| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/4AC8JCD |
| Repository | sid.inpe.br/plutao/2023/12.11.16.24.47 (restricted access) |
| Last Update | 2023:12.13.19.14.13 (UTC) lattes |
| Metadata Repository | sid.inpe.br/plutao/2023/12.11.16.24.48 |
| Metadata Last Update | 2024:01.02.17.00.38 (UTC) administrator |
| DOI | 10.1002/ieam.4852 |
| ISSN | 1551-3777 |
| Label | lattes: 8997858562195060 2 KappesKuplSilvWebe:2023:CaStAg |
| Citation Key | KappesKuplSilvWebe:2023:CaStAg |
| Title | Using Multi-Layer Perceptron (MLP) and Similarity-Weighted machine learning algorithm (SimWeight) to reconstruct the past: a case study of the agricultural expansion on grasslands in the Uruguayan Savannas  |
| Year | 2023 |
| Access Date | 2024, May 19 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 4776 KiB |
| 2. Context | |
| Author | 1 Kappes, Bruna Batista 2 Kuplich, Tatiana Mora 3 Silva, Tatiana Silva da 4 Weber, Eliseu José |
| Resume Identifier | 1 2 8JMKD3MGP5W/3C9JJ9P |
| Group | 1 2 COESU-CGGO-INPE-MCTI-GOV-BR |
| Affiliation | 1 Universidade Federal do Rio Grande do Sul (UFRGS) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Universidade Federal do Rio Grande do Sul (UFRGS) 4 Universidade Federal do Rio Grande do Sul (UFRGS) |
| Author e-Mail Address | 1 brunakappes@gmail.com 2 tatiana.kuplich@inpe.br |
| Journal | Integrated Environmental Assessment and Management |
| Volume | 2023 |
| Pages | 1-16 |
| History (UTC) | 2023-12-13 19:14:16 :: lattes -> administrator :: 2023 2024-01-02 17:00:38 :: administrator -> simone :: 2023 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Version Type | publisher |
| Keywords | Hindcasting Land change modeling Land use and land cover Pampa biome Red List of Ecosystems |
| Abstract | Changes in land use and land cover (LULC) have significant implications for biodiversity, ecosystem functioning, and deforestation. Modeling LULC changes is crucial to understanding anthropogenic impacts on environmental conservation and ecosystem services. Although previous studies have focused on predicting future changes, there is a growing need to determine past scenarios using new assessment tools. This study proposes a methodology for LULC past scenario generation based on transition analysis. Aiming to hindcast LULC scenario in 1970 based on the transition analysis of the past 35 years (from 1985 to 2020), two machine learning algorithms, multilayer perceptron (MLP) and similarity weighted (SimWeight), were employed to determine the driver variables most related to conversions in LULC and to simulate the past. The study focused on the Aristida spp. grasslands in the Uruguayan savannas, where native grasslands have been extensively converted to agricultural areas. Land use and land cover data from the MapBiomas project were integrated with spatial variables such as altimetry, slope, pedology, and linear distances from rivers, roads, urban areas, agriculture, forest, forestry, and native grasslands. The accuracy of the predicted maps was assessed through stratified random sampling of reference images from the Multispectral Scanner (MSS) sensor. The results demonstrate a reduction of approximately 659 934 ha of native grasslands in the study area between 1985 and 2020, directly proportional to the increase in cultivable areas. The MLP algorithm exhibited moderate performance, with notable errors in classifying agriculture and grassland areas. In contrast, the SimWeight algorithm displayed better accuracy, particularly in distinguishing grassland and agriculture classes. The modeled map using SimWeight accurately represented the transitions between grassland and agriculture with a high level of agreement. By modeling the 1970s scenario using the SimWeight model, it was estimated that the Aristida spp. grasslands experienced a substantial reduction in grassland coverage, ranging from 9982.31 to 10 022.32 km2 between 1970 and 2020. This represents a range of 60.8%61.07% of the total grassland area in 1970. These findings provide valuable insights into the driving factors behind land use change in the Aristida spp. grasslands and offer useful information for land management, conservation, and sustainable development in the region. The study's main contribution lies in the hindcasting of past LULC scenarios, utilizing a tool used primarily for forecasting future scenarios. |
| Area | SRE |
| Arrangement | urlib.net > CGGO > Using Multi-Layer Perceptron... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| Target File | Integr Envir Assess Manag - 2023 - Kappes - Using multilayer perceptron and similarity‐weighted machine learning.pdf |
| User Group | lattes |
| Reader Group | administrator lattes |
| Visibility | shown |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/46KUBT5 |
| Dissemination | WEBSCI; PORTALCAPES; SCOPUS. |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn lineage mark mirrorrepository month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |