inverted_index.values | 23 |
| abstract_inverted_index.(CDOM), | 42 |
| abstract_inverted_index.(MdAPE) | 154 |
| abstract_inverted_index.Further | 181 |
| abstract_inverted_index.Rrs-SPM | 124 |
| abstract_inverted_index.aquatic | 52 |
| abstract_inverted_index.bodies. | 92 |
| abstract_inverted_index.colored | 38 |
| abstract_inverted_index.diverse | 51 |
| abstract_inverted_index.enhance | 205 |
| abstract_inverted_index.improve | 83 |
| abstract_inverted_index.optical | 66 |
| abstract_inverted_index.organic | 40 |
| abstract_inverted_index.reduced | 156 |
| abstract_inverted_index.results | 146 |
| abstract_inverted_index.scheme, | 75 |
| abstract_inverted_index.schemes | 198 |
| abstract_inverted_index.several | 188 |
| abstract_inverted_index.various | 90 |
| abstract_inverted_index.However, | 21 |
| abstract_inverted_index.absolute | 151 |
| abstract_inverted_index.accuracy | 85, 207 |
| abstract_inverted_index.analysis | 183 |
| abstract_inverted_index.compared | 135 |
| abstract_inverted_index.estimate | 48 |
| abstract_inverted_index.existing | 140 |
| abstract_inverted_index.frequent | 14 |
| abstract_inverted_index.particle | 32, 72 |
| abstract_inverted_index.proposed | 167 |
| abstract_inverted_index.quality. | 20 |
| abstract_inverted_index.schemes, | 98 |
| abstract_inverted_index.schemes: | 65 |
| abstract_inverted_index.Retrieval | 0 |
| abstract_inverted_index.algorithm | 115, 133 |
| abstract_inverted_index.combining | 94 |
| abstract_inverted_index.developed | 111 |
| abstract_inverted_index.different | 200 |
| abstract_inverted_index.difficult | 45 |
| abstract_inverted_index.dissolved | 39 |
| abstract_inverted_index.evaluated | 171 |
| abstract_inverted_index.matchups, | 175 |
| abstract_inverted_index.satellite | 174, 189 |
| abstract_inverted_index.showcases | 185 |
| abstract_inverted_index.suspended | 2 |
| abstract_inverted_index.accurately | 47 |
| abstract_inverted_index.algorithm. | 57 |
| abstract_inverted_index.classified | 100 |
| abstract_inverted_index.estimation | 88, 114, 132, 142 |
| abstract_inverted_index.integrated | 77 |
| abstract_inverted_index.monitoring | 17 |
| abstract_inverted_index.percentage | 152 |
| abstract_inverted_index.widespread | 16 |
| abstract_inverted_index.algorithms, | 143 |
| abstract_inverted_index.comparative | 182 |
| abstract_inverted_index.composition | 33, 73 |
| abstract_inverted_index.demonstrate | 191 |
| abstract_inverted_index.effectively | 204 |
| abstract_inverted_index.estimation. | 210 |
| abstract_inverted_index.particulate | 3 |
| abstract_inverted_index.performance | 127, 164 |
| abstract_inverted_index.reflectance | 9 |
| abstract_inverted_index.environments | 53 |
| abstract_inverted_index.concentration | 5 |
| abstract_inverted_index.measurements, | 125 |
| abstract_inverted_index.classification | 64, 69, 74, 97, 197 |
| abstract_inverted_index.remote-sensing | 8 |
| abstract_inverted_index.semi-analytical | 80 |
| abstract_inverted_index.(organic-dominated | 34 |
| abstract_inverted_index.mineral-dominated) | 36 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.51921019 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |