Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon Forest Article Swipe
Samuel José Silva Soares da Rocha
,
Flora Magdaline Benitez Romero
,
Carlos Moreira Miquelino Eleto Torres
,
Laércio Antônio Gonçalves Jacovine
,
Sabina Cerruto Ribeiro
,
Paulo Henrique Villanova
,
Bruno Leão Said Schettini
,
Vicente Toledo Machado de Morais
,
Leonardo Pequeno Reis
,
Maria Paula Miranda Xavier Rufino
,
Indira Bifano Comini
,
Ivaldo da Silva Tavares Júnior
,
Águida Beatriz Traváglia Viana
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/su15129452
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/su15129452
Accurate estimation of the volume and above-ground biomass of exploitable trees by the practice of selective logging is essential for the elaboration of a sustainable management plan. The objective of this study is to develop machine learning models capable of estimating the volume and biomass of commercial trees in the Southwestern Amazon, based on dendrometric, climatic and topographic characteristics. The study was carried out in the municipality of Porto Acre, Acre state, Brazil. The volume and biomass of sample trees were determined using dendrometric, climatic and topographic variables. The Boruta algorithm was applied to select the best set of variables. Support Vector Machines (SVM), Artificial Neural Networks (ANN), Random Forests (RF) and the Generalized Linear Model (GLM) were the machine learning methods evaluated. In general, the evaluated methods showed a satisfactory generalization power. The results showed that the volume and biomass predictions of commercial trees in the Amazon rainforest differed between the techniques (p < 0.05). ANNs showed the best performance in predicting the volume and biomass of commercial trees, with the highest ryŷ and the lowest RSME and MAE. Thus, machine learning methods such as SVM, ANN, RF and GLM are shown to be useful and efficient tools for estimating the volume and biomass of commercial trees in the Amazon rainforest. These methods can be useful tools to improve the accuracy of estimates in forest management plans.
Related Topics
Concepts
Biomass (ecology)
Amazon rainforest
Random forest
Support vector machine
Volume (thermodynamics)
Acre
Artificial neural network
Environmental science
Rainforest
Mathematics
Logging
Forestry
Machine learning
Agricultural engineering
Computer science
Agroforestry
Geography
Engineering
Ecology
Biology
Quantum mechanics
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/su15129452
- https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764
- OA Status
- gold
- Cited By
- 11
- References
- 71
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380538064
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4380538064Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/su15129452Digital Object Identifier
- Title
-
Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon ForestWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-12Full publication date if available
- Authors
-
Samuel José Silva Soares da Rocha, Flora Magdaline Benitez Romero, Carlos Moreira Miquelino Eleto Torres, Laércio Antônio Gonçalves Jacovine, Sabina Cerruto Ribeiro, Paulo Henrique Villanova, Bruno Leão Said Schettini, Vicente Toledo Machado de Morais, Leonardo Pequeno Reis, Maria Paula Miranda Xavier Rufino, Indira Bifano Comini, Ivaldo da Silva Tavares Júnior, Águida Beatriz Traváglia VianaList of authors in order
- Landing page
-
https://doi.org/10.3390/su15129452Publisher landing page
- PDF URL
-
https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764Direct OA link when available
- Concepts
-
Biomass (ecology), Amazon rainforest, Random forest, Support vector machine, Volume (thermodynamics), Acre, Artificial neural network, Environmental science, Rainforest, Mathematics, Logging, Forestry, Machine learning, Agricultural engineering, Computer science, Agroforestry, Geography, Engineering, Ecology, Biology, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6, 2024: 5Per-year citation counts (last 5 years)
- References (count)
-
71Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4380538064 |
|---|---|
| doi | https://doi.org/10.3390/su15129452 |
| ids.doi | https://doi.org/10.3390/su15129452 |
| ids.openalex | https://openalex.org/W4380538064 |
| fwci | 4.68087084 |
| type | article |
| title | Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon Forest |
| biblio.issue | 12 |
| biblio.volume | 15 |
| biblio.last_page | 9452 |
| biblio.first_page | 9452 |
| topics[0].id | https://openalex.org/T11880 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9998000264167786 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2309 |
| topics[0].subfield.display_name | Nature and Landscape Conservation |
| topics[0].display_name | Forest ecology and management |
| topics[1].id | https://openalex.org/T11164 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9957000017166138 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2305 |
| topics[1].subfield.display_name | Environmental Engineering |
| topics[1].display_name | Remote Sensing and LiDAR Applications |
| topics[2].id | https://openalex.org/T10111 |
| topics[2].field.id | https://openalex.org/fields/23 |
| topics[2].field.display_name | Environmental Science |
| topics[2].score | 0.9854000210762024 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2303 |
| topics[2].subfield.display_name | Ecology |
| topics[2].display_name | Remote Sensing in Agriculture |
| is_xpac | False |
| apc_list.value | 2200 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2382 |
| apc_paid.value | 2200 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2382 |
| concepts[0].id | https://openalex.org/C115540264 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6864213347434998 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2945560 |
| concepts[0].display_name | Biomass (ecology) |
| concepts[1].id | https://openalex.org/C535291247 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6596815586090088 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q177567 |
| concepts[1].display_name | Amazon rainforest |
| concepts[2].id | https://openalex.org/C169258074 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6140760779380798 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q245748 |
| concepts[2].display_name | Random forest |
| concepts[3].id | https://openalex.org/C12267149 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5663094520568848 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q282453 |
| concepts[3].display_name | Support vector machine |
| concepts[4].id | https://openalex.org/C20556612 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5643455982208252 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q4469374 |
| concepts[4].display_name | Volume (thermodynamics) |
| concepts[5].id | https://openalex.org/C48508581 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5353550910949707 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q4675074 |
| concepts[5].display_name | Acre |
| concepts[6].id | https://openalex.org/C50644808 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4919002056121826 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[6].display_name | Artificial neural network |
| concepts[7].id | https://openalex.org/C39432304 |
| concepts[7].level | 0 |
| concepts[7].score | 0.47824278473854065 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[7].display_name | Environmental science |
| concepts[8].id | https://openalex.org/C2619416 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4326038062572479 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q9444 |
| concepts[8].display_name | Rainforest |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.42823922634124756 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| concepts[10].id | https://openalex.org/C125620115 |
| concepts[10].level | 2 |
| concepts[10].score | 0.41354769468307495 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q845249 |
| concepts[10].display_name | Logging |
| concepts[11].id | https://openalex.org/C97137747 |
| concepts[11].level | 1 |
| concepts[11].score | 0.35141104459762573 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q38112 |
| concepts[11].display_name | Forestry |
| concepts[12].id | https://openalex.org/C119857082 |
| concepts[12].level | 1 |
| concepts[12].score | 0.3429475426673889 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[12].display_name | Machine learning |
| concepts[13].id | https://openalex.org/C88463610 |
| concepts[13].level | 1 |
| concepts[13].score | 0.32765674591064453 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q194118 |
| concepts[13].display_name | Agricultural engineering |
| concepts[14].id | https://openalex.org/C41008148 |
| concepts[14].level | 0 |
| concepts[14].score | 0.3035241365432739 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[14].display_name | Computer science |
| concepts[15].id | https://openalex.org/C54286561 |
| concepts[15].level | 1 |
| concepts[15].score | 0.26802611351013184 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q397350 |
| concepts[15].display_name | Agroforestry |
| concepts[16].id | https://openalex.org/C205649164 |
| concepts[16].level | 0 |
| concepts[16].score | 0.22562602162361145 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q1071 |
| concepts[16].display_name | Geography |
| concepts[17].id | https://openalex.org/C127413603 |
| concepts[17].level | 0 |
| concepts[17].score | 0.21784734725952148 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[17].display_name | Engineering |
| concepts[18].id | https://openalex.org/C18903297 |
| concepts[18].level | 1 |
| concepts[18].score | 0.16273263096809387 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[18].display_name | Ecology |
| concepts[19].id | https://openalex.org/C86803240 |
| concepts[19].level | 0 |
| concepts[19].score | 0.08394676446914673 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[19].display_name | Biology |
| concepts[20].id | https://openalex.org/C62520636 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[20].display_name | Quantum mechanics |
| concepts[21].id | https://openalex.org/C121332964 |
| concepts[21].level | 0 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[21].display_name | Physics |
| keywords[0].id | https://openalex.org/keywords/biomass |
| keywords[0].score | 0.6864213347434998 |
| keywords[0].display_name | Biomass (ecology) |
| keywords[1].id | https://openalex.org/keywords/amazon-rainforest |
| keywords[1].score | 0.6596815586090088 |
| keywords[1].display_name | Amazon rainforest |
| keywords[2].id | https://openalex.org/keywords/random-forest |
| keywords[2].score | 0.6140760779380798 |
| keywords[2].display_name | Random forest |
| keywords[3].id | https://openalex.org/keywords/support-vector-machine |
| keywords[3].score | 0.5663094520568848 |
| keywords[3].display_name | Support vector machine |
| keywords[4].id | https://openalex.org/keywords/volume |
| keywords[4].score | 0.5643455982208252 |
| keywords[4].display_name | Volume (thermodynamics) |
| keywords[5].id | https://openalex.org/keywords/acre |
| keywords[5].score | 0.5353550910949707 |
| keywords[5].display_name | Acre |
| keywords[6].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[6].score | 0.4919002056121826 |
| keywords[6].display_name | Artificial neural network |
| keywords[7].id | https://openalex.org/keywords/environmental-science |
| keywords[7].score | 0.47824278473854065 |
| keywords[7].display_name | Environmental science |
| keywords[8].id | https://openalex.org/keywords/rainforest |
| keywords[8].score | 0.4326038062572479 |
| keywords[8].display_name | Rainforest |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.42823922634124756 |
| keywords[9].display_name | Mathematics |
| keywords[10].id | https://openalex.org/keywords/logging |
| keywords[10].score | 0.41354769468307495 |
| keywords[10].display_name | Logging |
| keywords[11].id | https://openalex.org/keywords/forestry |
| keywords[11].score | 0.35141104459762573 |
| keywords[11].display_name | Forestry |
| keywords[12].id | https://openalex.org/keywords/machine-learning |
| keywords[12].score | 0.3429475426673889 |
| keywords[12].display_name | Machine learning |
| keywords[13].id | https://openalex.org/keywords/agricultural-engineering |
| keywords[13].score | 0.32765674591064453 |
| keywords[13].display_name | Agricultural engineering |
| keywords[14].id | https://openalex.org/keywords/computer-science |
| keywords[14].score | 0.3035241365432739 |
| keywords[14].display_name | Computer science |
| keywords[15].id | https://openalex.org/keywords/agroforestry |
| keywords[15].score | 0.26802611351013184 |
| keywords[15].display_name | Agroforestry |
| keywords[16].id | https://openalex.org/keywords/geography |
| keywords[16].score | 0.22562602162361145 |
| keywords[16].display_name | Geography |
| keywords[17].id | https://openalex.org/keywords/engineering |
| keywords[17].score | 0.21784734725952148 |
| keywords[17].display_name | Engineering |
| keywords[18].id | https://openalex.org/keywords/ecology |
| keywords[18].score | 0.16273263096809387 |
| keywords[18].display_name | Ecology |
| keywords[19].id | https://openalex.org/keywords/biology |
| keywords[19].score | 0.08394676446914673 |
| keywords[19].display_name | Biology |
| language | en |
| locations[0].id | doi:10.3390/su15129452 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S10134376 |
| locations[0].source.issn | 2071-1050 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2071-1050 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Sustainability |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764 |
| 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 | Sustainability |
| locations[0].landing_page_url | https://doi.org/10.3390/su15129452 |
| locations[1].id | pmh:oai:mdpi.com:/2071-1050/15/12/9452/ |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400947 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | MDPI (MDPI AG) |
| locations[1].source.host_organization | https://openalex.org/I4210097602 |
| locations[1].source.host_organization_name | Multidisciplinary Digital Publishing Institute (Switzerland) |
| locations[1].source.host_organization_lineage | https://openalex.org/I4210097602 |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Text |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Sustainability; Volume 15; Issue 12; Pages: 9452 |
| locations[1].landing_page_url | https://dx.doi.org/10.3390/su15129452 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5067330029 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-6686-1936 |
| authorships[0].author.display_name | Samuel José Silva Soares da Rocha |
| authorships[0].countries | BR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I1315085146 |
| authorships[0].affiliations[0].raw_affiliation_string | Departamento de Ciências Florestais, Universidade Federal de Lavras, Lavras 37200-900, MG, Brazil |
| authorships[0].institutions[0].id | https://openalex.org/I1315085146 |
| authorships[0].institutions[0].ror | https://ror.org/0122bmm03 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I1315085146 |
| authorships[0].institutions[0].country_code | BR |
| authorships[0].institutions[0].display_name | Universidade Federal de Lavras |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Samuel José Silva Soares da Rocha |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Departamento de Ciências Florestais, Universidade Federal de Lavras, Lavras 37200-900, MG, Brazil |
| authorships[1].author.id | https://openalex.org/A5061526841 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9417-1780 |
| authorships[1].author.display_name | Flora Magdaline Benitez Romero |
| authorships[1].countries | BR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I187079419 |
| authorships[1].affiliations[0].raw_affiliation_string | Instituto Nacional de Pesquisas da Amazônia—INPA, Manaus 69067-375, AM, Brazil |
| authorships[1].institutions[0].id | https://openalex.org/I187079419 |
| authorships[1].institutions[0].ror | https://ror.org/01xe86309 |
| authorships[1].institutions[0].type | facility |
| authorships[1].institutions[0].lineage | https://openalex.org/I187079419 |
| authorships[1].institutions[0].country_code | BR |
| authorships[1].institutions[0].display_name | National Institute of Amazonian Research |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Flora Magdaline Benitez Romero |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Instituto Nacional de Pesquisas da Amazônia—INPA, Manaus 69067-375, AM, Brazil |
| authorships[2].author.id | https://openalex.org/A5058602598 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0255-2637 |
| authorships[2].author.display_name | Carlos Moreira Miquelino Eleto Torres |
| authorships[2].countries | BR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[2].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[2].institutions[0].id | https://openalex.org/I146165071 |
| authorships[2].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[2].institutions[0].country_code | BR |
| authorships[2].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Carlos Moreira Miquelino Eleto Torres |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[3].author.id | https://openalex.org/A5033947235 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-5485-3090 |
| authorships[3].author.display_name | Laércio Antônio Gonçalves Jacovine |
| authorships[3].countries | BR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[3].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[3].institutions[0].id | https://openalex.org/I146165071 |
| authorships[3].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[3].institutions[0].country_code | BR |
| authorships[3].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Laércio Antônio Gonçalves Jacovine |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[4].author.id | https://openalex.org/A5012208831 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-4504-3050 |
| authorships[4].author.display_name | Sabina Cerruto Ribeiro |
| authorships[4].countries | BR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I1317776637 |
| authorships[4].affiliations[0].raw_affiliation_string | Centro de Ciências Biológicas e da Natureza, Universidade Federal do Acre (UFAC), Campus Universitário BR 364, Km 04, Distrito Industrial, Rio Branco 69920-900, AC, Brazil |
| authorships[4].institutions[0].id | https://openalex.org/I1317776637 |
| authorships[4].institutions[0].ror | https://ror.org/05hag2y10 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I1317776637 |
| authorships[4].institutions[0].country_code | BR |
| authorships[4].institutions[0].display_name | Universidade Federal do Acre |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Sabina Cerruto Ribeiro |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Centro de Ciências Biológicas e da Natureza, Universidade Federal do Acre (UFAC), Campus Universitário BR 364, Km 04, Distrito Industrial, Rio Branco 69920-900, AC, Brazil |
| authorships[5].author.id | https://openalex.org/A5063454454 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-4187-2740 |
| authorships[5].author.display_name | Paulo Henrique Villanova |
| authorships[5].countries | BR |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[5].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[5].institutions[0].id | https://openalex.org/I146165071 |
| authorships[5].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[5].institutions[0].country_code | BR |
| authorships[5].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Paulo Henrique Villanova |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[6].author.id | https://openalex.org/A5017091630 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-6510-4511 |
| authorships[6].author.display_name | Bruno Leão Said Schettini |
| authorships[6].countries | BR |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[6].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[6].institutions[0].id | https://openalex.org/I146165071 |
| authorships[6].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[6].institutions[0].country_code | BR |
| authorships[6].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Bruno Leão Said Schettini |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[7].author.id | https://openalex.org/A5081545735 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-5227-1951 |
| authorships[7].author.display_name | Vicente Toledo Machado de Morais |
| authorships[7].countries | BR |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I165476936 |
| authorships[7].affiliations[0].raw_affiliation_string | Brandt Meio Ambiente LTDA, Alameda do Ingá, 89, Vale do Sereno, Nova Lima 34006-042, MG, Brazil |
| authorships[7].institutions[0].id | https://openalex.org/I165476936 |
| authorships[7].institutions[0].ror | https://ror.org/05a99n355 |
| authorships[7].institutions[0].type | company |
| authorships[7].institutions[0].lineage | https://openalex.org/I165476936 |
| authorships[7].institutions[0].country_code | BR |
| authorships[7].institutions[0].display_name | Vale (Brazil) |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Vicente Toledo Machado de Morais Junior |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Brandt Meio Ambiente LTDA, Alameda do Ingá, 89, Vale do Sereno, Nova Lima 34006-042, MG, Brazil |
| authorships[8].author.id | https://openalex.org/A5005493583 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-5829-1598 |
| authorships[8].author.display_name | Leonardo Pequeno Reis |
| authorships[8].countries | BR |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I4210147329 |
| authorships[8].affiliations[0].raw_affiliation_string | Instituto de Desenvolvimento Sustentável Mamirauá, Tefé 69553-225, AM, Brazil |
| authorships[8].institutions[0].id | https://openalex.org/I4210147329 |
| authorships[8].institutions[0].ror | https://ror.org/04encyw73 |
| authorships[8].institutions[0].type | nonprofit |
| authorships[8].institutions[0].lineage | https://openalex.org/I4210147329 |
| authorships[8].institutions[0].country_code | BR |
| authorships[8].institutions[0].display_name | Instituto de Desenvolvimento Sustentável Mamirauá |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Leonardo Pequeno Reis |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Instituto de Desenvolvimento Sustentável Mamirauá, Tefé 69553-225, AM, Brazil |
| authorships[9].author.id | https://openalex.org/A5007576294 |
| authorships[9].author.orcid | https://orcid.org/0000-0001-6594-2152 |
| authorships[9].author.display_name | Maria Paula Miranda Xavier Rufino |
| authorships[9].countries | BR |
| authorships[9].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[9].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[9].institutions[0].id | https://openalex.org/I146165071 |
