Geotechnologies applied to analysis of the rural environmental cadastre

Santos, Patrícia Pereira dos; Menezes, Sady Júnior Martins da Costa de; Júnior, Waldir Cintra de Jesus; Telles, Lucas Arthur de Almeida; Souza, Marcelo Henrique de; Silva, Samuel Ferreira da; Santos, Alexandre Rosa dos

doi:10.1016/j.landusepol.2020.105127

“…According to Rajão et al (2020) the CAR is a tool that aims to integrate the environmental information of rural properties and possessions, aiming to create a database for control, monitoring, environmental and economic planning and combating deforestation, as recommended by Law n° 12.651, may 25, 2012. However, Santos et al (2021) in their study emphasizes that the CAR is a self‐declaratory document in which the owner informs the size of the rural property and its location, as well as the Legal Reserve that varies from 0% to 80% according to the Brazilian biome, Anthropized area (deforestation after 22 July 2008), consolidated (deforestation before July 22, 2008) and remaining native vegetation. Therefore, as this is self‐declared information, there are several discrepancies between what is declared and what is actually true, causing overlaps with other properties.…”

Section: Resultsmentioning

confidence: 99%

Sustainability assessment in cities in the eastern amazon

Lima,

Progênio,

Costa

et al. 2023

Sustainable Development

1

0

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Indicators are important tools that help monitor and assess sustainability, providing crucial information for public management. This study aimed to analyze the behavior of municipalities in eastern amazon (State of Pará), through sustainability indicators that cover social, economic, environmental and basic sanitation dimensions, applying the statistical method of multivariate analysis. For the selection of indicators, a checklist of academic papers on sustainability was carried out. For the composition of the clusters, the Ward method was applied. To validate the number of groups, the Pakhira‐Bandyopadhyay‐Maulik (PBM) index was used, obtaining 2 groups for the sanitation and general dimensions, 3 for environmental and social and 7 groups for economic. In this study, it was possible to demonstrate that several municipalities have deficiencies related to access to water supply and mainly sewage collection and treatment, causing various consequences for the population, as they do not comply with the commitments of the Sustainable Development Goals.

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“…O CAR, além do fornecimento do cadastro e de auxiliar os produtores rurais que desejam possuir uma regularizac ¸ão ambiental, precisa de um monitoramento geográfico das áreas ocupadas para assegurar o devido combate ao desmatamento. Os estudos reportados em [5] e [6] mostraram a importância do monitoramento das áreas em conjunto do cadastro.…”

Section: Introduc ¸ãOunclassified

Classificação e Interpretação de dados do Cadastro Ambiental Rural utilizando técnicas de Aprendizagem de Máquina

Borges¹,

Ferreira²,

Júnior³

2021

Anais Do 15. Congresso Brasileiro De Inteligência Computacional

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The Rural Environmental Registry (CAR) consists of a mandatory public electronic registry for all rural properties in the Brazilian territory, integrates environmental information of the properties, assists the monitoring of them and the fight against deforestation. However, a large number of registrations are carried out erroneously generating inconsistent data, leading these to be canceled and/or to be requested to correct the registration. Performing automatic verification of these records is important to improve the processing of records. This paper proposes an automatic classification method to approve or cancel the CAR registers with interpretation of the classifications performed. For this, four machine learning-based classifiers were tested and the results were evaluated. The model with the best performance was used to interpret the classification using the Local Interpretable Model-agnostic Explanations (LIME) algorithm. The results showed the potential of the method in future real applications.

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“…De forma a incentivar os agricultores a fazerem o cadastro e manterem o mesmo devidamente regularizado, o governo promove incentivos aos proprietários rurais que realizam o cadastro, como crédito rural facilitado com prazos e taxas melhores que o praticado no mercado, facilitação na contratação de seguro agrícola, dentre outros dispostos no Código Florestal (Brasil, 2012). Além do cadastro em si, o monitoramento geográfico das áreas ocupadas de forma a mapear as áreas degradadas e auxiliar no combate ao desmatamento se faz importante, reforçado pelos estudos realizados por dos Santos et al (2020) e Arvor et al (2021).…”

Section: Introdu ç ãOunclassified

Classificação de Dados do Cadastro Ambiental Rural com uso de Algoritmos de Aprendizagem de Máquina

Borges

¹

,

Ferreira

²

,

Júnior

³

2021

Procedings Do XV Simpósio Brasileiro De Automação Inteligente

0

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The Rural Environmental Registry (CAR) consists of a mandatory public electronic registry for all rural properties in the Brazilian territory, integrates environmental information of the properties, assists the monitoring of them, and the fight against deforestation. However, a large number of registrations are carried out erroneously generating inconsistent data, leading these to be canceled and/or to be requested to correct the registration. Carrying out these checks manually is very expensive, since a specialized workforce is required and Brazil has an immense amount of rural properties. In this context, this work aims to provide an intelligent machine learning-based system that allows to verify and classify CAR data into approved or canceled data quickly and effectively. For this purpose, three learning models were trained using real data from registers. In addition to the classification, the SMOTE tool was used to treat the imbalance between classes. Results were generated using measures of performance of classifiers and comparative studies between the methods were also performed. The results showed potential use of the method in future automated predictions, reaching performance indices above 0.90 (90%). Resumo: O Cadastro Ambiental Rural (CAR) consiste em um registro público eletrônico obrigatório para todos os imóveis rurais do território brasileiro, integra informações ambientais das propriedades, auxilia o monitoramento das mesmas e no combate ao desmatamento. Entretanto, um grande número de cadastros é realizado de maneira errônea gerando dados inconsistentes, levando estes a serem cancelados e/ou a serem pedidas retificações para o devido preenchimento do cadastro. Realizar essas verificações de forma manual é deveras oneroso, uma vez que é requerida uma mão de obra especializada e o Brasil possui uma imensa quantidade de imóveis rurais. Neste contexto, este trabalho tem como objetivo fornecer um sistema inteligente baseado em aprendizagem de máquina que permita verificar e classificar os dados do CAR em aprovados ou cancelados de maneira rápida e eficaz. Para isto, três modelos de aprendizagem foram treinados utilizando dados reais de cadastros. Além da classificação, foi utilizada a ferramenta SMOTE para tratamento do desbalanceamento entre as classes. Foram gerados resultados utilizando medidas de desempenho de classificadores e realizados, também, estudos comparativos entre os métodos. Os resultados apresentados mostraram potencial uso do método em futuras predições automatizadas, atingindo índices de desempenho acima de 0.90 (90%).

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Geotechnologies applied to analysis of the rural environmental cadastre

Cited by 9 publications

References 5 publications

Sustainability assessment in cities in the eastern amazon

Sustainability assessment in cities in the eastern amazon

Classificação e Interpretação de dados do Cadastro Ambiental Rural utilizando técnicas de Aprendizagem de Máquina

Classificação de Dados do Cadastro Ambiental Rural com uso de Algoritmos de Aprendizagem de Máquina

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