| authorships[9].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[9].institutions[0].type | education |
| authorships[9].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[9].institutions[0].country_code | BR |
| authorships[9].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Maria Paula Miranda Xavier Rufino |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[10].author.id | https://openalex.org/A5042327928 |
| authorships[10].author.orcid | https://orcid.org/0000-0003-1815-5783 |
| authorships[10].author.display_name | Indira Bifano Comini |
| authorships[10].countries | BR |
| authorships[10].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[10].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[10].institutions[0].id | https://openalex.org/I146165071 |
| authorships[10].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[10].institutions[0].type | education |
| authorships[10].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[10].institutions[0].country_code | BR |
| authorships[10].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[10].author_position | middle |
| authorships[10].raw_author_name | Indira Bifano Comini |
| authorships[10].is_corresponding | False |
| authorships[10].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[11].author.id | https://openalex.org/A5053604286 |
| authorships[11].author.orcid | https://orcid.org/0000-0001-5226-0638 |
| authorships[11].author.display_name | Ivaldo da Silva Tavares Júnior |
| authorships[11].countries | BR |
| authorships[11].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[11].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[11].institutions[0].id | https://openalex.org/I146165071 |
| authorships[11].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[11].institutions[0].type | education |
| authorships[11].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[11].institutions[0].country_code | BR |
| authorships[11].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[11].author_position | middle |
| authorships[11].raw_author_name | Ivaldo da Silva Tavares Júnior |
| authorships[11].is_corresponding | False |
| authorships[11].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[12].author.id | https://openalex.org/A5024650860 |
| authorships[12].author.orcid | https://orcid.org/0000-0001-6779-2661 |
| authorships[12].author.display_name | Águida Beatriz Traváglia Viana |
| authorships[12].countries | BR |
| authorships[12].affiliations[0].institution_ids | https://openalex.org/I146165071 |
| authorships[12].affiliations[0].raw_affiliation_string | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| authorships[12].institutions[0].id | https://openalex.org/I146165071 |
| authorships[12].institutions[0].ror | https://ror.org/0409dgb37 |
| authorships[12].institutions[0].type | education |
| authorships[12].institutions[0].lineage | https://openalex.org/I146165071 |
| authorships[12].institutions[0].country_code | BR |
| authorships[12].institutions[0].display_name | Universidade Federal de Viçosa |
| authorships[12].author_position | last |
| authorships[12].raw_author_name | Águida Beatriz Traváglia Viana |
| authorships[12].is_corresponding | False |
| authorships[12].raw_affiliation_strings | Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Viçosa 36570-900, MG, Brazil |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon Forest |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11880 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9998000264167786 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2309 |
| primary_topic.subfield.display_name | Nature and Landscape Conservation |
| primary_topic.display_name | Forest ecology and management |
| related_works | https://openalex.org/W4318822567, https://openalex.org/W4394455541, https://openalex.org/W4399610140, https://openalex.org/W1905899120, https://openalex.org/W1775026715, https://openalex.org/W2609527536, https://openalex.org/W4385818796, https://openalex.org/W4394070866, https://openalex.org/W2787038603, https://openalex.org/W2025720449 |
| cited_by_count | 11 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 6 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 5 |
| locations_count | 2 |
| best_oa_location.id | doi:10.3390/su15129452 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S10134376 |
| best_oa_location.source.issn | 2071-1050 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2071-1050 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Sustainability |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764 |
| 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 | Sustainability |
| best_oa_location.landing_page_url | https://doi.org/10.3390/su15129452 |
| primary_location.id | doi:10.3390/su15129452 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S10134376 |
| primary_location.source.issn | 2071-1050 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2071-1050 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Sustainability |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2071-1050/15/12/9452/pdf?version=1686628764 |
| 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 | Sustainability |
| primary_location.landing_page_url | https://doi.org/10.3390/su15129452 |
| publication_date | 2023-06-12 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W1978642993, https://openalex.org/W2052494086, https://openalex.org/W2123574709, https://openalex.org/W1992452171, https://openalex.org/W2133613984, https://openalex.org/W1986040739, https://openalex.org/W2170447717, https://openalex.org/W2113521108, https://openalex.org/W2059343473, https://openalex.org/W2148682635, https://openalex.org/W1964043798, https://openalex.org/W2030618373, https://openalex.org/W1995095340, https://openalex.org/W2156654227, https://openalex.org/W2129990354, https://openalex.org/W2781478421, https://openalex.org/W2884178717, https://openalex.org/W3042269172, https://openalex.org/W2530797269, https://openalex.org/W2759761740, https://openalex.org/W2744288739, https://openalex.org/W2745102831, https://openalex.org/W2123932570, https://openalex.org/W1998048588, https://openalex.org/W2052467489, https://openalex.org/W2773578505, https://openalex.org/W1978053013, https://openalex.org/W2905659887, https://openalex.org/W1981213426, https://openalex.org/W2048605790, https://openalex.org/W2327646892, https://openalex.org/W2134105845, https://openalex.org/W2754397646, https://openalex.org/W2915990397, https://openalex.org/W2805091105, https://openalex.org/W2461639478, https://openalex.org/W2916956764, https://openalex.org/W2137787581, https://openalex.org/W2907788294, https://openalex.org/W3180206543, https://openalex.org/W4309569456, https://openalex.org/W3096261963, https://openalex.org/W3003390797, https://openalex.org/W4323047299, https://openalex.org/W1963988599, https://openalex.org/W2630700149, https://openalex.org/W180836830, https://openalex.org/W3048390865, https://openalex.org/W2614464134, https://openalex.org/W2156665896, https://openalex.org/W2944954104, https://openalex.org/W4237405726, https://openalex.org/W2207216579, https://openalex.org/W2158118208, https://openalex.org/W2170375547, https://openalex.org/W1546824454, https://openalex.org/W2166842656, https://openalex.org/W1528328767, https://openalex.org/W2916009518, https://openalex.org/W2016023958, https://openalex.org/W2099206930, https://openalex.org/W2261059368, https://openalex.org/W6601578796, https://openalex.org/W2897608386, https://openalex.org/W2779834058, https://openalex.org/W2936859456, https://openalex.org/W2911964244, https://openalex.org/W1983865151, https://openalex.org/W2076723282, https://openalex.org/W2208808953, https://openalex.org/W38301456 |
| referenced_works_count | 71 |
| abstract_inverted_index.a | 23, 129 |
| abstract_inverted_index.(p | 153 |
| abstract_inverted_index.In | 123 |
| abstract_inverted_index.RF | 188 |
| abstract_inverted_index.as | 185 |
| abstract_inverted_index.be | 194, 215 |
| abstract_inverted_index.by | 11 |
| abstract_inverted_index.in | 48, 64, 145, 161, 208, 224 |
| abstract_inverted_index.is | 17, 32 |
| abstract_inverted_index.of | 2, 8, 14, 22, 29, 39, 45, 67, 77, 98, 142, 167, 205, 222 |
| abstract_inverted_index.on | 53 |
| abstract_inverted_index.to | 33, 93, 193, 218 |
| abstract_inverted_index.GLM | 190 |
| abstract_inverted_index.The | 27, 59, 73, 88, 133 |
| abstract_inverted_index.and | 5, 43, 56, 75, 85, 111, 139, 165, 174, 178, 189, 196, 203 |
| abstract_inverted_index.are | 191 |
| abstract_inverted_index.can | 214 |
| abstract_inverted_index.for | 19, 199 |
| abstract_inverted_index.out | 63 |
| abstract_inverted_index.set | 97 |
| abstract_inverted_index.the | 3, 12, 20, 41, 49, 65, 95, 112, 118, 125, 137, 146, 151, 158, 163, 171, 175, 201, 209, 220 |
| abstract_inverted_index.was | 61, 91 |
| abstract_inverted_index.< | 154 |
| abstract_inverted_index.(RF) | 110 |
| abstract_inverted_index.ANN, | 187 |
| abstract_inverted_index.ANNs | 156 |
| abstract_inverted_index.Acre | 70 |
| abstract_inverted_index.MAE. | 179 |
| abstract_inverted_index.RSME | 177 |
| abstract_inverted_index.SVM, | 186 |
| abstract_inverted_index.best | 96, 159 |
| abstract_inverted_index.ryŷ | 173 |
| abstract_inverted_index.such | 184 |
| abstract_inverted_index.that | 136 |
| abstract_inverted_index.this | 30 |
| abstract_inverted_index.were | 80, 117 |
| abstract_inverted_index.with | 170 |
| abstract_inverted_index.(GLM) | 116 |
| abstract_inverted_index.Acre, | 69 |
| abstract_inverted_index.Model | 115 |
| abstract_inverted_index.Porto | 68 |
| abstract_inverted_index.These | 212 |
| abstract_inverted_index.Thus, | 180 |
| abstract_inverted_index.based | 52 |
| abstract_inverted_index.plan. | 26 |
| abstract_inverted_index.shown | 192 |
| abstract_inverted_index.study | 31, 60 |
| abstract_inverted_index.tools | 198, 217 |
| abstract_inverted_index.trees | 10, 47, 79, 144, 207 |
| abstract_inverted_index.using | 82 |
| abstract_inverted_index.(ANN), | 107 |
| abstract_inverted_index.(SVM), | 103 |
| abstract_inverted_index.0.05). | 155 |
| abstract_inverted_index.Amazon | 147, 210 |
| abstract_inverted_index.Boruta | 89 |
| abstract_inverted_index.Linear | 114 |
| abstract_inverted_index.Neural | 105 |
| abstract_inverted_index.Random | 108 |
| abstract_inverted_index.Vector | 101 |
| abstract_inverted_index.forest | 225 |
| abstract_inverted_index.lowest | 176 |
| abstract_inverted_index.models | 37 |
| abstract_inverted_index.plans. | 227 |
| abstract_inverted_index.power. | 132 |
| abstract_inverted_index.sample | 78 |
| abstract_inverted_index.select | 94 |
| abstract_inverted_index.showed | 128, 135, 157 |
| abstract_inverted_index.state, | 71 |
| abstract_inverted_index.trees, | 169 |
| abstract_inverted_index.useful | 195, 216 |
| abstract_inverted_index.volume | 4, 42, 74, 138, 164, 202 |
| abstract_inverted_index.Amazon, | 51 |
| abstract_inverted_index.Brazil. | 72 |
| abstract_inverted_index.Forests | 109 |
| abstract_inverted_index.Support | 100 |
| abstract_inverted_index.applied | 92 |
| abstract_inverted_index.between | 150 |
| abstract_inverted_index.biomass | 7, 44, 76, 140, 166, 204 |
| abstract_inverted_index.capable | 38 |
| abstract_inverted_index.carried | 62 |
| abstract_inverted_index.develop | 34 |
| abstract_inverted_index.highest | 172 |
| abstract_inverted_index.improve | 219 |
| abstract_inverted_index.logging | 16 |
| abstract_inverted_index.machine | 35, 119, 181 |
| abstract_inverted_index.methods | 121, 127, 183, 213 |
| abstract_inverted_index.results | 134 |
| abstract_inverted_index.Accurate | 0 |
| abstract_inverted_index.Machines | 102 |
| abstract_inverted_index.Networks | 106 |
| abstract_inverted_index.accuracy | 221 |
| abstract_inverted_index.climatic | 55, 84 |
| abstract_inverted_index.differed | 149 |
| abstract_inverted_index.general, | 124 |
| abstract_inverted_index.learning | 36, 120, 182 |
| abstract_inverted_index.practice | 13 |
| abstract_inverted_index.algorithm | 90 |
| abstract_inverted_index.efficient | 197 |
| abstract_inverted_index.essential | 18 |
| abstract_inverted_index.estimates | 223 |
| abstract_inverted_index.evaluated | 126 |
| abstract_inverted_index.objective | 28 |
| abstract_inverted_index.selective | 15 |
| abstract_inverted_index.Artificial | 104 |
| abstract_inverted_index.commercial | 46, 143, 168, 206 |
| abstract_inverted_index.determined | 81 |
| abstract_inverted_index.estimating | 40, 200 |
| abstract_inverted_index.estimation | 1 |
| abstract_inverted_index.evaluated. | 122 |
| abstract_inverted_index.management | 25, 226 |
| abstract_inverted_index.predicting | 162 |
| abstract_inverted_index.rainforest | 148 |
| abstract_inverted_index.techniques | 152 |
| abstract_inverted_index.variables. | 87, 99 |
| abstract_inverted_index.Generalized | 113 |
| abstract_inverted_index.elaboration | 21 |
| abstract_inverted_index.exploitable | 9 |
| abstract_inverted_index.performance | 160 |
| abstract_inverted_index.predictions | 141 |
| abstract_inverted_index.rainforest. | 211 |
| abstract_inverted_index.sustainable | 24 |
| abstract_inverted_index.topographic | 57, 86 |
| abstract_inverted_index.Southwestern | 50 |
| abstract_inverted_index.above-ground | 6 |
| abstract_inverted_index.municipality | 66 |
| abstract_inverted_index.satisfactory | 130 |
| abstract_inverted_index.dendrometric, | 54, 83 |
| abstract_inverted_index.generalization | 131 |
| abstract_inverted_index.characteristics. | 58 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5067330029 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I1315085146 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.9421782 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |